Detection of meteorological extreme effect on historical crop yield anomaly

NASA Astrophysics Data System (ADS)

Kim, W.; Iizumi, T.; Nishimori, M.

2017-12-01

Meteorological extremes of temperature and precipitation are a critical issue in the global climate change, and some studies investigating how the extreme changes in accordance with the climate change are continuously reported. However, it is rarely understandable that the extremes affect crop yield worldwide as heatwave, coolwave, drought, and flood, albeit some local or national reports are available. Therefore, we globally investigated the extremes effects on the variability of historical yield of maize, rice, soy, and wheat with a standardized index and a historical yield anomaly. For the regression analysis, the standardized index is annually aggregated in the consideration of a crop calendar, and the historical yield is detrended with 5-year moving average. Throughout this investigation, we found that the relationship between the aggregated standardized index and the historical yield anomaly shows not merely positive correlation but also negative correlation in all crops in the globe. Namely, the extremes cause decrease of crop yield as a matter of course, but increase in some regions contrastingly. These results help us to quantify the extremes effect on historical crop yield anomaly.

Global Agriculture Yields and Conflict under Future Climate

NASA Astrophysics Data System (ADS)

Rising, J.; Cane, M. A.

2013-12-01

Aspects of climate have been shown to correlate significantly with conflict. We investigate a possible pathway for these effects through changes in agriculture yields, as predicted by field crop models (FAO's AquaCrop and DSSAT). Using satellite and station weather data, and surveyed data for soil and management, we simulate major crop yields across all countries between 1961 and 2008, and compare these to FAO and USDA reported yields. Correlations vary by country and by crop, from approximately .8 to -.5. Some of this range in crop model performance is explained by crop varieties, data quality, and other natural, economic, and political features. We also quantify the ability of AquaCrop and DSSAT to simulate yields under past cycles of ENSO as a proxy for their performance under changes in climate. We then describe two statistical models which relate crop yields to conflict events from the UCDP/PRIO Armed Conflict dataset. The first relates several preceding years of predicted yields of the major grain in each country to any conflict involving that country. The second uses the GREG ethnic group maps to identify differences in predicted yields between neighboring regions. By using variation in predicted yields to explain conflict, rather than actual yields, we can identify the exogenous effects of weather on conflict. Finally, we apply precipitation and temperature time-series under IPCC's A1B scenario to the statistical models. This allows us to estimate the scale of the impact of future yields on future conflict. Centroids of the major growing regions for each country's primary crop, based on USDA FAS consumption. Correlations between simulated yields and reported yields, for AquaCrop and DSSAT, under the assumption that no irrigation, fertilization, or pest control is used. Reported yields are the average of FAO yields and USDA FAS yields, where both are available.

Meta-analysis of climate impacts and uncertainty on crop yields in Europe

NASA Astrophysics Data System (ADS)

Knox, Jerry; Daccache, Andre; Hess, Tim; Haro, David

2016-11-01

Future changes in temperature, rainfall and soil moisture could threaten agricultural land use and crop productivity in Europe, with major consequences for food security. We assessed the projected impacts of climate change on the yield of seven major crop types (viz wheat, barley, maize, potato, sugar beet, rice and rye) grown in Europe using a systematic review (SR) and meta-analysis of data reported in 41 original publications from an initial screening of 1748 studies. Our approach adopted an established SR procedure developed by the Centre for Evidence Based Conservation constrained by inclusion criteria and defined methods for literature searches, data extraction, meta-analysis and synthesis. Whilst similar studies exist to assess climate impacts on crop yield in Africa and South Asia, surprisingly, no comparable synthesis has been undertaken for Europe. Based on the reported results (n = 729) we show that the projected change in average yield in Europe for the seven crops by the 2050s is +8%. For wheat and sugar beet, average yield changes of +14% and +15% are projected, respectively. There were strong regional differences with crop impacts in northern Europe being higher (+14%) and more variable compared to central (+6%) and southern (+5) Europe. Maize is projected to suffer the largest negative mean change in southern Europe (-11%). Evidence of climate impacts on yield was extensive for wheat, maize, sugar beet and potato, but very limited for barley, rice and rye. The implications for supporting climate adaptation policy and informing climate impacts crop science research in Europe are discussed.

Integrated crop management practices for maximizing grain yield of double-season rice crop.

PubMed

Wang, Depeng; Huang, Jianliang; Nie, Lixiao; Wang, Fei; Ling, Xiaoxia; Cui, Kehui; Li, Yong; Peng, Shaobing

2017-01-12

Information on maximum grain yield and its attributes are limited for double-season rice crop grown under the subtropical environment. This study was conducted to examine key characteristics associated with high yielding double-season rice crop through a comparison between an integrated crop management (ICM) and farmers' practice (FP). Field experiments were conducted in the early and late seasons in the subtropical environment of Wuxue County, Hubei Province, China in 2013 and 2014. On average, grain yield in ICM was 13.5% higher than that in FP. A maximum grain yield of 9.40 and 10.53 t ha -1 was achieved under ICM in the early- and late-season rice, respectively. Yield improvement of double-season rice with ICM was achieved with the combined effects of increased plant density and optimized nutrient management. Yield gain of ICM resulted from a combination of increases in sink size due to more panicle number per unit area and biomass production, further supported by the increased leaf area index, leaf area duration, radiation use efficiency, crop growth rate, and total nitrogen uptake compared with FP. Further enhancement in the yield potential of double-season rice should focus on increasing crop growth rate and biomass production through improved and integrated crop management practices.

Analysis of Biomass Feedstock Availability and Variability for the Peace River Region of Alberta, Canada

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stephen, Jamie; Sokhansanj, Shahabaddine; Bi, X.T.

2009-11-01

Biorefineries or other biomass-dependent facilities require a predictable, dependable feedstock supplied over many years to justify capital investments. Determining inter-year variability in biomass availability is essential to quantifying the feedstock supply risk. Using a geographic information system (GIS) and historic crop yield data, average production was estimated for 10 sites in the Peace River region of Alberta, Canada. Four high-yielding potential sites were investigated for variability over a 20 year time-frame (1980 2000). The range of availability was large, from double the average in maximum years to nothing in minimum years. Biomass availability is a function of grain yield, themore » biomass to grain ratio, the cropping frequency, and residue retention rate to ensure future crop productivity. Storage strategies must be implemented and alternate feedstock sources identified to supply biomass processing facilities in low-yield years.« less

Evaluating the synchronicity in yield variations of staple crops at global scale

NASA Astrophysics Data System (ADS)

Yokozawa, M.

2014-12-01

Reflecting the recent globalization trend in world commodity market, several major production countries are producing large amount of staple crops, especially, maize and soybean. Thus, simultaneous crop failure (abrupt reduction in crop yield, lean year) due to extreme weather and/or climate change could lead to unstable food supply. This study try to examine the synchronicity in yield variations of staple crops at global scale. We use a gridded crop yields database, which includes the historical year-to-year changes in staple crop yields with a spatial resolution of 1.125 degree in latitude/longitude during a period of 1982-2006 (Iizumi et al. 2013). It has been constructed based on the agriculture statistics issued by local administrative bureaus in each country. For the regions being lack of data, an interpolation was conducted to obtain the values referring to the NPP estimates from satellite data as well as FAO country yield. For each time series of the target crop yield, we firstly applied a local kernel regression to represent the long-term trend component. Next, the deviations of yearly yield from the long-term trend component were defined as ΔY(i, y) in year y at grid i. Then, the correlation of deviation between grids i and j in year y is defined as Cij(y) = ΔY(i, y) ΔY(j, y). In addition, Pij = <ΔY(i, y) ΔY(j, y)> represents the time-averaged correlation of deviation between grids i and j. Bracket <...> means the time average operation over 25 years (1982-2006). As the results, figures show the time changes in the number of grid pairs, in which both the deviation are negative. It represent the time changes in ratio of the grid pairs where both crop yields synchronically decreased to the total grid pairs. The years denoted by arrows in the figures indicate the case that all the ratios of three country pairs (i.e. China-USA, USA-Brazil and Brazil-China) are relatively larger (>0.6 for soybean and >0.5 for maize). This suggests that the reductions in crop yield occurred synchronically in three countries in these years, which are the simultaneous lean years (as of lower yield compared to that of long-term trend).

Quantifying blue and green virtual water contents in global crop production as well as potential production losses without irrigation

NASA Astrophysics Data System (ADS)

Siebert, Stefan; Döll, Petra

2010-04-01

SummaryCrop production requires large amounts of green and blue water. We developed the new global crop water model GCWM to compute consumptive water use (evapotranspiration) and virtual water content (evapotranspiration per harvested biomass) of crops at a spatial resolution of 5' by 5', distinguishing 26 crop classes, and blue versus green water. GCWM is based on the global land use data set MIRCA2000 that provides monthly growing areas for 26 crop classes under rainfed and irrigated conditions for the period 1998-2002 and represents multi-cropping. By computing daily soil water balances, GCWM determines evapotranspiration of blue and green water for each crop and grid cell. Cell-specific crop production under both rainfed and irrigated conditions is computed by downscaling average crop yields reported for 402 national and sub-national statistical units, relating rainfed and irrigated crop yields reported in census statistics to simulated ratios of actual to potential crop evapotranspiration for rainfed crops. By restricting water use of irrigated crops to green water only, the potential production loss without any irrigation was computed. For the period 1998-2002, the global value of total crop water use was 6685 km 3 yr -1, of which blue water use was 1180 km 3 yr -1, green water use of irrigated crops was 919 km 3 yr -1 and green water use of rainfed crops was 4586 km 3 yr -1. Total crop water use was largest for rice (941 km 3 yr -1), wheat (858 km 3 yr -1) and maize (722 km 3 yr -1). The largest amounts of blue water were used for rice (307 km 3 yr -1) and wheat (208 km 3 yr -1). Blue water use as percentage of total crop water use was highest for date palms (85%), cotton (39%), citrus fruits (33%), rice (33%) and sugar beets (32%), while for cassava, oil palm and cocoa, almost no blue water was used. Average crop yield of irrigated cereals was 442 Mg km -2 while average yield of rainfed cereals was only 266 Mg km -2. Average virtual water content of cereal crops was 1109 m 3 Mg -1 of green water and 291 m 3 Mg -1 of blue water, while average crop water productivity of cereal crops was 714 g m -3. If currently irrigated crops were not irrigated, global production of dates, rice, cotton, citrus and sugar cane would decrease by 60%, 39%, 38%, 32% and 31%, respectively. Forty-three per cent of cereal production was on irrigated land, and without irrigation, cereal production on irrigated land would decrease by 47%, corresponding to a 20% loss of total cereal production. The largest cereal production losses would occur in Northern Africa (66%) and Southern Asia (45%) while losses would be very low for Northern Europe (0.001%), Western Europe (1.2%), Eastern Europe (1.5%) and Middle Africa (1.6%). Uncertainties and limitations are discussed in the manuscript, and a comparison of GCWM results to statistics or results of other studies shows good agreement at the regional scale, but larger differences for specific countries.

Linking crop yield anomalies to large-scale atmospheric circulation in Europe.

PubMed

Ceglar, Andrej; Turco, Marco; Toreti, Andrea; Doblas-Reyes, Francisco J

2017-06-15

Understanding the effects of climate variability and extremes on crop growth and development represents a necessary step to assess the resilience of agricultural systems to changing climate conditions. This study investigates the links between the large-scale atmospheric circulation and crop yields in Europe, providing the basis to develop seasonal crop yield forecasting and thus enabling a more effective and dynamic adaptation to climate variability and change. Four dominant modes of large-scale atmospheric variability have been used: North Atlantic Oscillation, Eastern Atlantic, Scandinavian and Eastern Atlantic-Western Russia patterns. Large-scale atmospheric circulation explains on average 43% of inter-annual winter wheat yield variability, ranging between 20% and 70% across countries. As for grain maize, the average explained variability is 38%, ranging between 20% and 58%. Spatially, the skill of the developed statistical models strongly depends on the large-scale atmospheric variability impact on weather at the regional level, especially during the most sensitive growth stages of flowering and grain filling. Our results also suggest that preceding atmospheric conditions might provide an important source of predictability especially for maize yields in south-eastern Europe. Since the seasonal predictability of large-scale atmospheric patterns is generally higher than the one of surface weather variables (e.g. precipitation) in Europe, seasonal crop yield prediction could benefit from the integration of derived statistical models exploiting the dynamical seasonal forecast of large-scale atmospheric circulation.

The Role of Climate Covariability on Crop Yields in the Conterminous United States

DOE PAGES

Leng, Guoyong; Zhang, Xuesong; Huang, Maoyi; ...

2016-09-12

The covariability of temperature (T), precipitation (P) and radiation (R) is an important aspect in understanding the climate influence on crop yields. Here in this paper, we analyze county-level corn and soybean yields and observed climate for the period 1983–2012 to understand how growing-season (June, July and August) mean T, P and R influence crop yields jointly and in isolation across the CONterminous United States (CONUS). Results show that nationally averaged corn and soybean yields exhibit large interannual variability of 21% and 22%, of which 35% and 32% can be significantly explained by T and P, respectively. By including R,more » an additional of 5% in variability can be explained for both crops. Using partial regression analyses, we find that studies that ignore the covariability among T, P, and R can substantially overestimate the sensitivity of crop yields to a single climate factor at the county scale. Further analyses indicate large spatial variation in the relative contributions of different climate variables to the variability of historical corn and soybean yields. Finally, the structure of the dominant climate factors did not change substantially over 1983–2012, confirming the robustness of the findings, which have important implications for crop yield prediction and crop model validations.« less

Climate-Driven Crop Yield and Yield Variability and Climate Change Impacts on the U.S. Great Plains Agricultural Production.

PubMed

Kukal, Meetpal S; Irmak, Suat

2018-02-22

Climate variability and trends affect global crop yields and are characterized as highly dependent on location, crop type, and irrigation. U.S. Great Plains, due to its significance in national food production, evident climate variability, and extensive irrigation is an ideal region of investigation for climate impacts on food production. This paper evaluates climate impacts on maize, sorghum, and soybean yields and effect of irrigation for individual counties in this region by employing extensive crop yield and climate datasets from 1968-2013. Variability in crop yields was a quarter of the regional average yields, with a quarter of this variability explained by climate variability, and temperature and precipitation explained these in singularity or combination at different locations. Observed temperature trend was beneficial for maize yields, but detrimental for sorghum and soybean yields, whereas observed precipitation trend was beneficial for all three crops. Irrigated yields demonstrated increased robustness and an effective mitigation strategy against climate impacts than their non-irrigated counterparts by a considerable fraction. The information, data, and maps provided can serve as an assessment guide for planners, managers, and policy- and decision makers to prioritize agricultural resilience efforts and resource allocation or re-allocation in the regions that exhibit risk from climate variability.

Random Forests for Global and Regional Crop Yield Predictions.

PubMed

Jeong, Jig Han; Resop, Jonathan P; Mueller, Nathaniel D; Fleisher, David H; Yun, Kyungdahm; Butler, Ethan E; Timlin, Dennis J; Shim, Kyo-Moon; Gerber, James S; Reddy, Vangimalla R; Kim, Soo-Hyung

2016-01-01

Accurate predictions of crop yield are critical for developing effective agricultural and food policies at the regional and global scales. We evaluated a machine-learning method, Random Forests (RF), for its ability to predict crop yield responses to climate and biophysical variables at global and regional scales in wheat, maize, and potato in comparison with multiple linear regressions (MLR) serving as a benchmark. We used crop yield data from various sources and regions for model training and testing: 1) gridded global wheat grain yield, 2) maize grain yield from US counties over thirty years, and 3) potato tuber and maize silage yield from the northeastern seaboard region. RF was found highly capable of predicting crop yields and outperformed MLR benchmarks in all performance statistics that were compared. For example, the root mean square errors (RMSE) ranged between 6 and 14% of the average observed yield with RF models in all test cases whereas these values ranged from 14% to 49% for MLR models. Our results show that RF is an effective and versatile machine-learning method for crop yield predictions at regional and global scales for its high accuracy and precision, ease of use, and utility in data analysis. RF may result in a loss of accuracy when predicting the extreme ends or responses beyond the boundaries of the training data.

Quantifying the Limitation to World Cereal Production Due To Soil Phosphorus Status

NASA Astrophysics Data System (ADS)

Kvakić, Marko; Pellerin, Sylvain; Ciais, Philippe; Achat, David L.; Augusto, Laurent; Denoroy, Pascal; Gerber, James S.; Goll, Daniel; Mollier, Alain; Mueller, Nathaniel D.; Wang, Xuhui; Ringeval, Bruno

2018-01-01

Phosphorus (P) is an essential element for plant growth. Low P availability in soils is likely to limit crop yields in many parts of the world, but this effect has never been quantified at the global scale by process-based models. Here we attempt to estimate P limitation in three major cereals worldwide for the year 2000 by combining information on soil P distribution in croplands and a generic crop model, while accounting for the nature of soil-plant P transport. As a global average, the diffusion-limited soil P supply meets the crop's P demand corresponding to the climatic yield potential, due to the legacy soil P in highly fertilized areas. However, when focusing on the spatial distribution of P supply versus demand, we found strong limitation in regions like North and South America, Africa, and Eastern Europe. Averaged over grid cells where P supply is lower than demand, the global yield gap due to soil P is estimated at 22, 55, and 26% in winter wheat, maize, and rice. Assuming that a fraction (20%) of the annual P applied in fertilizers is directly available to the plant, the global P yield gap lowers by only 5-10%, underlying the importance of the existing soil P supply in sustaining crop yields. The study offers a base for exploring P limitation in crops worldwide but with certain limitations remaining. These could be better accounted for by describing the agricultural P cycle with a fully coupled and mechanistic soil-crop model.

Root length densities of UK wheat and oilseed rape crops with implications for water capture and yield

PubMed Central

White, Charlotte A.; Sylvester-Bradley, Roger; Berry, Peter M.

2015-01-01

Root length density (RLD) was measured to 1 m depth for 17 commercial crops of winter wheat (Triticum aestivum) and 40 crops of winter oilseed rape [Brassica napus; oilseed rape (OSR)] grown in the UK between 2004 and 2013. Taking the critical RLD (cRLD) for water capture as 1cm cm–3, RLDs appeared inadequate for full water capture on average below a depth of 0.32 m for winter wheat and below 0.45 m for OSR. These depths compare unfavourably (for wheat) with average depths of ‘full capture’ of 0.86 m and 0.48 m, respectively, determined for three wheat crops and one OSR crop studied in the 1970s and 1980s, and treated as references here. A simple model of water uptake and yield indicated that these shortfalls in wheat and OSR rooting compared with the reference data might be associated with shortfalls of up to 3.5 t ha–1 and 1.2 t ha–1, respectively, in grain yields under water-limited conditions, as increasingly occur through climate change. Coupled with decreased summer rainfall, poor rooting of modern arable crops could explain much of the yield stagnation that has been observed on UK farms since the 1990s. Methods of monitoring and improving rooting under commercial conditions are reviewed and discussed. PMID:25750427

A quality assessment of the MARS crop yield forecasting system for the European Union

NASA Astrophysics Data System (ADS)

van der Velde, Marijn; Bareuth, Bettina

2015-04-01

Timely information on crop production forecasts can become of increasing importance as commodity markets are more and more interconnected. Impacts across large crop production areas due to (e.g.) extreme weather and pest outbreaks can create ripple effects that may affect food prices and availability elsewhere. The MARS Unit (Monitoring Agricultural ResourceS), DG Joint Research Centre, European Commission, has been providing forecasts of European crop production levels since 1993. The operational crop production forecasting is carried out with the MARS Crop Yield Forecasting System (M-CYFS). The M-CYFS is used to monitor crop growth development, evaluate short-term effects of anomalous meteorological events, and provide monthly forecasts of crop yield at national and European Union level. The crop production forecasts are published in the so-called MARS bulletins. Forecasting crop yield over large areas in the operational context requires quality benchmarks. Here we present an analysis of the accuracy and skill of past crop yield forecasts of the main crops (e.g. soft wheat, grain maize), throughout the growing season, and specifically for the final forecast before harvest. Two simple benchmarks to assess the skill of the forecasts were defined as comparing the forecasts to 1) a forecast equal to the average yield and 2) a forecast using a linear trend established through the crop yield time-series. These reveal a variability in performance as a function of crop and Member State. In terms of production, the yield forecasts of 67% of the EU-28 soft wheat production and 80% of the EU-28 maize production have been forecast superior to both benchmarks during the 1993-2013 period. In a changing and increasingly variable climate crop yield forecasts can become increasingly valuable - provided they are used wisely. We end our presentation by discussing research activities that could contribute to this goal.

Nut crop yield records show that budbreak-based chilling requirements may not reflect yield decline chill thresholds

NASA Astrophysics Data System (ADS)

Pope, Katherine S.; Dose, Volker; Da Silva, David; Brown, Patrick H.; DeJong, Theodore M.

2015-06-01

Warming winters due to climate change may critically affect temperate tree species. Insufficiently cold winters are thought to result in fewer viable flower buds and the subsequent development of fewer fruits or nuts, decreasing the yield of an orchard or fecundity of a species. The best existing approximation for a threshold of sufficient cold accumulation, the "chilling requirement" of a species or variety, has been quantified by manipulating or modeling the conditions that result in dormant bud breaking. However, the physiological processes that affect budbreak are not the same as those that determine yield. This study sought to test whether budbreak-based chilling thresholds can reasonably approximate the thresholds that affect yield, particularly regarding the potential impacts of climate change on temperate tree crop yields. County-wide yield records for almond ( Prunus dulcis), pistachio ( Pistacia vera), and walnut ( Juglans regia) in the Central Valley of California were compared with 50 years of weather records. Bayesian nonparametric function estimation was used to model yield potentials at varying amounts of chill accumulation. In almonds, average yields occurred when chill accumulation was close to the budbreak-based chilling requirement. However, in the other two crops, pistachios and walnuts, the best previous estimate of the budbreak-based chilling requirements was 19-32 % higher than the chilling accumulations associated with average or above average yields. This research indicates that physiological processes beyond requirements for budbreak should be considered when estimating chill accumulation thresholds of yield decline and potential impacts of climate change.

[Main interspecific competition and land productivity of fruit-crop intercropping in Loess Region of West Shauxi].

PubMed

Yun, Lei; Bi, Hua-Xing; Tian, Xiao-Ling; Cui, Zhe-Wei; Zhou, Hui-Zi; Gao, Lu-Bo; Liu, Li-Xia

2011-05-01

Taking the four typical fruit-crop intercropping models, i.e., walnut-peanut, walnut-soybean, apple-peanut, and apple-soybean, in the Loess Region of western Shanxi Province as the objects, this paper analyzed the crop (peanut and soybean) photosynthetic active radiation (PAR), net photosynthetic rate (P(n)), yield, and soil moisture content. Comparing with crop monoculture, fruit-crop intercropping decreased the crop PAR and P(n). The smaller the distance from tree rows, the smaller the crop PAR and P(n). There was a significantly positive correlation between the P(n) and crop yield, suggesting that illumination was one of the key factors affecting crop yield. From the whole trend, the 0-100 cm soil moisture content had no significant differences between walnut-crop intercropping systems and corresponding monoculture cropping systems, but had significant differences between apple-crop intercropping systems and corresponding monoculture cropping systems, indicating that the competition for soil moisture was more intense in apple-crop intercropping systems than in walnut-crop intercropping systems. Comparing with monoculture, fruit-crop intercropping increased the land use efficiency and economic benefit averagely by 70% and 14%, respectively, and walnut-crop intercropping was much better than apple-crop intercropping. To increase the crop yield in fruit-crop intercropping systems, the following strategies should be taken: strengthening the management of irrigation and fertilization, increasing the distances or setting root barriers between crop and tree rows, regularly and properly pruning, and planting shade-tolerant crops in intercropping.

Monitoring Agricultural Drought Using Geographic Information Systems and Remote Sensing on the Primary Corn and Soybean Belt in the United States

NASA Astrophysics Data System (ADS)

Al-Shomrany, Adel

The study aims to evaluate various remote sensing drought indices to assess those most fitting for monitoring agricultural drought. The objectives are (1) to assess and study the impact of drought effect on (corn and soybean) crop production by crop mapping information and GIS technology; (2) to use Geographical Weighted Regression (GWR) as a technical approach to evaluate the spatial relationships between precipitation vs. irrigated and non-irrigated corn and soybean yield, using a Nebraska county-level case study; (3) to assess agricultural drought indices derived from remote sensing (NDVI, NMDI, NDWI, and NDII6); (4) to develop an optimal approach for agricultural drought detection based on remote sensing measurements to determine the relationship between US county-level yields versus relatively common variables collected. Extreme drought creates low corn and soybean production where irrigation systems are not implemented. This results in a lack of moisture in soil leading to dry land and stale crop yields. When precipitation and moisture is found across all states, corn and soybean production flourishes. For Kansas, Nebraska, and South Dakota, irrigation management methods assist in strong crop yields throughout SPI monthly averages. The data gathered on irrigation consisted of using drought indices gathered by the national agricultural statistics service website. For the SPI levels ranging between one-month and nine-months, Kansas and Nebraska performed the best out of all 12-states contained in the Midwestern primary Corn and Soybean Belt. The reasoning behind Kansas and Nebraska's results was due to a more efficient and sustainable irrigation system, where upon South Dakota lacked. South Dakota was leveled by strong correlations throughout all SPI periods for corn only. Kansas showed its strongest correlations for the two-month and three-month averages, for both corn and soybean. Precipitation regression with irrigated and non-irrigated maize (corn) and soybean levels show yields as a function of precipitation. The GWR models predicted that yields were significantly better than OLS performances for maize (corn) and soybean. The OLS regression model when used showed a general trend of correlation between observed yields and long-term mean precipitation totals, with 84% and 63% of the variability in mean yield explained by the mean annual precipitation for the non-irrigated crops. The GWR technique performance in predicting yields was significantly better than OLS performances. For instance in the months of June, July, and August precipitations had greater impacts on maize (corn) yields than soybeans under non-irrigated conditions as a result of the greater sensitivity maize (corn) had to water stress. SPI is capable of offering various time-scales enabling it to show initial warning signs of drought conditions and accompanying severity levels. SPI calculation techniques used for various locations are reflected upon the precipitation records acquired during those periods. Over the 3, 6, and 9-month periods, NDII6 performed the best out of all of the MODIS indices as shown in its results in monitoring vegetation moisture and drought detection. NDII6 performed the best due to its detection abilities. The 9-month SPI provides an indication of inter-seasonal precipitation patterns over medium timescale duration. A new approach used is to average corn and soybean yields for all counties of the study area in comparison with average anomalies of the MODIS indices for the growing season between May through September from 2006-2012. There was a strong correlation between average corn yields versus MODIS NDII6 averages for these years with R2 equaling 0.62. That means NDII6 is the best indicator to show drought conditions and vegetation moisture monitoring. There was a weak correlation with R2 = 0.16 between averages of soybean yields and averages of precipitation. Irrigation and management systems, technological improvements from hybrids, producer management techniques, and other management practices have an impact on crop yield productions. (Abstract shortened by ProQuest.).

Bee pollination increases yield quantity and quality of cash crops in Burkina Faso, West Africa.

PubMed

Stein, Katharina; Coulibaly, Drissa; Stenchly, Kathrin; Goetze, Dethardt; Porembski, Stefan; Lindner, André; Konaté, Souleymane; Linsenmair, Eduard K

2017-12-18

Mutualistic biotic interactions as among flowering plants and their animal pollinators are a key component of biodiversity. Pollination, especially by insects, is a key element in ecosystem functioning, and hence constitutes an ecosystem service of global importance. Not only sexual reproduction of plants is ensured, but also yields are stabilized and genetic variability of crops is maintained, counteracting inbreeding depression and facilitating system resilience. While experiencing rapid environmental change, there is an increased demand for food and income security, especially in sub-Saharan communities, which are highly dependent on small scale agriculture. By combining exclusion experiments, pollinator surveys and field manipulations, this study for the first time quantifies the contribution of bee pollinators to smallholders' production of the major cash crops, cotton and sesame, in Burkina Faso. Pollination by honeybees and wild bees significantly increased yield quantity and quality on average up to 62%, while exclusion of pollinators caused an average yield gap of 37% in cotton and 59% in sesame. Self-pollination revealed inbreeding depression effects on fruit set and low germination rates in the F1-generation. Our results highlight potential negative consequences of any pollinator decline, provoking risks to agriculture and compromising crop yields in sub-Saharan West Africa.

Temperature Increase Reduces Global Yields of Major Crops in Four Independent Estimates

NASA Technical Reports Server (NTRS)

Zhao, Chuang; Liu, Bing; Piao, Shilong; Wang, Xuhui; Lobell, David B.; Huang, Yao; Huang, Mengtian; Yao, Yitong; Bassu, Simona; Ciais, Philippe;

Temperature increase reduces global yields of major crops in four independent estimates

PubMed Central

Zhao, Chuang; Piao, Shilong; Wang, Xuhui; Lobell, David B.; Huang, Yao; Huang, Mengtian; Yao, Yitong; Bassu, Simona; Ciais, Philippe; Durand, Jean-Louis; Elliott, Joshua; Ewert, Frank; Janssens, Ivan A.; Li, Tao; Lin, Erda; Liu, Qiang; Martre, Pierre; Peng, Shushi; Wallach, Daniel; Wang, Tao; Wu, Donghai; Liu, Zhuo; Zhu, Yan; Zhu, Zaichun; Asseng, Senthold

2017-01-01

Wheat, rice, maize, and soybean provide two-thirds of human caloric intake. Assessing the impact of global temperature increase on production of these crops is therefore critical to maintaining global food supply, but different studies have yielded different results. Here, we investigated the impacts of temperature on yields of the four crops by compiling extensive published results from four analytical methods: global grid-based and local point-based models, statistical regressions, and field-warming experiments. Results from the different methods consistently showed negative temperature impacts on crop yield at the global scale, generally underpinned by similar impacts at country and site scales. Without CO2 fertilization, effective adaptation, and genetic improvement, each degree-Celsius increase in global mean temperature would, on average, reduce global yields of wheat by 6.0%, rice by 3.2%, maize by 7.4%, and soybean by 3.1%. Results are highly heterogeneous across crops and geographical areas, with some positive impact estimates. Multimethod analyses improved the confidence in assessments of future climate impacts on global major crops and suggest crop- and region-specific adaptation strategies to ensure food security for an increasing world population. PMID:28811375

Temperature increase reduces global yields of major crops in four independent estimates.

PubMed

Zhao, Chuang; Liu, Bing; Piao, Shilong; Wang, Xuhui; Lobell, David B; Huang, Yao; Huang, Mengtian; Yao, Yitong; Bassu, Simona; Ciais, Philippe; Durand, Jean-Louis; Elliott, Joshua; Ewert, Frank; Janssens, Ivan A; Li, Tao; Lin, Erda; Liu, Qiang; Martre, Pierre; Müller, Christoph; Peng, Shushi; Peñuelas, Josep; Ruane, Alex C; Wallach, Daniel; Wang, Tao; Wu, Donghai; Liu, Zhuo; Zhu, Yan; Zhu, Zaichun; Asseng, Senthold

2017-08-29

Wheat, rice, maize, and soybean provide two-thirds of human caloric intake. Assessing the impact of global temperature increase on production of these crops is therefore critical to maintaining global food supply, but different studies have yielded different results. Here, we investigated the impacts of temperature on yields of the four crops by compiling extensive published results from four analytical methods: global grid-based and local point-based models, statistical regressions, and field-warming experiments. Results from the different methods consistently showed negative temperature impacts on crop yield at the global scale, generally underpinned by similar impacts at country and site scales. Without CO 2 fertilization, effective adaptation, and genetic improvement, each degree-Celsius increase in global mean temperature would, on average, reduce global yields of wheat by 6.0%, rice by 3.2%, maize by 7.4%, and soybean by 3.1%. Results are highly heterogeneous across crops and geographical areas, with some positive impact estimates. Multimethod analyses improved the confidence in assessments of future climate impacts on global major crops and suggest crop- and region-specific adaptation strategies to ensure food security for an increasing world population.

Yield variability prediction by remote sensing sensors with different spatial resolution

NASA Astrophysics Data System (ADS)

Kumhálová, Jitka; Matějková, Štěpánka

2017-04-01

Currently, remote sensing sensors are very popular for crop monitoring and yield prediction. This paper describes how satellite images with moderate (Landsat satellite data) and very high (QuickBird and WorldView-2 satellite data) spatial resolution, together with GreenSeeker hand held crop sensor, can be used to estimate yield and crop growth variability. Winter barley (2007 and 2015) and winter wheat (2009 and 2011) were chosen because of cloud-free data availability in the same time period for experimental field from Landsat satellite images and QuickBird or WorldView-2 images. Very high spatial resolution images were resampled to worse spatial resolution. Normalised difference vegetation index was derived from each satellite image data sets and it was also measured with GreenSeeker handheld crop sensor for the year 2015 only. Results showed that each satellite image data set can be used for yield and plant variability estimation. Nevertheless, better results, in comparison with crop yield, were obtained for images acquired in later phenological phases, e.g. in 2007 - BBCH 59 - average correlation coefficient 0.856, and in 2011 - BBCH 59-0.784. GreenSeeker handheld crop sensor was not suitable for yield estimation due to different measuring method.

A Systems Modeling Approach to Forecast Corn Economic Optimum Nitrogen Rate.

PubMed

Puntel, Laila A; Sawyer, John E; Barker, Daniel W; Thorburn, Peter J; Castellano, Michael J; Moore, Kenneth J; VanLoocke, Andrew; Heaton, Emily A; Archontoulis, Sotirios V

2018-01-01

Historically crop models have been used to evaluate crop yield responses to nitrogen (N) rates after harvest when it is too late for the farmers to make in-season adjustments. We hypothesize that the use of a crop model as an in-season forecast tool will improve current N decision-making. To explore this, we used the Agricultural Production Systems sIMulator (APSIM) calibrated with long-term experimental data for central Iowa, USA (16-years in continuous corn and 15-years in soybean-corn rotation) combined with actual weather data up to a specific crop stage and historical weather data thereafter. The objectives were to: (1) evaluate the accuracy and uncertainty of corn yield and economic optimum N rate (EONR) predictions at four forecast times (planting time, 6th and 12th leaf, and silking phenological stages); (2) determine whether the use of analogous historical weather years based on precipitation and temperature patterns as opposed to using a 35-year dataset could improve the accuracy of the forecast; and (3) quantify the value added by the crop model in predicting annual EONR and yields using the site-mean EONR and the yield at the EONR to benchmark predicted values. Results indicated that the mean corn yield predictions at planting time ( R 2 = 0.77) using 35-years of historical weather was close to the observed and predicted yield at maturity ( R 2 = 0.81). Across all forecasting times, the EONR predictions were more accurate in corn-corn than soybean-corn rotation (relative root mean square error, RRMSE, of 25 vs. 45%, respectively). At planting time, the APSIM model predicted the direction of optimum N rates (above, below or at average site-mean EONR) in 62% of the cases examined ( n = 31) with an average error range of ±38 kg N ha -1 (22% of the average N rate). Across all forecast times, prediction error of EONR was about three times higher than yield predictions. The use of the 35-year weather record was better than using selected historical weather years to forecast (RRMSE was on average 3% lower). Overall, the proposed approach of using the crop model as a forecasting tool could improve year-to-year predictability of corn yields and optimum N rates. Further improvements in modeling and set-up protocols are needed toward more accurate forecast, especially for extreme weather years with the most significant economic and environmental cost.

A Systems Modeling Approach to Forecast Corn Economic Optimum Nitrogen Rate

PubMed Central

Puntel, Laila A.; Sawyer, John E.; Barker, Daniel W.; Thorburn, Peter J.; Castellano, Michael J.; Moore, Kenneth J.; VanLoocke, Andrew; Heaton, Emily A.; Archontoulis, Sotirios V.

2018-01-01

Historically crop models have been used to evaluate crop yield responses to nitrogen (N) rates after harvest when it is too late for the farmers to make in-season adjustments. We hypothesize that the use of a crop model as an in-season forecast tool will improve current N decision-making. To explore this, we used the Agricultural Production Systems sIMulator (APSIM) calibrated with long-term experimental data for central Iowa, USA (16-years in continuous corn and 15-years in soybean-corn rotation) combined with actual weather data up to a specific crop stage and historical weather data thereafter. The objectives were to: (1) evaluate the accuracy and uncertainty of corn yield and economic optimum N rate (EONR) predictions at four forecast times (planting time, 6th and 12th leaf, and silking phenological stages); (2) determine whether the use of analogous historical weather years based on precipitation and temperature patterns as opposed to using a 35-year dataset could improve the accuracy of the forecast; and (3) quantify the value added by the crop model in predicting annual EONR and yields using the site-mean EONR and the yield at the EONR to benchmark predicted values. Results indicated that the mean corn yield predictions at planting time (R2 = 0.77) using 35-years of historical weather was close to the observed and predicted yield at maturity (R2 = 0.81). Across all forecasting times, the EONR predictions were more accurate in corn-corn than soybean-corn rotation (relative root mean square error, RRMSE, of 25 vs. 45%, respectively). At planting time, the APSIM model predicted the direction of optimum N rates (above, below or at average site-mean EONR) in 62% of the cases examined (n = 31) with an average error range of ±38 kg N ha−1 (22% of the average N rate). Across all forecast times, prediction error of EONR was about three times higher than yield predictions. The use of the 35-year weather record was better than using selected historical weather years to forecast (RRMSE was on average 3% lower). Overall, the proposed approach of using the crop model as a forecasting tool could improve year-to-year predictability of corn yields and optimum N rates. Further improvements in modeling and set-up protocols are needed toward more accurate forecast, especially for extreme weather years with the most significant economic and environmental cost. PMID:29706974

Yield stability of processing sweet corn and relationship to genotype adoption

USDA-ARS?s Scientific Manuscript database

Yield stability is a crop genotype’s performance over a range of environmental conditions, such that a specific genotype may be less sensitive to environmental change (i.e. above-average stability) or more sensitive to environmental change (i.e. below-average stability) relative to other genotypes. ...

Climate Variability and Yields of Major Staple Food Crops in Northern Ghana

NASA Astrophysics Data System (ADS)

Amikuzuno, J.

2012-12-01

Climate variability, the short-term fluctuations in average weather conditions, and agriculture affect each other. Climate variability affects the agroecological and growing conditions of crops and livestock, and is recently believed to be the greatest impediment to the realisation of the first Millennium Development Goal of reducing poverty and food insecurity in arid and semi-arid regions of developing countries. Conversely, agriculture is a major contributor to climate variability and change by emitting greenhouse gases and reducing the agroecology's potential for carbon sequestration. What however, is the empirical evidence of this inter-dependence of climate variability and agriculture in Sub-Sahara Africa? In this paper, we provide some insight into the long run relationship between inter-annual variations in temperature and rainfall, and annual yields of the most important staple food crops in Northern Ghana. Applying pooled panel data of rainfall, temperature and yields of the selected crops from 1976 to 2010 to cointegration and Granger causality models, there is cogent evidence of cointegration between seasonal, total rainfall and crop yields; and causality from rainfall to crop yields in the Sudano-Guinea Savannah and Guinea Savannah zones of Northern Ghana. This suggests that inter-annual yields of the crops have been influenced by the total mounts of rainfall in the planting season. Temperature variability over the study period is however stationary, and is suspected to have minimal effect if any on crop yields. Overall, the results confirm the appropriateness of our attempt in modelling long-term relationships between the climate and crop yield variables.

Contribution of insect pollinators to crop yield and quality varies with agricultural intensification

PubMed Central

Potts, Simon G.; Steffan-Dewenter, Ingolf; Vaissière, Bernard E.; Woyciechowski, Michal; Krewenka, Kristin M.; Tscheulin, Thomas; Roberts, Stuart P.M.; Szentgyörgyi, Hajnalka; Westphal, Catrin; Bommarco, Riccardo

2014-01-01

Background. Up to 75% of crop species benefit at least to some degree from animal pollination for fruit or seed set and yield. However, basic information on the level of pollinator dependence and pollinator contribution to yield is lacking for many crops. Even less is known about how insect pollination affects crop quality. Given that habitat loss and agricultural intensification are known to decrease pollinator richness and abundance, there is a need to assess the consequences for different components of crop production. Methods. We used pollination exclusion on flowers or inflorescences on a whole plant basis to assess the contribution of insect pollination to crop yield and quality in four flowering crops (spring oilseed rape, field bean, strawberry, and buckwheat) located in four regions of Europe. For each crop, we recorded abundance and species richness of flower visiting insects in ten fields located along a gradient from simple to heterogeneous landscapes. Results. Insect pollination enhanced average crop yield between 18 and 71% depending on the crop. Yield quality was also enhanced in most crops. For instance, oilseed rape had higher oil and lower chlorophyll contents when adequately pollinated, the proportion of empty seeds decreased in buckwheat, and strawberries’ commercial grade improved; however, we did not find higher nitrogen content in open pollinated field beans. Complex landscapes had a higher overall species richness of wild pollinators across crops, but visitation rates were only higher in complex landscapes for some crops. On the contrary, the overall yield was consistently enhanced by higher visitation rates, but not by higher pollinator richness. Discussion. For the four crops in this study, there is clear benefit delivered by pollinators on yield quantity and/or quality, but it is not maximized under current agricultural intensification. Honeybees, the most abundant pollinator, might partially compensate the loss of wild pollinators in some areas, but our results suggest the need of landscape-scale actions to enhance wild pollinator populations. PMID:24749007

Contribution of insect pollinators to crop yield and quality varies with agricultural intensification.

PubMed

Bartomeus, Ignasi; Potts, Simon G; Steffan-Dewenter, Ingolf; Vaissière, Bernard E; Woyciechowski, Michal; Krewenka, Kristin M; Tscheulin, Thomas; Roberts, Stuart P M; Szentgyörgyi, Hajnalka; Westphal, Catrin; Bommarco, Riccardo

2014-01-01

Background. Up to 75% of crop species benefit at least to some degree from animal pollination for fruit or seed set and yield. However, basic information on the level of pollinator dependence and pollinator contribution to yield is lacking for many crops. Even less is known about how insect pollination affects crop quality. Given that habitat loss and agricultural intensification are known to decrease pollinator richness and abundance, there is a need to assess the consequences for different components of crop production. Methods. We used pollination exclusion on flowers or inflorescences on a whole plant basis to assess the contribution of insect pollination to crop yield and quality in four flowering crops (spring oilseed rape, field bean, strawberry, and buckwheat) located in four regions of Europe. For each crop, we recorded abundance and species richness of flower visiting insects in ten fields located along a gradient from simple to heterogeneous landscapes. Results. Insect pollination enhanced average crop yield between 18 and 71% depending on the crop. Yield quality was also enhanced in most crops. For instance, oilseed rape had higher oil and lower chlorophyll contents when adequately pollinated, the proportion of empty seeds decreased in buckwheat, and strawberries' commercial grade improved; however, we did not find higher nitrogen content in open pollinated field beans. Complex landscapes had a higher overall species richness of wild pollinators across crops, but visitation rates were only higher in complex landscapes for some crops. On the contrary, the overall yield was consistently enhanced by higher visitation rates, but not by higher pollinator richness. Discussion. For the four crops in this study, there is clear benefit delivered by pollinators on yield quantity and/or quality, but it is not maximized under current agricultural intensification. Honeybees, the most abundant pollinator, might partially compensate the loss of wild pollinators in some areas, but our results suggest the need of landscape-scale actions to enhance wild pollinator populations.

Understanding the Changes in Global Crop Yields Through Changes in Climate and Technology

NASA Astrophysics Data System (ADS)

Najafi, Ehsan; Devineni, Naresh; Khanbilvardi, Reza M.; Kogan, Felix

2018-03-01

During the last few decades, the global agricultural production has risen and technology enhancement is still contributing to yield growth. However, population growth, water crisis, deforestation, and climate change threaten the global food security. An understanding of the variables that caused past changes in crop yields can help improve future crop prediction models. In this article, we present a comprehensive global analysis of the changes in the crop yields and how they relate to different large-scale and regional climate variables, climate change variables and technology in a unified framework. A new multilevel model for yield prediction at the country level is developed and demonstrated. The structural relationships between average yield and climate attributes as well as trends are estimated simultaneously. All countries are modeled in a single multilevel model with partial pooling to automatically group and reduce estimation uncertainties. El Niño-southern oscillation (ENSO), Palmer drought severity index (PDSI), geopotential height anomalies (GPH), historical carbon dioxide (CO2) concentration and country-based time series of GDP per capita as an approximation of technology measurement are used as predictors to estimate annual agricultural crop yields for each country from 1961 to 2013. Results indicate that these variables can explain the variability in historical crop yields for most of the countries and the model performs well under out-of-sample verifications. While some countries were not generally affected by climatic factors, PDSI and GPH acted both positively and negatively in different regions for crop yields in many countries.

Benefits of seasonal forecasts of crop yields

NASA Astrophysics Data System (ADS)

Sakurai, G.; Okada, M.; Nishimori, M.; Yokozawa, M.

2017-12-01

Major factors behind recent fluctuations in food prices include increased biofuel production and oil price fluctuations. In addition, several extreme climate events that reduced worldwide food production coincided with upward spikes in food prices. The stabilization of crop yields is one of the most important tasks to stabilize food prices and thereby enhance food security. Recent development of technologies related to crop modeling and seasonal weather forecasting has made it possible to forecast future crop yields for maize and soybean. However, the effective use of these technologies remains limited. Here we present the potential benefits of seasonal crop-yield forecasts on a global scale for choice of planting day. For this purpose, we used a model (PRYSBI-2) that can well replicate past crop yields both for maize and soybean. This model system uses a Bayesian statistical approach to estimate the parameters of a basic process-based model of crop growth. The spatial variability of model parameters was considered by estimating the posterior distribution of the parameters from historical yield data by using the Markov-chain Monte Carlo (MCMC) method with a resolution of 1.125° × 1.125°. The posterior distributions of model parameters were estimated for each spatial grid with 30 000 MCMC steps of 10 chains each. By using this model and the estimated parameter distributions, we were able to estimate not only crop yield but also levels of associated uncertainty. We found that the global average crop yield increased about 30% as the result of the optimal selection of planting day and that the seasonal forecast of crop yield had a large benefit in and near the eastern part of Brazil and India for maize and the northern area of China for soybean. In these countries, the effects of El Niño and Indian Ocean dipole are large. The results highlight the importance of developing a system to forecast global crop yields.

Salience Assignment for Multiple-Instance Data and Its Application to Crop Yield Prediction

NASA Technical Reports Server (NTRS)

Wagstaff, Kiri L.; Lane, Terran

2010-01-01

An algorithm was developed to generate crop yield predictions from orbital remote sensing observations, by analyzing thousands of pixels per county and the associated historical crop yield data for those counties. The algorithm determines which pixels contain which crop. Since each known yield value is associated with thousands of individual pixels, this is a multiple instance learning problem. Because individual crop growth is related to the resulting yield, this relationship has been leveraged to identify pixels that are individually related to corn, wheat, cotton, and soybean yield. Those that have the strongest relationship to a given crop s yield values are most likely to contain fields with that crop. Remote sensing time series data (a new observation every 8 days) was examined for each pixel, which contains information for that pixel s growth curve, peak greenness, and other relevant features. An alternating-projection (AP) technique was used to first estimate the "salience" of each pixel, with respect to the given target (crop yield), and then those estimates were used to build a regression model that relates input data (remote sensing observations) to the target. This is achieved by constructing an exemplar for each crop in each county that is a weighted average of all the pixels within the county; the pixels are weighted according to the salience values. The new regression model estimate then informs the next estimate of the salience values. By iterating between these two steps, the algorithm converges to a stable estimate of both the salience of each pixel and the regression model. The salience values indicate which pixels are most relevant to each crop under consideration.

Crop responses to elevated CO2 and interactions with H2O, N, and temperature.

PubMed

Kimball, Bruce A

2016-06-01

About twenty-seven years ago, free-air CO2 enrichment (FACE) technology was developed that enabled the air above open-field plots to be enriched with CO2 for entire growing seasons. Since then, FACE experiments have been conducted on cotton, wheat, ryegrass, clover, potato, grape, rice, barley, sugar beet, soybean, cassava, rape, mustard, coffee (C3 crops), and sorghum and maize (C4 crops). Elevated CO2 (550ppm from an ambient concentration of about 353ppm in 1990) decreased evapotranspiration about 10% on average and increased canopy temperatures about 0.7°C. Biomass and yield were increased by FACE in all C3 species, but not in C4 species except when water was limiting. Yields of C3 grain crops were increased on average about 19%. Copyright © 2016 Elsevier Ltd. All rights reserved.

Biochar boosts tropical but not temperate crop yields

NASA Astrophysics Data System (ADS)

Jeffery, Simon; Abalos, Diego; Prodana, Marija; Catarina Bastos, Ana; van Groenigen, Jan Willem; Hungate, Bruce A.; Verheijen, Frank

2017-05-01

Applying biochar to soil is thought to have multiple benefits, from helping mitigate climate change [1, 2], to managing waste [3] to conserving soil [4]. Biochar is also widely assumed to boost crop yield [5, 6], but there is controversy regarding the extent and cause of any yield benefit [7]. Here we use a global-scale meta-analysis to show that biochar has, on average, no effect on crop yield in temperate latitudes, yet elicits a 25% average increase in yield in the tropics. In the tropics, biochar increased yield through liming and fertilization, consistent with the low soil pH, low fertility, and low fertilizer inputs typical of arable tropical soils. We also found that, in tropical soils, high-nutrient biochar inputs stimulated yield substantially more than low-nutrient biochar, further supporting the role of nutrient fertilization in the observed yield stimulation. In contrast, arable soils in temperate regions are moderate in pH, higher in fertility, and generally receive higher fertilizer inputs, leaving little room for additional benefits from biochar. Our findings demonstrate that the yield-stimulating effects of biochar are not universal, but may especially benefit agriculture in low-nutrient, acidic soils in the tropics. Biochar management in temperate zones should focus on potential non-yield benefits such as lime and fertilizer cost savings, greenhouse gas emissions control, and other ecosystem services.

A comprehensively quantitative method of evaluating the impact of drought on crop yield using daily multi-scale SPEI and crop growth process model.

PubMed

Wang, Qianfeng; Wu, Jianjun; Li, Xiaohan; Zhou, Hongkui; Yang, Jianhua; Geng, Guangpo; An, Xueli; Liu, Leizhen; Tang, Zhenghong

2017-04-01

The quantitative evaluation of the impact of drought on crop yield is one of the most important aspects in agricultural water resource management. To assess the impact of drought on wheat yield, the Environmental Policy Integrated Climate (EPIC) crop growth model and daily Standardized Precipitation Evapotranspiration Index (SPEI), which is based on daily meteorological data, are adopted in the Huang Huai Hai Plain. The winter wheat crop yields are estimated at 28 stations, after calibrating the cultivar coefficients based on the experimental site data, and SPEI data was taken 11 times across the growth season from 1981 to 2010. The relationship between estimated yield and multi-scale SPEI were analyzed. The optimum time scale SPEI to monitor drought during the crop growth period was determined. The reference yield was determined by averaging the yields from numerous non-drought years. From this data, we propose a comprehensive quantitative method which can be used to predict the impact of drought on wheat yields by combining the daily multi-scale SPEI and crop growth process model. This method was tested in the Huang Huai Hai Plain. The results suggested that estimation of calibrated EPIC was a good predictor of crop yield in the Huang Huai Hai Plain, with lower RMSE (15.4 %) between estimated yield and observed yield at six agrometeorological stations. The soil moisture at planting time was affected by the precipitation and evapotranspiration during the previous 90 days (about 3 months) in the Huang Huai Hai Plain. SPEI G90 was adopted as the optimum time scale SPEI to identify the drought and non-drought years, and identified a drought year in 2000. The water deficit in the year 2000 was significant, and the rate of crop yield reduction did not completely correspond with the volume of water deficit. Our proposed comprehensive method which quantitatively evaluates the impact of drought on crop yield is reliable. The results of this study further our understanding why the adoption of counter measures against drought is important and direct farmers to choose drought-resistant crops.

The Use of Cover Crops as Climate-Smart Management in Midwest Cropping Systems

NASA Astrophysics Data System (ADS)

Basche, A.; Miguez, F.; Archontoulis, S.; Kaspar, T.

2014-12-01

The observed trends in the Midwestern United States of increasing rainfall variability will likely continue into the future. Events such as individual days of heavy rain as well as seasons of floods and droughts have large impacts on agricultural productivity and the natural resource base that underpins it. Such events lead to increased soil erosion, decreased water quality and reduced corn and soybean yields. Winter cover crops offer the potential to buffer many of these impacts because they essentially double the time for a living plant to protect and improve the soil. However, at present, cover crops are infrequently utilized in the Midwest (representing 1-2% of row cropped land cover) in particular due to producer concerns over higher costs and management, limited time and winter growing conditions as well as the potential harm to corn yields. In order to expand their use, there is a need to quantify how cover crops impact Midwest cropping systems in the long term and namely to understand how to optimize the benefits of cover crops while minimizing their impacts on cash crops. We are working with APSIM, a cropping systems platform, to specifically quantify the long term future impacts of cover crop incorporation in corn-based cropping systems. In general, our regional analysis showed only minor changes to corn and soybean yields (<1% differences) when a cover crop was or was not included in the simulation. Further, a "bad spring" scenario (where every third year had an abnormally wet/cold spring and cover crop termination and planting cash crop were within one day) did not result in any major changes to cash crop yields. Through simulations we estimate an average increase of 4-9% organic matter improvement in the topsoil and an average decrease in soil erosion of 14-32% depending on cover crop planting date and growth. Our work is part of the Climate and Corn-based Cropping Systems Coordinated Agriculture Project (CSCAP), a collaboration of eleven Midwestern institutions established to evaluate how conservation practices, including cover crops, improve the resilience of Midwest agriculture to future change. Such collaborations can help better quantify long term impacts of conservation practices on the landscape that ultimately lead to more climate-smart management of such agricultural systems.

System dynamics approach for modeling of sugar beet yield considering the effects of climatic variables.

PubMed

Pervin, Lia; Islam, Md Saiful

2015-02-01

The aim of this study was to develop a system dynamics model for computation of yields and to investigate the dependency of yields on some major climatic parameters, i.e. temperature and rainfall, for Beta vulgaris subsp. (sugar beet crops) under future climate change scenarios. A system dynamics model was developed which takes account of the effects of rainfall and temperature on sugar beet yields under limited irrigation conditions. A relationship was also developed between the seasonal evapotranspiration and seasonal growing degree days for sugar beet crops. The proposed model was set to run for the present time period of 1993-2012 and for the future period 2013-2040 for Lethbridge region (Alberta, Canada). The model provides sugar beet yields on a yearly basis which are comparable to the present field data. It was found that the future average yield will be increased at about 14% with respect to the present average yield. The proposed model can help to improve the understanding of soil water conditions and irrigation water requirements of an area under certain climatic conditions and can be used for future prediction of yields for any crops in any region (with the required information to be provided). The developed system dynamics model can be used as a supporting tool for decision making, for improvement of agricultural management practice of any region. © 2014 Society of Chemical Industry.

Crop response to deep tillage - a meta-analysis

NASA Astrophysics Data System (ADS)

Schneider, Florian; Don, Axel; Hennings, Inga; Schmittmann, Oliver; Seidel, Sabine J.

2017-04-01

Subsoil, i.e. the soil layer below the topsoil, stores tremendous stocks of nutrients and can keep water even under drought conditions. Deep tillage may be a method to enhance the plant-availability of subsoil resources. However, in field trials, deep tillage effects on crop yields were inconsistent. Therefore, we conducted a meta-analysis of crop yield response to subsoiling, deep ploughing and deep mixing of soil profiles. Our search resulted in 1530 yield comparisons following deep and conventional control tillage on 67 experimental cropping sites. The vast majority of the data derived from temperate latitudes, from trials conducted in the USA (679 observations) and Germany (630 observations). On average, crop yield response to deep tillage was slightly positive (6% increase). However, individual deep tillage effects were highly scattered including about 40% yield depressions after deep tillage. Deep tillage on soils with root restrictive layers increased crop yields about 20%, while soils containing >70% silt increased the risk of yield depressions following deep tillage. Generally, deep tillage effects increased with drought intensity indicating deep tillage as climate adaptation measure at certain sites. Our results suggest that deep tillage can facilitate the plant-availability of subsoil nutrients, which increases crop yields if (i) nutrients in the topsoil are growth limiting, and (ii) deep tillage does not come at the cost of impairing topsoil fertility. On sites with root restrictive soil layers, deep tillage can be an effective measure to mitigate drought stress and improve the resilience of crops. However, deep tillage should only be performed on soils with a stable structure, i.e. <70% silt content. We will discuss the contribution of deep tillage options to enhance the sustainability of agricultural production by facilitating the uptake of nutrients and water from the subsoil.

Potential economic benefits of adapting agricultural production systems to future climate change

USGS Publications Warehouse

Fagre, Daniel B.; Pederson, Gregory; Bengtson, Lindsey E.; Prato, Tony; Qui, Zeyuan; Williams, Jimmie R.

2010-01-01

Potential economic impacts of future climate change on crop enterprise net returns and annual net farm income (NFI) are evaluated for small and large representative farms in Flathead Valley in Northwest Montana. Crop enterprise net returns and NFI in an historical climate period (1960–2005) and future climate period (2006–2050) are compared when agricultural production systems (APSs) are adapted to future climate change. Climate conditions in the future climate period are based on the A1B, B1, and A2 CO2 emission scenarios from the Intergovernmental Panel on Climate Change Fourth Assessment Report. Steps in the evaluation include: (1) specifying crop enterprises and APSs (i.e., combinations of crop enterprises) in consultation with locals producers; (2) simulating crop yields for two soils, crop prices, crop enterprises costs, and NFIs for APSs; (3) determining the dominant APS in the historical and future climate periods in terms of NFI; and (4) determining whether NFI for the dominant APS in the historical climate period is superior to NFI for the dominant APS in the future climate period. Crop yields are simulated using the Environmental/Policy Integrated Climate (EPIC) model and dominance comparisons for NFI are based on the stochastic efficiency with respect to a function (SERF) criterion. Probability distributions that best fit the EPIC-simulated crop yields are used to simulate 100 values for crop yields for the two soils in the historical and future climate periods. Best-fitting probability distributions for historical inflation-adjusted crop prices and specified triangular probability distributions for crop enterprise costs are used to simulate 100 values for crop prices and crop enterprise costs. Averaged over all crop enterprises, farm sizes, and soil types, simulated net return per ha averaged over all crop enterprises decreased 24% and simulated mean NFI for APSs decreased 57% between the historical and future climate periods. Although adapting APSs to future climate change is advantageous (i.e., NFI with adaptation is superior to NFI without adaptation based on SERF), in six of the nine cases in which adaptation is advantageous, NFI with adaptation in the future climate period is inferior to NFI in the historical climate period. Therefore, adaptation of APSs to future climate change in Flathead Valley is insufficient to offset the adverse impacts on NFI of such change.

Potential economic benefits of adapting agricultural production systems to future climate change.

PubMed

Prato, Tony; Zeyuan, Qiu; Pederson, Gregory; Fagre, Dan; Bengtson, Lindsey E; Williams, Jimmy R

2010-03-01

Potential economic impacts of future climate change on crop enterprise net returns and annual net farm income (NFI) are evaluated for small and large representative farms in Flathead Valley in Northwest Montana. Crop enterprise net returns and NFI in an historical climate period (1960-2005) and future climate period (2006-2050) are compared when agricultural production systems (APSs) are adapted to future climate change. Climate conditions in the future climate period are based on the A1B, B1, and A2 CO(2) emission scenarios from the Intergovernmental Panel on Climate Change Fourth Assessment Report. Steps in the evaluation include: (1) specifying crop enterprises and APSs (i.e., combinations of crop enterprises) in consultation with locals producers; (2) simulating crop yields for two soils, crop prices, crop enterprises costs, and NFIs for APSs; (3) determining the dominant APS in the historical and future climate periods in terms of NFI; and (4) determining whether NFI for the dominant APS in the historical climate period is superior to NFI for the dominant APS in the future climate period. Crop yields are simulated using the Environmental/Policy Integrated Climate (EPIC) model and dominance comparisons for NFI are based on the stochastic efficiency with respect to a function (SERF) criterion. Probability distributions that best fit the EPIC-simulated crop yields are used to simulate 100 values for crop yields for the two soils in the historical and future climate periods. Best-fitting probability distributions for historical inflation-adjusted crop prices and specified triangular probability distributions for crop enterprise costs are used to simulate 100 values for crop prices and crop enterprise costs. Averaged over all crop enterprises, farm sizes, and soil types, simulated net return per ha averaged over all crop enterprises decreased 24% and simulated mean NFI for APSs decreased 57% between the historical and future climate periods. Although adapting APSs to future climate change is advantageous (i.e., NFI with adaptation is superior to NFI without adaptation based on SERF), in six of the nine cases in which adaptation is advantageous, NFI with adaptation in the future climate period is inferior to NFI in the historical climate period. Therefore, adaptation of APSs to future climate change in Flathead Valley is insufficient to offset the adverse impacts on NFI of such change.

Impacts of soil and groundwater salinization on tree crop performance in post-tsunami Aceh Barat, Indonesia

NASA Astrophysics Data System (ADS)

Marohn, C.; Distel, A.; Dercon, G.; Wahyunto; Tomlinson, R.; Noordwijk, M. v.; Cadisch, G.

2012-09-01

The Indian Ocean tsunami of December 2004 had far reaching consequences for agriculture in Aceh province, Indonesia, and particularly in Aceh Barat district, 150 km from the seaquake epicentre. In this study, the spatial distribution and temporal dynamics of soil and groundwater salinity and their impact on tree crops were monitored in Aceh Barat from 2006 to 2008. On 48 sampling points along ten transects, covering 40 km of coastline, soil and groundwater salinity were measured and related to mortality and yield depression of the locally most important tree crops. Given a yearly rainfall of over 3000 mm, initial groundwater salinity declined rapidly from over 10 to less than 2 mS cm-1 within two years. On the other hand, seasonal dynamics of the groundwater table in combination with intrusion of saline water into the groundwater body led to recurring elevated salinity, sufficient to affect crops. Tree mortality and yield depression in the flooded area varied considerably between tree species. Damage to coconut (65% trees damaged) was related to tsunami run-up height, while rubber (50% trees damaged) was mainly affected by groundwater salinity. Coconut yields (-35% in average) were constrained by groundwater Ca2+ and Mg2+, while rubber yields (-65% on average) were related to groundwater chloride, pH and soil sodium. These findings have implications on planting deep-rooted tree crops as growth will be constrained by ongoing oscillations of the groundwater table and salinity.

Understanding the Impact of Extreme Temperature on Crop Production in Karnataka in India

NASA Astrophysics Data System (ADS)

Mahato, S.; Murari, K. K.; Jayaraman, T.

2017-12-01

The impact of extreme temperature on crop yield is seldom explored in work around climate change impact on agriculture. Further, these studies are restricted mainly to crops such as wheat and maize. Since different agro-climatic zones bear different crops and cropping patterns, it is important to explore the nature of the impact of changes in climate variables in agricultural systems under differential conditions. The study explores the effects of temperature rise on the major crops paddy, jowar, ragi and tur in the state of Karnataka of southern India. The choice of the unit of study to understand impact of climate variability on crop yields is largely restricted to availability of data for the unit. While, previous studies have dealt with this issue by replacing yield with NDVI at finer resolution, the use of an index in place of yield data has its limitations and may not reflect the true estimates. For this study, the unit considered is taluk, i.e. sub-district level. The crop yield for taluk is obtained between the year the 1995 to 2011 by aggregating point yield data from crop cutting experiments for each year across the taluks. The long term temperature data shows significantly increasing trend that ranges between 0.6 to 0.75 C across Karnataka. Further, the analysis suggests a warming trend in seasonal average temperature for Kharif and Rabi seasons across districts. The study also found that many districts exhibit the tendency of occurrence of extreme temperature days, which is of particular concern in terms of crop yield, since exposure of crops to extreme temperature has negative consequences for crop production and productivity. Using growing degree days GDD, extreme degree days EDD and total season rainfall as predictor variables, the fixed effect model shows that EDD is a more influential parameter as compared to GDD and rainfall. Also it has a statistically significant negative effect in most cases. Further, quantile regression was used to evaluate the robustness of the estimates of EDD in relation to crop yield. This showed the estimates to be robust across quantiles for most of the crops studied. Thus indicating a strong negative influence of exposure to extreme temperature on crop yield in the region.

Impacts of climate variability and change on crop yield in sub-Sahara Africa

NASA Astrophysics Data System (ADS)

Pan, S.; Zhang, J.; Yang, J.; Chen, G.; Xu, R.; Zhang, B.; Lou, Y.

2017-12-01

Much concern has been raised about the impacts of climate change and climate extremes on Africa's food security. The impact of climate change on Africa's agriculture is likely to be severe compared to other continents due to high rain-fed agricultural dependence, and limited ability to mitigate and adapt to climate change. In recent decades, warming in Africa is more pronounced and faster than the global average and this trend is likely to continue in the future. However, quantitative assessment on impacts of climate extremes and climate change on crop yield has not been well investigated yet. By using an improved agricultural module of the Dynamic Land Ecosystem Model (DLEM-AG2) driven by spatially-explicit information on land use, climate and other environmental changes, we have assessed impacts of historical climate variability and future climate change on food crop yield across the sub-Sahara Africa during1980-2016 and the rest of the 21st century (2017-2099). Our simulated results indicate that African crop yield in the past three decades shows an increasing trend primarily due to cropland expansion. However, crop yield shows substantially spatial and temporal variation due to inter-annual and inter-decadal climate variability and spatial heterogeneity of environmental drivers. Droughts have largely reduced crop yield in the most vulnerable regions of Sub-Sahara Africa. Future projections with DLEM-AG2 show that food crop production in Sub-Sahara Africa would be favored with limiting end-of-century warming to below 1.50 C.

Analysis of a large dataset of mycorrhiza inoculation field trials on potato shows highly significant increases in yield.

PubMed

Hijri, Mohamed

2016-04-01

An increasing human population requires more food production in nutrient-efficient systems in order to simultaneously meet global food needs while reducing the environmental footprint of agriculture. Arbuscular mycorrhizal fungi (AMF) have the potential to enhance crop yield, but their efficiency has yet to be demonstrated in large-scale crop production systems. This study reports an analysis of a dataset consisting of 231 field trials in which the same AMF inoculant (Rhizophagus irregularis DAOM 197198) was applied to potato over a 4-year period in North America and Europe under authentic field conditions. The inoculation was performed using a liquid suspension of AMF spores that was sprayed onto potato seed pieces, yielding a calculated 71 spores per seed piece. Statistical analysis showed a highly significant increase in marketable potato yield (ANOVA, P < 0.0001) for inoculated fields (42.2 tons/ha) compared with non-inoculated controls (38.3 tons/ha), irrespective of trial year. The average yield increase was 3.9 tons/ha, representing 9.5 % of total crop yield. Inoculation was profitable with a 0.67-tons/ha increase in yield, a threshold reached in almost 79 % of all trials. This finding clearly demonstrates the benefits of mycorrhizal-based inoculation on crop yield, using potato as a case study. Further improvements of these beneficial inoculants will help compensate for crop production deficits, both now and in the future.

Crop yield and light/energy efficiency in a closed ecological system: Laboratory Biosphere experiments with wheat and sweet potato

NASA Astrophysics Data System (ADS)

Nelson, M.; Dempster, W. F.; Silverstone, S.; Alling, A.; Allen, J. P.; van Thillo, M.

Two crop growth experiments in the soil-based closed ecological facility, Laboratory Biosphere, were conducted from 2003 to 2004 with candidate space life support crops. Apogee wheat (Utah State University variety) was grown, planted at two densities, 400 and 800 seeds m -2. The lighting regime for the wheat crop was 16 h of light - 8 h dark at a total light intensity of around 840 μmol m -2 s -1 and 48.4 mol m -2 d -1 over 84 days. Average biomass was 1395 g m -2, 16.0 g m -2 d -1 and average seed production was 689 g m -2 and 7.9 g m -2 d -1. The less densely planted side was more productive than the denser planting, with 1634 g m -2 and 18.8 g m -2 d -1 of biomass vs. 1156 g m -2 and 13.3 g m -2 d -1; and a seed harvest of 812.3 g m -2 and 9.3 g m -2 d -1 vs. 566.5 g m -2 and 6.5 g m -2 d -1. Harvest index was 0.49 for the wheat crop. The experiment with sweet potato used TU-82-155 a compact variety developed at Tuskegee University. Light during the sweet potato experiment, on a 18 h on/6 h dark cycle, totaled 5568 total moles of light per square meter in 126 days for the sweet potatoes, or an average of 44.2 mol m -2 d -1. Temperature regime was 28 ± 3 °C day/22 ± 4 °C night. Sweet potato tuber yield was 39.7 kg wet weight, or an average of 7.4 kg m -2, and 7.7 kg dry weight of tubers since dry weight was about 18.6% wet weight. Average per day production was 58.7 g m -2 d -1 wet weight and 11.3 g m -2 d -1. For the wheat, average light efficiency was 0.34 g biomass per mole, and 0.17 g seed per mole. The best area of wheat had an efficiency of light utilization of 0.51 g biomass per mole and 0.22 g seed per mole. For the sweet potato crop, light efficiency per tuber wet weight was 1.33 g mol -1 and 0.34 g dry weight of tuber per mole of light. The best area of tuber production had 1.77 g mol -1 wet weight and 0.34 g mol -1 of light dry weight. The Laboratory Biosphere experiment's light efficiency was somewhat higher than the USU field results but somewhat below greenhouse trials at comparable light levels, and the best portion of the crop at 0.22 g mol -1 was in-between those values. Sweet potato production was overall close to 50% higher than trials using hydroponic methods with TU-82-155 at NASA JSC. Compared to projected yields for the Mars on Earth life support system, these wheat yields were about 15% higher, and the sweet potato yields averaged over 80% higher.

Crop yield and light / energy efficiency in a closed ecological system: two laboratory biosphere experiments

NASA Astrophysics Data System (ADS)

Nelson, M.; Dempster, W. F.; Silverstone, S.; Alling, A.; Allen, J. P.; van Thillo, M.

Two crop growth experiments in the soil-based closed ecological facity, Laboratory Biosphere, were conducted from 2003-2004 with candidate space life support crops. Apogee wheat (Utah State University variety) was grown, planted in 2 densities, 400 and 800 seeds m-2. The lighting regime for the wheat crop was 16 hours of light -- 8 hours dark at a total light intensity of around 840 mol m2 sec-1 and 48.4 mol m-2 d-1 over 84 days Average biomass was 1395 g m-2, 16.0 g m-2 day-1 and average seed production was 689 g m-2 and 7.9 g m2 day-1. The less densely planted side was more productive than the denser planting, with 1634 g m-2 and 18.8g m-2 day-1 of biomass vs. 1156 g m-2 and 13.3 g m-2 day-1; and a seed harvest of 812.3 g m-2 and 9.3 g m-2 day-1 vs. 566.5 g m-2 and 6.5 g m-2 day-1 Harvest index was 0.49 for the wheat crop. The experiment with sweet potato used TU-82-155, a compact variety developed at Tuskegee University. Light during the sweet potato experiment, on a 16 hour on/8 hours dark cycle, totalled 5568 total moles of light in 126 days for the sweet potatoes, or an average of 44.2 moles m-2 day-1. Temperature regime was 28 deg +/- 3 deg C day /22 deg +/- 4 deg C night. Sweet potato tuber yield was 39.7 kg wet weight, or an average of 7.4 kg m-2 and 7.7 kg dry weight of tubers since dry weight was about 18.6% wet weight.^Average per day production was 58.7 g m-2 day-1 wet weight and 11.3 g m-2 day-1. For the wheat, average light efficiency was 0.34 grams biomass per mole, and 0.17 grams seed per mole. The best area of wheat had an efficiency of light utilization of 0.51 g biomass per mole and 0.22 g seed per mole. For the sweet potato crop, light efficiency per tuber wet weight was 7.13 g/mole and 1.38 g dry weight of tuber per mole of light. The best area of tuber production had 9.49 g/mole wet weight and 1.85 g/mole of light dry weight. Production from the wheat was The Laboratory Biosphere experiment's light efficiency was somewhat higher than the USU field results but somewhat below greenhouse trials at comparable light levels, and the best portion of the crop at 0.22g/mole was inbetween those values. Sweet potato production was overall close to 50% higher than trials using hydroponic methods with TU-82-155 at NASA JSC. Compared to projected yields for the Mars on Earth life support system, these wheat yields were about 15% higher, and the sweet potato yields averaged over 80% higher

Rice Crop Monitoring and Yield Assessment with MODIS 250m Gridded Vegetation Products: A Case Study of Sa Kaeo Province, Thailand

NASA Astrophysics Data System (ADS)

Wijesingha, J. S. J.; Deshapriya, N. L.; Samarakoon, L.

2015-04-01

Billions of people in the world depend on rice as a staple food and as an income-generating crop. Asia is the leader in rice cultivation and it is necessary to maintain an up-to-date rice-related database to ensure food security as well as economic development. This study investigates general applicability of high temporal resolution Moderate Resolution Imaging Spectroradiometer (MODIS) 250m gridded vegetation product for monitoring rice crop growth, mapping rice crop acreage and analyzing crop yield, at the province-level. The MODIS 250m Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) time series data, field data and crop calendar information were utilized in this research in Sa Kaeo Province, Thailand. The following methodology was used: (1) data pre-processing and rice plant growth analysis using Vegetation Indices (VI) (2) extraction of rice acreage and start-of-season dates from VI time series data (3) accuracy assessment, and (4) yield analysis with MODIS VI. The results show a direct relationship between rice plant height and MODIS VI. The crop calendar information and the smoothed NDVI time series with Whittaker Smoother gave high rice acreage estimation (with 86% area accuracy and 75% classification accuracy). Point level yield analysis showed that the MODIS EVI is highly correlated with rice yield and yield prediction using maximum EVI in the rice cycle predicted yield with an average prediction error 4.2%. This study shows the immense potential of MODIS gridded vegetation product for keeping an up-to-date Geographic Information System of rice cultivation.

Breeding and Domesticating Crops Adapted to Drought and Salinity: A New Paradigm for Increasing Food Production

PubMed Central

Fita, Ana; Rodríguez-Burruezo, Adrián; Boscaiu, Monica; Prohens, Jaime; Vicente, Oscar

2015-01-01

World population is expected to reach 9.2 × 109 people by 2050. Feeding them will require a boost in crop productivity using innovative approaches. Current agricultural production is very dependent on large amounts of inputs and water availability is a major limiting factor. In addition, the loss of genetic diversity and the threat of climate change make a change of paradigm in plant breeding and agricultural practices necessary. Average yields in all major crops are only a small fraction of record yields, and drought and soil salinity are the main factors responsible for yield reduction. Therefore there is the need to enhance crop productivity by improving crop adaptation. Here we review the present situation and propose the development of crops tolerant to drought and salt stress for addressing the challenge of dramatically increasing food production in the near future. The success in the development of crops adapted to drought and salt depends on the efficient and combined use of genetic engineering and traditional breeding tools. Moreover, we propose the domestication of new halophilic crops to create a ‘saline agriculture’ which will not compete in terms of resources with conventional agriculture. PMID:26617620

Productivity and sustainability of rainfed wheat-soybean system in the North China Plain: results from a long-term experiment and crop modelling

PubMed Central

Qin, Wei; Wang, Daozhong; Guo, Xisheng; Yang, Taiming; Oenema, Oene

2015-01-01

A quantitative understanding of yield response to water and nutrients is key to improving the productivity and sustainability of rainfed cropping systems. Here, we quantified the effects of rainfall, fertilization (NPK) and soil organic amendments (with straw and manure) on yields of a rainfed wheat-soybean system in the North China Plain (NCP), using 30-years’ field experimental data (1982–2012) and the simulation model-AquaCrop. On average, wheat and soybean yields were 5 and 2.5 times higher in the fertilized treatments than in the unfertilized control (CK), respectively. Yields of fertilized treatments increased and yields of CK decreased over time. NPK + manure increased yields more than NPK alone or NPK + straw. The additional effect of manure is likely due to increased availability of K and micronutrients. Wheat yields were limited by rainfall and can be increased through soil mulching (15%) or irrigation (35%). In conclusion, combined applications of fertilizer NPK and manure were more effective in sustaining high crop yields than recommended fertilizer NPK applications. Manure applications led to strong accumulation of NPK and relatively low NPK use efficiencies. Water deficiency in wheat increased over time due to the steady increase in yields, suggesting that the need for soil mulching increases. PMID:26627707

Annual Crop-Yield Variation, Child Survival, and Nutrition Among Subsistence Farmers in Burkina Faso.

PubMed

Belesova, Kristine; Gasparrini, Antonio; Sié, Ali; Sauerborn, Rainer; Wilkinson, Paul

2018-02-01

Whether year-to-year variation in crop yields affects the nutrition, health, and survival of subsistence-farming populations is relevant to the understanding of the potential impacts of climate change. However, the empirical evidence is limited. We examined the associations of child survival with interannual variation in food crop yield and middle-upper arm circumference (MUAC) in a subsistence-farming population of rural Burkina Faso. The study was of 44,616 children aged <5 years included in the Nouna Health and Demographic Surveillance System, 1992-2012, whose survival was analyzed in relation to the food crop yield in the year of birth (which ranged from 65% to 120% of the period average) and, for a subset of 16,698 children, to MUAC, using shared-frailty Cox proportional hazards models. Survival was appreciably worse in children born in years with low yield (full-adjustment hazard ratio = 1.11 (95% confidence interval: 1.02, 1.20) for a 90th- to 10th-centile decrease in annual crop yield) and in children with small MUAC (hazard ratio = 2.72 (95% confidence interval: 2.15, 3.44) for a 90th- to 10th-centile decrease in MUAC). These results suggest an adverse impact of variations in crop yields, which could increase under climate change. © The Author(s) 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Crop and varietal diversification of rainfed rice based cropping systems for higher productivity and profitability in Eastern India

PubMed Central

Panda, B. B.; Raja, R.; Singh, Teekam; Tripathi, R.; Shahid, M.; Nayak, A. K.

2017-01-01

Rice-rice system and rice fallows are no longer productive in Southeast Asia. Crop and varietal diversification of the rice based cropping systems may improve the productivity and profitability of the systems. Diversification is also a viable option to mitigate the risk of climate change. In Eastern India, farmers cultivate rice during rainy season (June–September) and land leftovers fallow after rice harvest in the post-rainy season (November–May) due to lack of sufficient rainfall or irrigation amenities. However, in lowland areas, sufficient residual soil moistures are available in rice fallow in the post-rainy season (November–March), which can be utilized for raising second crops in the region. Implementation of suitable crop/varietal diversification is thus very much vital to achieve this objective. To assess the yield performance of rice varieties under timely and late sown conditions and to evaluate the performance of dry season crops following them, three different duration rice cultivars were transplanted in July and August. In dry season several non-rice crops were sown in rice fallow to constitute a cropping system. The results revealed that tiller occurrence, biomass accumulation, dry matter remobilization, crop growth rate, and ultimately yield were significantly decreased under late transplanting. On an average, around 30% yield reduction obtained under late sowing may be due to low temperature stress and high rainfall at reproductive stages of the crop. Dry season crops following short duration rice cultivars performed better in terms of grain yield. In the dry season, toria was profitable when sown earlier and if sowing was delayed greengram was suitable. Highest system productivity and profitability under timely sown rice may be due to higher dry matter remobilization from source to sink. A significant correlation was observed between biomass production and grain yield. We infer that late transplanting decrease the tiller occurrence and assimilate remobilization efficiency, which may be responsible for the reduced grain yield. PMID:28437487

Crop and varietal diversification of rainfed rice based cropping systems for higher productivity and profitability in Eastern India.

PubMed

Lal, B; Gautam, Priyanka; Panda, B B; Raja, R; Singh, Teekam; Tripathi, R; Shahid, M; Nayak, A K

2017-01-01

Rice-rice system and rice fallows are no longer productive in Southeast Asia. Crop and varietal diversification of the rice based cropping systems may improve the productivity and profitability of the systems. Diversification is also a viable option to mitigate the risk of climate change. In Eastern India, farmers cultivate rice during rainy season (June-September) and land leftovers fallow after rice harvest in the post-rainy season (November-May) due to lack of sufficient rainfall or irrigation amenities. However, in lowland areas, sufficient residual soil moistures are available in rice fallow in the post-rainy season (November-March), which can be utilized for raising second crops in the region. Implementation of suitable crop/varietal diversification is thus very much vital to achieve this objective. To assess the yield performance of rice varieties under timely and late sown conditions and to evaluate the performance of dry season crops following them, three different duration rice cultivars were transplanted in July and August. In dry season several non-rice crops were sown in rice fallow to constitute a cropping system. The results revealed that tiller occurrence, biomass accumulation, dry matter remobilization, crop growth rate, and ultimately yield were significantly decreased under late transplanting. On an average, around 30% yield reduction obtained under late sowing may be due to low temperature stress and high rainfall at reproductive stages of the crop. Dry season crops following short duration rice cultivars performed better in terms of grain yield. In the dry season, toria was profitable when sown earlier and if sowing was delayed greengram was suitable. Highest system productivity and profitability under timely sown rice may be due to higher dry matter remobilization from source to sink. A significant correlation was observed between biomass production and grain yield. We infer that late transplanting decrease the tiller occurrence and assimilate remobilization efficiency, which may be responsible for the reduced grain yield.

The role of climatic variables in winter cereal yields: a retrospective analysis.

PubMed

Luo, Qunying; Wen, Li

2015-02-01

This study examined the effects of observed climate including [CO2] on winter cereal [winter wheat (Triticum aestivum), barley (Hordeum vulgare) and oat (Avena sativa)] yields by adopting robust statistical analysis/modelling approaches (i.e. autoregressive fractionally integrated moving average, generalised addition model) based on long time series of historical climate data and cereal yield data at three locations (Moree, Dubbo and Wagga Wagga) in New South Wales, Australia. Research results show that (1) growing season rainfall was significantly, positively and non-linearly correlated with crop yield at all locations considered; (2) [CO2] was significantly, positively and non-linearly correlated with crop yields in all cases except wheat and barley yields at Wagga Wagga; (3) growing season maximum temperature was significantly, negatively and non-linearly correlated with crop yields at Dubbo and Moree (except for barley); and (4) radiation was only significantly correlated with oat yield at Wagga Wagga. This information will help to identify appropriate management adaptation options in dealing with the risk and in taking the opportunities of climate change.

Impact assessment and recommendation of alternative conjunctive water use strategies for salt affected agricultural lands through a field scale decision support system - a case study.

PubMed

Kaur, Ravinder; Paul, Madhumita; Malik, Rashmi

2007-06-01

Conjunctive use of saline/non-saline irrigation waters is generally aimed at minimizing yield losses and enhancing flexibility of cropping, without much alteration in farming operations. Recommendation of location-specific suitable conjunctive water use plans requires assessment of their long-term impacts on soil salinization/sodification and crop yield reductions. This is conventionally achieved through long-term field experiments. However such impact evaluations are site specific, expensive and time consuming. Appropriate decision support systems (DSS) can be time-efficient and cost-effective means for such long-term impact evaluations. This study demonstrates the application of one such (indigenously developed) DSS for recommending best conjunctive water use plans for a, rice-wheat growing, salt affected farmer's field in Gurgaon district of Haryana (India). Before application, the DSS was extensively validated on several farmers and controlled experimental fields in Gurgaon and Karnal districts of Haryana (India). Validation of DSS showed its potential to give realistic estimates of root zone soil salinity (with R = 0.76-0.94; AMRE = 0.03-0.06; RMSPD = 0.51-0.90); sodicity (with R = 0.99; AMRE = 0.02; RMSPD = 0.84) and relative crop yield reductions (AMRE = 0.24), under existing (local) resource management practices. Long term (10 years) root zone salt build ups and associated rice/wheat crop yield reductions, in a salt affected farmer's field, under varied conjunctive water use scenarios were evaluated with the validated DSS. It was observed that long-term applications of canal (CW) and tube well (TW) waters in a cycle and in 1:1 mixed mode, during Kharif season, predicted higher average root zone salt reductions (2-9%) and lower rice crop yield reductions (4-5%) than the existing practice of 3-CW, 3-TW, 3-CW. Besides this, long-term application of 75% CW mixed with 25% TW, during Rabi season, predicted about 17% lower average root-zone salt reductions than the cyclic applications of (1-CW, 1-TW, 2-CW) and (2-CW, 1-TW, 1-CW, i.e., existing irrigation strategy). However, average wheat crop yield reductions (16-17%) simulated under all these strategies were almost at par. In general, cyclic-conjunctive water use strategies emerged as better options than the blending modes. These results were in complete confirmation with actual long-term conjunctive water use experiments on similar soils. It was thus observed that such pre-validated tools could be efficient means for designing, local resource and target crop yield-specific, appropriate conjunctive water use plans for irrigated agricultural lands.

Hydrologic and related data for water-supply planning in an intensive-study area, northeastern Wichita County, Kansas

USGS Publications Warehouse

Kume, Jack; Dunlap, L.E.; Gutentag, E.D.; Thomas, J.G.

1979-01-01

Data are presented that result from an intensive geohydrologic study for water-supply planning in a 12-square-mile area in northeastern Wichita County, Kansas. These data include records of wells, test drilling, chemical analyses, ground-water levels, rainfall, soilmoisture, well yield, solar radiation, crop yield, and crop acreage. Data indicate that water levels in the unconsolidated aquifer are declining at an average annual rate of about 1 to 2 feet per year (1950-78). This decline is the aquifer's response to pumping by irrigation wells for watering corn, wheat, grain sorghum, and other crops.

GIS development to monitor climate change and its geohydrological consequences on non-monsoon crop pattern in Himalaya

NASA Astrophysics Data System (ADS)

Rawat, Pradeep K.

2014-09-01

The main objective of the study was to assess climate change and its geohydrological impacts on non-monsoon crop pattern at watershed level through GIS development on climate informatics, land use informatics, hydro-informatics and agro-informatics. The Dabka watershed constitutes a part of the Kosi Basin in densely populated Lesser Himalaya, India in district Nainital has been selected for the case illustration. This reconnaissance study analyzed the climatic database for last three decades (1982-2012) and estimates that the average temperature and evaporation loss have been rising with the rate of 0.07 °C/yr and 4.03 mm/yr respectively whereas the average rainfall has been decreasing with the rate of 0.60 mm/yr. These rates of climate change increasing with mounting elevations. Consequently the existing microclimatic zones (sub-tropical, temperate and moist temperate) shifting towards higher altitudes and affecting the favorable conditions of the land use pattern and decreased the eco-friendly forest and vegetation cover. The land use degradation and high rate of deforestation (0.22 km2 or 1.5%/yr) leads to accelerate several hydrological problems during non-monsoon period (i.e. decreasing infiltration capacity of land surface, declining underground water level, drying up natural perennial springs and streams, decreasing irrigation water availability etc.). In order to that the non-monsoon crops yield has been decreasing with the rate of 0.60% each year as the results suggest that the average crop yield is just about 58 q/ha whereas twenty five to thirty year back it was recorded about 66 q/ha which is about 12% higher (8 q/ha) than existing yield. On the other hand the population increasing with the growth rate of 2% each year. Therefore, decreasing crop yield and increasing population raised food deficiency problem and the people adopting other occupations which ultimately affecting rural livelihood of the Himalaya.

Conservation Agriculture Improves Soil Quality, Crop Yield, and Incomes of Smallholder Farmers in North Western Ghana

PubMed Central

Naab, Jesse B.; Mahama, George Y.; Yahaya, Iddrisu; Prasad, P. V. V.

2017-01-01

Conservation agriculture (CA) practices are being widely promoted in many areas in sub-Saharan Africa to recuperate degraded soils and improve ecosystem services. This study examined the effects of three tillage practices [conventional moldboard plowing (CT), hand hoeing (MT) and no-tillage (NT)], and three cropping systems (continuous maize, soybean–maize annual rotation, and soybean/maize intercropping) on soil quality, crop productivity, and profitability in researcher and farmer managed on-farm trials from 2010 to 2013 in northwestern Ghana. In the researcher managed mother trial, the CA practices of NT, residue retention and crop rotation/intercropping maintained higher soil organic carbon, and total soil N compared to conventional tillage practices after 4 years. Soil bulk density was higher under NT than under CT soils in the researcher managed mother trails or farmers managed baby trials after 4 years. In the researcher managed mother trial, there was no significant difference between tillage systems or cropping systems in maize or soybean yields in the first three seasons. In the fourth season, crop rotation had the greatest impact on maize yields with CT maize following soybean increasing yields by 41 and 49% compared to MT and NT maize, respectively. In the farmers’ managed trials, maize yield ranged from 520 to 2700 kg ha-1 and 300 to 2000 kg ha-1 for CT and NT, respectively, reflecting differences in experience of farmers with NT. Averaged across farmers, CT cropping systems increased maize and soybean yield ranging from 23 to 39% compared with NT cropping systems. Partial budget analysis showed that the cost of producing maize or soybean is 20–29% cheaper with NT systems and gives higher returns to labor compared to CT practice. Benefit-to-cost ratios also show that NT cropping systems are more profitable than CT systems. We conclude that with time, implementation of CA practices involving NT, crop rotation, intercropping of maize and soybean along with crop residue retention presents a win–win scenario due to improved crop yield, increased economic return, and trends of increasing soil fertility. The biggest challenge, however, remains with producing enough biomass and retaining same on the field. PMID:28680427

Changes in yields and their variability at different levels of global warming

NASA Astrophysics Data System (ADS)

Childers, Katelin

2015-04-01

An assessment of climate change impacts at different levels of global warming is crucial to inform the political discussion about mitigation targets as well as for the inclusion of climate change impacts in Integrated Assessment Models (IAMs) that generally only provide global mean temperature change as an indicator of climate change. While there is a well-established framework for the scalability of regional temperature and precipitation changes with global mean temperature change we provide an assessment of the extent to which impacts such as crop yield changes can also be described in terms of global mean temperature changes without accounting for the specific underlying emissions scenario. Based on multi-crop-model simulations of the four major cereal crops (maize, rice, soy, and wheat) on a 0.5 x 0.5 degree global grid generated within ISI-MIP, we show the average spatial patterns of projected crop yield changes at one half degree warming steps. We find that emissions scenario dependence is a minor component of the overall variance of projected yield changes at different levels of global warming. Furthermore, scenario dependence can be reduced by accounting for the direct effects of CO2 fertilization in each global climate model (GCM)/impact model combination through an inclusion of the global atmospheric CO2 concentration as a second predictor. The choice of GCM output used to force the crop model simulations accounts for a slightly larger portion of the total yield variance, but the greatest contributor to variance in both global and regional crop yields and at all levels of warming, is the inter-crop-model spread. The unique multi impact model ensemble available with ISI-MIP data also indicates that the overall variability of crop yields is projected to increase in conjunction with increasing global mean temperature. This result is consistent throughout the ensemble of impact models and across many world regions. Such a hike in yield volatility could have significant policy implications by affecting food prices and supplies.

Midwest Agriculture: A comparison of AVHRR NDVI3g data and crop yields in Corn Belt region of the United States from 1982 to 2014

NASA Astrophysics Data System (ADS)

Glennie, E.; Anyamba, A.; Eastman, R.

2016-12-01

A time series of Advanced Very High Resolution Radiometer (AVHRR) derived normalized difference vegetation index (NDVI) images was compared to National Agricultural Statistics Service (NASS) corn yield data in the Corn Belt of the United States from 1982 to 2014. The relationship between NDVI and crop yields under El Nino, neutral, and La Nina conditions was used to assess 1) the reliability of using NDVI as an indicator of crop productivity, and 2) the response of the Corn Belt to El Nino/ Southern Oscillation (ENSO) teleconnection effects. First, bi-monthly NDVI data were combined into monthly data using the maximum value compositing technique to reduce cloud contamination and other effects. The most representative seasonal curve of NDVI values over the course of the study period was extracted to define the growing season in the region - May to October. Standardized NDVI anomalies were calculated and averaged to produce a growing season NDVI metrics to represent each Agricultural Statistics Division (ASD) for each year in the study period. The corn yields were detrended in order to remove effects of technological advancements on crop productivity (use of genetically modified seeds, fertilizer, herbicides). Correlation (R) values between the NDVI anomalies and detrended corn yields varied across the Corn Belt, with a maximum of 0.81 and mean of 0.49. While corn is the dominant crop in the region, some inconsistencies between corn yield and NDVI may be accounted for by an increase in soy yield for a given year due to crop rotation practices. The 10 El Nino events and 9 La Nina events that occurred between 1982 and 2014 are not reflected in a consistent manner in NDVI or corn yield data. However, composites of NDVI and crop yields for all El Nino events indicate there is a tendency for higher than normal NDVI and increased corn yields. Conversely, the composite crop yield image for La Nina events shows a slight decrease in productivity.

Hot spots of crop production changes at 1.5°C and 2°C

NASA Astrophysics Data System (ADS)

Schleussner, C. F.; Deryng, D.; Mueller, C.; Elliott, J. W.; Saeed, F.; Folberth, C.; Liu, W.; Wang, X.; Pugh, T.

2017-12-01

Studying changes in global and regional crop production is central for assessing the benefits of limiting global average temperature below 1.5ºC versus 2ºC. Projections of future climatic impacts on crop production are commonly focussed on focussing on mean changes. However, substantial risks are posed by extreme weather events such as heat waves and droughts that are of great relevance for imminent policy relevant questions such as price shocks or food security. Preliminary research on the benefits of keeping global average temperature increase below 1.5ºC versus 2ºC above pre-industrial levels has indicated that changes in extreme weather event occurrences will be more pronounced than changes in the mean climate. Here we will present results of crop yield projections for a set of global gridded crop models (GGCMs) for four major staple crops at 1.5°C and 2°C warming above pre-industrial levels using climate forcing data from the Half a degree Additional warming, Prognosis and Projected Impacts (HAPPI) project. We will assess changes in crop production on the global and regional level, and identify hot spots of change. The unique multi-ensemble setup allows to identify changes in extreme yield losses with multi-year to multi-decadal return periods, and thus elucidate the consequences for global and regional food security.

Impact of Spatial Soil and Climate Input Data Aggregation on Regional Yield Simulations

PubMed Central

Hoffmann, Holger; Zhao, Gang; Asseng, Senthold; Bindi, Marco; Biernath, Christian; Constantin, Julie; Coucheney, Elsa; Dechow, Rene; Doro, Luca; Eckersten, Henrik; Gaiser, Thomas; Grosz, Balázs; Heinlein, Florian; Kassie, Belay T.; Kersebaum, Kurt-Christian; Klein, Christian; Kuhnert, Matthias; Lewan, Elisabet; Moriondo, Marco; Nendel, Claas; Priesack, Eckart; Raynal, Helene; Roggero, Pier P.; Rötter, Reimund P.; Siebert, Stefan; Specka, Xenia; Tao, Fulu; Teixeira, Edmar; Trombi, Giacomo; Wallach, Daniel; Weihermüller, Lutz; Yeluripati, Jagadeesh; Ewert, Frank

2016-01-01

We show the error in water-limited yields simulated by crop models which is associated with spatially aggregated soil and climate input data. Crop simulations at large scales (regional, national, continental) frequently use input data of low resolution. Therefore, climate and soil data are often generated via averaging and sampling by area majority. This may bias simulated yields at large scales, varying largely across models. Thus, we evaluated the error associated with spatially aggregated soil and climate data for 14 crop models. Yields of winter wheat and silage maize were simulated under water-limited production conditions. We calculated this error from crop yields simulated at spatial resolutions from 1 to 100 km for the state of North Rhine-Westphalia, Germany. Most models showed yields biased by <15% when aggregating only soil data. The relative mean absolute error (rMAE) of most models using aggregated soil data was in the range or larger than the inter-annual or inter-model variability in yields. This error increased further when both climate and soil data were aggregated. Distinct error patterns indicate that the rMAE may be estimated from few soil variables. Illustrating the range of these aggregation effects across models, this study is a first step towards an ex-ante assessment of aggregation errors in large-scale simulations. PMID:27055028

Impact of Spatial Soil and Climate Input Data Aggregation on Regional Yield Simulations.

PubMed

Hoffmann, Holger; Zhao, Gang; Asseng, Senthold; Bindi, Marco; Biernath, Christian; Constantin, Julie; Coucheney, Elsa; Dechow, Rene; Doro, Luca; Eckersten, Henrik; Gaiser, Thomas; Grosz, Balázs; Heinlein, Florian; Kassie, Belay T; Kersebaum, Kurt-Christian; Klein, Christian; Kuhnert, Matthias; Lewan, Elisabet; Moriondo, Marco; Nendel, Claas; Priesack, Eckart; Raynal, Helene; Roggero, Pier P; Rötter, Reimund P; Siebert, Stefan; Specka, Xenia; Tao, Fulu; Teixeira, Edmar; Trombi, Giacomo; Wallach, Daniel; Weihermüller, Lutz; Yeluripati, Jagadeesh; Ewert, Frank

2016-01-01

We show the error in water-limited yields simulated by crop models which is associated with spatially aggregated soil and climate input data. Crop simulations at large scales (regional, national, continental) frequently use input data of low resolution. Therefore, climate and soil data are often generated via averaging and sampling by area majority. This may bias simulated yields at large scales, varying largely across models. Thus, we evaluated the error associated with spatially aggregated soil and climate data for 14 crop models. Yields of winter wheat and silage maize were simulated under water-limited production conditions. We calculated this error from crop yields simulated at spatial resolutions from 1 to 100 km for the state of North Rhine-Westphalia, Germany. Most models showed yields biased by <15% when aggregating only soil data. The relative mean absolute error (rMAE) of most models using aggregated soil data was in the range or larger than the inter-annual or inter-model variability in yields. This error increased further when both climate and soil data were aggregated. Distinct error patterns indicate that the rMAE may be estimated from few soil variables. Illustrating the range of these aggregation effects across models, this study is a first step towards an ex-ante assessment of aggregation errors in large-scale simulations.

Crop yield and light/energy efficiency in a closed ecological system: Laboratory Biosphere experiments with wheat and sweet potato.

PubMed

Nelson, M; Dempster, W F; Silverstone, S; Alling, A; Allen, J P; van Thillo, M

2005-01-01

Two crop growth experiments in the soil-based closed ecological facility, Laboratory Biosphere, were conducted from 2003 to 2004 with candidate space life support crops. Apogee wheat (Utah State University variety) was grown, planted at two densities, 400 and 800 seeds m-2. The lighting regime for the wheat crop was 16 h of light-8 h dark at a total light intensity of around 840 micromoles m-2 s-1 and 48.4 mol m-2 d-1 over 84 days. Average biomass was 1395 g m-2, 16.0 g m-2 d-1 and average seed production was 689 g m-2 and 7.9 g m-2 d-1. The less densely planted side was more productive than the denser planting, with 1634 g m-2 and 18.8 g m-2 d-1 of biomass vs. 1156 g m-2 and 13.3 g m-2 d-1; and a seed harvest of 812.3 g m-2 and 9.3 g m-2 d-1 vs. 566.5 g m-2 and 6.5 g m-2 d-1. Harvest index was 0.49 for the wheat crop. The experiment with sweet potato used TU-82-155 a compact variety developed at Tuskegee University. Light during the sweet potato experiment, on a 18 h on/6 h dark cycle, totaled 5568 total moles of light per square meter in 126 days for the sweet potatoes, or an average of 44.2 mol m-2 d-1. Temperature regime was 28 +/- 3 degrees C day/22 +/- 4 degrees C night. Sweet potato tuber yield was 39.7 kg wet weight, or an average of 7.4 kg m-2, and 7.7 kg dry weight of tubers since dry weight was about 18.6% wet weight. Average per day production was 58.7 g m-2 d-1 wet weight and 11.3 g m-2 d-1. For the wheat, average light efficiency was 0.34 g biomass per mole, and 0.17 g seed per mole. The best area of wheat had an efficiency of light utilization of 0.51 g biomass per mole and 0.22 g seed per mole. For the sweet potato crop, light efficiency per tuber wet weight was 1.33 g mol-1 and 0.34 g dry weight of tuber per mole of light. The best area of tuber production had 1.77 g mol-1 wet weight and 0.34 g mol-1 of light dry weight. The Laboratory Biosphere experiment's light efficiency was somewhat higher than the USU field results but somewhat below greenhouse trials at comparable light levels, and the best portion of the crop at 0.22 g mol-1 was in-between those values. Sweet potato production was overall close to 50% higher than trials using hydroponic methods with TU-82-155 at NASA JSC. Compared to projected yields for the Mars on Earth life support system, these wheat yields were about 15% higher, and the sweet potato yields averaged over 80% higher. c2005 Published by Elsevier Ltd on behalf of COSPAR.

Corn and soybean Landsat MSS classification performance as a function of scene characteristics

NASA Technical Reports Server (NTRS)

Batista, G. T.; Hixson, M. M.; Bauer, M. E.

1982-01-01

In order to fully utilize remote sensing to inventory crop production, it is important to identify the factors that affect the accuracy of Landsat classifications. The objective of this study was to investigate the effect of scene characteristics involving crop, soil, and weather variables on the accuracy of Landsat classifications of corn and soybeans. Segments sampling the U.S. Corn Belt were classified using a Gaussian maximum likelihood classifier on multitemporally registered data from two key acquisition periods. Field size had a strong effect on classification accuracy with small fields tending to have low accuracies even when the effect of mixed pixels was eliminated. Other scene characteristics accounting for variability in classification accuracy included proportions of corn and soybeans, crop diversity index, proportion of all field crops, soil drainage, slope, soil order, long-term average soybean yield, maximum yield, relative position of the segment in the Corn Belt, weather, and crop development stage.

ENSO and PDO-related climate variability impacts on Midwestern United States crop yields.

PubMed

Henson, Chasity; Market, Patrick; Lupo, Anthony; Guinan, Patrick

2017-05-01

An analysis of crop yields for the state of Missouri was completed to determine if an interannual or multidecadal variability existed as a result of the El Niño Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO). Corn and soybean yields were recorded in kilograms per hectare for each of the six climate regions of Missouri. An analysis using the Mokhov "method of cycles" demonstrated interannual, interdecadal, and multidecadal variations in crop yields. Cross-spectral analysis was used to determine which region was most impacted by ENSO and PDO influenced seasonal (April-September) temperature and precipitation. Interannual (multidecadal) variations found in the spectral analysis represent a relationship to ENSO (PDO) phase, while interdecadal variations represent a possible interaction between ENSO and PDO. Average crop yields were then calculated for each combination of ENSO and PDO phase, displaying a pronounced increase in corn and soybean yields when ENSO is warm and PDO is positive. Climate regions 1, 2, 4, and 6 displayed significant differences (p value of 0.10 or less) in yields between El Niño and La Niña years, representing 55-70 % of Missouri soybean and corn productivity, respectively. Final results give the opportunity to produce seasonal predictions of corn and soybean yields, specific to each climate region in Missouri, based on the combination of ENSO and PDO phases.

Simulation of crop yield variability by improved root-soil-interaction modelling

NASA Astrophysics Data System (ADS)

Duan, X.; Gayler, S.; Priesack, E.

2009-04-01

Understanding the processes and factors that govern the within-field variability in crop yield has attached great importance due to applications in precision agriculture. Crop response to environment at field scale is a complex dynamic process involving the interactions of soil characteristics, weather conditions and crop management. The numerous static factors combined with temporal variations make it very difficult to identify and manage the variability pattern. Therefore, crop simulation models are considered to be useful tools in analyzing separately the effects of change in soil or weather conditions on the spatial variability, in order to identify the cause of yield variability and to quantify the spatial and temporal variation. However, tests showed that usual crop models such as CERES-Wheat and CERES-Maize were not able to quantify the observed within-field yield variability, while their performance on crop growth simulation under more homogeneous and mainly non-limiting conditions was sufficent to simulate average yields at the field-scale. On a study site in South Germany, within-field variability in crop growth has been documented since years. After detailed analysis and classification of the soil patterns, two site specific factors, the plant-available-water and the O2 deficiency, were considered as the main causes of the crop growth variability in this field. Based on our measurement of root distribution in the soil profile, we hypothesize that in our case the insufficiency of the applied crop models to simulate the yield variability can be due to the oversimplification of the involved root models which fail to be sensitive to different soil conditions. In this study, the root growth model described by Jones et al. (1991) was adapted by using data of root distributions in the field and linking the adapted root model to the CERES crop model. The ability of the new root model to increase the sensitivity of the CERES crop models to different enviromental conditions was then evaluated by means of comparison of the simualtion results with measured data and by scenario calculations.

Plausible rice yield losses under future climate warming.

PubMed

Zhao, Chuang; Piao, Shilong; Wang, Xuhui; Huang, Yao; Ciais, Philippe; Elliott, Joshua; Huang, Mengtian; Janssens, Ivan A; Li, Tao; Lian, Xu; Liu, Yongwen; Müller, Christoph; Peng, Shushi; Wang, Tao; Zeng, Zhenzhong; Peñuelas, Josep

2016-12-19

Rice is the staple food for more than 50% of the world's population 1-3 . Reliable prediction of changes in rice yield is thus central for maintaining global food security. This is an extraordinary challenge. Here, we compare the sensitivity of rice yield to temperature increase derived from field warming experiments and three modelling approaches: statistical models, local crop models and global gridded crop models. Field warming experiments produce a substantial rice yield loss under warming, with an average temperature sensitivity of -5.2 ± 1.4% K -1 . Local crop models give a similar sensitivity (-6.3 ± 0.4% K -1 ), but statistical and global gridded crop models both suggest less negative impacts of warming on yields (-0.8 ± 0.3% and -2.4 ± 3.7% K -1 , respectively). Using data from field warming experiments, we further propose a conditional probability approach to constrain the large range of global gridded crop model results for the future yield changes in response to warming by the end of the century (from -1.3% to -9.3% K -1 ). The constraint implies a more negative response to warming (-8.3 ± 1.4% K -1 ) and reduces the spread of the model ensemble by 33%. This yield reduction exceeds that estimated by the International Food Policy Research Institute assessment (-4.2 to -6.4% K -1 ) (ref. 4). Our study suggests that without CO 2 fertilization, effective adaptation and genetic improvement, severe rice yield losses are plausible under intensive climate warming scenarios.

The Impact of Changing Snowmelt Timing on Non-Irrigated Crop Yield in Idaho

NASA Astrophysics Data System (ADS)

Murray, E. M.; Cobourn, K.; Flores, A. N.; Pierce, J. L.; Kunkel, M. L.

2013-12-01

The impacts of climate change on water resources have implications for both agricultural production and grower welfare. Many mountainous regions in the western U.S. rely on snowmelt as the dominant surface water source, and in Idaho, reconstructions of spring snowmelt timing have demonstrated a trend toward earlier, more variable snowmelt dates within the past 20 years. This earlier date and increased variability in snowmelt timing have serious implications for agriculture, but there is considerable uncertainty about how agricultural impacts vary by region, crop-type, and practices like irrigation vs. dryland farming. Establishing the relationship between snowmelt timing and agricultural yield is important for understanding how changes in large-scale climatic indices (like snowmelt date) may be associated with changes in agricultural yield. This is particularly important where local practitioner behavior is influenced by historically observed relationships between these climate indices and yield. In addition, a better understanding of the influence of changes in snowmelt on non-irrigated crop yield may be extrapolated to better understand how climate change may alter biomass production in non-managed ecosystems. To investigate the impact of snowmelt date on non-irrigated crop yield, we developed a multiple linear regression model to predict historical wheat and barley yield in several Idaho counties as a function of snowmelt date, climate variables (precipitation and growing degree-days), and spatial differences between counties. The relationship between snowmelt timing and non-irrigated crop yield at the county level is strong in many of the models, but differs in magnitude and direction for the two different crops. Results show interesting spatial patterns of variability in the correlation between snowmelt timing and crop yield. In four southern counties that border the Snake River Plain and one county bordering Oregon, non-irrigated wheat and/or barley yield are significantly lower in years with early snowmelt timing, on average (P < 0.10). In contrast, in northern Idaho, barley yield is significantly higher in years with early snowmelt timing. Overall, this statistical modeling exercise indicates that the trend toward earlier snowmelt date may positively impact non-irrigated crop yield in some regions of Idaho, while negatively impacting yield in other areas. Additional research is necessary to identify spatial controls on the variable relationship between snowmelt timing and yield. Regional variability in the response of crops to changes in snowmelt timing may indicate that external factors (e.g. higher amounts of summer rain in northern vs. southern Idaho) may play an important role in crop yield. This study indicates that targeted regional analysis is necessary to determine the influence of climate change on agriculture, as local variability can cause the same forcing to produce opposite results.

Effect of a 5-Year Multi-Crop Rotation on Mineral N and Hard Red Spring Wheat Yield, Protein, Test Weight and Economics in Western North Dakota, USA

NASA Astrophysics Data System (ADS)

Landblom, Douglas; Senturklu, Songul; Cihacek, Larry; Brevik, Eric

2016-04-01

The objectives of this non-irrigated cropping study was to employ the principles of soil health and determine the effect of rotation on seasonal mineral N, HRSW production, protein, test weight, and economics. Prior to the initiation of this research, the cropping study area had been previously seeded to hard red spring wheat (HRSW). The cropping systems consisted of a continuous HRSW control (C) compared to HRSW grown in a multi-crop 5-year rotation (R). The 5-yr rotation consisted of HRSW, cover crop (dual crop winter triticale-hairy vetch harvested for hay in June and immediately reseeded to a 7-species cover crop mix grazed by cows after weaning from mid-November to mid-December), forage corn, field pea-forage barley, and sunflower. The cereal grains, cover crops, and pea-barley intercrop were seeded using a JD 1590 no-till drill, 19 cm row spacing, and seed depth of 2.54 cm Cereal grain plant population was 3,088,750 plants/ha. The row crops were planted using a JD 7000 no-till planter, 76.2 cm row spacing, and seed depth of 5.08 cm. Plant population for the row crops was 46,947 plants/ha. Weeds were controlled using a pre-plant burn down and post-emergence control except for cover crops and pea-barley where a pre-plant burn down was the only chemical applied. Fertilizer application was based on soil test results and recommendations from the North Dakota State University Soil Testing Laboratory. During the 1st three years of the study 31.8 kg of N was applied to the C HRSW and then none the last two years of the 5-year period. The R HRSW was fertilized with 13.6 kg of N the 1st two years of the study and none the remaining three years of the 5-year period. However, chloride was low; therefore, 40.7-56.1 kg/ha were applied each year to both the C and R treatments. Based on 2014 and 2015 seasonal mineral N values, the data suggests that N levels were adequate to meet the 2690 kg/ha yield goal. In 2015, however, the R yield goal was exceeded by 673 kg/ha whereas the C yield goal of 2690 kg/ha was not achieved indicating that the multi-crop rotation enhanced soil quality and increased N cycling within the rotation management system. The 5-year average HRSW yield (C: 2690 vs. R: 2757 kg/ha; P=0.76), protein (C: 13.9 vs. R: 13.3%; P=0.06), and test weight (C: 28.1 vs. R: 28.0 kg/bu; P=0.81) did not differ between management treatments. Improved production is the result of enhanced nutrient cycling of available nutrients. Yields for crop years 1-5 were the same year 1, but in year 2, C wheat yield was 24.4% higher than R wheat (3,766 vs. 3,026 kg/ha). Change that started when the rotation was initiated became more evident in year three, when the yield margin between the two management practices began to narrow, but remained 20.5% higher for the C (3,161 vs. 2,623 kg/ha). Yield reversal became fully realized by year 4, when the R wheat yield was 9.1% higher (2,959 vs. 3,228 kg/ha), and by the 5th crop year R wheat yield was 38.9% higher than the C wheat yield (2,421 vs. 3,363 kg/ha). The 5-yr average input cost (C: 477 vs. R: 440/ha) and gross return (C: 650 vs. R: 638/ha) resulted in a net return that was 25 higher for R HRSW compared to the C HRSW (CTRL 173 vs. ROT 198/ha). The 5-yr net return from the C, R, and combination of all of the R crops was 173, 198, and 213/ha suggesting that growing continuous HRSW is less intensive, but also 14.5% less profitable.

Ecological intensification of cereal production systems: yield potential, soil quality, and precision agriculture.

PubMed

Cassman, K G

1999-05-25

Wheat (Triticum aestivum L.), rice (Oryza sativa L.), and maize (Zea mays L.) provide about two-thirds of all energy in human diets, and four major cropping systems in which these cereals are grown represent the foundation of human food supply. Yield per unit time and land has increased markedly during the past 30 years in these systems, a result of intensified crop management involving improved germplasm, greater inputs of fertilizer, production of two or more crops per year on the same piece of land, and irrigation. Meeting future food demand while minimizing expansion of cultivated area primarily will depend on continued intensification of these same four systems. The manner in which further intensification is achieved, however, will differ markedly from the past because the exploitable gap between average farm yields and genetic yield potential is closing. At present, the rate of increase in yield potential is much less than the expected increase in demand. Hence, average farm yields must reach 70-80% of the yield potential ceiling within 30 years in each of these major cereal systems. Achieving consistent production at these high levels without causing environmental damage requires improvements in soil quality and precise management of all production factors in time and space. The scope of the scientific challenge related to these objectives is discussed. It is concluded that major scientific breakthroughs must occur in basic plant physiology, ecophysiology, agroecology, and soil science to achieve the ecological intensification that is needed to meet the expected increase in food demand.

Breeding and genomics status in faba bean (Vicia faba L)

USDA-ARS?s Scientific Manuscript database

Faba bean is an important legume crop due to its high yield potential and nutrition dense grains. There are significant achievements in faba bean improvement during the last four decades, leading to the doubling the global yield average. This paper intends to review the genetic diversity, the breedi...

Impacts of climate change and climate extremes on major crops productivity in China at a global warming of 1.5 and 2.0 °C

NASA Astrophysics Data System (ADS)

Chen, Yi; Zhang, Zhao; Tao, Fulu

2018-05-01

A new temperature goal of holding the increase in global average temperature well below 2 °C above pre-industrial levels and pursuing efforts to limit the temperature increase to 1.5 °C above pre-industrial levels has been established in the Paris Agreement, which calls for an understanding of climate risk under 1.5 and 2.0 °C warming scenarios. Here, we evaluated the effects of climate change on growth and productivity of three major crops (i.e. maize, wheat, rice) in China during 2106-2115 in warming scenarios of 1.5 and 2.0 °C using a method of ensemble simulation with well-validated Model to capture the Crop-Weather relationship over a Large Area (MCWLA) family crop models, their 10 sets of optimal crop model parameters and 70 climate projections from four global climate models. We presented the spatial patterns of changes in crop growth duration, crop yield, impacts of heat and drought stress, as well as crop yield variability and the probability of crop yield decrease. Results showed that climate change would have major negative impacts on crop production, particularly for wheat in north China, rice in south China and maize across the major cultivation areas, due to a decrease in crop growth duration and an increase in extreme events. By contrast, with moderate increases in temperature, solar radiation, precipitation and atmospheric CO2 concentration, agricultural climate resources such as light and thermal resources could be ameliorated, which would enhance canopy photosynthesis and consequently biomass accumulations and yields. The moderate climate change would slightly worsen the maize growth environment but would result in a much more appropriate growth environment for wheat and rice. As a result, wheat, rice and maize yields would change by +3.9 (+8.6), +4.1 (+9.4) and +0.2 % (-1.7 %), respectively, in a warming scenario of 1.5 °C (2.0 °C). In general, the warming scenarios would bring more opportunities than risks for crop development and food security in China. Moreover, although the variability of crop yield would increase from 1.5 °C warming to 2.0 °C warming, the probability of a crop yield decrease would decrease. Our findings highlight that the 2.0 °C warming scenario would be more suitable for crop production in China, but more attention should be paid to the expected increase in extreme event impacts.

A Remote Sensing-Derived Corn Yield Assessment Model

NASA Astrophysics Data System (ADS)

Shrestha, Ranjay Man

Agricultural studies and food security have become critical research topics due to continuous growth in human population and simultaneous shrinkage in agricultural land. In spite of modern technological advancements to improve agricultural productivity, more studies on crop yield assessments and food productivities are still necessary to fulfill the constantly increasing food demands. Besides human activities, natural disasters such as flood and drought, along with rapid climate changes, also inflect an adverse effect on food productivities. Understanding the impact of these disasters on crop yield and making early impact estimations could help planning for any national or international food crisis. Similarly, the United States Department of Agriculture (USDA) Risk Management Agency (RMA) insurance management utilizes appropriately estimated crop yield and damage assessment information to sustain farmers' practice through timely and proper compensations. Through County Agricultural Production Survey (CAPS), the USDA National Agricultural Statistical Service (NASS) uses traditional methods of field interviews and farmer-reported survey data to perform annual crop condition monitoring and production estimations at the regional and state levels. As these manual approaches of yield estimations are highly inefficient and produce very limited samples to represent the entire area, NASS requires supplemental spatial data that provides continuous and timely information on crop production and annual yield. Compared to traditional methods, remote sensing data and products offer wider spatial extent, more accurate location information, higher temporal resolution and data distribution, and lower data cost--thus providing a complementary option for estimation of crop yield information. Remote sensing derived vegetation indices such as Normalized Difference Vegetation Index (NDVI) provide measurable statistics of potential crop growth based on the spectral reflectance and could be further associated with the actual yield. Utilizing satellite remote sensing products, such as daily NDVI derived from Moderate Resolution Imaging Spectroradiometer (MODIS) at 250 m pixel size, the crop yield estimation can be performed at a very fine spatial resolution. Therefore, this study examined the potential of these daily NDVI products within agricultural studies and crop yield assessments. In this study, a regression-based approach was proposed to estimate the annual corn yield through changes in MODIS daily NDVI time series. The relationship between daily NDVI and corn yield was well defined and established, and as changes in corn phenology and yield were directly reflected by the changes in NDVI within the growing season, these two entities were combined to develop a relational model. The model was trained using 15 years (2000-2014) of historical NDVI and county-level corn yield data for four major corn producing states: Kansas, Nebraska, Iowa, and Indiana, representing four climatic regions as South, West North Central, East North Central, and Central, respectively, within the U.S. Corn Belt area. The model's goodness of fit was well defined with a high coefficient of determination (R2>0.81). Similarly, using 2015 yield data for validation, 92% of average accuracy signified the performance of the model in estimating corn yield at county level. Besides providing the county-level corn yield estimations, the derived model was also accurate enough to estimate the yield at finer spatial resolution (field level). The model's assessment accuracy was evaluated using the randomly selected field level corn yield within the study area for 2014, 2015, and 2016. A total of over 120 plot level corn yield were used for validation, and the overall average accuracy was 87%, which statistically justified the model's capability to estimate plot-level corn yield. Additionally, the proposed model was applied to the impact estimation by examining the changes in corn yield due to flood events during the growing season. Using a 2011 Missouri River flood event as a case study, field-level flood impact map on corn yield throughout the flooded regions was produced and an overall agreement of over 82.2% was achieved when compared with the reference impact map. The future research direction of this dissertation research would be to examine other major crops outside the Corn Belt region of the U.S.

Effect of winter cover crops on soil nitrogen availability, corn yield, and nitrate leaching.

PubMed

Kuo, S; Huang, B; Bembenek, R

2001-10-25

Biculture of nonlegumes and legumes could serve as cover crops for increasing main crop yield, while reducing NO3 leaching. This study, conducted from 1994 to 1999, determined the effect of monocultured cereal rye (Secale cereale L.), annual ryegrass (Lolium multiflorum), and hairy vetch (Vicia villosa), and bicultured rye/vetch and ryegrass/vetch on N availability in soil, corn (Zea mays L.) yield, and NO3-N leaching in a silt loam soil. The field had been in corn and cover crop rotation since 1987. In addition to the cover crop treatments, there were four N fertilizer rates (0, 67, 134, and 201 kg N ha(-1), referred to as N0, N1, N2, and N3, respectively) applied to corn. The experiment was a randomized split-block design with three replications for each treatment. Lysimeters were installed in 1987 at 0.75 m below the soil surface for leachate collection for the N 0, N 2, and N 3 treatments. The result showed that vetch monoculture had the most influence on soil N availability and corn yield, followed by the bicultures. Rye or ryegrass monoculture had either no effect or an adverse effect on corn yield and soil N availability. Leachate NO3-N concentration was highest where vetch cover crop was planted regardless of N rates, which suggests that N mineralization of vetch N continued well into the fall and winter. Leachate NO3-N concentration increased with increasing N fertilizer rates and exceeded the U.S. Environmental Protection Agency's drinking water standard of 10 mg N l(-1) even at recommended N rate for corn in this region (coastal Pacific Northwest). In comparisons of the average NO3-N concentration during the period of high N leaching, monocultured rye and ryegrass or bicultured rye/vetch and ryegrass/vetch very effectively decreased N leaching in 1998 with dry fall weather. The amount of N available for leaching (determined based on the presidedress nitrate test, the amount of N fertilizer applied, and N uptake) correlated well with average NO3-N during the high N leaching period for vetch cover crop treatment and for the control without the cover crops. The correlation, however, failed for other cover crops largely because of variable effectiveness of the cover crops in reducing NO3 leaching during the 5 years of this study. Further research is needed to determine if relay cover crops planted into standing summer crops is a more appropriate approach than fall seeding in this region to gain sufficient growth of the cover crop by fall. Testing with other main crops that have earlier harvest dates than corn is also needed to further validate the effectiveness of the bicultures to increase soil N availability while protecting the water quality.

Assessment of Total Phenolic and Flavonoid Content, Antioxidant Properties, and Yield of Aeroponically and Conventionally Grown Leafy Vegetables and Fruit Crops: A Comparative Study

PubMed Central

Chandra, Suman; Khan, Shabana; Avula, Bharathi; Lata, Hemant; Yang, Min Hye; ElSohly, Mahmoud A.; Khan, Ikhlas A.

2014-01-01

A comparison of the product yield, total phenolics, total flavonoids, and antioxidant properties was done in different leafy vegetables/herbs (basil, chard, parsley, and red kale) and fruit crops (bell pepper, cherry tomatoes, cucumber, and squash) grown in aeroponic growing systems (AG) and in the field (FG). An average increase of about 19%, 8%, 65%, 21%, 53%, 35%, 7%, and 50% in the yield was recorded for basil, chard, red kale, parsley, bell pepper, cherry tomatoes, cucumber, and squash, respectively, when grown in aeroponic systems, compared to that grown in the soil. Antioxidant properties of AG and FG crops were evaluated using 2,2-diphenyl-1-picrylhydrazyl (DDPH) and cellular antioxidant (CAA) assays. In general, the study shows that the plants grown in the aeroponic system had a higher yield and comparable phenolics, flavonoids, and antioxidant properties as compared to those grown in the soil. PMID:24782905

A data-oriented semi-process model for evaluating the yields of major crops at global scale (PRYSBI-2)

NASA Astrophysics Data System (ADS)

Sakurai, G.; Iizumi, T.; Yokozawa, M.

2013-12-01

Demand for major cereal crops will double by 2050 compared to the amount in 2005 due to the population growth, dietary change, and increase in biofuel use. This requires substantial efforts to increase crop yields under changing climate, water resources, and land use. In order to explore possible paths to meet the supply target, global crop modeling is a useful approach. To that end, we developed a process-based large-area crop model (called PRYSBIE-2) for major crops, including soybean. This model consisted of the enzyme kinetics model for photosynthetic carbon assimilation and soil water balance model from SWAT. The parameter values on water stress, nitrogen stress were calibrated over global croplands from one grid cell to another (1.125° in latitude and longitude) using Markov Chain Monte Carlo (MCMC) methods. The historical yield data collected from major crop-producing countries on a state, county, or prefecture scale were used as the calibration data. Then we obtained the model parameter sets that can give high correlation coefficients between the historical and estimated yield time series for the period 1980-2006. We analyzed the impacts on soybean yields in the three top soybean-producing countries (the USA, China, and Brazil) associated with the changes in climate and CO2 during the period 1980-2006, using the model. We found that, given the simulated yields and reported harvested areas, the estimated average net benefit from the CO2 fertilization effect (with one standard deviation) in the USA, Brazil, and China in the years was 42.70×32.52 Mt, 35.30×28.55 Mt, and 12.52×15.11 Mt, respectively. Results suggest that the CO2-induced increases in soybean yields in the USA and China likely offset a part of the negative impacts on yields due to the historical temperature rise. In contrast, the net effect of the past change in climate and CO2 in Brazil appeared to be positive. This study demonstrates a quantitative estimation of the impacts of the changes in climate and CO2 during the past few decades using a new global crop model.

Comparison of Water and Nutrient Cycles in the North China Plain and U.S. High Plains related to Climate Forcing

NASA Astrophysics Data System (ADS)

Scanlon, B. R.; Pei, H.; Shen, Y.

2014-12-01

The North China Plain (NCP) and U.S. High Plains play critical roles in food production, which relies heavily on groundwater resources for irrigation and nutrients. Here we evaluate food production in terms of resource availability (water and nutrients) and impacts on resources (groundwater quantity and quality) within the context of climate forcing. Double cropping of corn and wheat in the NCP under intensive irrigation (80 - 90% of cropland) and massive N fertilization (384 kg/ha) resulted in total corn plus wheat yields of 13.4 kg/ha (2002 - 2011). In contrast, single cropping of corn on the USHP under less intensive irrigation (40% of cropland) and N fertilization (90 kg/ha) resulted in only 15% lower yield in the USHP (11.7 kg/ha) than in the NCP. However, irrigation essentially decouples crop production from climate extremes. Average corn and wheat yield in the NCP over the past three decades is not correlated with precipitation. Irrigated corn yield in the north and central USHP was actually higher during the recent 2012 drought by up to ~ 30% relative to the 30 year long-term mean yield whereas rainfed corn yield decreased by ~50% during the drought. The main impact of climate extremes on the aquifers is indirect through increased irrigation pumpage for crop production rather than direct through changes in recharge. Effects of crop production on groundwater quality should be much greater in the NCP because of ~4 times higher fertilizer application relative to that in the USHP. Field research experiments in the NCP indicate that much of this fertilizer application (> 200 kg N/ha) does not impact yield and could potentially leach into underlying aquifers. Projected groundwater depletion in these aquifers should result in a shift from intensive irrigation to more rainfed crop production, increasing vulnerability of crop production to climate extremes.

Interannual variability of crop water footprint

NASA Astrophysics Data System (ADS)

Tuninetti, M.; Tamea, S.; Laio, F.; Ridolfi, L.

2016-12-01

The crop water footprint, CWF, is a useful tool to investigate the water-food nexus, since it measures the water requirement for crop production. Heterogeneous spatial patterns of climatic conditions and agricultural practices have inspired a flourishing literature on the geographic assessment of CWF, mostly referred to a fixed (time-averaged) period. However, given that both climatic conditions and crop yield may vary substantially over time, also the CWF temporal dynamics need to be addressed. As other studies have done, we base the CWF variability on yield, while keeping the crop evapotranspiration constant over time. As a new contribution, we prove the feasibility of this approach by comparing these CWF estimates with the results obtained with a full model considering variations of crop evapotranspiration: overall, the estimates compare well showing high coefficients of determination that read 0.98 for wheat, 0.97 for rice, 0.97 for maize, and 0.91 for soybean. From this comparison, we derive also the precision of the method, which is around ±10% that is higher than the precision of the model used to evaluate the crop evapotranspiration (i.e., ±30%). Over the period between 1961 and 2013, the CWF of the most cultivated grains has sharply decreased on a global basis (i.e., -68% for wheat, -62% for rice, -66% for maize, and -52% for soybean), mainly driven by enhanced yield values. The higher water use efficiency in crop production implies a reduced virtual displacement of embedded water per ton of traded crop and as a result, the temporal variability of virtual water trade is different if considering constant or time-varying CWF. The proposed yield-based approach to estimate the CWF variability implies low computational costs and requires limited input data, thus, it represents a promising tool for time-dependent water footprint assessments.

Helping crops stand up to salt

DOE Office of Scientific and Technical Information (OSTI.GOV)

Raeburn, P.

1985-05-01

A new approach to the problem of increasing soil salinity is to raise salt-tolerant plants. The search for such plants involves finding new applications for naturally occurring salt-resistant plants (halophytes), using conventional breeding techniques to identify and strengthen crop varieties known to have better-than-average salt tolerance, and applying recombinant DNA methods to introduce salt resistance into existing plants. One promising plant is salicornia, which produces oil high in polyunsaturates at a greater yield than soybeans. Two varieties of atriplex yield as much animal feed as alfalfa and can be harvested several times a year. Seed companies are supporting the research.

Genotypic diversity effects on biomass production in native perennial bioenergy cropping systems

DOE PAGES

Morris, Geoffrey P.; Hu, Zhenbin; Grabowski, Paul P.; ...

2015-10-03

The perennial grass species that are being developed as biomass feedstock crops harbor extensive genotypic diversity, but the effects of this diversity on biomass production are not well understood. We investigated the effects of genotypic diversity in switchgrass (Panicum virgatum) and big bluestem (Andropogon gerardii) on perennial biomass cropping systems in two experiments conducted over 2008–2014 at a 5.4-ha fertile field site in northeastern Illinois, USA. We varied levels of switchgrass and big bluestem genotypic diversity using various local and nonlocal cultivars – under low or high species diversity, with or without nitrogen inputs – and quantified establishment, biomass yield,more » and biomass composition. In one experiment (‘agronomic trial’), we compared three switchgrass cultivars in monoculture to a switchgrass cultivar mixture and three different species mixtures, with or without N fertilization. In another experiment (‘diversity gradient’), we varied diversity levels in switchgrass and big bluestem (1, 2, 4, or 6 cultivars per plot), with one or two species per plot. In both experiments, cultivar mixtures produced yields equivalent to or greater than the best cultivars. In the agronomic trial, the three switchgrass mixture showed the highest production overall, though not significantly different than best cultivar monoculture. In the diversity gradient, genotypic mixtures had one-third higher biomass production than the average monoculture, and none of the monocultures were significantly higher yielding than the average mixture. Year-to-year variation in yields was lowest in the three-cultivar switchgrass mixtures and Cave-In-Rock (the southern Illinois cultivar) and also reduced in the mixture of switchgrass and big bluestem relative to the species monocultures. The effects of genotypic diversity on biomass composition were modest relative to the differences among species and genotypes. Our findings suggest that local genotypes can be included in biomass cropping systems without compromising yields and that genotypic mixtures could help provide high, stable yields of high-quality biomass feedstocks.« less

Genotypic diversity effects on biomass production in native perennial bioenergy cropping systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Morris, Geoffrey P.; Hu, Zhenbin; Grabowski, Paul P.

The perennial grass species that are being developed as biomass feedstock crops harbor extensive genotypic diversity, but the effects of this diversity on biomass production are not well understood. We investigated the effects of genotypic diversity in switchgrass (Panicum virgatum) and big bluestem (Andropogon gerardii) on perennial biomass cropping systems in two experiments conducted over 2008–2014 at a 5.4-ha fertile field site in northeastern Illinois, USA. We varied levels of switchgrass and big bluestem genotypic diversity using various local and nonlocal cultivars – under low or high species diversity, with or without nitrogen inputs – and quantified establishment, biomass yield,more » and biomass composition. In one experiment (‘agronomic trial’), we compared three switchgrass cultivars in monoculture to a switchgrass cultivar mixture and three different species mixtures, with or without N fertilization. In another experiment (‘diversity gradient’), we varied diversity levels in switchgrass and big bluestem (1, 2, 4, or 6 cultivars per plot), with one or two species per plot. In both experiments, cultivar mixtures produced yields equivalent to or greater than the best cultivars. In the agronomic trial, the three switchgrass mixture showed the highest production overall, though not significantly different than best cultivar monoculture. In the diversity gradient, genotypic mixtures had one-third higher biomass production than the average monoculture, and none of the monocultures were significantly higher yielding than the average mixture. Year-to-year variation in yields was lowest in the three-cultivar switchgrass mixtures and Cave-In-Rock (the southern Illinois cultivar) and also reduced in the mixture of switchgrass and big bluestem relative to the species monocultures. The effects of genotypic diversity on biomass composition were modest relative to the differences among species and genotypes. Our findings suggest that local genotypes can be included in biomass cropping systems without compromising yields and that genotypic mixtures could help provide high, stable yields of high-quality biomass feedstocks.« less

Ensemble yield simulations: Using heat-tolerant and later-maturing varieties to adapt to climate warming.

PubMed

Zhang, Yi; Zhao, Yanxia

2017-01-01

The use of modern crop varieties is a dominant method of obtaining high yields in crop production. Efforts to identify suitable varieties, with characteristics that would increase crop yield under future climate conditions, remain essential to developing sustainable agriculture and food security. This work aims to evaluate potential genotypic adaptations (i.e., using varieties with increased ability to produce desirable grain numbers under high temperatures and with enhanced thermal time requirements during the grain-filling period) to cope with the negative impacts of climate change on maize yield. The contributions of different options were investigated at six sites in the North China Plain using the APSIM model and the outputs of 8 GCMs under RCP4.5 scenarios. It was found that without considering adaptation options, mean maize yield would decrease by 7~18% during 2010-2039 relative to 1976-2005. A large decrease in grain number relative to stabilized grain weight decreased maize yield under future climate scenarios. Using heat-tolerant varieties, maize yield could increase on average by 6% to 10%. Using later maturing varieties, e.g., enhanced thermal time requirements during the grain-filling period, maize yield could increase by 7% to 10%. The optimal adaptation options were site specific.

Ensemble yield simulations: Using heat-tolerant and later-maturing varieties to adapt to climate warming

PubMed Central

Zhang, Yi

2017-01-01

The use of modern crop varieties is a dominant method of obtaining high yields in crop production. Efforts to identify suitable varieties, with characteristics that would increase crop yield under future climate conditions, remain essential to developing sustainable agriculture and food security. This work aims to evaluate potential genotypic adaptations (i.e., using varieties with increased ability to produce desirable grain numbers under high temperatures and with enhanced thermal time requirements during the grain-filling period) to cope with the negative impacts of climate change on maize yield. The contributions of different options were investigated at six sites in the North China Plain using the APSIM model and the outputs of 8 GCMs under RCP4.5 scenarios. It was found that without considering adaptation options, mean maize yield would decrease by 7~18% during 2010–2039 relative to 1976–2005. A large decrease in grain number relative to stabilized grain weight decreased maize yield under future climate scenarios. Using heat-tolerant varieties, maize yield could increase on average by 6% to 10%. Using later maturing varieties, e.g., enhanced thermal time requirements during the grain-filling period, maize yield could increase by 7% to 10%. The optimal adaptation options were site specific. PMID:28459880

Global Crop Yields, Climatic Trends and Technology Enhancement

NASA Astrophysics Data System (ADS)

Najafi, E.; Devineni, N.; Khanbilvardi, R.; Kogan, F.

2016-12-01

During the last decades the global agricultural production has soared up and technology enhancement is still making positive contribution to yield growth. However, continuing population, water crisis, deforestation and climate change threaten the global food security. Attempts to predict food availability in the future around the world can be partly understood from the impact of changes to date. A new multilevel model for yield prediction at the country scale using climate covariates and technology trend is presented in this paper. The structural relationships between average yield and climate attributes as well as trends are estimated simultaneously. All countries are modeled in a single multilevel model with partial pooling and/or clustering to automatically group and reduce estimation uncertainties. El Niño Southern Oscillation (ENSO), Palmer Drought Severity Index (PDSI), Geopotential height (GPH), historical CO2 level and time-trend as a relatively reliable approximation of technology measurement are used as predictors to estimate annual agricultural crop yields for each country from 1961 to 2007. Results show that these indicators can explain the variability in historical crop yields for most of the countries and the model performs well under out-of-sample verifications.

Impacts of plastic film mulching on crop yields, soil water, nitrate, and organic carbon in Northwestern China: A meta-analysis.

PubMed

Ma, Dedi; Chen, Lei; Qu, Hongchao; Wang, Yilin; Misselbrook, Tom; Jiang, Rui

2018-04-01

In order to increase crop yield in semi-arid and arid areas, plastic film mulching (PFM) is widely used in Northwestern China. To date, many studies have addressed the effects of PFM on soil physical and biochemical properties in rain-fed agriculture in Northwestern China, but the findings of different studies are often contradictory. Therefore, a comprehensive review of the impacts of PFM on soil water content, soil nutrients and food production is needed. We compiled the results of 1278 observations to evaluate the overall effects of PFM on soil water content, the distribution of nitrate and soil organic carbon, and crop yield in rain-fed agriculture in Northwestern China. Our results showed that PFM increased soil moisture and nitrate concentration in topsoils (0-20 cm) by 12.9% and 28.2%, respectively, but slightly decreased (1.8%) soil organic carbon (SOC) content in the 0-10 cm soil layer. PFM significantly increased grain yields by 43.1%, with greatest effect in spring maize (79.4%). When related to cumulative precipitation during the crop growing season, yield increase from PFM was greatest (72.8%) at 200-300 mm, which was attributed to the large increase for spring maize and potato, implying that crop zoning would be beneficial for PFM in this region. When related to N application rate, crop yields benefited most from PFM (80.2%) at 200-300 kg/ha. A cost-benefit analysis indicated that PFM increased economic return by an average of 29.5%, with the best improvement for spring maize (71.1%) and no increase for spring wheat. In conclusion, PFM can significantly increase crop yield and economic return (especially for spring maize) in rain-fed agriculture areas of Northwestern China. Crop zoning is recommended for PFM to achieve the largest economic benefit. However, full account needs to be taken of the environmental impacts relating to N loss, SOC depletion and film pollution to evaluate the sustainability of PFM systems and further research is required to quantify and mitigate these impacts.

EnviroAtlas - Cultivated biological nitrogen fixation in agricultural lands by 12-digit HUC in the Conterminous United States, 2006

EPA Pesticide Factsheets

This EnviroAtlas dataset contains data on the mean cultivated biological nitrogen fixation (C-BNF) in cultivated crop and hay/pasture lands per 12-digit Hydrologic Unit (HUC) in 2006. Nitrogen (N) inputs from the cultivation of legumes, which possess a symbiotic relationship with N-fixing bacteria, were calculated with a recently developed model relating county-level yields of various leguminous crops with BNF rates. We accessed county-level data on annual crop yields for soybeans (Glycine max L.), alfalfa (Medicago sativa L.), peanuts (Arachis hypogaea L.), various dry beans (Phaseolus, Cicer, and Lens spp.), and dry peas (Pisum spp.) for 2006 from the USDA Census of Agriculture (http://www.agcensus.usda.gov/index.php). We estimated the yield of the non-alfalfa leguminous component of hay as 32% of the yield of total non-alfalfa hay (http://www.agcensus.usda.gov/index.php). Annual rates of C-BNF by crop type were calculated using a model that relates yield to C-BNF. We assume yield data reflect differences in soil properties, water availability, temperature, and other local and regional factors that can influence root nodulation and rate of N fixation. We distributed county-specific, C-BNF rates to cultivated crop and hay/pasture lands delineated in the 2006 National Land Cover Database (30 x 30 m pixels) within the corresponding county. C-BNF data described here represent an average input to a typical agricultural land type within a county, i.e., they are not

Distribution Development for STORM Ingestion Input Parameters

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fulton, John

The Sandia-developed Transport of Radioactive Materials (STORM) code suite is used as part of the Radioisotope Power System Launch Safety (RPSLS) program to perform statistical modeling of the consequences due to release of radioactive material given a launch accident. As part of this modeling, STORM samples input parameters from probability distributions with some parameters treated as constants. This report described the work done to convert four of these constant inputs (Consumption Rate, Average Crop Yield, Cropland to Landuse Database Ratio, and Crop Uptake Factor) to sampled values. Consumption rate changed from a constant value of 557.68 kg / yr tomore » a normal distribution with a mean of 102.96 kg / yr and a standard deviation of 2.65 kg / yr. Meanwhile, Average Crop Yield changed from a constant value of 3.783 kg edible / m 2 to a normal distribution with a mean of 3.23 kg edible / m 2 and a standard deviation of 0.442 kg edible / m 2 . The Cropland to Landuse Database ratio changed from a constant value of 0.0996 (9.96%) to a normal distribution with a mean value of 0.0312 (3.12%) and a standard deviation of 0.00292 (0.29%). Finally the crop uptake factor changed from a constant value of 6.37e -4 (Bq crop /kg)/(Bq soil /kg) to a lognormal distribution with a geometric mean value of 3.38e -4 (Bq crop /kg)/(Bq soil /kg) and a standard deviation value of 3.33 (Bq crop /kg)/(Bq soil /kg)« less

Enhancing Soil Productivity Using a Multi-Crop Rotation and Beef Cattle Grazing

NASA Astrophysics Data System (ADS)

Şentürklü, Songül; Landblom, Douglas; Cihacek, Larry; Brevik, Eric

2016-04-01

Agricultural production systems that include complimentary plant, soil and animal interaction contribute to sustainability. In sustainable livestock systems integrated with crop production, the soil resource is impacted positively. The goal of this research was to maximize beef cattle and crop economic yield, while improving the soil resource by increasing soil organic matter (SOM) and subsequently seasonal soil nitrogen fertility over a 5-year period (2011-2015). Each experimental crop field used in the study was 1.74 ha. Small-seeded crops were planted using a JD 1590 No-Till drill. Corn (C) and sunflowers (SF) were planted using a JD 7000 No-Till planter. The cropping sequence used in the study was SF, hard red spring wheat (HRSW), fall seeded winter triticale-hairy vetch (T-HV), spring harvested for hay/mid-June seeded 7-species cover crop (CC; SF, Everleaf Oat, Flex Winter Pea, HV, Winfred Forage Rape, Ethiopian Cabbage, Hunter Leaf Turnip), C (85-day var.), and field pea-barley intercrop (PBY). The HRSW and SF were harvested as cash crops and the PBY, C, and CC were harvested by grazing cattle. In the system, yearling beef steers grazed PBY and unharvested C before feedlot entry, and after weaning, gestating cows grazed CC. Seasonal soil nitrogen fertility was measured at 0-15, 15-30, and 30-61 cm depths approximately every two weeks from June to October, 2014. The regression illustrating the relationship between SOM and average seasonal available mineral nitrogen shows that for each percentage increase in SOM there is a corresponding N increase of 1.47 kg/ha. Nitrogen fertilizer applications for the 5-year period of the study were variable; however, the overall trend was for reduced fertilizer requirement as SOM increased. At the same time, grain, oilseed, and annual forage crop yields increased year over year (2011-2015) except for the 2014 crop year, when above average precipitation delayed seeding and early frost killed the C and SF crops prematurely. Crop yields were as follows for the 5 crop years in the study (2011-2015): (1) CC was 0.25, 10.5, 8.03, 1.53, and 7.22t/ha, (2) C silage was 4.08, 9.04, 9.91, 8.65, and 14.4 t/ha, (3) C grain was 1.04, 3.81, 6.09, 3.11, and 5.1 t/ha, (4) SF was 1.10, 1.96, 2.42, 1.31, and 2.29 t/ha, (5) PBY forage was 0.0, 7.68, 11.2, 9.3, and 8.72 t/ha. When cattle grazed annual forage crops (C, PBY, and CC), animal manure and trampling contributed to the overall improvement of soil fertility. These data suggest that the combined effect of a multi-crop rotation that includes animal grazing enhances soil fertility and subsequently crop yields, and animal production for a sustainable integrated agricultural system.

Comparative assessment of smallholder sustainability using an agricultural sustainability framework and a yield based index insurance: A case study

NASA Astrophysics Data System (ADS)

Moshtaghi, Mehrdad; Adla, Soham; Pande, Saket; Disse, Markus; Savenije, Hubert

2017-04-01

The concept of sustainability is central to smallholder agriculture as subsistence farming is constantly impacted by livelihood insecurity and is constrained by access to capital, water technology and alternative employment opportunities. This study compares two approaches which aim at quantifying smallholder sustainability but differ in their underlying principles, methodologies for assessment and reporting, and applications. The yield index based insurance can protect the smallholder agriculture and help it to more economic sustainability because the income of smallholder depends on selling crops and this insurance scheme is based on crop yields. In this research, the trigger of this insurance sets on the basis of yields in previous years. The crop yields are calculated every year through socio-hydrology modeling and smallholder can get indemnity when crop yields are lower than average of previous five years (a crop failure). The FAO Sustainability Assessment of Food and Agriculture (SAFA) is an inclusive and comprehensive framework for sustainability assessment in the food and agricultural sector. It follows the UN definition of the 4 dimensions of sustainability (good governance, environmental integrity, economic resilience and social well-being) and includes 21 themes and 58 sub-themes with a multi-indicator approach. The direct sustainability corresponding to the FAO SAFA economic resilience dimension is compared with the indirect notion of sustainability derived from the yield based index insurance. A semi-synthetic comparison is conducted to understand the differences in the underlying principles, methodologies and application of the two approaches. Both approaches are applied to data from smallholder regions of Marathwada in Maharashtra (India) which experienced a severe rise in farmer suicides in the 2000s which has been attributed to a combination of socio-hydrological factors.

Assessing uncertainties in crop and pasture ensemble model simulations of productivity and N2 O emissions.

PubMed

Ehrhardt, Fiona; Soussana, Jean-François; Bellocchi, Gianni; Grace, Peter; McAuliffe, Russel; Recous, Sylvie; Sándor, Renáta; Smith, Pete; Snow, Val; de Antoni Migliorati, Massimiliano; Basso, Bruno; Bhatia, Arti; Brilli, Lorenzo; Doltra, Jordi; Dorich, Christopher D; Doro, Luca; Fitton, Nuala; Giacomini, Sandro J; Grant, Brian; Harrison, Matthew T; Jones, Stephanie K; Kirschbaum, Miko U F; Klumpp, Katja; Laville, Patricia; Léonard, Joël; Liebig, Mark; Lieffering, Mark; Martin, Raphaël; Massad, Raia S; Meier, Elizabeth; Merbold, Lutz; Moore, Andrew D; Myrgiotis, Vasileios; Newton, Paul; Pattey, Elizabeth; Rolinski, Susanne; Sharp, Joanna; Smith, Ward N; Wu, Lianhai; Zhang, Qing

2018-02-01

Simulation models are extensively used to predict agricultural productivity and greenhouse gas emissions. However, the uncertainties of (reduced) model ensemble simulations have not been assessed systematically for variables affecting food security and climate change mitigation, within multi-species agricultural contexts. We report an international model comparison and benchmarking exercise, showing the potential of multi-model ensembles to predict productivity and nitrous oxide (N 2 O) emissions for wheat, maize, rice and temperate grasslands. Using a multi-stage modelling protocol, from blind simulations (stage 1) to partial (stages 2-4) and full calibration (stage 5), 24 process-based biogeochemical models were assessed individually or as an ensemble against long-term experimental data from four temperate grassland and five arable crop rotation sites spanning four continents. Comparisons were performed by reference to the experimental uncertainties of observed yields and N 2 O emissions. Results showed that across sites and crop/grassland types, 23%-40% of the uncalibrated individual models were within two standard deviations (SD) of observed yields, while 42 (rice) to 96% (grasslands) of the models were within 1 SD of observed N 2 O emissions. At stage 1, ensembles formed by the three lowest prediction model errors predicted both yields and N 2 O emissions within experimental uncertainties for 44% and 33% of the crop and grassland growth cycles, respectively. Partial model calibration (stages 2-4) markedly reduced prediction errors of the full model ensemble E-median for crop grain yields (from 36% at stage 1 down to 4% on average) and grassland productivity (from 44% to 27%) and to a lesser and more variable extent for N 2 O emissions. Yield-scaled N 2 O emissions (N 2 O emissions divided by crop yields) were ranked accurately by three-model ensembles across crop species and field sites. The potential of using process-based model ensembles to predict jointly productivity and N 2 O emissions at field scale is discussed. © 2017 John Wiley & Sons Ltd.

Identification of climate-resilient integrated nutrient management practices for rice-rice cropping system--an empirical approach to uphold food security.

PubMed

Subash, N; Gangwar, B; Singh, Rajbir; Sikka, A K

2015-01-01

Yield datasets of long-term experiments on integrated nutrient management in rice-rice cropping systems were used to investigate the relationship of variability in rainfall, temperature, and integrated nutrient management (INM) practices in rice-rice cropping system in three different agroecological regions of India. Twelve treatments with different combinations of inorganic (chemical fertilizer) and organic (farmyard manure, green manure, and paddy straw) were compared with farmer's conventional practice. The intraseasonal variations in rice yields are largely driven by rainfall during kharif rice and by temperature during rabi rice. Half of the standard deviation from the average monthly as well as seasonal rainfall during kharif rice and 1 °C increase or decrease from the average maximum and minimum temperature during rabi rice has been taken as the classification of yield groups. The trends in the date of effective onset of monsoon indicate a 36-day delay during the 30-year period at Rajendranagar, which is statistically significant at 95 % confidence level. The mean annual maximum temperature shows an increasing trend in all the study sites. The length of monsoon also showed a shrinking trend in the rate of 40 days during the 30-year study period at Rajendranagar representing a semiarid region. At Bhubaneshwar, the application of 50 % recommended NPK through chemical fertilizers and 50 % N through green manure resulted in an overall average higher increase of 5.1 % in system productivity under both excess and deficit rainfall years and also during the years having seasonal mean maximum temperature ≥35 °C. However, at Jorhat, the application of 50 % recommended NPK through chemical fertilizers and 50 % N through straw resulted in an overall average higher increase of 7.4 % in system productivity, while at Rajendranagar, the application of 75 % NPK through chemical fertilizers and 25 % N through green manusre resulted in an overall average higher increase of 8.8 % in system productivity. This study highlights the adaptive capacity of different integrated nutrient management practices to rainfall and temperature variability under a rice-rice cropping system in humid, subhumid, and semiarid ecosystems.

Weather based risks and insurances for agricultural production

NASA Astrophysics Data System (ADS)

Gobin, Anne

2015-04-01

Extreme weather events such as frost, drought, heat waves and rain storms can have devastating effects on cropping systems. According to both the agriculture and finance sectors, a risk assessment of extreme weather events and their impact on cropping systems is needed. The principle of return periods or frequencies of natural hazards is adopted in many countries as the basis of eligibility for the compensation of associated losses. For adequate risk management and eligibility, hazard maps for events with a 20-year return period are often used. Damages due to extreme events are strongly dependent on crop type, crop stage, soil type and soil conditions. The impact of extreme weather events particularly during the sensitive periods of the farming calendar therefore requires a modelling approach to capture the mixture of non-linear interactions between the crop, its environment and the occurrence of the meteorological event in the farming calendar. Physically based crop models such as REGCROP (Gobin, 2010) assist in understanding the links between different factors causing crop damage. Subsequent examination of the frequency, magnitude and impacts of frost, drought, heat stress and soil moisture stress in relation to the cropping season and crop sensitive stages allows for risk profiles to be confronted with yields, yield losses and insurance claims. The methodology is demonstrated for arable food crops, bio-energy crops and fruit. The perspective of rising risk-exposure is exacerbated further by limited aid received for agricultural damage, an overall reduction of direct income support to farmers and projected intensification of weather extremes with climate change. Though average yields have risen continuously due to technological advances, there is no evidence that relative tolerance to adverse weather events has improved. The research is funded by the Belgian Science Policy Organisation (Belspo) under contract nr SD/RI/03A.

Possible mechanisms of pollination failure in hybrid carrot seed and implications for industry in a changing climate.

PubMed

Broussard, Melissa Ann; Mas, Flore; Howlett, Brad; Pattemore, David; Tylianakis, Jason M

2017-01-01

Approximately one-third of our food globally comes from insect-pollinated crops. The dependence on pollinators has been linked to yield instability, which could potentially become worse in a changing climate. Insect-pollinated crops produced via hybrid breeding (20% of fruit and vegetable production globally) are especially at risk as they are even more reliant on pollinators than open-pollinated plants. We already observe a wide range of fruit and seed yields between different cultivars of the same crop species, and it is unknown how existing variation will be affected in a changing climate. In this study, we examined how three hybrid carrot varieties with differential performance in the field responded to three temperature regimes (cooler than the historical average, average, and warmer that the historical average). We tested how temperature affected the plants' ability to set seed (seed set, pollen viability) as well as attract pollinators (nectar composition, floral volatiles). We found that there were significant intrinsic differences in nectar phenolics, pollen viability, and seed set between the carrot varieties, and that higher temperatures did not exaggerate those differences. However, elevated temperature did negatively affect several characteristics relating to the attraction and reward of pollinators (lower volatile production and higher nectar sugar concentration) across all varieties, which may decrease the attractiveness of this already pollinator-limited crop. Given existing predictions of lower pollinator populations in a warmer climate, reduced attractiveness would add yet another challenge to future food production.

Possible mechanisms of pollination failure in hybrid carrot seed and implications for industry in a changing climate

PubMed Central

Mas, Flore; Howlett, Brad; Pattemore, David; Tylianakis, Jason M.

2017-01-01

Approximately one-third of our food globally comes from insect-pollinated crops. The dependence on pollinators has been linked to yield instability, which could potentially become worse in a changing climate. Insect-pollinated crops produced via hybrid breeding (20% of fruit and vegetable production globally) are especially at risk as they are even more reliant on pollinators than open-pollinated plants. We already observe a wide range of fruit and seed yields between different cultivars of the same crop species, and it is unknown how existing variation will be affected in a changing climate. In this study, we examined how three hybrid carrot varieties with differential performance in the field responded to three temperature regimes (cooler than the historical average, average, and warmer that the historical average). We tested how temperature affected the plants' ability to set seed (seed set, pollen viability) as well as attract pollinators (nectar composition, floral volatiles). We found that there were significant intrinsic differences in nectar phenolics, pollen viability, and seed set between the carrot varieties, and that higher temperatures did not exaggerate those differences. However, elevated temperature did negatively affect several characteristics relating to the attraction and reward of pollinators (lower volatile production and higher nectar sugar concentration) across all varieties, which may decrease the attractiveness of this already pollinator-limited crop. Given existing predictions of lower pollinator populations in a warmer climate, reduced attractiveness would add yet another challenge to future food production. PMID:28665949

Yield Response of Spring Maize to Inter-Row Subsoiling and Soil Water Deficit in Northern China.

PubMed

Liu, Zhandong; Qin, Anzhen; Zhao, Ben; Ata-Ul-Karim, Syed Tahir; Xiao, Junfu; Sun, Jingsheng; Ning, Dongfeng; Liu, Zugui; Nan, Jiqin; Duan, Aiwang

2016-01-01

Long-term tillage has been shown to induce water stress episode during crop growth period due to low water retention capacity. It is unclear whether integrated water conservation tillage systems, such asspringdeepinter-row subsoiling with annual or biennial repetitions, can be developed to alleviate this issue while improve crop productivity. Experimentswere carried out in a spring maize cropping system on Calcaric-fluvicCambisolsatJiaozuoexperimentstation, northern China, in 2009 to 2014. Effects of threesubsoiling depths (i.e., 30 cm, 40 cm, and 50 cm) in combination with annual and biennial repetitionswasdetermined in two single-years (i.e., 2012 and 2014)againstthe conventional tillage. The objectives were to investigateyield response to subsoiling depths and soil water deficit(SWD), and to identify the most effective subsoiling treatment using a systematic assessment. Annualsubsoiling to 50 cm (AS-50) increased soil water storage (SWS, mm) by an average of8% in 0-20 cm soil depth, 19% in 20-80 cm depth, and 10% in 80-120 cm depth, followed by AS-40 and BS-50, whereas AS-30 and BS-30 showed much less effects in increasing SWS across the 0-120 cm soil profile, compared to the CK. AS-50 significantly reduced soil water deficit (SWD, mm) by an average of123% during sowing to jointing, 318% during jointing to filling, and 221% during filling to maturity, compared to the CK, followed by AS-40 and BS-50. An integrated effect on increasing SWS and reducing SWD helped AS-50 boost grain yield by an average of 31% and biomass yield by 30%, compared to the CK. A power function for subsoiling depth and a negative linear function for SWD were used to fit the measured yields, showing the deepest subsoiling depth (50 cm) with the lowest SWD contributed to the highest yield. Systematic assessment showed that AS-50 received the highest evaluation index (0.69 out of 1.0) among all treatments. Deepinter-row subsoilingwith annual repetition significantly boosts yield by alleviating SWD in critical growth period and increasing SWS in 20-80 cm soil depth. The results allow us to conclude that AS-50 can be adopted as an effective approach to increase crop productivity, alleviate water stress, and improve soil water availability for spring maize in northern China.

Fall rice straw management and winter flooding treatment effects on a subsequent soybean crop

USGS Publications Warehouse

Anders, M.M.; Windham, T.E.; McNew, R.W.; Reinecke, K.J.

2005-01-01

The effects of fall rice (Oryza sativa L.) straw management and winter flooding on the yield and profitability of subsequent irrigated and dryland soybean [Glycine max (L.) Merr.] crops were studied for 3 years. Rice straw treatments consisted of disking, rolling, or standing stubble. Winter flooding treatments consisted of maintaining a minimum water depth of 10 cm by pumping water when necessary, impounding available rainfall, and draining fields to prevent flooding. The following soybean crop was managed as a conventional-tillage system or no-till system. Tillage system treatments were further divided into irrigated or dryland. Results indicated that there were no significant effects from either fall rice straw management or winter flooding treatments on soybean seed yields. Soybean seed yields for, the conventional tillage system were significantly greater than those for the no-till system for the first 2 yrs and not different in the third year. Irrigated soybean seed yields were significantly greater than those from dryland plots for all years. Net economic returns averaged over the 3 yrs were greatest ($390.00 ha-1) from the irrigated no-till system.

Soil organic carbon dynamics and crop yield for different crop rotations in a degraded ferruginous tropical soil in a semi-arid region: a simulation approach.

PubMed

Soler, C M Tojo; Bado, V B; Traore, K; Bostick, W McNair; Jones, J W; Hoogenboom, G

2011-10-01

In recent years, simulation models have been used as a complementary tool for research and for quantifying soil carbon sequestration under widely varying conditions. This has improved the understanding and prediction of soil organic carbon (SOC) dynamics and crop yield responses to soil and climate conditions and crop management scenarios. The goal of the present study was to estimate the changes in SOC for different cropping systems in West Africa using a simulation model. A crop rotation experiment conducted in Farakô-Ba, Burkina Faso was used to evaluate the performance of the cropping system model (CSM) of the Decision Support System for Agrotechnology Transfer (DSSAT) for simulating yield of different crops. Eight crop rotations that included cotton, sorghum, peanut, maize and fallow, and three different management scenarios, one without N (control), one with chemical fertilizer (N) and one with manure applications, were studied. The CSM was able to simulate the yield trends of various crops, with inconsistencies for a few years. The simulated SOC increased slightly across the years for the sorghum-fallow rotation with manure application. However, SOC decreased for all other rotations except for the continuous fallow (native grassland), in which the SOC remained stable. The model simulated SOC for the continuous fallow system with a high degree of accuracy normalized root mean square error (RMSE)=0·001, while for the other crop rotations the simulated SOC values were generally within the standard deviation (s.d.) range of the observed data. The crop rotations that included a supplemental N-fertilizer or manure application showed an increase in the average simulated aboveground biomass for all crops. The incorporation of this biomass into the soil after harvest reduced the loss of SOC. In the present study, the observed SOC data were used for characterization of production systems with different SOC dynamics. Following careful evaluation of the CSM with observed soil organic matter (SOM) data similar to the study presented here, there are many opportunities for the application of the CSM for carbon sequestration and resource management in Sub-Saharan Africa.

Variation in Yield Gap Induced by Nitrogen, Phosphorus and Potassium Fertilizer in North China Plain

PubMed Central

Dai, Xiaoqin; Ouyang, Zhu; Li, Yunsheng; Wang, Huimin

2013-01-01

A field experiment was conducted under a wheat-maize rotation system from 1990 to 2006 in North China Plain (NCP) to determine the effects of N, P and K on yield and yield gap. There were five treatments: NPK, PK, NK, NP and a control. Average wheat and maize yields were the highest in the NPK treatment, followed by those in the NP plots among all treatments. For wheat and maize yield, a significant increasing trend over time was found in the NPK-treated plots and a decreasing trend in the NK-treated plots. In the absence of N or P, wheat and maize yields were significantly lower than those in the NPK treatment. For both crops, the increasing rate of the yield gap was the highest in the P omission plots, i.e., 189.1 kg ha−1 yr−1 for wheat and 560.6 kg ha−1 yr−1 for maize. The cumulative omission of P fertilizer induced a deficit in the soil available N and extractable P concentrations for maize. The P fertilizer was more pivotal in long-term wheat and maize growth and soil fertility conservation in NCP, although the N fertilizer input was important for both crops growth. The crop response to K fertilizers was much lower than that to N or P fertilizers, but for maize, the cumulative omission of K fertilizer decreased the yield by 26% and increased the yield gap at a rate of 322.7 kg ha−1 yr−1. The soil indigenous K supply was not sufficiently high to meet maize K requirement over a long period. The proper application of K fertilizers is necessary for maize production in the region. Thus, the appropriate application of N and P fertilizers for the growth of both crops, while regularly combining K fertilizers for maize growth, is absolutely necessary for sustainable crop production in the NCP. PMID:24349204

Variation in yield gap induced by nitrogen, phosphorus and potassium fertilizer in North China Plain.

PubMed

Dai, Xiaoqin; Ouyang, Zhu; Li, Yunsheng; Wang, Huimin

2013-01-01

A field experiment was conducted under a wheat-maize rotation system from 1990 to 2006 in North China Plain (NCP) to determine the effects of N, P and K on yield and yield gap. There were five treatments: NPK, PK, NK, NP and a control. Average wheat and maize yields were the highest in the NPK treatment, followed by those in the NP plots among all treatments. For wheat and maize yield, a significant increasing trend over time was found in the NPK-treated plots and a decreasing trend in the NK-treated plots. In the absence of N or P, wheat and maize yields were significantly lower than those in the NPK treatment. For both crops, the increasing rate of the yield gap was the highest in the P omission plots, i.e., 189.1 kg ha(-1) yr(-1) for wheat and 560.6 kg ha(-1) yr(-1) for maize. The cumulative omission of P fertilizer induced a deficit in the soil available N and extractable P concentrations for maize. The P fertilizer was more pivotal in long-term wheat and maize growth and soil fertility conservation in NCP, although the N fertilizer input was important for both crops growth. The crop response to K fertilizers was much lower than that to N or P fertilizers, but for maize, the cumulative omission of K fertilizer decreased the yield by 26% and increased the yield gap at a rate of 322.7 kg ha(-1) yr(-1). The soil indigenous K supply was not sufficiently high to meet maize K requirement over a long period. The proper application of K fertilizers is necessary for maize production in the region. Thus, the appropriate application of N and P fertilizers for the growth of both crops, while regularly combining K fertilizers for maize growth, is absolutely necessary for sustainable crop production in the NCP.

Current nitrogen management status and measures to improve the intensive wheat-maize system in China.

PubMed

Cui, Zhenling; Chen, Xinping; Zhang, Fusuo

2010-01-01

During the first 35 years of the Green Revolution, Chinese grain production doubled, greatly reducing food shortage, but at a high environmental cost. In 2005, China alone accounted for around 38% of the global N fertilizer consumption, but the average on-farm N recovery efficiency for the intensive wheat-maize system was only 16-18%. Current on-farm N use efficiency (NUE) is much lower than in research trials or on-farm in other parts of the world, which is attributed to the overuse of chemical N fertilizer, ignorance of the contribution of N from the environment and the soil, poor synchrony between crop N demand and N supply, failure to bring crop yield potential into full play, and an inability to effectively inhibit N losses. Based on such analyses, some measures to drastically improve NUE in China are suggested, such as managing various N sources to limit the total applied N, spatially and temporally matching rhizospheric N supply with N demand in high-yielding crops, reducing N losses, and simultaneously achieving high-yield and high NUE. Maximizing crop yields using a minimum of N inputs requires an integrated, interdisciplinary cooperation and major scientific and practical breakthroughs involving plant nutrition, soil science, agronomy, and breeding.

Estimating national crop yield potential and the relevance of weather data sources

NASA Astrophysics Data System (ADS)

Van Wart, Justin

2011-12-01

To determine where, when, and how to increase yields, researchers often analyze the yield gap (Yg), the difference between actual current farm yields and crop yield potential. Crop yield potential (Yp) is the yield of a crop cultivar grown under specific management limited only by temperature and solar radiation and also by precipitation for water limited yield potential (Yw). Yp and Yw are critical components of Yg estimations, but are very difficult to quantify, especially at larger scales because management data and especially daily weather data are scarce. A protocol was developed to estimate Yp and Yw at national scales using site-specific weather, soils and management data. Protocol procedures and inputs were evaluated to determine how to improve accuracy of Yp, Yw and Yg estimates. The protocol was also used to evaluate raw, site-specific and gridded weather database sources for use in simulations of Yp or Yw. The protocol was applied to estimate crop Yp in US irrigated maize and Chinese irrigated rice and Yw in US rainfed maize and German rainfed wheat. These crops and countries account for >20% of global cereal production. The results have significant implications for past and future studies of Yp, Yw and Yg. Accuracy of national long-term average Yp and Yw estimates was significantly improved if (i) > 7 years of simulations were performed for irrigated and > 15 years for rainfed sites, (ii) > 40% of nationally harvested area was within 100 km of all simulation sites, (iii) observed weather data coupled with satellite derived solar radiation data were used in simulations, and (iv) planting and harvesting dates were specified within +/- 7 days of farmers actual practices. These are much higher standards than have been applied in national estimates of Yp and Yw and this protocol is a substantial step in making such estimates more transparent, robust, and straightforward. Finally, this protocol may be a useful tool for understanding yield trends and directing research and development efforts aimed at providing for a secure and stable future food supply.

Breaking continuous potato cropping with legumes improves soil microbial communities, enzyme activities and tuber yield

PubMed Central

Qin, Shuhao; Yeboah, Stephen; Cao, Li; Zhang, Junlian; Shi, Shangli; Liu, Yuhui

2017-01-01

This study was conducted to explore the changes in soil microbial populations, enzyme activity, and tuber yield under the rotation sequences of Potato–Common vetch (P–C), Potato–Black medic (P–B) and Potato–Longdong alfalfa (P–L) in a semi–arid area of China. The study also determined the effects of continuous potato cropping (without legumes) on the above mentioned soil properties and yield. The number of bacteria increased significantly (p < 0.05) under P–B rotation by 78%, 85% and 83% in the 2, 4 and 7–year continuous cropping soils, respectively compared to P–C rotation. The highest fungi/bacteria ratio was found in P–C (0.218), followed by P–L (0.184) and then P–B (0.137) rotation over the different cropping years. In the continuous potato cropping soils, the greatest fungi/bacteria ratio was recorded in the 4–year (0.4067) and 7–year (0.4238) cropping soils and these were significantly higher than 1–year (0.3041), 2–year (0.2545) and 3–year (0.3030) cropping soils. Generally, actinomycetes numbers followed the trend P–L>P–C>P–B. The P–L rotation increased aerobic azotobacters in 2–year (by 26% and 18%) and 4–year (40% and 21%) continuous cropping soils compared to P–C and P–B rotation, respectively. Generally, the highest urease and alkaline phosphate activity, respectively, were observed in P–C (55.77 mg g–1) and (27.71 mg g–1), followed by P–B (50.72 mg mg–1) and (25.64 mg g–1) and then P–L (41.61 mg g–1) and (23.26 mg g–1) rotation. Soil urease, alkaline phosphatase and hydrogen peroxidase activities decreased with increasing years of continuous potato cropping. On average, the P–B rotation significantly increased (p <0.05) tuber yield by 19% and 18%, compared to P–C and P–L rotation respectively. P–L rotation also increased potato tuber yield compared to P–C, but the effect was lesser relative to P–B rotation. These results suggest that adopting potato–legume rotation system has the potential to improve soil biology environment, alleviate continuous cropping obstacle and increase potato tuber yield in semi–arid region. PMID:28463981

Reducing N2O and NO emissions while sustaining crop productivity in a Chinese vegetable-cereal double cropping system.

PubMed

Yao, Zhisheng; Yan, Guangxuan; Zheng, Xunhua; Wang, Rui; Liu, Chunyan; Butterbach-Bahl, Klaus

2017-12-01

High nitrogen (N) inputs in Chinese vegetable and cereal productions played key roles in increasing crop yields. However, emissions of the potent greenhouse gas nitrous oxide (N 2 O) and atmospheric pollutant nitric oxide (NO) increased too. For lowering the environmental costs of crop production, it is essential to optimize N strategies to maintain high crop productivity, while reducing the associated N losses. We performed a 2 year-round field study regarding the effect of different combinations of poultry manure and chemical N fertilizers on crop yields, N use efficiency (NUE) and N 2 O and NO fluxes from a Welsh onion-winter wheat system in the North China Plain. Annual N 2 O and NO emissions averaged 1.14-3.82 kg N ha -1 yr -1 (or 5.54-13.06 g N kg -1 N uptake) and 0.57-1.87 kg N ha -1 yr -1 (or 2.78-6.38 g N kg -1 N uptake) over all treatments, respectively. Both N 2 O and NO emissions increased linearly with increasing total N inputs, and the mean annual direct emission factors (EF d ) were 0.39% for N 2 O and 0.19% for NO. Interestingly, the EF d for chemical N fertilizers (N 2 O: 0.42-0.48%; NO: 0.07-0.11%) was significantly lower than for manure N (N 2 O: 1.35%; NO: 0.76%). Besides, a negative power relationship between yield-scaled N 2 O, NO or N 2 O + NO emissions and NUE was observed, suggesting that improving NUE in crop production is crucial for increasing crop yields while decreasing nitrogenous gas release. Compared to the current farmers' fertilization rate, alternative practices with reduced chemical N fertilizers increased NUE and decreased annual N 2 O + NO emissions substantially, while crop yields remained unaffected. As a result, annual yield-scaled N 2 O + NO emissions were reduced by > 20%. Our study shows that a reduction of current application rates of chemical N fertilizers by 30-50% does not affect crop productivity, while at the same time N 2 O and NO emissions would be reduced significantly. Copyright © 2017 Elsevier Ltd. All rights reserved.

How Do Various Maize Crop Models Vary in Their Responses to Climate Change Factors?

NASA Technical Reports Server (NTRS)

Bassu, Simona; Brisson, Nadine; Grassini, Patricio; Durand, Jean-Louis; Boote, Kenneth; Lizaso, Jon; Jones, James W.; Rosenzweig, Cynthia; Ruane, Alex C.; Adam, Myriam;

How do various maize crop models vary in their responses to climate change factors?

PubMed

Bassu, Simona; Brisson, Nadine; Durand, Jean-Louis; Boote, Kenneth; Lizaso, Jon; Jones, James W; Rosenzweig, Cynthia; Ruane, Alex C; Adam, Myriam; Baron, Christian; Basso, Bruno; Biernath, Christian; Boogaard, Hendrik; Conijn, Sjaak; Corbeels, Marc; Deryng, Delphine; De Sanctis, Giacomo; Gayler, Sebastian; Grassini, Patricio; Hatfield, Jerry; Hoek, Steven; Izaurralde, Cesar; Jongschaap, Raymond; Kemanian, Armen R; Kersebaum, K Christian; Kim, Soo-Hyung; Kumar, Naresh S; Makowski, David; Müller, Christoph; Nendel, Claas; Priesack, Eckart; Pravia, Maria Virginia; Sau, Federico; Shcherbak, Iurii; Tao, Fulu; Teixeira, Edmar; Timlin, Dennis; Waha, Katharina

2014-07-01

Potential consequences of climate change on crop production can be studied using mechanistic crop simulation models. While a broad variety of maize simulation models exist, it is not known whether different models diverge on grain yield responses to changes in climatic factors, or whether they agree in their general trends related to phenology, growth, and yield. With the goal of analyzing the sensitivity of simulated yields to changes in temperature and atmospheric carbon dioxide concentrations [CO2 ], we present the largest maize crop model intercomparison to date, including 23 different models. These models were evaluated for four locations representing a wide range of maize production conditions in the world: Lusignan (France), Ames (USA), Rio Verde (Brazil) and Morogoro (Tanzania). While individual models differed considerably in absolute yield simulation at the four sites, an ensemble of a minimum number of models was able to simulate absolute yields accurately at the four sites even with low data for calibration, thus suggesting that using an ensemble of models has merit. Temperature increase had strong negative influence on modeled yield response of roughly -0.5 Mg ha(-1) per °C. Doubling [CO2 ] from 360 to 720 μmol mol(-1) increased grain yield by 7.5% on average across models and the sites. That would therefore make temperature the main factor altering maize yields at the end of this century. Furthermore, there was a large uncertainty in the yield response to [CO2 ] among models. Model responses to temperature and [CO2 ] did not differ whether models were simulated with low calibration information or, simulated with high level of calibration information. © 2014 John Wiley & Sons Ltd.

Midwest agriculture and ENSO: A comparison of AVHRR NDVI3g data and crop yields in the United States Corn Belt from 1982 to 2014

NASA Astrophysics Data System (ADS)

Glennie, Erin; Anyamba, Assaf

2018-06-01

A time series of Advanced Very High Resolution Radiometer (AVHRR) derived normalized difference vegetation index (NDVI) data were compared to National Agricultural Statistics Service (NASS) corn yield data in the United States Corn Belt from 1982 to 2014. The main objectives of the comparison were to assess 1) the consistency of regional Corn Belt responses to El Niño/Southern Oscillation (ENSO) teleconnection signals, and 2) the reliability of using NDVI as an indicator of crop yield. Regional NDVI values were used to model a seasonal curve and to define the growing season - May to October. Seasonal conditions in each county were represented by NDVI and land surface temperature (LST) composites, and corn yield was represented by average annual bushels produced per acre. Correlation analysis between the NDVI, LST, corn yield, and equatorial Pacific sea surface temperature anomalies revealed patterns in land surface dynamics and corn yield, as well as typical impacts of ENSO episodes. It was observed from the study that growing seasons coincident with La Niña events were consistently warmer, but El Niño events did not consistently impact NDVI, temperature, or corn yield data. Moreover, the El Niño and La Niña composite images suggest that impacts vary spatially across the Corn Belt. While corn is the dominant crop in the region, some inconsistencies between corn yield and NDVI may be attributed to soy crops and other background interference. The overall correlation between the total growing season NDVI anomaly and detrended corn yield was 0.61(p = 0.00013), though the strength of the relationship varies across the Corn Belt.

Historical and simulated ecosystem carbon dynamics in Ghana: Land use, management, and climate

USGS Publications Warehouse

Tan, Z.; Tieszen, L.L.; Tachie-Obeng, E.; Liu, S.; Dieye, A.M.

2009-01-01

We used the General Ensemble biogeochemical Modeling System (GEMS) to simulate responses of natural and managed ecosystems to changes in land use and land cover, management, and climate for a forest/savanna transitional zone in central Ghana. Model results show that deforestation for crop production during the 20th century resulted in a substantial reduction in ecosystem carbon (C) stock from 135.4 Mg C ha−1 in 1900 to 77.0 Mg C ha−1 in 2000, and in soil organic C stock within the top 20 cm of soil from 26.6 Mg C ha−1 to 21.2 Mg C ha−1. If no land use change takes place from 2000 through 2100, low and high climate change scenarios (increase in temperature and decrease in precipitation over time) will result in losses of soil organic C stock by 16% and 20%, respectively. A low nitrogen (N) fertilization rate is the principal constraint on current crop production. An increase in N fertilization under the low climate change scenario would lead to an increase in the average crop yield by 21% with 30 kg N ha−1 and by 42% with 60 kg N ha−1 (varying with crop species), accordingly, the average soil C stock would decrease by 2% and increase by 17%, in all cropping systems by 2100. The results suggest that a reasonable N fertilization rate is critical to achieve food security and agricultural sustainability in the study area through the 21st century. Adaptation strategies for climate change in this study area require national plans to support policies and practices that provide adequate N fertilizers to sustain soil C and crop yields and to consider high temperature tolerant crop species if these temperature projections are exceeded.

Historical and simulated ecosystem carbon dynamics in Ghana: land use, management, and climate

NASA Astrophysics Data System (ADS)

Tan, Z.; Tieszen, L. L.; Tachie-Obeng, E.; Liu, S.; Dieye, A. M.

2009-01-01

We used the General Ensemble biogeochemical Modeling System (GEMS) to simulate responses of natural and managed ecosystems to changes in land use and land cover, management, and climate for a forest/savanna transitional zone in central Ghana. Model results show that deforestation for crop production during the 20th century resulted in a substantial reduction in ecosystem carbon (C) stock from 135.4 Mg C ha-1 in 1900 to 77.0 Mg C ha-1 in 2000, and in soil organic C stock within the top 20 cm of soil from 26.6 Mg C ha-1 to 21.2 Mg C ha-1. If no land use change takes place from 2000 through 2100, low and high climate change scenarios (increase in temperature and decrease in precipitation over time) will result in losses of soil organic C stock by 16% and 20%, respectively. A low nitrogen (N) fertilization rate is the principal constraint on current crop production. An increase in N fertilization under the low climate change scenario would lead to an increase in the average crop yield by 21% with 30 kg N ha-1 and by 42% with 60 kg N ha-1 (varying with crop species), accordingly, the average soil C stock would decrease by 2% and increase by 17%, in all cropping systems by 2100. The results suggest that a reasonable N fertilization rate is critical to achieve food security and agricultural sustainability in the study area through the 21st century. Adaptation strategies for climate change in this study area require national plans to support policies and practices that provide adequate N fertilizers to sustain soil C and crop yields and to consider high temperature tolerant crop species if these temperature projections are exceeded.

Climate change and maize yield in Iowa

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xu, Hong; Twine, Tracy E.; Girvetz, Evan

Climate is changing across the world, including the major maize-growing state of Iowa in the USA. To maintain crop yields, farmers will need a suite of adaptation strategies, and choice of strategy will depend on how the local to regional climate is expected to change. Here we predict how maize yield might change through the 21 st century as compared with late 20 th century yields across Iowa, USA, a region representing ideal climate and soils for maize production that contributes substantially to the global maize economy. To account for climate model uncertainty, we drive a dynamic ecosystem model withmore » output from six climate models and two future climate forcing scenarios. Despite a wide range in the predicted amount of warming and change to summer precipitation, all simulations predict a decrease in maize yields from late 20 th century to middle and late 21 st century ranging from 15% to 50%. Linear regression of all models predicts a 6% state-averaged yield decrease for every 1°C increase in warm season average air temperature. When the influence of moisture stress on crop growth is removed from the model, yield decreases either remain the same or are reduced, depending on predicted changes in warm season precipitation. Lastly, our results suggest that even if maize were to receive all the water it needed, under the strongest climate forcing scenario yields will decline by 10-20% by the end of the 21 st century.« less

Climate change and maize yield in Iowa

DOE PAGES

Xu, Hong; Twine, Tracy E.; Girvetz, Evan

2016-05-24

Climate is changing across the world, including the major maize-growing state of Iowa in the USA. To maintain crop yields, farmers will need a suite of adaptation strategies, and choice of strategy will depend on how the local to regional climate is expected to change. Here we predict how maize yield might change through the 21 st century as compared with late 20 th century yields across Iowa, USA, a region representing ideal climate and soils for maize production that contributes substantially to the global maize economy. To account for climate model uncertainty, we drive a dynamic ecosystem model withmore » output from six climate models and two future climate forcing scenarios. Despite a wide range in the predicted amount of warming and change to summer precipitation, all simulations predict a decrease in maize yields from late 20 th century to middle and late 21 st century ranging from 15% to 50%. Linear regression of all models predicts a 6% state-averaged yield decrease for every 1°C increase in warm season average air temperature. When the influence of moisture stress on crop growth is removed from the model, yield decreases either remain the same or are reduced, depending on predicted changes in warm season precipitation. Lastly, our results suggest that even if maize were to receive all the water it needed, under the strongest climate forcing scenario yields will decline by 10-20% by the end of the 21 st century.« less

Adverse weather impacts on arable cropping systems

NASA Astrophysics Data System (ADS)

Gobin, Anne

2016-04-01

Damages due to extreme or adverse weather strongly depend on crop type, crop stage, soil conditions and management. The impact is largest during the sensitive periods of the farming calendar, and requires a modelling approach to capture the interactions between the crop, its environment and the occurrence of the meteorological event. The hypothesis is that extreme and adverse weather events can be quantified and subsequently incorporated in current crop models. Since crop development is driven by thermal time and photoperiod, a regional crop model was used to examine the likely frequency, magnitude and impacts of frost, drought, heat stress and waterlogging in relation to the cropping season and crop sensitive stages. Risk profiles and associated return levels were obtained by fitting generalized extreme value distributions to block maxima for air humidity, water balance and temperature variables. The risk profiles were subsequently confronted with yields and yield losses for the major arable crops in Belgium, notably winter wheat, winter barley, winter oilseed rape, sugar beet, potato and maize at the field (farm records) to regional scale (statistics). The average daily vapour pressure deficit (VPD) and reference evapotranspiration (ET0) during the growing season is significantly lower (p < 0.001) and has a higher variability before 1988 than after 1988. Distribution patterns of VPD and ET0 have relevant impacts on crop yields. The response to rising temperatures depends on the crop's capability to condition its microenvironment. Crops short of water close their stomata, lose their evaporative cooling potential and ultimately become susceptible to heat stress. Effects of heat stress therefore have to be combined with moisture availability such as the precipitation deficit or the soil water balance. Risks of combined heat and moisture deficit stress appear during the summer. These risks are subsequently related to crop damage. The methodology of defining meteorological risks and subsequently relating the risk to the cropping calendar will be demonstrated for major arable crops in Belgium. Physically based crop models assist in understanding the links between adverse weather events, sensitive crop stages and crop damage. Financial support was obtained from Belspo under research contract SD/RI/03A.

Spatial Mapping of Agricultural Water Productivity Using the SWAT Model

NASA Astrophysics Data System (ADS)

Thokal, Rajesh Tulshiram; Gorantiwar, S. D.; Kothari, Mahesh; Bhakar, S. R.; Nandwana, B. P.

2015-03-01

The Sina river basin is facing both episodic and chronic water shortages due to intensive irrigation development. The main objective of this study was to characterize the hydrologic processes of the Sina river basin and assess crop water productivity using the distributed hydrologic model, SWAT. In the simulation year (1998-1999), the inflow to reservoir from upstream side was the major contributor to the reservoir accounting for 92 % of the total required water release for irrigation purpose (119.5 Mm3), while precipitation accounted for 4.1 Mm3. Annual release of water for irrigation was 119.5 Mm3 out of which 54 % water was diverted for irrigation purpose, 26 % was wasted as conveyance loss, average discharge at the command outlet was estimated as 4 % and annual average ground-water recharge coefficient was in the range of 13-17 %. Various scenarios involving water allocation rule were tested with the goal of increasing economic water productivity values in the Sina Irrigation Scheme. Out of those, only most benefited allocation rule is analyzed in this paper. Crop yield varied from 1.98 to 25.9 t/ha, with the majority of the area between 2.14 and 2.78 t/ha. Yield and WP declined significantly in loamy soils of the irrigation command. Crop productivity in the basin was found in the lower range when compared with potential and global values. The findings suggested that there was a potential to improve further. Spatial variations in yield and WP were found to be very high for the crops grown during rabi season, while those were low for the crops grown during kharif season. The crop yields and WP during kharif season were more in the lower reach of the irrigation commands, where loamy soil is more concentrated. Sorghum in both seasons was most profitable. Sorghum fetched net income fivefold that of sunflower, two and half fold of pearl millet and one and half fold of mung beans as far as crop during kharif season were concerned and it fetched fourfold that of groundnut, threefold of wheat, twofold of onion during rabi season and was sevenfold of sugarcane. Analysis suggests that maximization of the area by provision of supplemental irrigation to rainfed areas as well as better on-farm water management practices can provide opportunities for improving water productivity.

Cost-benefit trade-offs of bird activity in apple orchards.

PubMed

Peisley, Rebecca K; Saunders, Manu E; Luck, Gary W

2016-01-01

Birds active in apple orchards in south-eastern Australia can contribute positively (e.g., control crop pests) or negatively (e.g., crop damage) to crop yields. Our study is the first to identify net outcomes of these activities, using six apple orchards, varying in management intensity, in south-eastern Australia as a study system. We also conducted a predation experiment using real and artificial codling moth (Cydia pomonella) larvae (a major pest in apple crops). We found that: (1) excluding birds from branches of apple trees resulted in an average of 12.8% more apples damaged by insects; (2) bird damage to apples was low (1.9% of apples); and (3) when trading off the potential benefits (biological control) with costs (bird damage to apples), birds provided an overall net benefit to orchard growers. We found that predation of real codling moth larvae was higher than for plasticine larvae, suggesting that plasticine prey models are not useful for inferring actual predation levels. Our study shows how complex ecological interactions between birds and invertebrates affect crop yield in apples, and provides practical strategies for improving the sustainability of orchard systems.

Global crop yield response to extreme heat stress under multiple climate change futures

NASA Astrophysics Data System (ADS)

Deryng, D.; Conway, D.; Ramankutty, N.; Price, J.; Warren, R.

2014-12-01

Extreme heat stress during the crop reproductive period can be critical for crop productivity. Projected changes in the frequency and severity of extreme climatic events are expected to negatively impact crop yields and global food production. This study applies the global crop model PEGASUS to quantify, for the first time at the global scale, impacts of extreme heat stress on maize, spring wheat and soybean yields resulting from 72 climate change scenarios for the 21st century. Our results project maize to face progressively worse impacts under a range of RCPs but spring wheat and soybean to improve globally through to the 2080s due to CO2 fertilization effects, even though parts of the tropic and sub-tropic regions could face substantial yield declines. We find extreme heat stress at anthesis (HSA) by the 2080s (relative to the 1980s) under RCP 8.5, taking into account CO2 fertilization effects, could double global losses of maize yield (dY = -12.8 ± 6.7% versus -7.0 ± 5.3% without HSA), reduce projected gains in spring wheat yield by half (dY = 34.3 ± 13.5% versus 72.0 ± 10.9% without HSA) and in soybean yield by a quarter (dY = 15.3 ± 26.5% versus 20.4 ± 22.1% without HSA). The range reflects uncertainty due to differences between climate model scenarios; soybean exhibits both positive and negative impacts, maize is generally negative and spring wheat generally positive. Furthermore, when assuming CO2 fertilization effects to be negligible, we observe drastic climate mitigation policy as in RCP 2.6 could avoid more than 80% of the global average yield losses otherwise expected by the 2080s under RCP 8.5. We show large disparities in climate impacts across regions and find extreme heat stress adversely affects major producing regions and lower income countries.

Global crop yield response to extreme heat stress under multiple climate change futures

NASA Astrophysics Data System (ADS)

Deryng, Delphine; Conway, Declan; Ramankutty, Navin; Price, Jeff; Warren, Rachel

2014-03-01

Extreme heat stress during the crop reproductive period can be critical for crop productivity. Projected changes in the frequency and severity of extreme climatic events are expected to negatively impact crop yields and global food production. This study applies the global crop model PEGASUS to quantify, for the first time at the global scale, impacts of extreme heat stress on maize, spring wheat and soybean yields resulting from 72 climate change scenarios for the 21st century. Our results project maize to face progressively worse impacts under a range of RCPs but spring wheat and soybean to improve globally through to the 2080s due to CO2 fertilization effects, even though parts of the tropic and sub-tropic regions could face substantial yield declines. We find extreme heat stress at anthesis (HSA) by the 2080s (relative to the 1980s) under RCP 8.5, taking into account CO2 fertilization effects, could double global losses of maize yield (ΔY = -12.8 ± 6.7% versus - 7.0 ± 5.3% without HSA), reduce projected gains in spring wheat yield by half (ΔY = 34.3 ± 13.5% versus 72.0 ± 10.9% without HSA) and in soybean yield by a quarter (ΔY = 15.3 ± 26.5% versus 20.4 ± 22.1% without HSA). The range reflects uncertainty due to differences between climate model scenarios; soybean exhibits both positive and negative impacts, maize is generally negative and spring wheat generally positive. Furthermore, when assuming CO2 fertilization effects to be negligible, we observe drastic climate mitigation policy as in RCP 2.6 could avoid more than 80% of the global average yield losses otherwise expected by the 2080s under RCP 8.5. We show large disparities in climate impacts across regions and find extreme heat stress adversely affects major producing regions and lower income countries.

Preliminary evaluation of spectral, normal and meteorological crop stage estimation approaches

NASA Technical Reports Server (NTRS)

Cate, R. B.; Artley, J. A.; Doraiswamy, P. C.; Hodges, T.; Kinsler, M. C.; Phinney, D. E.; Sestak, M. L. (Principal Investigator)

1980-01-01

Several of the projects in the AgRISTARS program require crop phenology information, including classification, acreage and yield estimation, and detection of episodal events. This study evaluates several crop calendar estimation techniques for their potential use in the program. The techniques, although generic in approach, were developed and tested on spring wheat data collected in 1978. There are three basic approaches to crop stage estimation: historical averages for an area (normal crop calendars), agrometeorological modeling of known crop-weather relationships agrometeorological (agromet) crop calendars, and interpretation of spectral signatures (spectral crop calendars). In all, 10 combinations of planting and biostage estimation models were evaluated. Dates of stage occurrence are estimated with biases between -4 and +4 days while root mean square errors range from 10 to 15 days. Results are inconclusive as to the superiority of any of the models and further evaluation of the models with the 1979 data set is recommended.

Biofuels on the landscape: Is "land sharing" preferable to "land sparing"?

NASA Astrophysics Data System (ADS)

DeLucia, E. H.; Anderson-Teixeira, K. J.; Duval, B. D.; Long, S. P.

2012-12-01

Widespread land use changes—and ensuing effects on biodiversity and ecosystem services—are expected as a result of expanding bioenergy production. Although almost all US production of ethanol today is from corn, it is envisaged that future ethanol production will also draw from cellulosic sources such as perennial grasses. In selecting optimal bioenergy crops, there is debate as to whether it is preferable from an environmental standpoint to cultivate bioenergy crops with high ecosystem services (a "land sharing" strategy) or to grow crops with lower ecosystem services but higher yield, thereby requiring less land to meet bioenergy demand (a "land sparing" strategy). Here, we develop a simple model to address this question. Assuming that bioenergy crops are competing with uncultivated land, our model calculates land requirements to meet a given bioenergy demand intensity based upon the yields of bioenergy crops and combines fractional land cover of each ecosystem type with its associated ecosystem services to determine whether land sharing or land sparing strategies maximize ecosystem services at the landscape level. We apply this model to a case in which climate protection through GHG regulation—an ecosystem's greenhouse gas value (GHGV)—is the ecosystem service of interest. We consider five bioenergy crops competing for land area with five unfarmed ecosystem types in the central and eastern US. Our results show that the relative advantages of land sparing and land sharing depend upon the type of ecosystem with which the bioenergy crop is competing for land; as the GHGV value of the unfarmed land increases, the preferable strategy shifts from land sharing to land sparing. This implies that, while it may be preferable to replace ecologically degraded land with high-GHGV, lower yielding bioenergy crops, average landscape GHGV will most often be maximized through high yielding bioenergy crops that leave more land for uncultivated, high-GHGV ecosystems. While our case study focuses on GHGV, the same principles will be generally applicable to any ecosystem service whose value does not depend upon the spatial configuration of the landscape. Whenever bioenergy crops have substantially lower ecosystem services than the ecosystems with which they are competing for land, the most effective strategy for meeting bioenergy demand while maximizing ecosystem services on a landscape level is one of land sparing—that is, focusing simultaneously on maximizing the yield of bioenergy crops while preserving or restoring natural ecosystems.

Cropping management using color and color infrared aerial photographs

NASA Technical Reports Server (NTRS)

Morgan, K. M.; Morris-Jones, D. R.; Lee, G. B.; Kiefer, R. W.

1979-01-01

The Universal Soil Loss Equation (USLE) is a widely accepted tool for erosion prediction and conservation planning. Solving this equation yields the long-term average annual soil loss that can be expected from rill and inter-rill erosion. In this study, manual interpretation of color and color infrared 70 mm photography at the scale of 1:60,000 is used to determine the cropping management factor in the USLE. Accurate information was collected about plowing practices and crop residue cover (unharvested vegetation) for the winter season on agricultural land in Pheasant Branch Creek watershed in Dane County, Wisconsin.

New insights into phosphorus management in agriculture--A crop rotation approach.

PubMed

Łukowiak, Remigiusz; Grzebisz, Witold; Sassenrath, Gretchen F

2016-01-15

This manuscript presents research results examining phosphorus (P) management in a soil–plant system for three variables: i) internal resources of soil available phosphorus, ii) cropping sequence, and iii) external input of phosphorus (manure, fertilizers). The research was conducted in long-term cropping sequences with oilseed rape (10 rotations) and maize (six rotations) over three consecutive growing seasons (2004/2005, 2005/2006, and 2006/2007) in a production farm on soils originated from Albic Luvisols in Poland. The soil available phosphorus pool, measured as calcium chloride extractable P (CCE-P), constituted 28% to 67% of the total phosphorus input (PTI) to the soil–plant system in the spring. Oilseed rape and maize dominant cropping sequences showed a significant potential to utilize the CCE-P pool within the soil profile. Cropping sequences containing oilseed rape significantly affected the CCE-P pool, and in turn contributed to the P(TI). The P(TI) uptake use efficiency was 50% on average. Therefore, the CCE-P pool should be taken into account as an important component of a sound and reliable phosphorus balance. The instability of the yield prediction, based on the P(TI), was mainly due to an imbalanced management of both farmyard manure and phosphorus fertilizer. Oilseed rape plants provide a significant positive impact on the CCE-P pool after harvest, improving the productive stability of the entire cropping sequence. This phenomenon was documented by the P(TI) increase during wheat cultivation following oilseed rape. The Unit Phosphorus Uptake index also showed a higher stability in oilseed rape cropping systems compared to rotations based on maize. Cropping sequences are a primary factor impacting phosphorus management. Judicious implementation of crop rotations can improve soil P resources, efficiency of crop P use, and crop yield and yield stability. Use of cropping sequences can reduce the need for external P sources such as farmyard manure and chemical fertilizers.

Evolutionary agroecology: individual fitness and population yield in wheat (Triticum aestivum).

PubMed

Weiner, Jacob; Du, Yan-Lei; Zhang, Cong; Qin, Xiao-Liang; Li, Feng-Min

2017-09-01

Although the importance of group selection in nature is highly controversial, several researchers have argued that plant breeding for agriculture should be based on group selection, because the goal in agriculture is to optimize population production, not individual fitness. A core hypothesis behind this claim is that crop genotypes with the highest individual fitness in a mixture of genotypes will not produce the highest population yield, because fitness is often increased by "selfish" behaviors, which reduce population performance. We tested this hypothesis by growing 35 cultivars of spring wheat (Triticum aestivum L.) in mixtures and monocultures, and analyzing the relationship between population yield in monoculture and individual yield in mixture. The relationship was unimodal, as predicted. The highest-yielding populations were from cultivars that had intermediate fitness, and these produced, on average, 35% higher yields than cultivars with the highest fitness. It is unlikely that plant breeding or genetic engineering can improve traits that natural selection has been optimizing for millions of years, but there is unutilized potential in traits that increase crop yield by decreasing individual fitness. © 2017 by the Ecological Society of America.

Predawn respiration rates during flowering are highly predictive of yield response in Gossypium hirsutum when yield variability is water-induced.

PubMed

Snider, John L; Chastain, Daryl R; Meeks, Calvin D; Collins, Guy D; Sorensen, Ronald B; Byrd, Seth A; Perry, Calvin D

2015-07-01

Respiratory carbon evolution by leaves under abiotic stress is implicated as a major limitation to crop productivity; however, respiration rates of fully expanded leaves are positively associated with plant growth rates. Given the substantial sensitivity of plant growth to drought, it was hypothesized that predawn respiration rates (RPD) would be (1) more sensitive to drought than photosynthetic processes and (2) highly predictive of water-induced yield variability in Gossypium hirsutum. Two studies (at Tifton and Camilla Georgia) addressed these hypotheses. At Tifton, drought was imposed beginning at the onset of flowering (first flower) and continuing for three weeks (peak bloom) followed by a recovery period, and predawn water potential (ΨPD), RPD, net photosynthesis (AN) and maximum quantum yield of photosystem II (Fv/Fm) were measured throughout the study period. At Camilla, plants were exposed to five different irrigation regimes throughout the growing season, and average ΨPD and RPD were determined between first flower and peak bloom for all treatments. For both sites, fiber yield was assessed at crop maturity. The relationships between ΨPD, RPD and yield were assessed via non-linear regression. It was concluded for field-grown G. hirsutum that (1) RPD is exceptionally sensitive to progressive drought (more so than AN or Fv/Fm) and (2) average RPD from first flower to peak bloom is highly predictive of water-induced yield variability. Copyright © 2015 Elsevier GmbH. All rights reserved.

The Potential of Five Winter-grown Crops to Reduce Root-knot Nematode Damage and Increase Yield of Tomato

PubMed Central

López-Pérez, Jose Antonio; Roubtsova, Tatiana; de Cara García, Miguel

2010-01-01

Broccoli (Brassica oleracea), carrot (Daucus carota), marigold (Tagetes patula), nematode-resistant tomato (Solanum lycopersicum), and strawberry (Fragaria ananassa) were grown for three years during the winter in a root-knot nematode (Meloidogyne incognita) infested field in Southern California. Each year in the spring, the tops of all crops were shredded and incorporated in the soil. Amendment with poultry litter was included as a sub-treatment. The soil was then covered with clear plastic for six weeks and M. incognita-susceptible tomato was grown during the summer season. Plastic tarping raised the average soil temperature at 13 cm depth by 7°C.The different winter-grown crops or the poultry litter did not affect M. incognita soil population levels. However, root galling on summer tomato was reduced by 36%, and tomato yields increased by 19% after incorporating broccoli compared to the fallow control. This crop also produced the highest amount of biomass of the five winter-grown crops. Over the three-year trial period, poultry litter increased tomato yields, but did not affect root galling caused by M. incognita. We conclude that cultivation followed by soil incorporation of broccoli reduced M. incognita damage to tomato. This effect is possibly due to delaying or preventing a portion of the nematodes to reach the host roots. We also observed that M. incognita populations did not increase under a host crop during the cool season when soil temperatures remained low (< 18°C). PMID:22736848

LACIE--An Application of Meteorology for United States and Foreign Wheat Assessment.

NASA Astrophysics Data System (ADS)

Hill, Jerry D.; Strommen, Norton D.; Sakamoto, Clarence M.; Leduc, Sharon K.

1980-01-01

The development of a critical world food situation during the early 1970's was the background leading to the Large Area Crop Inventory Experiment (LACIE). The need was to develop a capability for timely monitoring of crops on a global scale. Three U.S. Government agencies, NASA, NOAA and USDA, undertook the task of developing technology to extract the crop-related information available from the global weather-reporting network and the Landsat satellite. This paper describes the overall LACIE technical approach to make a quasi-operational application of existing research results and the accomplishments of this cooperative experiment in utilizing the weather information.Using available agrometeorological data, techniques were implemented to estimate crop development, assess relative crop vigor and estimate yield for wheat, the crop of principal interest to the experiment. Global weather data were utilized in preparing timely yield estimates for selected areas of the U.S. Great Plains, the U.S.S.R. and Canada. Additionally, wheat yield models were developed and pilot tested for Brazil, Australia, India and Argentina. The results of the work show that heading dates for wheat in North America can be predicted with an average absolute error of about 5 days for winter wheat and 4 days for spring wheat. Independent tests of wheat yield models over a 10-year period for the U.S. Great Plains produced a root-mean-square error of 1.12 quintals per hectare (q ha1) while similar tests in the U.S.S.R. produced an error of 1.31 q ha1. Research designed to improve the initial capability is described as is the rationale for further evolution of a capability to monitor global climate and assess its impact on world food supplies.

Simulation of targeted pollutant-mitigation-strategies to reduce nitrate and sediment hotspots in agricultural watershed.

PubMed

Teshager, Awoke Dagnew; Gassman, Philip W; Secchi, Silvia; Schoof, Justin T

2017-12-31

About 50% of U.S. water pollution problems are caused by non-point source (NPS) pollution, primarily sediment and nutrients from agricultural areas, despite the widespread implementation of agricultural Best Management Practices (BMPs). However, the effectiveness of implementation strategies and type of BMPs at watershed scale are still not well understood. In this study, the Soil and Water Assessment Tool (SWAT) ecohydrological model was used to assess the effectiveness of pollutant mitigation strategies in the Raccoon River watershed (RRW) in west-central Iowa, USA. We analyzed fourteen management scenarios based on systematic combinations of five strategies: fertilizer/manure management, changing row-crop land to perennial grass, vegetative filter strips, cover crops and shallower tile drainage systems, specifically aimed at reducing nitrate and total suspended sediment yields from hotspot areas in the RRW. Moreover, we assessed implications of climate change on management practices, and the impacts of management practices on water availability, row crop yield, and total agricultural production. Our results indicate that sufficient reduction of nitrate load may require either implementation of multiple management practices (38.5% with current setup) or conversion of extensive areas into perennial grass (up to 49.7%) to meet and maintain the drinking water standard. However, climate change may undermine the effectiveness of management practices, especially late in the 21st century, cutting the reduction by up to 65% for nitrate and more for sediment loads. Further, though our approach is targeted, it resulted in a slight decrease (~5%) in watershed average crop yield and hence an overall reduction in total crop production, mainly due to the conversion of row-crop lands to perennial grass. Such yield reductions could be quite spatially heterogeneously distributed (0 to 40%). Copyright © 2017 Elsevier B.V. All rights reserved.

A heterogeneous landscape does not guarantee high crop pollination

PubMed Central

Hambäck, Peter A.; Lemessa, Debissa; Nemomissa, Sileshi; Hylander, Kristoffer

2016-01-01

The expansion of pollinator-dependent crops, especially in the developing world, together with reports of worldwide pollinator declines, raises concern of possible yield gaps. Farmers directly reliant on pollination services for food supply often live in regions where our knowledge of pollination services is poor. In a manipulative experiment replicated at 23 sites across an Ethiopian agricultural landscape, we found poor pollination services and severe pollen limitation in a common oil crop. With supplementary pollination, the yield increased on average by 91%. Despite the heterogeneous agricultural matrix, we found a low bee abundance, which may explain poor pollination services. The variation in pollen limitation was unrelated to surrounding forest cover, local bee richness and bee abundance. While practices that commonly increase pollinators (restricted pesticide use, flower strips) are an integral part of the landscape, these elements are apparently insufficient. Management to increase pollination services is therefore in need of urgent investigation. PMID:27629036

Estimating yield gaps at the cropping system level.

PubMed

Guilpart, Nicolas; Grassini, Patricio; Sadras, Victor O; Timsina, Jagadish; Cassman, Kenneth G

2017-05-01

Yield gap analyses of individual crops have been used to estimate opportunities for increasing crop production at local to global scales, thus providing information crucial to food security. However, increases in crop production can also be achieved by improving cropping system yield through modification of spatial and temporal arrangement of individual crops. In this paper we define the cropping system yield potential as the output from the combination of crops that gives the highest energy yield per unit of land and time, and the cropping system yield gap as the difference between actual energy yield of an existing cropping system and the cropping system yield potential. Then, we provide a framework to identify alternative cropping systems which can be evaluated against the current ones. A proof-of-concept is provided with irrigated rice-maize systems at four locations in Bangladesh that represent a range of climatic conditions in that country. The proposed framework identified (i) realistic alternative cropping systems at each location, and (ii) two locations where expected improvements in crop production from changes in cropping intensity (number of crops per year) were 43% to 64% higher than from improving the management of individual crops within the current cropping systems. The proposed framework provides a tool to help assess food production capacity of new systems ( e.g. with increased cropping intensity) arising from climate change, and assess resource requirements (water and N) and associated environmental footprint per unit of land and production of these new systems. By expanding yield gap analysis from individual crops to the cropping system level and applying it to new systems, this framework could also be helpful to bridge the gap between yield gap analysis and cropping/farming system design.

SPATIO-TEMPORAL MODELING OF AGRICULTURAL YIELD DATA WITH AN APPLICATION TO PRICING CROP INSURANCE CONTRACTS

PubMed Central

Ozaki, Vitor A.; Ghosh, Sujit K.; Goodwin, Barry K.; Shirota, Ricardo

2009-01-01

This article presents a statistical model of agricultural yield data based on a set of hierarchical Bayesian models that allows joint modeling of temporal and spatial autocorrelation. This method captures a comprehensive range of the various uncertainties involved in predicting crop insurance premium rates as opposed to the more traditional ad hoc, two-stage methods that are typically based on independent estimation and prediction. A panel data set of county-average yield data was analyzed for 290 counties in the State of Paraná (Brazil) for the period of 1990 through 2002. Posterior predictive criteria are used to evaluate different model specifications. This article provides substantial improvements in the statistical and actuarial methods often applied to the calculation of insurance premium rates. These improvements are especially relevant to situations where data are limited. PMID:19890450

Light, plants, and power for life support on Mars

NASA Technical Reports Server (NTRS)

Salisbury, F. B.; Dempster, W. F.; Allen, J. P.; Alling, A.; Bubenheim, D.; Nelson, M.; Silverstone, S.

2002-01-01

Regardless of how well other growing conditions are optimized, crop yields will be limited by the available light up to saturation irradiances. Considering the various factors of clouds on Earth, dust storms on Mars, thickness of atmosphere, and relative orbits, there is roughly 2/3 as much light averaged annually on Mars as on Earth. On Mars, however, crops must be grown under controlled conditions (greenhouse or growth rooms). Because there presently exists no material that can safely be pressurized, insulated, and resist hazards of puncture and deterioration to create life support systems on Mars while allowing for sufficient natural light penetration as well, artificial light will have to be supplied. If high irradiance is provided for long daily photoperiods, the growing area can be reduced by a factor of 3-4 relative to the most efficient irradiance for cereal crops such as wheat and rice, and perhaps for some other crops. Only a small penalty in required energy will be incurred by such optimization. To obtain maximum yields, crops must be chosen that can utilize high irradiances. Factors that increase ability to convert high light into increased productivity include canopy architecture, high-yield index (harvest index), and long-day or day-neutral flowering and tuberization responses. Prototype life support systems such as Bios-3 in Siberia or the Mars on Earth Project need to be undertaken to test and further refine systems and parameters.

Light, plants, and power for life support on Mars.

PubMed

Salisbury, F B; Dempster, W F; Allen, J P; Alling, A; Bubenheim, D; Nelson, M; Silverstone, S

2002-01-01

Regardless of how well other growing conditions are optimized, crop yields will be limited by the available light up to saturation irradiances. Considering the various factors of clouds on Earth, dust storms on Mars, thickness of atmosphere, and relative orbits, there is roughly 2/3 as much light averaged annually on Mars as on Earth. On Mars, however, crops must be grown under controlled conditions (greenhouse or growth rooms). Because there presently exists no material that can safely be pressurized, insulated, and resist hazards of puncture and deterioration to create life support systems on Mars while allowing for sufficient natural light penetration as well, artificial light will have to be supplied. If high irradiance is provided for long daily photoperiods, the growing area can be reduced by a factor of 3-4 relative to the most efficient irradiance for cereal crops such as wheat and rice, and perhaps for some other crops. Only a small penalty in required energy will be incurred by such optimization. To obtain maximum yields, crops must be chosen that can utilize high irradiances. Factors that increase ability to convert high light into increased productivity include canopy architecture, high-yield index (harvest index), and long-day or day-neutral flowering and tuberization responses. Prototype life support systems such as Bios-3 in Siberia or the Mars on Earth Project need to be undertaken to test and further refine systems and parameters.

Soil Moisture Anomaly as Predictor of Crop Yield Deviation in Germany

NASA Astrophysics Data System (ADS)

Peichl, Michael; Thober, Stephan; Schwarze, Reimund; Meyer, Volker; Samaniego, Luis

2016-04-01

Natural hazards, such as droughts, have the potential to drastically diminish crop yield in rain-fed agriculture. For example, the drought in 2003 caused direct losses of 1.5 billion EUR only in Germany (COPA-COGECA 2003). Predicting crop yields allows to economize the mitigation of risks of weather extremes. Economic approaches for quantifying agricultural impacts of natural hazards mainly rely on temperature and related concepts. For instance extreme heat over the growing season is considered as best predictor of corn yield (Auffhammer and Schlenker 2014). However, those measures are only able to provide a proxy for the available water content in the root zone that ultimately determines plant growth and eventually crop yield. The aim of this paper is to analyse whether soil moisture has a causal effect on crop yield that can be exploited in improving adaptation measures. For this purpose, reduced form fixed effect panel models are developed with yield as dependent variable for both winter wheat and silo maize crops. The explanatory variables used are soil moisture anomalies, precipitation and temperature. The latter two are included to estimate the current state of the water balance. On the contrary, soil moisture provides an integrated signal over several months. It is also the primary source of water supply for plant growth. For each crop a single model is estimated for every month within the growing period to study the variation of the effects over time. Yield data is available for Germany as a whole on the level of administrative districts from 1990 to 2010. Station data by the German Weather Service are obtained for precipitation and temperature and are aggregated to the same spatial units. Simulated soil moisture computed by the mesoscale Hydrologic Model (mHM, www.ufz.de/mhm) is transformed into Soil Moisture Index (SMI), which represents the monthly soil water quantile and hence accounts directly for the water content available to plants. The results indicate that wet and dry soil moisture anomalies have a causal effect on crop yields. However, the effects vary in magnitude and direction for each crop depending on the month. For instance dry soil moisture anomalies in July, August and September reduce silo maize yield more than ten percent with respect to average conditions. Extreme wetness, however, increases silo maize yield in the same time period. A negative effect is observed for winter wheat during this period for both wet and dry anomalies. The reduction due to dry anomalies is smaller for winter wheat than for silo maize. This study shows that the impact of soil moisture anomalies varies dependent on months and crops. These evolving patterns provide new insights to improve adaptation measures for extreme soil moisture conditions. References Auffhammer, M., and W. Schlenker. 2014. "Empirical studies on agricultural impacts and adaptation." Energy Economics 46:555-561. COPA-COGECA. 2003. "Assessment of the impact of the heat wave and drought of the summer 2003 on agriculture and forestry." In Committee of Agricultural Organisations in the European Union General Committee for Agricultural Cooperation in the European Union, Brussels. p. 15.

Non-Crop Host Sampling Yields Insights into Small-Scale Population Dynamics of Drosophila suzukii (Matsumura)

PubMed Central

Loeb, Gregory M.

2018-01-01

Invasive, polyphagous crop pests subsist on a number of crop and non-crop resources. While knowing the full range of host species is important, a seasonal investigation into the use of non-crop plants adjacent to cropping systems provide key insights into some of the factors determining local population dynamics. This study investigated the infestation of non-crop plants by the invasive Drosophila suzukii (Matsumura), a pest of numerous economically important stone and small fruit crops, by sampling fruit-producing non-crop hosts adjacent to commercial plantings weekly from June through November in central New York over a two-year period. We found D. suzukii infestation rates (number of flies emerged/kg fruit) peaked mid-August through early September, with Rubus allegheniensis Porter and Lonicera morrowii Asa Gray showing the highest average infestation in both years. Interannual infestation patterns were similar despite a lower number of adults caught in monitoring traps the second year, suggesting D. suzukii host use may be density independent. PMID:29301358

Paddy crop yield estimation in Kashmir Himalayan rice bowl using remote sensing and simulation model.

PubMed

Muslim, Mohammad; Romshoo, Shakil Ahmad; Rather, A Q

2015-06-01

The Kashmir Himalayan region of India is expected to be highly prone to the change in agricultural land use because of its geo-ecological fragility, strategic location vis-à-vis the Himalayan landscape, its trans-boundary river basins, and inherent socio-economic instabilities. Food security and sustainability of the region are thus greatly challenged by these impacts. The effect of future climate change, increased competition for land and water, labor from non-agricultural sectors, and increasing population adds to this complex problem. In current study, paddy rice yield at regional level was estimated using GIS-based environment policy integrated climate (GEPIC) model. The general approach of current study involved combining regional level crop database, regional soil data base, farm management data, and climatic data outputs with GEPIC model. The simulated yield showed that estimated production to be 4305.55 kg/ha (43.05 q h(-1)). The crop varieties like Jhelum, K-39, Chenab, China 1039, China-1007, and Shalimar rice-1 grown in plains recorded average yield of 4783.3 kg/ha (47.83 q ha(-1)). Meanwhile, high altitude areas with varieties like Kohsaar, K-78 (Barkat), and K-332 recorded yield of 4102.2 kg/ha (41.02 q ha(-1)). The observed and simulated yield showed a good match with R (2) = 0.95, RMSE = 132.24 kg/ha, respectively.

A comprehensive assessment of the correlations between field crop yields and commonly used MODIS products

NASA Astrophysics Data System (ADS)

Johnson, David M.

2016-10-01

An exploratory assessment was undertaken to determine the correlation strength and optimal timing of several commonly used Moderate Resolution Imaging Spectroradiometer (MODIS) composited imagery products against crop yields for 10 globally significant agricultural commodities. The crops analyzed included barley, canola, corn, cotton, potatoes, rice, sorghum, soybeans, sugarbeets, and wheat. The MODIS data investigated included the Normalized Difference Vegetation Index (NDVI), Fraction of Photosynthetically Active Radiation (FPAR), Leaf Area Index (LAI), and Gross Primary Production (GPP), in addition to daytime Land Surface Temperature (DLST) and nighttime LST (NLST). The imagery utilized all had 8-day time intervals, but NDVI had a 250 m spatial resolution while the other products were 1000 m. These MODIS datasets were also assessed from both the Terra and Aqua satellites, with their differing overpass times, to document any differences. A follow-on analysis, using the Terra 250 m NDVI data as a benchmark, looked at the yield prediction utility of NDVI at two spatial scales (250 m vs. 1000 m), two time precisions (8-day vs. 16-day), and also assessed the Enhanced Vegetation Index (EVI, at 250 m, 16-day). The analyses spanned the major farming areas of the United States (US) from the summers of 2008-2013 and used annual county-level average crop yield data from the US Department of Agriculture as a basis. All crops, except rice, showed at least some positive correlations to each of the vegetation related indices in the middle of the growing season, with NDVI performing slightly better than FPAR. LAI was somewhat less strongly correlated and GPP weak overall. Conversely, some of the crops, particularly canola, corn, and soybeans, also showed negative correlations to DLST mid-summer. NLST, however, was never correlated to crop yield, regardless of the crop or seasonal timing. Differences between the Terra and Aqua results were found to be minimal. The 1000 m resolution NDVI showed somewhat poorer performance than the 250 m and suggests spatial resolution is helpful but not a necessity. The 8-day versus 16-day NDVI relationships to yields were very similar other than for the temporal precision. Finally, the EVI often showed the very best performance of all the variables, all things considered.

Application of Serratia marcescens RZ-21 significantly enhances peanut yield and remediates continuously cropped peanut soil.

PubMed

Ma, Hai-Yan; Yang, Bo; Wang, Hong-Wei; Yang, Qi-Yin; Dai, Chuan-Chao

2016-01-15

Continuous cropping practices cause a severe decline in peanut yield. The aim of this study was to investigate the remediation effect of Serratia marcescens on continuously cropped peanut soil. A pot experiment was conducted under natural conditions to determine peanut agronomic indices, soil microorganism characteristics, soil enzyme activities and antagonism ability to typical pathogens at different growth stages. Four treatments were applied to red soil as follows: an active fermentation liquor of S. marcescens (RZ-21), an equivalent sterilized fermentation liquor (M), an equivalent fermentation medium (P) and distilled water (CK). S. marcescens significantly inhibited the two typical plant pathogens Fusarium oxysporum A1 and Ralstonia solanacearum B1 and reduced their populations in rhizosphere soil. The RZ-21 treatment significantly increased peanut yield, vine dry weight, root nodules and taproot length by 62.3, 33, 72 and 61.4% respectively, followed by the M treatment. The P treatment also increased root nodules and root length slightly. RZ-21 also enhanced the activities of soil urease, sucrase and hydrogen peroxidase at various stages. In addition, RZ-21 and M treatments increased the average population of soil bacteria and decreased the average population of fungi in the three critical peanut growth stages, except for M in the case of the fungal population at flowering, thus balancing the structure of the soil microorganism community. This is the first report of S. marcescens being applied to continuously cropped peanut soil. The results suggest that S. marcescens RZ-21 has the potential to improve the soil environment and agricultural products and thus allow the development of sustainable management practices. © 2015 Society of Chemical Industry.

Effect of Crop Rotation on Meloidogyne spp. and Pratylenchus spp. Populations in Strawberry Fields in Taiwan

PubMed Central

Chen, P.; Tsay, T.T.

2006-01-01

Changes in population levels of Meloidogyne hapla, M. incognita, Pratylenchus coffeae, and P. penetrans were studied in 12 strawberry fields in the Dahu region of Taiwan. Ten potential rotation crops and two cultural practices were evaluated for their effect on nematode populations and influence on strawberry yield. Rotation with rice or taro and the cultural practice of flooding and bare fallowing for four months were found to reduce nematode soil populations to two or fewer nematodes per 100 ml soil. Average strawberry yields increased between 2.4% to 6.3% following taro compared to the bare fallow treatment. Corn suppressed M. incognita and M. hapla populations and resulted in an increased in strawberry yield compared to bare fallow. Other phytopathogens also present in these fields limited taro as the rotation choice for nematode management. Results of this research and economic analysis of the input requirements for various rotation crops, corn and bare fallow were recommended as the most appropriate rotation strategies for nematode management in strawberry in this region. PMID:19259538

Real-time monitoring of smallholder farmer responses to intra-seasonal climate variability in central Kenya

NASA Astrophysics Data System (ADS)

Krell, N.; Evans, T. P.; Estes, L. D.; Caylor, K. K.

2017-12-01

While international metrics of food security and water availability are generated as spatial averages at the regional to national levels, climate variability impacts are differentially felt at the household level. This project investigated scales of variability of climate impacts on smallholder farmers using social and environmental data in central Kenya. Using sub-daily real-time environmental measurements to monitor smallholder agriculture, we investigated how changes in seasonal precipitation affected food security around Laikipia county from September 2015 to present. We also conducted SMS-based surveys of over 700 farmers to understand farmers' decision-making within the growing season. Our results highlight field-scale heterogeneity in biophysical and social factors governing crop yields using locally sensed real-time environmental data and weekly farmer-reported information about planting, harvesting, irrigation, and crop yields. Our preliminary results show relationships between changes in seasonal precipitation, NDVI, and soil moisture related to crop yields and decision-making at several scales. These datasets present a unique opportunity to collect highly spatially and temporally resolved information from data-poor regions at the household level.

Modeling olive-crop forecasting in Tunisia

NASA Astrophysics Data System (ADS)

Ben Dhiab, Ali; Ben Mimoun, Mehdi; Oteros, Jose; Garcia-Mozo, Herminia; Domínguez-Vilches, Eugenio; Galán, Carmen; Abichou, Mounir; Msallem, Monji

2017-05-01

Tunisia is the world's second largest olive oil-producing region after the European Union. This paper reports on the use of models to forecast local olive crops, using data for Tunisia's five main olive-producing areas: Mornag, Jemmel, Menzel Mhiri, Chaal, and Zarzis. Airborne pollen counts were monitored over the period 1993-2011 using a Cour trap. Forecasting models were constructed using agricultural data (harvest size in tonnes of fruit/year) and data for several weather-related and phenoclimatic variables (rainfall, humidity, temperature, Growing Degree Days, and Chilling). Analysis of these data revealed that the amount of airborne pollen emitted over the pollen season as a whole (i.e., the Pollen Index) was the variable most influencing harvest size. Findings for all local models also indicated that the amount, timing, and distribution of rainfall (except during blooming) had a positive impact on final olive harvests. Air temperature also influenced final crop yield in three study provinces (Menzel Mhiri, Chaal, and Zarzis), but with varying consequences: in the model constructed for Chaal, cumulative maximum temperature from budbreak to start of flowering contributed positively to yield; in the Menzel Mhiri model, cumulative average temperatures during fruit development had a positive impact on output; in Zarzis, by contrast, cumulative maximum temperature during the period prior to flowering negatively influenced final crop yield. Data for agricultural and phenoclimatic variables can be used to construct valid models to predict annual variability in local olive-crop yields; here, models displayed an accuracy of 98, 93, 92, 91, and 88 % for Zarzis, Mornag, Jemmel, Chaal, and Menzel Mhiri, respectively.

Plant Productivity and Characterization of Zeoponic Substrates after Three Successive Crops of Radish (Raphanus sativus L.)

NASA Technical Reports Server (NTRS)

Gruener, J. E.; Ming, Douglas W.; Galindo, C., Jr.; Henderson, K. E.; Golden, D. C.

2007-01-01

The National Aeronautics and Space Administration (NASA) has developed a zeolite-based synthetic substrate, termed zeoponics. The zeoponic substrate (consisting of NH4(-) and K-exchanged clinoptilolite, synthetic apatite, and dolomite) provides all of the plant-essential nutrients through mineral dissolution and ion exchange, with only the addition of water. Previous studies have shown high productivity of wheat in zeoponic substrates; however, no experiments have been conducted on other crops. The objective of this study was to determine the productivity and nutrient uptake of radish (Raphanus sativus L.) grown in zeoponic substrates with three successive crops in the same substrate. Radish was chosen because of its sensitivities to NH4(+). Average fresh weights of edible roots were similar for radish grown in zeoponic substrates watered with deionized H2O (10.97 g/plant) and in potting mix control substrate irrigated with nutrient solution (10.92 g/plant). Average fresh weight production of edible roots for radish grown in same zeoponic substrate increased in yield over time with the lowest yield in the first crop (7.10 g/plant) and highest in the third crop (13.90 g/plant). The Ca plant tissue levels in radishes (1.8-2.9 wt. %) grown in zeoponic substrates are lower than the suggested sufficient range of 3.0-4.5 wt. % Ca; however, the Ca level is highest (2.9 wt. %) in radishes grown in the third crop in the same zeoponic substrates. The higher radish yield in the third crop was attributed to a reduction in an NH4(-) induced Ca deficiency that has been previously described for wheat grown in zeoponic substrates. The P levels in plant tissues of radish grown in the zeoponic substrates ranged from 0.94-1.15 wt. %; which is slightly higher than the sufficient levels of 0.3-0.7 wt. %. With the exception of Ca and P, other macronutrient and micronutrient levels in radish grown in zeoponic substrates were well within the recommended sufficient ranges. After three successive crops of radish growth, the zeoponic substrates had 52% of the original NH4(-)N and 78% of the original K remaining on zeolite exchange sites. Zeoponic substrates are capable of long-term productivity of radishes for space.

A probabilistic model framework for evaluating year-to-year variation in crop productivity

NASA Astrophysics Data System (ADS)

Yokozawa, M.; Iizumi, T.; Tao, F.

2008-12-01

Most models describing the relation between crop productivity and weather condition have so far been focused on mean changes of crop yield. For keeping stable food supply against abnormal weather as well as climate change, evaluating the year-to-year variations in crop productivity rather than the mean changes is more essential. We here propose a new framework of probabilistic model based on Bayesian inference and Monte Carlo simulation. As an example, we firstly introduce a model on paddy rice production in Japan. It is called PRYSBI (Process- based Regional rice Yield Simulator with Bayesian Inference; Iizumi et al., 2008). The model structure is the same as that of SIMRIW, which was developed and used widely in Japan. The model includes three sub- models describing phenological development, biomass accumulation and maturing of rice crop. These processes are formulated to include response nature of rice plant to weather condition. This model inherently was developed to predict rice growth and yield at plot paddy scale. We applied it to evaluate the large scale rice production with keeping the same model structure. Alternatively, we assumed the parameters as stochastic variables. In order to let the model catch up actual yield at larger scale, model parameters were determined based on agricultural statistical data of each prefecture of Japan together with weather data averaged over the region. The posterior probability distribution functions (PDFs) of parameters included in the model were obtained using Bayesian inference. The MCMC (Markov Chain Monte Carlo) algorithm was conducted to numerically solve the Bayesian theorem. For evaluating the year-to-year changes in rice growth/yield under this framework, we firstly iterate simulations with set of parameter values sampled from the estimated posterior PDF of each parameter and then take the ensemble mean weighted with the posterior PDFs. We will also present another example for maize productivity in China. The framework proposed here provides us information on uncertainties, possibilities and limitations on future improvements in crop model as well.

Combining satellite remote sensing and surveys to understand persistent yield variation--- a case study in North China Plain

NASA Astrophysics Data System (ADS)

Zhao, Y.; Lobell, D. B.; Chen, X.

2015-12-01

A large gap between maize yields on average farmers' fields and the highest yields achieved by either experiment or farmers is typical throughout the developing world, including in the North China Plain (NCP). This maize yield gap as identified by previous studies indicates large opportunities for raising yield by improving agronomy. Quzhou county is typical of the winter-wheat summer-maize system in NCP where the average plot size is as small as 0.25 hectares. To analyze this cropping system amidst the challenge of substantial heterogeneity, we identified fields that were either persistently higher or lower yielding according to the remote sensing yield estimates, and then conducted detailed field surveys. We found irrigation facility to be a major constraint to yield both in terms of irrigation water quality and farmers' access to wells. In total, improving the access to unsalty water would be associated with a 0.32t/ha (4.2%) increase in multi-year average yield. In addition, farmers' method of choosing cultivar, which likely relates to their overall knowledge level, significantly explained yield variation. In particular, those choosing cultivars according to technician advice, personal experiences and high yielding neighbors' advice had on average higher yield than farmers that either followed seed sellers' advice or collectively purchased seeds. Overall, the study presents a generalizable methodology of assessing yield gap as well as its persistent factors using a combination of satellite and survey data.

Weather-based forecasts of California crop yields

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lobell, D B; Cahill, K N; Field, C B

2005-09-26

Crop yield forecasts provide useful information to a range of users. Yields for several crops in California are currently forecast based on field surveys and farmer interviews, while for many crops official forecasts do not exist. As broad-scale crop yields are largely dependent on weather, measurements from existing meteorological stations have the potential to provide a reliable, timely, and cost-effective means to anticipate crop yields. We developed weather-based models of state-wide yields for 12 major California crops (wine grapes, lettuce, almonds, strawberries, table grapes, hay, oranges, cotton, tomatoes, walnuts, avocados, and pistachios), and tested their accuracy using cross-validation over themore » 1980-2003 period. Many crops were forecast with high accuracy, as judged by the percent of yield variation explained by the forecast, the number of yields with correctly predicted direction of yield change, or the number of yields with correctly predicted extreme yields. The most successfully modeled crop was almonds, with 81% of yield variance captured by the forecast. Predictions for most crops relied on weather measurements well before harvest time, allowing for lead times that were longer than existing procedures in many cases.« less

A comparison of cellulosic fuel yields and separated soil-surface CO2 fluxes in maize and prairie biofuel cropping systems

NASA Astrophysics Data System (ADS)

Nichols, Virginia A.

It has been suggested that strategic incorporation of perennial vegetation into agricultural landscapes could provide ecosystem services while maintaining agricultural productivity. To evaluate potential use of prairie as a Midwestern cellulosic feedstock, we investigated theoretical cellulosic fuel yields, as well as soil-surface carbon dioxide emissions of prairie-based biofuel systems as compared to maize-based systems on fertile soils in Boone County, IA, USA. Investigated systems were: a maize-soybean rotation grown for grain only, continuous maize grown for grain and stover both with and without a winter rye cover crop, and a 31-species reconstructed prairie grown with and without spring nitrogen fertilization for fall-harvested biomass. From 2009-2013, the highest producing system was N-fertilized prairie, averaging 10.4 Mg ha -1 yr-1 above-ground biomass with average harvest removals of 7.8 Mg ha-1 yr-1. The unfertilized prairie produced 7.4 Mg ha-1 yr-1, averaging harvests of 5.3 Mg ha-1 yr-1. Lowest cellulosic biomass harvests were realized from continuous maize systems, averaging 3.5 Mg ha -1 yr-1 when grown with, and 3.7 Mg ha-1 yr-1 when grown without a winter rye cover crop, respectively. Un-fertilized prairie biomass and maize stover had equivalent dietary conversion ratios at 330 g ethanol kg-1 dry biomass, but N-fertilized prairie was lower at 315. Over four years prairie systems averaged 1287 L cellulosic ethanol ha-1 yr-1 more than maize systems, with fertilization increasing prairie ethanol production by 865 L ha-1 yr-1. Harvested biomass accounted for >90% of ethanol yield variation. A major hurdle in carbon cycling studies is the separation of the soil-surface CO2 flux into its respective components. From 2012-2013 we used a shading method to separate soil-surface CO2 resulting from oxidation of soil organic matter and CO2 derived from live-root activity in three systems: unfertilized prairie, N-fertilized prairie, and continuous maize. Contrary to our hypothesis, total growing-season root CO2 flux was not proportional to end-of-season root biomass of cropping systems; unfertilized prairie contained nearly twice the root biomass of N-fertilized prairie, but the two systems' total root CO2 fluxes were not significantly different in either year. We found that the total growing-season flux of both root- and organic matter-derived CO 2 was higher in the prairie systems compared to the maize system. However, on a percentage basis, the prairies' soil-surface CO2 flux from May-September averaged 29% root-derived while from mid-June through September the maize averaged 22% root-derived. The percentage of the total CO2 flux that was root-derived in a given system varied from year to year, indicating there is no set relationship for a given cropping system.

Catch crops as universal and effective method for reducing nitrogen leaching loss in spring cereal production: A meta-analysis.

NASA Astrophysics Data System (ADS)

Valkama, Elena; Lemola, Riitta; Känkänen, Hannu; Turtola, Eila

2016-04-01

Sustainable farms produce adequate amounts of a high-quality product, protect their resources and are both environmentally friendly and economically profitable. Nitrogen (N) fertilization decisively influences the cereal yields as well as increases soil N balance (N input in fertilizer - N output in harvested yield), thereby leading to N losses to the environment. However, while N input reduction affects soil N balance, such approach would markedly reduce N leaching loss only in case of abnormally high N balances. As an alternative approach, the growing of catch crops aims to prevent nutrient leaching in autumn after harvest and during the following winter, but due to competition, catch crops may also reduce yields of the main crop. Although studies have explored the environmental effects of catch crops in cereal production in the Nordic countries (Denmark, Sweden, Finland and Norway) during the past 40 years, none has yet carried out a meta-analysis. We quantitatively summarized 35 studies on the effect of catch crops (non-legume and legume) undersown in spring cereals on N leaching loss or its risk as estimated by the content of soil nitrate N or its sum with ammonium in late autumn. The meta-analysis also included the grain yield and N content of spring cereals. To identify sources of variation, we studied the effects of soil texture and management (ploughing time, the amount of N applied, fertilizer type), as well as climatic (annual precipitation) and experimental conditions (duration of experiments, lysimeter vs. field experiments). Finally, we examined whether the results differed between the countries or over the decades. Compared to control groups with no catch crops, non-legume catch crops, mainly ryegrass species, reduced N leaching loss by 50% on average, and soil nitrate N or inorganic N by 35% in autumn. Italian ryegrass depleted soil N more effectively (by 60%) than did perennial ryegrass or Westerwolds ryegrass (by 25%). In contrast, legumes (white and red clovers) did not diminish the risk for N leaching. Otherwise, the effect on N leaching and its risk were consistent across the studies conducted in different countries on clay and coarse-textured mineral soils with different ploughing times, N fertilization rates (50-160 kg/ ha), and amounts of annual precipitation (480-1040 mm). Non-legume catch crops reduced grain yield by 3% with no changes in grain N content. In contrast, legumes and mixed catch crops increased both grain yield and grain N content by 6%. In spring cereal production, undersown non-legume catch crops are deemed a universal and effective method for reducing N leaching loss across the various soils, management practices and weather conditions in the Nordic countries. The environmental benefits of using non-legume catch crops appear considerable compared to the adverse reduction in grain yields, amounting to only a few percent. Catch crops are advisable for fields at high risk for N leaching (e.g., sandy soils or soils and crops requiring high N fertilization).

Assessing the combined effects of climatic factors on spring wheat phenophase and grain yield in Inner Mongolia, China

PubMed Central

Pu, Feiyu; Li, Yunpeng; Xu, Jingwen; Li, Ning; Zhang, Yi; Guo, Jianping; Pan, Zhihua

2017-01-01

Understanding the regional relationships between climate change and crop production will benefit strategic decisions for future agricultural adaptation in China. In this study, the combined effects of climatic factors on spring wheat phenophase and grain yield over the past three decades in Inner Mongolia, China, were explored based on the daily climate variables from 1981–2014 and detailed observed data of spring wheat from 1981–2014. Inner Mongolia was divided into three different climate type regions, the eastern, central and western regions. The data were gathered from 10 representative agricultural meteorological experimental stations in Inner Mongolia and analysed with the Agricultural Production Systems Simulator (APSIM) model. First, the performance of the APSIM model in the spring wheat planting areas of Inner Mongolia was tested. Then, the key climatic factors limiting the phenophases and yield of spring wheat were identified. Finally, the responses of spring wheat phenophases and yield to climate change were further explored regionally. Our results revealed a general yield reduction of spring wheat in response to the pronounced climate warming from 1981 to 2014, with an average of 3564 kg·ha-1. The regional differences in yields were significant. The maximum potential yield of spring wheat was found in the western region. However, the minimum potential yield was found in the middle region. The air temperature and soil surface temperature were the optimum climatic factors that affected the key phenophases of spring wheat in Inner Mongolia. The influence of the average maximum temperature on the key phenophases of spring wheat was greater than the average minimum temperature, followed by the relative humidity and solar radiation. The most insensitive climatic factors were precipitation, wind speed and reference crop evapotranspiration. As for the yield of spring wheat, temperature, solar radiation and air relative humidity were major meteorological factors that affected in the eastern and western Inner Mongolia. Furthermore, the effect of the average minimum temperature on yield was greater than that of the average maximum temperature. The increase of temperature in the western and middle regions would reduce the spring wheat yield, while in the eastern region due to the rising temperature, the spring wheat yield increased. The increase of solar radiation in the eastern and central regions would increase the yield of spring wheat. The increased air relative humidity would make the western spring wheat yield increased and the eastern spring wheat yield decreased. Finally, the models describing combined effects of these dominant climatic factors on the maturity and yield in different regions of Inner Mongolia were used to establish geographical differences. Our findings have important implications for improving climate change impact studies and for local agricultural production to cope with ongoing climate change. PMID:29099842

Assessing the combined effects of climatic factors on spring wheat phenophase and grain yield in Inner Mongolia, China.

PubMed

Zhao, Junfang; Pu, Feiyu; Li, Yunpeng; Xu, Jingwen; Li, Ning; Zhang, Yi; Guo, Jianping; Pan, Zhihua

2017-01-01

Understanding the regional relationships between climate change and crop production will benefit strategic decisions for future agricultural adaptation in China. In this study, the combined effects of climatic factors on spring wheat phenophase and grain yield over the past three decades in Inner Mongolia, China, were explored based on the daily climate variables from 1981-2014 and detailed observed data of spring wheat from 1981-2014. Inner Mongolia was divided into three different climate type regions, the eastern, central and western regions. The data were gathered from 10 representative agricultural meteorological experimental stations in Inner Mongolia and analysed with the Agricultural Production Systems Simulator (APSIM) model. First, the performance of the APSIM model in the spring wheat planting areas of Inner Mongolia was tested. Then, the key climatic factors limiting the phenophases and yield of spring wheat were identified. Finally, the responses of spring wheat phenophases and yield to climate change were further explored regionally. Our results revealed a general yield reduction of spring wheat in response to the pronounced climate warming from 1981 to 2014, with an average of 3564 kg·ha-1. The regional differences in yields were significant. The maximum potential yield of spring wheat was found in the western region. However, the minimum potential yield was found in the middle region. The air temperature and soil surface temperature were the optimum climatic factors that affected the key phenophases of spring wheat in Inner Mongolia. The influence of the average maximum temperature on the key phenophases of spring wheat was greater than the average minimum temperature, followed by the relative humidity and solar radiation. The most insensitive climatic factors were precipitation, wind speed and reference crop evapotranspiration. As for the yield of spring wheat, temperature, solar radiation and air relative humidity were major meteorological factors that affected in the eastern and western Inner Mongolia. Furthermore, the effect of the average minimum temperature on yield was greater than that of the average maximum temperature. The increase of temperature in the western and middle regions would reduce the spring wheat yield, while in the eastern region due to the rising temperature, the spring wheat yield increased. The increase of solar radiation in the eastern and central regions would increase the yield of spring wheat. The increased air relative humidity would make the western spring wheat yield increased and the eastern spring wheat yield decreased. Finally, the models describing combined effects of these dominant climatic factors on the maturity and yield in different regions of Inner Mongolia were used to establish geographical differences. Our findings have important implications for improving climate change impact studies and for local agricultural production to cope with ongoing climate change.

Cost-benefit trade-offs of bird activity in apple orchards

PubMed Central

Saunders, Manu E.; Luck, Gary W.

2016-01-01

Birds active in apple orchards in south–eastern Australia can contribute positively (e.g., control crop pests) or negatively (e.g., crop damage) to crop yields. Our study is the first to identify net outcomes of these activities, using six apple orchards, varying in management intensity, in south–eastern Australia as a study system. We also conducted a predation experiment using real and artificial codling moth (Cydia pomonella) larvae (a major pest in apple crops). We found that: (1) excluding birds from branches of apple trees resulted in an average of 12.8% more apples damaged by insects; (2) bird damage to apples was low (1.9% of apples); and (3) when trading off the potential benefits (biological control) with costs (bird damage to apples), birds provided an overall net benefit to orchard growers. We found that predation of real codling moth larvae was higher than for plasticine larvae, suggesting that plasticine prey models are not useful for inferring actual predation levels. Our study shows how complex ecological interactions between birds and invertebrates affect crop yield in apples, and provides practical strategies for improving the sustainability of orchard systems. PMID:27413639

Economic feasibility analysis of conventional and dedicated energy crop production

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nelson, R.G.; Langemeier, M.R.; Krehbiel, L.R.

Economic feasibilities (net return per acre) associated with conventional agricultural crop production versus that of dedicated bioenergy crop (herbaceous energy crops) were investigated for northeastern Kansas. Conventional agricultural crops examined were corn, soybeans, wheat, sorghum and alfalfa and dedicated herbaceous energy crops included big bluestem/indiangrass, switchgrass, eastern gamagrass, brome, fescue and cane hay. Costs, prices and government program information from public and private sources were used to project the net return per acre over a six-year period beginning in 1997. Three soil productivity levels (low, average and high), which had a direct effect on the net return per acre, weremore » used to model differences in expected yield. In all three soil productivity cases, big bluestem/indiangrass, switchgrass and brome hay provided a higher net return per acre versus conventional crops grown on both program and non-program acres. Eastern gamagrass, fescue hay and cane hay had returns that were similar or less than returns provided by conventional crops.« less

Unmanned aircraft system-derived crop height and normalized difference vegetation index metrics for sorghum yield and aphid stress assessment

NASA Astrophysics Data System (ADS)

Stanton, Carly; Starek, Michael J.; Elliott, Norman; Brewer, Michael; Maeda, Murilo M.; Chu, Tianxing

2017-04-01

A small, fixed-wing unmanned aircraft system (UAS) was used to survey a replicated small plot field experiment designed to estimate sorghum damage caused by an invasive aphid. Plant stress varied among 40 plots through manipulation of aphid densities. Equipped with a consumer-grade near-infrared camera, the UAS was flown on a recurring basis over the growing season. The raw imagery was processed using structure-from-motion to generate normalized difference vegetation index (NDVI) maps of the fields and three-dimensional point clouds. NDVI and plant height metrics were averaged on a per plot basis and evaluated for their ability to identify aphid-induced plant stress. Experimental soil signal filtering was performed on both metrics, and a method filtering low near-infrared values before NDVI calculation was found to be the most effective. UAS NDVI was compared with NDVI from sensors onboard a manned aircraft and a tractor. The correlation results showed dependence on the growth stage. Plot averages of NDVI and canopy height values were compared with per-plot yield at 14% moisture and aphid density. The UAS measures of plant height and NDVI were correlated to plot averages of yield and insect density. Negative correlations between aphid density and NDVI were seen near the end of the season in the most damaged crops.

Assessment of impact of climate change and adaptation strategies on maize production in Uganda

NASA Astrophysics Data System (ADS)

Kikoyo, Duncan A.; Nobert, Joel

2016-06-01

Globally, various climatic studies have estimated a reduction of crop yields due to changes in surface temperature and precipitation especially for the developing countries which is heavily dependent on agriculture and lacks resources to counter the negative effects of climate change. Uganda's economy and the wellbeing of its populace depend on rain-fed agriculture which is susceptible to climate change. This study quantified the impacts of climate change and variability in Uganda and how coping strategies can enhance crop production against climate change and/or variability. The study used statistical methods to establish various climate change and variability indicators across the country, and uses the FAO AquaCrop model to simulate yields under possible future climate scenarios with and without adaptation strategies. Maize, the most widely grown crop was used for the study. Meteorological, soil and crop data were collected for various districts representing the maize growing ecological zones in the country. Based on this study, it was found that temperatures have increased by up to 1 °C across much of Uganda since the 1970s, with rates of warming around 0.3 °C per decade across the country. High altitude, low rainfall regions experience the highest level of warming, with over 0.5 °C/decade recorded in Kasese. Rainfall is variable and does not follow a specific significant increasing or decreasing trend. For both future climate scenarios, Maize yields will reduce in excess of 4.7% for the fast warming-low rainfall climates but increase on average by 3.5% for slow warming-high rainfall regions, by 2050. Improved soil fertility can improve yields by over 50% while mulching and use of surface water management practices improve yields by single digit percentages. The use of fertilizer application needs to go hand in hand with other water management strategies since more yields as a result of the improved soil fertility leads to increased water stress, especially for the dry climates.

Is Bhutan destined for 100% organic? Assessing the economy-wide effects of a large-scale conversion policy.

PubMed

Feuerbacher, Arndt; Luckmann, Jonas; Boysen, Ole; Zikeli, Sabine; Grethe, Harald

2018-01-01

Organic agriculture (OA) is considered a strategy to make agriculture more sustainable. Bhutan has embraced the ambitious goal of becoming the world's first 100% organic nation. By analysing recent on-farm data in Bhutan, we found organic crop yields on average to be 24% lower than conventional yields. Based on these yield gaps, we assess the effects of the 100% organic conversion policy by employing an economy-wide computable general equilibrium (CGE) model with detailed representation of Bhutan's agricultural sector incorporating agroecological zones, crop nutrients, and field operations. Despite a low dependency on agrochemicals from the onset of this initiative, we find a considerable reduction in Bhutan's GDP, substantial welfare losses, particularly for non-agricultural households, and adverse impacts on food security. The yield gap is the main driver for a strong decline in domestic agricultural production, which is largely compensated by increased food imports, resulting in a weakening of the country's cereal self-sufficiency. Current organic by default farming practices in Bhutan are still underdeveloped and do not apply the systems approach of organic farming as defined in the IFOAM organic farming standards. This is reflected in the strong decline of nitrogen (N) availability to crops in our simulation and bears potential for increased yields in OA. Improvement of soil-fertility practices, e.g., the adoption of N-fixing crops, improved animal husbandry systems with increased provision of animal manure and access to markets with price premium for organic products could help to lower the economic cost of the large-scale conversion.

Is Bhutan destined for 100% organic? Assessing the economy-wide effects of a large-scale conversion policy

PubMed Central

Luckmann, Jonas; Boysen, Ole; Zikeli, Sabine; Grethe, Harald

2018-01-01

Organic agriculture (OA) is considered a strategy to make agriculture more sustainable. Bhutan has embraced the ambitious goal of becoming the world’s first 100% organic nation. By analysing recent on-farm data in Bhutan, we found organic crop yields on average to be 24% lower than conventional yields. Based on these yield gaps, we assess the effects of the 100% organic conversion policy by employing an economy-wide computable general equilibrium (CGE) model with detailed representation of Bhutan’s agricultural sector incorporating agroecological zones, crop nutrients, and field operations. Despite a low dependency on agrochemicals from the onset of this initiative, we find a considerable reduction in Bhutan’s GDP, substantial welfare losses, particularly for non-agricultural households, and adverse impacts on food security. The yield gap is the main driver for a strong decline in domestic agricultural production, which is largely compensated by increased food imports, resulting in a weakening of the country’s cereal self-sufficiency. Current organic by default farming practices in Bhutan are still underdeveloped and do not apply the systems approach of organic farming as defined in the IFOAM organic farming standards. This is reflected in the strong decline of nitrogen (N) availability to crops in our simulation and bears potential for increased yields in OA. Improvement of soil-fertility practices, e.g., the adoption of N-fixing crops, improved animal husbandry systems with increased provision of animal manure and access to markets with price premium for organic products could help to lower the economic cost of the large-scale conversion. PMID:29897989

Optimum timing of insecticide applications against diamondback moth Plutella xylostella in cole crops using threshold catches in sex pheromone traps.

PubMed

Reddy, G V; Guerrero, A

2001-01-01

Field trials were conducted in cabbage (Brassica oleracea var capitata), cauliflower (B oleracea var botrytis) and knol khol (B oleracea gongylodes) crops at two different locations in Karnataka State (India) to optimize the timing of insecticide applications to control the diamondback moth, Plutella xylostella, using sex pheromone traps. Our results indicate that applications of cartap hydrochloride as insecticide during a 12-24 h period after the pheromone traps had caught on average 8, 12 and 16 males per trap per night in cabbage, cauliflower and knol khol, respectively, were significantly more effective than regular insecticide sprays at 7, 9, 12 or 15 days after transplantation. This was demonstrated by estimation of the mean number of eggs and larvae per plant, the percentage of holes produced, as well as the marketable yield of the three crops at each location. A good correlation between the immature stages, infestation level, the estimated crop yield and the number of moths caught in pheromone traps was also found, indicating the usefulness of pheromone-based monitoring traps to predict population densities of the pest.

Consequence of climate mitigation on the risk of hunger.

PubMed

Hasegawa, Tomoko; Fujimori, Shinichiro; Shin, Yonghee; Tanaka, Akemi; Takahashi, Kiyoshi; Masui, Toshihiko

2015-06-16

Climate change and mitigation measures have three major impacts on food consumption and the risk of hunger: (1) changes in crop yields caused by climate change; (2) competition for land between food crops and energy crops driven by the use of bioenergy; and (3) costs associated with mitigation measures taken to meet an emissions reduction target that keeps the global average temperature increase to 2 °C. In this study, we combined a global computable general equilibrium model and a crop model (M-GAEZ), and we quantified the three impacts on risk of hunger through 2050 based on the uncertainty range associated with 12 climate models and one economic and demographic scenario. The strong mitigation measures aimed at attaining the 2 °C target reduce the negative effects of climate change on yields but have large negative impacts on the risk of hunger due to mitigation costs in the low-income countries. We also found that in a strongly carbon-constrained world, the change in food consumption resulting from mitigation measures depends more strongly on the change in incomes than the change in food prices.

No-tillage and fertilization management on crop yields and nitrate leaching in North China Plain

PubMed Central

Huang, Manxiang; Liang, Tao; Wang, Lingqing; Zhou, Chenghu

2015-01-01

A field experiment was performed from 2003 to 2008 to evaluate the effects of tillage system and nitrogen management regimes on crop yields and nitrate leaching from the fluvo-aquic soil with a winter wheat (Triticum aestivum L.)–maize (Zea mays L.) double-cropping system. The tillage systems consisted of conventional tillage (CT) and no-tillage (NT). Three nitrogen management regimes were included: 270 kg N ha−1 of urea for wheat and 225 kg N ha−1 of urea for maize (U), 180 kg N ha−1 of urea and 90 kg N ha−1 of straw for wheat and 180 kg N of urea and 45 kg N ha−1 of straw for maize (S), 180 kg N ha−1 of urea and 90 kg N ha−1 of manure for wheat and 180 kg N ha−1 of urea and 45 kg N ha−1 of manure for maize (M). An array of tension-free pan lysimeters (50 cm × 75 cm) were installed (1.2 m deep) to measure water flow and -N movement. No significant effect of the N management regime on yields of winter wheat and maize grain was found in the 5-year rotation. Tillage systems had significant influences on -N leaching from the second year and thereafter interacted with N management regimes on -N loads during all maize seasons. The average yield-scaled -N leaching losses were in order of CTS < NTS< CTU < NTU

Extrapolating effects of conservation tillage on yield, soil moisture and dry spell mitigation using simulation modelling

NASA Astrophysics Data System (ADS)

Mkoga, Z. J.; Tumbo, S. D.; Kihupi, N.; Semoka, J.

There is big effort to disseminate conservation tillage practices in Tanzania. Despite wide spread field demonstrations there has been some field experiments meant to assess and verify suitability of the tillage options in local areas. Much of the experiments are short lived and thus long term effects of the tillage options are unknown. Experiments to study long term effects of the tillage options are lacking because they are expensive and cannot be easily managed. Crop simulation models have the ability to use long term weather data and the local soil parameters to assess long term effects of the tillage practices. The Agricultural Production Systems Simulator (APSIM) crop simulation model; was used to simulate long term production series of soil moisture and grain yield based on the soil and weather conditions in Mkoji sub-catchment of the great Ruaha river basin in Tanzania. A 24 year simulated maize yield series based on conventional tillage with ox-plough, without surface crop residues (CT) treatment was compared with similar yield series based on conservation tillage (ox-ripping, with surface crop residues (RR)). Results showed that predicted yield averages were significantly higher in conservation tillage than in conventional tillage ( P < 0.001). Long term analysis, using APSIM simulation model, showed that average soil moisture in the conservation tillage was significantly higher ( P < 0.05) (about 0.29 mm/mm) than in conventional tillage (0.22 mm/mm) treatment during the seasons which received rainfall between 468 and 770 mm. Similarly the conservation tillage treatment recorded significantly higher yields (4.4 t/ha) ( P < 0.01) than the conventional tillage (3.6 t/ha) treatment in the same range of seasonal rainfall. On the other hand there was no significant difference in soil moisture for the seasons which received rainfall above 770 mm. In these seasons grain yield in conservation tillage treatment was significantly lower (3.1 kg/ha) than in the conventional tillage treatment (4.8 kg/ha) ( P < 0.05). Results also indicated a probability of 0.5 of getting higher yield in conservation than in conventional tillage practice. The conservation tillage treatment had the ability to even-out the acute and long intra-seasonal dry spells. For example a 36-days agricultural dry spell which occurred between 85th and 130th day after planting in the 1989/1990 season (in the CT treatment) was mitigated to zero days in the RR treatment by maintaining soil moisture above the critical point. Critical soil moisture for maize was measured at 0.55 of maximum soil moisture that can be depleted crop (0.55 D). It is concluded that conservation tillage practice where ripping and surface crop residues is used is much more effective in mitigating dry spells and increase productivity in a seasonal rainfall range of between 460 and 770 mm. It is recommended that farmers in the area adopt that type of conservation tillage because rainfall was in this range (460-770 mm) in 12 out of the past 24 years, indicating possibility of yield losses once in every 2 years.

The use of remotely-sensed snow, soil moisture and vegetation indices to develop resilience to climate change in Kazakhstan

NASA Astrophysics Data System (ADS)

Saidaliyeva, Zarina; Davenport, Ian; Nobakht, Mohamad; White, Kevin; Shahgedanova, Maria

2017-04-01

Kazakhstan is a major producer of grain. Large scale grain production dominates in the north, making Kazakhstan one of the largest exporters of grain in the world. Agricultural production accounts for 9% of the national GDP, providing 25% of national employment. The south relies on grain production from household farms for subsistence, and has low resilience, so is vulnerable to reductions in output. Yields in the south depend on snowmelt and glacier runoff. The major limit to production is water supply, which is affected by glacier retreat and frequent droughts. Climate change is likely to impact all climate drivers negatively, leading to a decrease in crop yield, which will impact Kazakhstan and countries dependent on importing its produce. This work makes initial steps in modelling the impact of climate change on crop yield, by identifying the links between snowfall, soil moisture and agricultural productivity. Several remotely-sensed data sources are being used. The availability of snowmelt water over the period 2010-2014 is estimated by extracting the annual maximum snow water equivalent (SWE) from the Globsnow dataset, which assimilates satellite microwave observations with field observations to produce a spatial map. Soil moisture over the period 2010-2016 is provided by the ESA Soil Moisture and Ocean Salinity (SMOS) mission. Vegetation density is approximated by the Normalised Difference Vegetation Index (NDVI) produced from NASA's MODIS instruments. Statistical information on crop yields is provided by the Ministry of National Economy of the Republic of Kazakhstan Committee on Statistics. Demonstrating the link between snowmelt yield and agricultural productivity depends on showing the impact of snow mass during winter on remotely-sensed soil moisture, the link between soil moisture and vegetation density, and finally the link between vegetation density and crop yield. Soil moisture maps were extracted from SMOS observations, and resampled onto a 40km x 40km grid, and analysed to produce monthly averages. The monthly maximum snow water equivalent estimates for March were resampled onto the same grid, to approximate the total snow contributing to snowmelt. The MODIS MOD13A2 1km 16-day NDVI product was resampled onto the same 40km grid, and aggregated into 32-day averages. Annual crop yield is available in terms of kg of yield per hectare for each region in Kazakhstan between 2004 and 2015. To show the connection between the snowmelt and soil moisture, the cells within the snow and soil moisture grids were compared to calculate correlation. Data were aggregated per region. Regions in northern Kazakhstan showed the strongest correlations, because more of the soil water supply is derived from snowmelt than rain, and the southern regions showed poor correlation because of the greater influence of rainfall and irrigation. Correlations between soil moisture and vegetation density, and crop yield are ongoing, and results will be presented. It is envisaged that this research will assist the Kazakh farming community, providing real-time soil moisture data from SMOS.

Efficiency of repeated phytoextraction of cadmium and zinc from an agricultural soil contaminated with sewage sludge.

PubMed

Luo, Kai; Ma, Tingting; Liu, Hongyan; Wu, Longhua; Ren, Jing; Nai, Fengjiao; Li, Rui; Chen, Like; Luo, Yongming; Christie, Peter

2015-01-01

Long-term application of sewage sludge resulted in soil cadmium (Cd) and zinc (Zn) contamination in a pot experiment conducted to phytoextract Cd/Zn repeatedly using Sedum plumbizincicola and Apium graceolens in monoculture or intercropping mode eight times. Shoot yields and soil physicochemical properties changed markedly with increasing number of remediation crops when the two plant species were intercropped compared with the unplanted control soil and the two monoculture treatments. Changes in soil microbial indices such as average well colour development, soil enzyme activity and soil microbial counts were also significantly affected by the growth of the remediation plants, especially intercropping with S. plumbizincicola and A. graveolens. The higher yields and amounts of Cd taken up indicated that intercropping of the hyperaccumulator and the vegetable species may be suitable for simultaneous agricultural production and soil remediation, with larger crop yields and higher phytoremediation efficiencies than under monoculture conditions.

Crop weather models of barley and spring wheat yield for agrophysical units in North Dakota

NASA Technical Reports Server (NTRS)

Leduc, S. (Principal Investigator)

1982-01-01

Models based on multiple regression were developed to estimate barley yield and spring wheat yield from weather data for Agrophysical units(APU) in North Dakota. The predictor variables are derived from monthly average temperature and monthly total precipitation data at meteorological stations in the cooperative network. The models are similar in form to the previous models developed for Crop Reporting Districts (CRD). The trends and derived variables were the same and the approach to select the significant predictors was similar to that used in developing the CRD models. The APU models show sight improvements in some of the statistics of the models, e.g., explained variation. These models are to be independently evaluated and compared to the previously evaluated CRD models. The comparison will indicate the preferred model area for this application, i.e., APU or CRD.

[Impacts of climate change on food production in Gansu: A review].

PubMed

Yang, Feng-ke; He, Bao-lin; Gao, Shi-ming

2015-03-01

The climate of Gansu turned to be overall warming-drying and partly warming-wetting since 1986. In contrast to that of 1960, the average annual temperature had raised by 1.1°C with the average annual precipitation decreased by 28 mm correspondingly, which made the arid region expanded southward by 50 km in 2010. Climate warming increased the growth period effective accumulated temperature of main food grain crops and lengthened the crop growth period. It changed crop maturity, crop disposition, cropping system and generally increased the cultivatable area and planting altitude above the sea level of major crops and expanded northward the multiple cropping system, which further resulted in expansion of autumn grain crop sown area, shrink of summer grain crop sown area, and replacement of strong winter early maturing varieties by weak winter middle late maturing varieties. It benefited the crop yield by increasing the use efficiency of photo-thermal resources. Warming-wetting climate increased the climate productivity of oasis crop while warming-drying weather decreased the climate productivity of rainfed crops, which were mostly determined by the precipitation regimes and water conditions. Any advanced technique that can increase precipitation use ratio and water use efficiency as well as improve and promote soil quality and fertility should be regarded as an effective countermeasure to increase food grain production under climate change in Gsansu. So, selecting and breeding new crop varieties with the characteristics of strong resistance, weak winter, middle-late mature and high water use efficiency, establishing new planting structure and cropping system that suitable to the precipitation and temperature features of changed climate, are the development direction of food grain production in Gansu to cope with the climate change.

Effects of different on-farm management on yield and water use efficiency of Potato crop cultivated in semiarid environments under subsurface drip irrigation

NASA Astrophysics Data System (ADS)

Ghazouani, Hiba; Provenzano, Giuseppe; Rallo, Giovanni; Mguidiche, Amel; Douh, Boutheina; Boujelben, Abdelhamid

2016-04-01

In Tunisia the amount of water for irrigated agriculture is higher than about 80% of the total resource.The increasing population and the rising food demand, associated to the negative effects of climate change,make it crucial to adopt strategies aiming to improve water use efficiency (WUE). Moreover, the absence of an effective public policy for water management amplifies the imbalance between water supply and its demand. Despite improved irrigation technologies can enhance the efficiency of water distribution systems, to achieve environmental goals it is also necessaryto identify on-farm management strategies accounting for actual crop water requirement. The main objective of the paper was to assess the effects of different on-farm managementstrategies (irrigation scheduling and planting date) on yield and water use efficiency of Potato crop (Solanumtuberosum L.) irrigated with a subsurface drip system, under the semi-arid climate of central Tunisia. Experiments were carried out during three growing seasons (2012, 2014 and 2015) at the High Agronomic Institute of ChottMariem in Sousse, by considering different planting dates and irrigation depths, the latter scheduled according to the climate observed during the season. All the considered treatments received the same pesticide and fertilizer management. Experiments evidenced that the climatic variability characterizing the examined seasons (photoperiod, solar radiation and average temperature) affects considerably the crop phenological stages, and the late sowing shortens the crop cycle.It has also been demonstrated that Leaf Area Index (LAI) and crop yield resulted relatively higher for those treatments receiving larger amounts of seasonal water. Crop yield varied between 16.3 t/ha and 39.1 t/ha, with a trend linearly related to the ratio between the seasonal amount of water supplied (Irrigation, I and Precipitation, P) and the maximum crop evapotranspiration (ETm). The maximum crop yield was in particular obtained for a value of this ratio equal to 1.45. Moreover, when increasing the seasonal pluviometric deficit (P-ETm) and therefore the irrigation depth (I), standard deviations of crop yield tended to decrease, as a consequence ofthe more uniform soil water content in the root zone. In terms of agronomic water use efficiency (AWUE),differences among the investigated treatments varied in a quite narrow range,due to thecombined effects of seasonal precipitation and atmospheric water demand on irrigation depths and crop yield.On the other hand, when considering irrigation water use efficiency (IWUE), more relevant differences between treatments were observed,being the higher values of IWUEgenerally associated to the lower irrigation depths. However, to define the best irrigation management strategy it is necessary, from one side, to consider the availability of water and from the other, to perform aneconomic analysis accounting for the cost of water and the related benefits achievable by the farmer.

Building a statistical emulator for prediction of crop yield response to climate change: a global gridded panel data set approach

NASA Astrophysics Data System (ADS)

Mistry, Malcolm; De Cian, Enrica; Wing, Ian Sue

2015-04-01

There is widespread concern that trends and variability in weather induced by climate change will detrimentally affect global agricultural productivity and food supplies. Reliable quantification of the risks of negative impacts at regional and global scales is a critical research need, which has so far been met by forcing state-of-the-art global gridded crop models with outputs of global climate model (GCM) simulations in exercises such as the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP)-Fastrack. Notwithstanding such progress, it remains challenging to use these simulation-based projections to assess agricultural risk because their gridded fields of crop yields are fundamentally denominated as discrete combinations of warming scenarios, GCMs and crop models, and not as model-specific or model-averaged yield response functions of meteorological shifts, which may have their own independent probability of occurrence. By contrast, the empirical climate economics literature has adeptly represented agricultural responses to meteorological variables as reduced-form statistical response surfaces which identify the crop productivity impacts of additional exposure to different intervals of temperature and precipitation [cf Schlenker and Roberts, 2009]. This raises several important questions: (1) what do the equivalent reduced-form statistical response surfaces look like for crop model outputs, (2) do they exhibit systematic variation over space (e.g., crop suitability zones) or across crop models with different characteristics, (3) how do they compare to estimates based on historical observations, and (4) what are the implications for the characterization of climate risks? We address these questions by estimating statistical yield response functions for four major crops (maize, rice, wheat and soybeans) over the historical period (1971-2004) as well as future climate change scenarios (2005-2099) using ISIMIP-Fastrack data for five GCMs and seven crop models under rain-fed and irrigated management regimes. Our approach, which is patterned after Lobell and Burke [2010], is a novel application of cross-section/time-series statistical techniques from the climate economics literature to large, high-dimension, multi-model datasets, and holds considerable promise as a diagnostic methodology to elucidate uncertainties in the processes simulated by crop models, and to support the development of climate impact intercomparison exercises.

The effect of inter-annual variability of consumption, production, trade and climate on crop-related green and blue water footprints and inter-regional virtual water trade: A study for China (1978-2008).

PubMed

Zhuo, La; Mekonnen, Mesfin M; Hoekstra, Arjen Y

2016-05-01

Previous studies into the relation between human consumption and indirect water resources use have unveiled the remote connections in virtual water (VW) trade networks, which show how communities externalize their water footprint (WF) to places far beyond their own region, but little has been done to understand variability in time. This study quantifies the effect of inter-annual variability of consumption, production, trade and climate on WF and VW trade, using China over the period 1978-2008 as a case study. Evapotranspiration, crop yields and green and blue WFs of crops are estimated at a 5 × 5 arc-minute resolution for 22 crops, for each year in the study period, thus accounting for climate variability. The results show that crop yield improvements during the study period helped to reduce the national average WF of crop consumption per capita by 23%, with a decreasing contribution to the total from cereals and increasing contribution from oil crops. The total consumptive WFs of national crop consumption and crop production, however, grew by 6% and 7%, respectively. By 2008, 28% of total water consumption in crop fields in China served the production of crops for export to other regions and, on average, 35% of the crop-related WF of a Chinese consumer was outside its own province. Historically, the net VW within China was from the water-rich South to the water-scarce North, but intensifying North-to-South crop trade reversed the net VW flow since 2000, which amounted 6% of North's WF of crop production in 2008. South China thus gradually became dependent on food supply from the water-scarce North. Besides, during the whole study period, China's domestic inter-regional VW flows went dominantly from areas with a relatively large to areas with a relatively small blue WF per unit of crop, which in 2008 resulted in a trade-related blue water loss of 7% of the national total blue WF of crop production. The case of China shows that domestic trade, as governed by economics and governmental policies rather than by regional differences in water endowments, determines inter-regional water dependencies and may worsen rather than relieve the water scarcity in a country. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Nutritive quality and protein production from grain legumes in a boreal climate.

PubMed

Lizarazo, Clara I; Lampi, Anna-Maija; Liu, Jingwei; Sontag-Strohm, Tuula; Piironen, Vieno; Stoddard, Frederick L

2015-08-15

Boreal cropping systems are heavily focused on the production of small-grain cereals; to improve their resilience to climate change and to achieve food and feed security, diversification is needed. This study investigated the potential of faba bean, narrow-leafed lupin and lentil as protein crops in southern Finland, where faba bean is traditional but the other two are novel. Early cultivars of narrow-leafed lupin and lentil matured adequately. Protein concentration in faba bean was, at 32%, higher than the world average of 29%, while those of narrow-leafed lupin and lentil were close to their world averages. Protein yields decreased in the order faba bean > narrow-leafed lupin > lentil. Lipid content of faba bean and lentil was about 1.2% and that of narrow-leafed lupin about 5.5%, and fatty acid composition was largely oleic and linoleic in all three species. Both lentil and narrow-leafed lupin can be added to the range of feed and food crops produced at high latitudes in Europe. While faba bean produces the greatest protein yield and lysine concentration, the higher sulfur amino acid concentration in lupin, its oil content and its adaptation to acid, sandy soils not suitable for faba bean make it an attractive alternative. © 2014 Society of Chemical Industry.

Climate change impacts on crop yield and quality with CO2 fertilization in China

PubMed Central

Erda, Lin; Wei, Xiong; Hui, Ju; Yinlong, Xu; Yue, Li; Liping, Bai; Liyong, Xie

2005-01-01

A regional climate change model (PRECIS) for China, developed by the UK's Hadley Centre, was used to simulate China's climate and to develop climate change scenarios for the country. Results from this project suggest that, depending on the level of future emissions, the average annual temperature increase in China by the end of the twenty-first century may be between 3 and 4 °C. Regional crop models were driven by PRECIS output to predict changes in yields of key Chinese food crops: rice, maize and wheat. Modelling suggests that climate change without carbon dioxide (CO2) fertilization could reduce the rice, maize and wheat yields by up to 37% in the next 20–80 years. Interactions of CO2 with limiting factors, especially water and nitrogen, are increasingly well understood and capable of strongly modulating observed growth responses in crops. More complete reporting of free-air carbon enrichment experiments than was possible in the Intergovernmental Panel on Climate Change's Third Assessment Report confirms that CO2 enrichment under field conditions consistently increases biomass and yields in the range of 5–15%, with CO2 concentration elevated to 550 ppm Levels of CO2 that are elevated to more than 450 ppm will probably cause some deleterious effects in grain quality. It seems likely that the extent of the CO2 fertilization effect will depend upon other factors such as optimum breeding, irrigation and nutrient applications. PMID:16433100

Climate change and drought effects on rural income distribution in the Mediterranean: a case study for Spain

NASA Astrophysics Data System (ADS)

Quiroga, Sonia; Suárez, Cristina

2016-06-01

This paper examines the effects of climate change and drought on agricultural incomes in Spanish rural areas. Present research has focused on the effects of these extreme climatological events through response functions, considering effects on crop productivity and average incomes. Among the impacts of droughts, we focused on potential effects on income distribution. The study of the effects on abnormally dry periods is therefore needed in order to perform an analysis of diverse social aspects in the long term. We estimate crop production functions for a range of Mediterranean crops in Spain and we use a measure of the decomposition of inequality to estimate the impact of climate change and drought on yield disparities. Certain adaptation measures may require a better understanding of risks by the public to achieve general acceptance. We provide empirical estimations for the marginal effects of the two impacts considered: farms' average income and income distribution. Our estimates consider crop production response to both biophysical and socio-economic aspects to analyse long-term implications on competitiveness and disparities. As for the results, we find disparities in the adaptation priorities depending on the crop and the region analysed.

Analysing reduced tillage practices within a bio-economic modelling framework.

PubMed

Townsend, Toby J; Ramsden, Stephen J; Wilson, Paul

2016-07-01

Sustainable intensification of agricultural production systems will require changes in farm practice. Within arable cropping systems, reducing the intensity of tillage practices (e.g. reduced tillage) potentially offers one such sustainable intensification approach. Previous researchers have tended to examine the impact of reduced tillage on specific factors such as yield or weed burden, whilst, by definition, sustainable intensification necessitates a system-based analysis approach. Drawing upon a bio-economic optimisation model, 'MEETA', we quantify trade-off implications between potential yield reductions, reduced cultivation costs and increased crop protection costs. We extend the MEETA model to quantify farm-level net margin, in addition to quantifying farm-level gross margin, net energy, and greenhouse gas emissions. For the lowest intensity tillage system, zero tillage, results demonstrate financial benefits over a conventional tillage system even when the zero tillage system includes yield penalties of 0-14.2% (across all crops). Average yield reductions from zero tillage literature range from 0 to 8.5%, demonstrating that reduced tillage offers a realistic and attainable sustainable intensification intervention, given the financial and environmental benefits, albeit that yield reductions will require more land to compensate for loss of calories produced, negating environmental benefits observed at farm-level. However, increasing uptake of reduced tillage from current levels will probably require policy intervention; an extension of the recent changes to the CAP ('Greening') provides an opportunity to do this.

Environmental Change: Precipitation and N, P, K, mg Fertilization Influences on Crop Yield Under Temperate Climate Conditions

NASA Astrophysics Data System (ADS)

László Phd, Dd. M.

2009-04-01

Summary: Agroecological quality has a well estabished dependence on climate-rainfall changes because the water problems are pressing. Therefore, there is, growing concern about the potentially wide ranging risks that climate change would have on these key industries as the nature and extent of anticipated changes have become more evident. It also includes changes in land use and in plant production and their management. These changes are unprecedented in terms of both their rate and their spatial extent. Changes in land use (agrotechnics, soil, cultivation, fertility, quality, protection etc.) and in plant production (plant, nutrition, rotation, protection etc.) are currently the main manifestations. As an interdisciplinary problem it is necessary to study such a complex matter in terms of agricultural production. Generally, among natural catastrophes, droughts and floods cause the greatest problems in field crop production. The droughts and the floods that were experienced in Hungary in the early 1980s have drawn renewed attention to the analyses of these problems. New research on climate change-soil-plant systems are focused on yield and yield quality. This paper reports of the climate changes (rainfall); soil (acidic sandy brown forest) properties, mineral N, P, K, Mg fertilisation level and plant interactions on rye (Secale cereale L.), on potato (Solanum tuberosum L.) and on winter wheat (Triticum aestivum L.) yields in a long term field experiment set up at Nyírlugos in north-eastern Hungary under temperate climate conditions in 1962. Results are summarised from 1962 to 1990. Main conclusions were as follows: 1. Rye: a, Experimental years were characterised by frequent extremes of precipitation variabilities and changes. b, By an average year, at a satisfactory fertilisation level (N: 90 kg ha-1 and NP, NK, NPK, NPKMg combinations) the maximum yield reached 3.8 t ha-1. But yield was decreased by 17% and by 52% due to drought and excess rainfall, respectively. Negative effects (drought, excess rainfall) were diminished by 20-25% with Mg treatments. c, Correlation between rye yields and precipitation during vegetation seasons showed that optimum yield (4.0 t ha-1) develops in the 430-470 mm range. 2. Potato: a, Trial years were estimated by recurrent extremes of climate. b, In vegetation seasons poor in rainfall yield safety in potato cannot be secured by fertilisation (N, NP, NK, NPK, NPKMg) alone. Under this weather condition yield was decreased by 35%. c, Optimum yields range between 17-21 t ha-1 at 280-350 mm. 3. Winter wheat: a, Climate was manifested mainly by precipitation using average, drought, dry and rainy levels. b, Yields from drought year effects with N, NP and NK combinations were diminished to 48% and with NPK and NPKMg treatments fell to 51%. c, Optimum yields (3.5-4.0 t ha-1) were developed at 450-500 mm. This paper summarises quantified results of rye, potato and winter wheat research with regarding to interaction effects and relationships between climate (rainfall)-mineral nutrition-crop production changes in Hungary during a long term field experiment to agricultural sustainability. Key words: ecology, rainfall, crop, fertilization, yield Introduction: "Climate Change" are recognized as a serious environmental issues [1]. Presently the build up of greenhouse gases in the atmosphere and the inertia in trends in emissions means that we can expect significant changes for at least the next few decades and probably for the whole 21th century too [2]. It would badly need to understand what might be involved in adapting to the new climates. A decade ago, researchers asked the „what if" question. For example, what will be the impact if climate changes. Now, we must increasingly address the following question: how do we respond effectivelly to prevent damaging impacts and take advantage of new climatic opportunities [3]. This question requires detailed in information regarding expected impacts and effectíve adaptive measures. Information on adaptation is required for governments, landscape planners, stakeholders, farmers, producers, processors, supermarkets and consumers. Not only the local effects and options, but also the spatial implications must be understood. Will yields be maintained on the present range of farms. Where will new crops be grown. Will new processing plants be required. Will there be competition for water. Most recent agricultural impact studies have concentrated on the effects of mean changes in climate on crop production, whilst only limited investigations into the effects of climate variability on agriculture have been undertaken. The paucity of studies in this area is not least due to the considerable uncertainty regarding how climate variability may change in the future in response to greenhouse gas induced warming but also as a result of the uncertainty in the response of agricultural crops to changes in climate variability, effected most probably through changes in the frequency of extreme climatic events. That changes showed in variance have a greater effect on the frequency of extreme climatic events than do changes in the mean values. Hence, it is important to attempt to include changes in variability in scenarios of climate change. Weather change in Hungary was started about of 1850. Among the natural catastrophes, drought and flooding caused by over-abundant rainfall cause the greatest problem in plant nutrition and in field crop production nowadays too [4]. It is why we found it necessary to revise and to analyse this problem. Rye (Secale cereale L.), potato (Solanum tuberosum L.) and winter wheat (Triticum aestivum L.) are most important crops of many World countries [5] but little research in the field of climate change impact assessment has been undertaken. All three plant are sensitive to the prevailing weather conditions (rainfall) and, hence, it is important to evaluate the effects of anthropogenic climate change on their production. These crops are demanding indicator of soil nutrient status also. Have a particularly high requirement for supply of soil nitrogen, phosphorus, potassium and magnesium. From 1962 to 1990 this paper describes climate-rainfall-change and N, P, K and Mg-mineral fertilisation effects on rye, potato and winter wheat yield on a acidic sandy brown forest soil at long term experiment scale under temperate climate conditions at Hungary. Material and Method: The effect of rainfall quantity and distribution on certain crop fertilisation factors (N, P, K, Mg and yield) were studied in a long-term field experiment on acidic sandy brown forest soil at North-Eastern Hungary set up in 1962 and 2002. Ploughed layer of the experiment soil had a pH(KCl) 4.5, humus 0.5%, CEC 5-10 mgeq 100 g-1. The topsoil was poor in all four macronutrients N, P, K and Mg. Rye, potato and winter wheat experiments involved 2x2x16x8 = 512, 2x2x16x8 = 512 and 2x16x4 = 128 plots. The gross and net plot size was 10x5 = 50 m2 and 35.5 m2. The experimental designe was split-split-plot. Average treatments were rye N:45 kg, P2O5:24, K2O:40, MgO:7.5 kg ha-1 year-1, potato N:75 kg, P2O5:24, K2O:75, MgO:15 kg ha-1 year-1, winter wheat N:45 kg, P2O5:24, K2O:40, MgO:7.5 kg ha-1 year-1 from 1962 to 1980 and N:75 kg, P2O5:90, K2O:90, MgO:140 kg ha-1 year-1 from 1981 to 1990 in the form of 25% calcium ammonium nitrate, 18% superphosphate, 40% potassium chloride, and magnesium sulphate. The groundwater table was at a depth of 2-3 m. Ecological (rainfall) and experimental data bases were estimated by Hungarian traditional [6] and RISSAC-HAS [3] standards and MANOVA (SPSS). Results: Climate-rainfall-change and mineral fertilisation effects on rye yield a. Experimental years were characterised by frequent extremes of precipitation variabilities and changes. One year had an 450 mm average rainfall (1966), one year had a more humid (1970) and three years had a very dry (1964, 1968, 1972) character. b. Weather anomalies as drought or to much rainfall did not cause significant differences on rye yield without fertilisation (average year: 1.66 t ha-1, drought year: 1.51 t ha-1, over rainfall year: 1.47 t ha-1). c. Yields varied from 2.01 to 3.04 t ha-1 under low (N: 30 kg ha-1 and NP, NK, NPK, NPKMg combinations) fertilisation input. Yields were decreased by 14% and 10% by drought and also by excess of rainfall. d. At mean fertilisation (N: 60 kg ha-1 and NP, NK, NPK, NPKMg combinations) level the maximum yield had reached 3.6 t ha-1 in average year. In years with excess rainfall, rye yields decreased as an average of fertilisation treatments by 20%. e. By an average year, at satisfactory fertilisation (N: 90 kg ha-1 and NP, NK, NPK, NPKMg combinations) level the maximum yield reached 3.8 t ha-1. But these yields were decreased with 17% and with 52% by drought and excess rainfall weather conditions respects. Negative effects (drought, excess rainfall) were diminished with 20-25% on the Mg treatments. f. Correlations between rye yields and the sums of precipitations during vegetation period (control: R = 0.99***, N: R = 0.84***, NP: R = 0.84***, NK: R = 0.91***, NPK: R = 0.85***, NPKMg: R = 0.65**) showed that optimum yields will develop in 430-470 mm range. Under and above these range of rainfall yields will decrease. Climate-rainfall-change and mineral fertilisation effects on potato yield a. Trial years (1963, 1965, 1967, 1969, 1971) were characterised by recurrent extremes of climate under vegetation seasons of potato. Three period had average rainfall, while two were very dry. b. All in all, droughts in the winter or summer half-year had much the same effect on yields. Precipitation deficiency in the winter could not be counterbalanced by average rainfall during the vegetation period, and its effect on the yield was similar to that of summer drought. c. Yield and quality were influenced by rainfall to a greater extent than by fertilisation. d. In vegetation periods poor in rainfall yield and quality safety in potato cannot be secured by fertilisation alone, they were decreased to 35%. It was also concluded that economic yields could not be achieved with poor nutrient supply even with a normal quantity and distribution of rainfall. e. The unfavorable effects of climate anomalies (drought, over-abundance of water in the topsoil) on the yield formation, yield quantity and quality of potato depended decisively on the time of year when they were experienced and the period for which they lasted. f. With the help of regression analysis it was found the polynomial correlation between rainfall and yield could be observed in case of the control: R = 0.98***, N: R = 0.95***, NP: R = 0.96***, NK: R = 0.95***, NPK: R = 0.98***, NPKMg: R = 0.96*** nutrition systems. The optimum yield ranges between 17-20 t ha-1 at 280-350 mm of rainfall. Climate-rainfall-change and mineral fertilisation effects on winter wheat yield a. Climate-rainfall-conditions of winter wheat years were determined by mainly precipitation on-, average (1982 and 1989)-, drought (1976 and 1990)-, dry (1974) and rainy (1978 and 1980) level. b. Experimental years climate-rainfall-character were formed by winter half-years (october-march), months (october-september), pre-months of sowing (august), critical sequential month number in vegetation seasons (september-july) and critical sequential month number in experimental years (september-august). c. In average years without any mineral fertilisation wheat yield was stabilized on the level of 1.8 t ha-1. Under N, P, K and Mg fertiliser input minimum and maximum yields were 2.7 and 4.1 t ha-1. Yield was only increased by whole NPK and Mg completed NPKMg treatment. d. Without mineral fertilisation on control plots yield was decreased by drought year effect compared with average with a 39%. On N, NP and NK combinations yields were diminished to 48%. Drought damage on yield production was rised more to 51% by NPK and NPKMg application. e. But in dry years and in average years yields were similar on control plots. Yields were decreased for average year effect on N, NP, NK and NPK, NPKMg treatments with 20% and with 16%. f. Under excess rainy weather conditions without fertiliser application yields were decreased more dramaticaly (56%) than under drought seasons (39%) to case of average rainfall effects. Yield was damaged with a 47% by unfavourable (N, NP, NK) nutrition. But this negative effect of excess rainfall condition was diminished on NPK and NPKMg treatments to 41%. g. Correlations of regression analysis between yields and the sums of precipitations during vegetation seasons (control: R = 0.59***, N: R = 0.57***, NP: R = 0.76***, NK: R = 0.53**, NPK: R = 0.67***, NPKMg R = 0.70**) showed that optimum yields will develop in 450-500 mm range. Above these range of rainfall yields will decrease swiftly. This paper gives opportunities summarise quantified results of rye-potato-winter wheat researches with regarding to interaction effects and relationships between climate (rainfall)-mineral nutrition-crop production changes at Hungary in a long term field experiment system under temperate climate conditions to agricultural sustainability. Acknowledgement: This research was supported by Hungarian Academy of Sciences, H-Budapest References [1] Johnston A.E.: Some aspects of nitrogen use efficiency in arable agriculture. K. Scogs-o. Lantbr. Akad. Tidskr. 2000, 8, 139. [2] Márton L.: Climate change and N, P, K, Mg fertilization effect analysis at Tisza-river basin in a long term field experiment. Szent István University, Gödöllő 2001, 9. [3] Márton L.: Climate change, N-fertilisation effect on rye (Secale cereale L.) yield in a long term field experiment. [in:] Rural development-Ecologically farming-Agriculture, (Eds M Palkovics), University Veszprém, Keszthely 2001, 924-929. [4] José A.B., Estáquio M.J. and Márton L.: Results of Crotalaria ssp. effects on soil conservation. Congress on Conservation Agriculture (Eds Armando MV), ECAF., Madrid, 2001. 5, 1-4. [5] Kádár I., Márton L. and Horváth S.: Mineral fertilisation of potato (Solanum tuberosum L.) on calcareous chernozem soil. Plant Production, 2000, 49, 291-306. [6] Harnos, Zs.: Időjárás és időjárás-termés összefüggéseinek idősoros elemzése, [in:] Aszály 1983 (Szerk.: Baráth Cs-né, Győrffy B., Harnos Zs.). KÉE. Budapest 1993. [7] Márton L.: Climate-Rainfall Change (CRC) and mineral fertilisation (MF) effects on different crop production. [in:] Challenges of the new millennium our joint responsibility. (Eds A. Borhidi). MTA ÖBKI, Budapest 2002, 1, 110-111. [8] Márton L.: Rainfall, mineral fertilisation and winter wheat (Triticum aestivum L.) yield relations. Plant Production, 2002, 51, 529-542.

Increasing crop diversity mitigates weather variations and improves yield stability.

PubMed

Gaudin, Amélie C M; Tolhurst, Tor N; Ker, Alan P; Janovicek, Ken; Tortora, Cristina; Martin, Ralph C; Deen, William

2015-01-01

Cropping sequence diversification provides a systems approach to reduce yield variations and improve resilience to multiple environmental stresses. Yield advantages of more diverse crop rotations and their synergistic effects with reduced tillage are well documented, but few studies have quantified the impact of these management practices on yields and their stability when soil moisture is limiting or in excess. Using yield and weather data obtained from a 31-year long term rotation and tillage trial in Ontario, we tested whether crop rotation diversity is associated with greater yield stability when abnormal weather conditions occur. We used parametric and non-parametric approaches to quantify the impact of rotation diversity (monocrop, 2-crops, 3-crops without or with one or two legume cover crops) and tillage (conventional or reduced tillage) on yield probabilities and the benefits of crop diversity under different soil moisture and temperature scenarios. Although the magnitude of rotation benefits varied with crops, weather patterns and tillage, yield stability significantly increased when corn and soybean were integrated into more diverse rotations. Introducing small grains into short corn-soybean rotation was enough to provide substantial benefits on long-term soybean yields and their stability while the effects on corn were mostly associated with the temporal niche provided by small grains for underseeded red clover or alfalfa. Crop diversification strategies increased the probability of harnessing favorable growing conditions while decreasing the risk of crop failure. In hot and dry years, diversification of corn-soybean rotations and reduced tillage increased yield by 7% and 22% for corn and soybean respectively. Given the additional advantages associated with cropping system diversification, such a strategy provides a more comprehensive approach to lowering yield variability and improving the resilience of cropping systems to multiple environmental stresses. This could help to sustain future yield levels in challenging production environments.

Determining molecular responses to environmental change in soybeans

USDA-ARS?s Scientific Manuscript database

As the global climate changes, plants will be challenged by environmental stresses that are more extreme and more frequent. The average yield loss due to environmental stresses is currently estimated to be more than 50% for major crop species and is the major limitation to world food production. The...

7 CFR 760.808 - General provisions.

Code of Federal Regulations, 2010 CFR

2010-01-01

... harvested production does not exist; (2) The loss is due to an ineligible cause of loss or practices, soil... provisions. (a) For calculations of loss, the participant's existing unit structure will be used as the basis... (2) For NAP covered crops, part 1437 of this title. (b) County average yield for loss calculations...

Evaluating variable rate fungicide applications for control of Sclerotinia

USDA-ARS?s Scientific Manuscript database

Oklahoma peanut growers continue to try to increase yields and reduce input costs. Perhaps the largest input in a peanut crop is fungicide applications. This is especially true for areas in the state that have high disease pressure from Sclerotinia. On average, a single fungicide application cost...

Weather based risks and insurances for crop production in Belgium

NASA Astrophysics Data System (ADS)

Gobin, Anne

2014-05-01

Extreme weather events such as late frosts, droughts, heat waves and rain storms can have devastating effects on cropping systems. Damages due to extreme events are strongly dependent on crop type, crop stage, soil type and soil conditions. The perspective of rising risk-exposure is exacerbated further by limited aid received for agricultural damage, an overall reduction of direct income support to farmers and projected intensification of weather extremes with climate change. According to both the agriculture and finance sectors, a risk assessment of extreme weather events and their impact on cropping systems is needed. The impact of extreme weather events particularly during the sensitive periods of the farming calendar requires a modelling approach to capture the mixture of non-linear interactions between the crop, its environment and the occurrence of the meteorological event. The risk of soil moisture deficit increases towards harvesting, such that drought stress occurs in spring and summer. Conversely, waterlogging occurs mostly during early spring and autumn. Risks of temperature stress appear during winter and spring for chilling and during summer for heat. Since crop development is driven by thermal time and photoperiod, the regional crop model REGCROP (Gobin, 2010) enabled to examine the likely frequency, magnitude and impacts of frost, drought, heat stress and waterlogging in relation to the cropping season and crop sensitive stages. The risk profiles were subsequently confronted with yields, yield losses and insurance claims for different crops. Physically based crop models such as REGCROP assist in understanding the links between different factors causing crop damage as demonstrated for cropping systems in Belgium. Extreme weather events have already precipitated contraction of insurance coverage in some markets (e.g. hail insurance), and the process can be expected to continue if the losses or damages from such events increase in the future. Climate change will stress this further and impacts on crop growth are expected to be twofold, owing to the sensitive stages occurring earlier during the growing season and to the changes in return period of extreme weather events. Though average yields have risen continuously due to technological advances, there is no evidence that relative tolerance to adverse weather events has improved. The research is funded by the Belgian Science Policy Organisation (Belspo) under contract nr SD/RI/03A.

Effects of Potassium Mineral Fertilization on Potato (Solanum tuberosum L.) Yield on a Chernozem Soil in Hungary

NASA Astrophysics Data System (ADS)

László, Márton, ,, Dr.

2010-05-01

Nowadays potato (Solanum tuberosum L.) is a more important throughout the world between field crops. As potato is such a potassium demanding crop, it is particularly important that the potassium fertilizers used should be correctly balanced. Applying the adequate quantity of balanced K- fertilizer is the first requirement for achieving optimum yield and doing so will result in potatoes of acceptable quality. Potato potassium nutrition has been studied at the Research Institute for Soil Science and Agricultural Chemistry of the Hungarian Academy of Sciences (RISSAC-HAS)- Experiment Station, Nagyhörcsök (chernozem soil) in a long term field experiment designed to determine NPK- nutrient requirements. The method of the experiment was 43 mixed factorial design with 64 treatments in 2 repetitions with 128 plots. The residual effects of K- levels brought about by build- up fertilization were studied. Potato were planted in 1978. The experimental dates were estimated by multivariate analysis of variance (MANOVA). On the basis of foliar analysis at early flowering about 4.5 to 5.0% K in dry matter proved to be satisfactory for obtaining maximum yield (32.6 t/ha). The yields increased by 22%, 34%, and 38% at 124-140, 141-168 and 169-208 ppm soil AL- K2O rates, respectively. The tubers concentrated much N 19% and less P 81% than potassium. Results for tuber maximum uptake of potassium reached a maximum about 130 days after planting. The improvement of the K supply of the soil increased yield and induced low concentrations of numerous microelements on leaves considered to be important. Key words: Potato (Solanum tuberosum L.), chernozem soil, potassium, yield Introduction Potato is an important food crop, more particularly in the temperate zone, especially in Europe and Asia. Between 1981 and 1995, in spite of an 18% decrease in cultivated area production increased by 13% because the average yield increased from 11.0 to 15.1 t/ha. Potato is a soil nutrients demanding crop and has a particularly high requirement for potassium. Tubers remove 1.5 times more potassium than nitrogen and 4 or 5 times the amount of phosphate. The quantity of nutrients taken up by a crop is not necessarily an indication of responsiveness to fertilizers but potato, because its root system is relativly poorly developed in relation to yield is extremly responsive to all nutrients (Márton 1984). As potato is such a demanding crop, it is particularly important that the potassium fertilizers used should be correctly balanced (Burton 1966). Applying the adequate quantity of balanced K- fertilizer is the first requirement for achieving optimum yield and doing so will result in potatoes of acceptable quality (Márton 2000). It is not the objective of present publication to give recommendations K- fertilizers which vary greatly according to local conditions. We intend to discuss various aspects of potassium effects on the basis of our research results. The importance of potatoes In terms of area planted, potato is the twelfth most important crop in all the world (18.48 million hectares) by FAO in 1995. In terms of total production it occupies the 5th position with 280 million t, between maize (515 mio) and sugar beet (266 mio). It is a high yielding crop. The world average being 15.1 t/ha, the third highest yielding crop on the bases of fresh matter following sugar cane (62.6 t/ha) and sugar beet (33.9 t/ha). Area planted, production and yield (1981 and 1995) Between 1981 and 1995 the total world area planted declined by 18%. While the importance of the crop declined more or less markedly in Europe, and in N. and C. America, there has been an increase in S. America (Márton 1999). The area planted in Asia has more than doubled and in Africa tripled. Despite of the reduction in area, world production has actually increased by 13% in the same period. This increase in production is due to a general 37% growth in yield from 11 to 15.1 t/ha. The potential yields of varieties, estimated at 85-100 t/ha for potato, 75-85 t/ha for beet and 12-15 t/ha for wheat (Evans 1977). These are far higher than the yields commonly obtained in practice. World average yields were only 1/6th of the potential for potato, 1/6th for wheat and 2/5th for sugar beet in 1995. Utilization of the crop The major part of potato production is usually used for human consumption. Human consumption of potatoes however has declined in the industrialised countries as the standard of living has increased. In these countries an increasing proportion of the crop is used for manufacturing products such as crisp, oven-ready chips, dehydrated potato powder. Thus, in Hungary the consumption of potatoes per person decreased from 110 kg in 1951/1960 to 60 kg in 1995, whereas the consumption of processed potatoes increased from 1 to 15 kg/person during this period. Uptake of potassium Potassium is the nutrient taken up by potato in the greatest quantity, it also takes up much nitrogen and appreciable amounts of phosphorus, calcium, magnesium and sulphur (Perrenoud 1993). Maximum uptakes by different varieties in Japan range between 140 and 267 K2O (Kali Kenkyu Kai 1980). In England, potatoes grown on the " blueprint" system and giving the very high yield of 77.7 t/ha took up 450 kg/ha K2O (Anderson and Hewgill 1978). Brazílian experiments with 6 varieties showed the following uptakes (kg/ha): potassium 207-367 (Motta 1976). Removal of potassium by tubers 23 experimental crops in France (Loué 1977), -with a mean yield of 37.3 t/ha tubers removed: 196 kg K2O, respectively. It is equal to 5.3 kg K2O per 1 tonne tuber. Motta Macedo (1976) reports the following removals in kg/ha for 6 varieties grown in Brazíl: K2O: 118-192. In 14 experiments in India (Grewal and Singh 1979) a mean yield of 28.8 t/ha tuber was obtained which removed an average of 91 kg/ha K2O. At very high yield level, nutrient removal in tuber is very high. Anderson and Hewgill (1978) report a yield of 90 t/ha, obtained at Stockbridge House in 1973 which contained 487 kg K2O in the tubers. The effects of potassium fertilizer on yield The averages of 1267 experimental results (607 from 8 developed countries and 660 from 10 developing countries) were estimated. Yields increased by 14, 10 and 11% for 1-100, 101-200 and 201-300 kg/ha K2O rates, respectively. The greater average effect of potassium on yield at the 1-100 kg/ha K2O rate as compared to higher doses was due to the strong effect of this nutrient in experiments. 1 kg K2O produces 32, 16 and 13 kg tubers when 1-100, 101-200 and 201-300 kg/ha K2O are applied. An example of the effect of potassium on yield is in the Siebold (1971) reports that heavy potash dressing had spectacular effects on yield on a soil which fixed potassium strongly. Nutrient interactions In 17 years of a long- term experiment at Aspach (France) (Loué 1977) positive interactions between N and K were recorded in 15 years and negative in 2. Yadav and Tripathi (1973) recorded an NxK interaction amounting to 4.44 t/ha tubers in India. Materials and Methods The NPK fertilization field trial was set up at the Nagyhörcsök Experiment Station of the Research Institute for Soil Science and Agricultural Chemistry of the Hungarian Academy of Sciences by Imre Kádár in the autumn of 1973. The method of the experiment was 43 design of the mixed factorial with 64 treatments, in 2 repetitions with 128 plots. The gross and net size of the plots were 6 x 6 = 36 m2 and 24.5 m2 respectivly. N fertilization was repeated yearly. As regards P and K residual effects of nutrient levels brought about by build-up fertilization in autumn 1973, were recorded. The experiment was carried out in South-East Hungary on a calcareous chernozem soil. The clay fraction (0.002 mm) content of the soil was 20 % and silt fraction (0.02 mm) 40 %. The 0.05-0.02 mm fraction was 35-50 %. The main characteristics of the soil (plough layer) are as follows: CaCO3 5 %, humus 3 %, pH(KCl) = 7.4-7.8, AL-P2O5 = 50-80 ppm, AL-K2O = 120-140 ppm, Mg(KCl) = 120-150 ppm, EDTA-Mn = 100-150 ppm, EDTA-Zn = 1-2 ppm, EDTA-Cu = 2-4 ppm. The initial nutrient supply of the soil was poor in P and medium in K. After build-up fertilization (1973) the easily soluble phosphorus and potassium contents of the soil rapidly decreased without yearly maintenance fertilization. In the first four years of the experiment winter wheat-winter wheat-maize-maize were grown. Potatoes (variety: Desirée) were planted by hand in 1978. Plant sampling was carried out by averaging 20 subsamples per plot. The experimental data were estimated by multivariate analysis of variance, MANOVA. In this paper We would like to present the potassium effects on potato yield. Results and Discussion Uptake of potassium Under the experimental conditions of 1978, on the basis of foliar analysis at early flowering, in dry matter about 4.5 to 5.0% K proved to be satisfactory for obtaining maximum yield (32.6 t/ha). Effects of K- fertilizers on yield Potato yields increased by 22%, 34% and 38% at 124-140, 141-168 and 169-208 ppm soil AL- K2O rates, respectively. That the average effect of potassium on yield was greater at 208 ppm K2O than at higher rates is due to the strong effect of this nutrient in experiments. 1 ppm K2O produced 268, 232 and 185 kg tubers when 124-140, 141-168 and 169-208 ppm K2O were applied. These results are very similar to those reported by Siebold (1971), he found that heavy dressing of potash had spectacular effects on the yield on a soil with strong potassium- fixing ability. Removal of potassium and other nutrients in tuber The tubers removed much nitrogen, 0.1 times more than potassium and 6 times as much as phosphorus. Removal of calcium and magnesium were much lower but still significant. In experiment- giving a mean yield of 32.6 t/ha tubers on K- effects on average of NP removed 454 kg N, 76 kg P2O5, 488 kg K2O, 81 kg CaO, 26 kg MgO and 14 kg/t N, 2 kg/t P2O5, 15 kg/t K2O, 3 kg/t CaO and 0.8 kg per tonne MgO, respectivly. We found that 32.6 t/ha crop removed 1.8 kg sodium, 1.6 kg iron, 400 g zinc and 100 g manganese. Pattern of potassium and other nutrient uptake The uptake of nutrients during potato growth were studied. Results for tuber average uptake of nitrogen (472 kg/ha), phosphorus (77 kg/ha) and potassium (426 kg/ha) reached a maximum about 130 days after planting. It was observed that crop took up about 3.6 kg N, 0.5 kg P and 3.0 kg K per ha per day. Nutrient interaction Improving K- supply of the soil was found to increase yield and induce low concentration of numerous elements on leaves considered as important. K- fertilization had a negative effect mainly on the Mg and Ca contents. Thus e.g. K/Mg ratio increased from 3 to 11 at yearly flowering as an effect of K fertilization, that however, should not be considered an unfavourable ratio as yet and on these plots K fertilization still remained effective. Acknowledgements This research was supported by Research Institute for Soil Science and Agricultural Chemistry of the Hungarian Academy of Sciences. References Anderson, G.D.-Hewgill, D. (1978).: Effects of nitrogen, phosphorus and potassium on ‘Blueprint' grown potatoes. Maximising Yields of crops. ADASARC Symposium. 139-150. Burton, W.G. (1966).: The potato. Veemann. Wageningen. Evans, S.A. (1977).: The place of fertilizers in ‘Blueprints' for the production of potatoes and cereals. Fertilizer use and production of carbohydrates and lipids. Proc. 13th Coll. Inst. Bern, 231-241. FAO. (1995).: Production Yearbook, Vol. 49. Grewal, J.S. (1975).: Manuring of potatoes. Indian Farming. 25:15-17. Kali, K.K. (1980).: Private communication. Tokyo. Loué, A. (1977).: Fertilisation et nutrition minérale de la pomme de terre. Expérimentation et études agronomiques, SCPA. Mulhouse. 147. Márton, L. (1984).: Fertilization effects on potato yield and quality. Doctoral dissertation. KAU. Keszthely. Márton, L.-Jose, A.B. (1999).: Potato (Solanum tuberosum L.) production in Brazíl. Acta Agronomica Óváriensis. 41:153-158. Márton, L. (2000).: Nitrogen, phosphorus and potassium effects on potato quality. In: Agro markets and conditions. Agricultural University of Veszprém. 241-247. Keszthely. Hungary. Motta Macedo, M.C. (1976).: Absorcao de nutrientes por cultivares nacionais de batatinha (Solanum tuberosum L.). Diss., Escola Superior. Luiz de Queiroz da Universidade de Sáo Paulo. Perrenoud, S.: (1993).: Potato. Fertilizing for high yield. IPI Bulletin. N.8. Basel. Switz. Siebold, M. (1971).: Kartoffelanbau auf kalifixierenden Böden. Kartoffelbau. 22:12-13. Yadav, S.C.-Tripathi, B.R. (1973).: Studies on soil moisture regimes and nitrogen, phosphorus and potash fertilization on yield of potato (S. tuberosum L.). Plant Sci. 5:97-104.

Impact of crop rotation and soil amendments on long-term no-tilled soybean yields

USDA-ARS?s Scientific Manuscript database

Continuous cropping systems without cover crops are perceived as unsustainable for long-term yield and soil health. To test this, cropping sequence and cover crop effects on soybean (Glycine max L.) yields were assessed. Main effects were 10 cropping sequences of soybean, corn (Zea mays L.), and co...

Tradeoffs between water requirements and yield stability in annual vs. perennial crops

NASA Astrophysics Data System (ADS)

Vico, Giulia; Brunsell, Nathaniel A.

2018-02-01

Population growth and changes in climate and diets will likely further increase the pressure on agriculture and water resources globally. Currently, staple crops are obtained from annuals plants. A shift towards perennial crops may enhance many ecosystem services, but at the cost of higher water requirements and lower yields. It is still unclear when the advantages of perennial crops overcome their disadvantages and perennial crops are thus a sustainable solution. Here we combine a probabilistic description of the soil water balance and crop development with an extensive dataset of traits of congeneric annuals and perennials to identify the conditions for which perennial crops are more viable than annual ones with reference to yield, yield stability, and effective use of water. We show that the larger and more developed roots of perennial crops allow a better exploitation of soil water resources and a reduction of yield variability with respect to annual species, but their yields remain lower when considering grain crops. Furthermore, perennial crops have higher and more variable irrigation requirements and lower water productivity. These results are important to understand the potential consequences for yield, its stability, and water resource use of a shift from annual to perennial crops and, more generally, if perennial crops may be more resilient than annual crops in the face of climatic fluctuations.

Statistical emulators of maize, rice, soybean and wheat yields from global gridded crop models

DOE PAGES

Blanc, Élodie

2017-01-26

This study provides statistical emulators of crop yields based on global gridded crop model simulations from the Inter-Sectoral Impact Model Intercomparison Project Fast Track project. The ensemble of simulations is used to build a panel of annual crop yields from five crop models and corresponding monthly summer weather variables for over a century at the grid cell level globally. This dataset is then used to estimate, for each crop and gridded crop model, the statistical relationship between yields, temperature, precipitation and carbon dioxide. This study considers a new functional form to better capture the non-linear response of yields to weather,more » especially for extreme temperature and precipitation events, and now accounts for the effect of soil type. In- and out-of-sample validations show that the statistical emulators are able to replicate spatial patterns of yields crop levels and changes overtime projected by crop models reasonably well, although the accuracy of the emulators varies by model and by region. This study therefore provides a reliable and accessible alternative to global gridded crop yield models. By emulating crop yields for several models using parsimonious equations, the tools provide a computationally efficient method to account for uncertainty in climate change impact assessments.« less

Statistical emulators of maize, rice, soybean and wheat yields from global gridded crop models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Blanc, Élodie

This study provides statistical emulators of crop yields based on global gridded crop model simulations from the Inter-Sectoral Impact Model Intercomparison Project Fast Track project. The ensemble of simulations is used to build a panel of annual crop yields from five crop models and corresponding monthly summer weather variables for over a century at the grid cell level globally. This dataset is then used to estimate, for each crop and gridded crop model, the statistical relationship between yields, temperature, precipitation and carbon dioxide. This study considers a new functional form to better capture the non-linear response of yields to weather,more » especially for extreme temperature and precipitation events, and now accounts for the effect of soil type. In- and out-of-sample validations show that the statistical emulators are able to replicate spatial patterns of yields crop levels and changes overtime projected by crop models reasonably well, although the accuracy of the emulators varies by model and by region. This study therefore provides a reliable and accessible alternative to global gridded crop yield models. By emulating crop yields for several models using parsimonious equations, the tools provide a computationally efficient method to account for uncertainty in climate change impact assessments.« less

Yield and Economic Responses of Peanut to Crop Rotation Sequence

USDA-ARS?s Scientific Manuscript database

Proper crop rotation is essential to maintaining high peanut yield and quality. However, the economic considerations of maintaining or altering crop rotation sequences must incorporate the commodity prices, production costs, and yield responses of all crops in, or potentially in, the crop rotation ...

Planetary opportunities in crop water management: Potential to outweigh cropland expansion

NASA Astrophysics Data System (ADS)

Jägermeyr, Jonas; Gerten, Dieter; Lucht, Wolfgang; Heinke, Jens

2014-05-01

Global available land and water resources probably cannot feed projected future human populations under current productivity levels. Moreover, the planetary boundaries of both land use change and water consumption are being approached rapidly, and at the same time competition between food production, bioenergy plantations and biodiversity conservation is increasing. Global cropland is expected to expand to meet future demands, while considerable yield gaps remain in many world regions. Yield increases in Sub-Saharan Africa, for example, are currently mainly based on expansion of arable land into currently non-agricultural areas - while small-scale irrigation and water conservancy methods are considered very promising to boost yields there. In the here presented modeling study we investigate, at global scale, to what degree different on-farm options to better manage green and blue water might contribute to a global crop yield increase under conditions of current climate and projected future climate change. We consider methods aiming for a maximization of crops' water use efficiency and an optimal use of available on-farm water (precipitation): reducing unproductive soil evaporation (vapor shift, VS), collecting surface runoff after rain events to mitigate subsequent dry-spells (rain-water harvesting, RWH), increasing irrigation efficiency, and expanding irrigated area into rain-fed cropland (based on water savings from higher efficiencies). Global yield simulations based on hypothetical scenarios of these management opportunities are performed with the LPJmL ecohydrological modeling framework driven by reanalysis data and GCM ensemble simulations. We consider a range of about 20 climate change projections to cover respective uncertainties, and we analyze the effects of increasing CO2 concentration on the crops and their water demand. Crops are represented in a process-based and dynamic way by 12 crop functional types, each for rain-fed and irrigated areas, with prescribed annual fractions of cropland per 0.5° x 0.5° grid cell. We recalculate from the yield increase how much cropland expansion can be avoided in 30-yr averages. Our results show that the studied affordable low-tech solutions for small-scale farmers on water-limited croplands can have a considerable effect on yields at the global scale. A simulated global ~15% yield increase from a low-intensity water management scenario (25% of runoff used for RWH, 25% of soil evaporation avoided to achieve VS, slight irrigation efficiency improvement) could outweigh, i.e. possibly avoid, an estimated 120 Mha of cropland expansion under current climatic conditions. A (rather theoretical) maximum-intensity water management scenario (85% VS, 85% RWH, surface irrigation replaced by sprinkler systems) shows the potential to increase global yields by more than 35% without expansion or withdrawing additional irrigation water. Climate change will have adverse effects on crop yields in many regions, but as we sow such adaptation opportunities have the potential to mitigate or compensate these impacts in many countries. Overall, proper water management (sustainably maximizing on-farm water use efficiency) can substantially increase global crop yields and at the same time relax rates of land cover conversion.

Interactions of CO2, temperature and management practices: simulations with a modified version of CERES-Wheat

NASA Technical Reports Server (NTRS)

Tubiello, F. N.; Rosenzweig, C.; Volk, T.

1995-01-01

A new growth subroutine was developed for CERES-Wheat, a computer model of wheat (Triticum aestivum) growth and development. The new subroutine simulates canopy photosynthetic response to CO2 concentrations and light levels, and includes the effects of temperature on canopy light-use efficiency. Its performance was compared to the original CERES-Wheat V-2 10 in 30 different cases. Biomass and yield predictions of the two models were well correlated (correlation coefficient r > 0.95). As an application, summer growth of spring wheat was simulated at one site. Modeled crop responses to higher mean temperatures, different amounts of minimum and maximum warming, and doubled CO2 concentrations were compared to observations. The importance of irrigation and nitrogen fertilization in modulating the wheat crop climatic responses were also analyzed. Specifically, in agreement with observations, rainfed crops were found to be more sensitive to CO2 increases than irrigated ones. On the other hand, low nitrogen applications depressed the ability of the wheat crop to respond positively to CO2 increases. In general, the positive effects of high CO2 on grain yield were found to be almost completely counterbalanced by the negative effects of high temperatures. Depending on how temperature minima and maxima were increased, yield changes averaged across management practices ranged from -4% to 8%.

Yield and Economic Performance of Organic and Conventional Cotton-Based Farming Systems – Results from a Field Trial in India

PubMed Central

Forster, Dionys; Andres, Christian; Verma, Rajeev; Zundel, Christine; Messmer, Monika M.; Mäder, Paul

2013-01-01

The debate on the relative benefits of conventional and organic farming systems has in recent time gained significant interest. So far, global agricultural development has focused on increased productivity rather than on a holistic natural resource management for food security. Thus, developing more sustainable farming practices on a large scale is of utmost importance. However, information concerning the performance of farming systems under organic and conventional management in tropical and subtropical regions is scarce. This study presents agronomic and economic data from the conversion phase (2007–2010) of a farming systems comparison trial on a Vertisol soil in Madhya Pradesh, central India. A cotton-soybean-wheat crop rotation under biodynamic, organic and conventional (with and without Bt cotton) management was investigated. We observed a significant yield gap between organic and conventional farming systems in the 1st crop cycle (cycle 1: 2007–2008) for cotton (−29%) and wheat (−27%), whereas in the 2nd crop cycle (cycle 2: 2009–2010) cotton and wheat yields were similar in all farming systems due to lower yields in the conventional systems. In contrast, organic soybean (a nitrogen fixing leguminous plant) yields were marginally lower than conventional yields (−1% in cycle 1, −11% in cycle 2). Averaged across all crops, conventional farming systems achieved significantly higher gross margins in cycle 1 (+29%), whereas in cycle 2 gross margins in organic farming systems were significantly higher (+25%) due to lower variable production costs but similar yields. Soybean gross margin was significantly higher in the organic system (+11%) across the four harvest years compared to the conventional systems. Our results suggest that organic soybean production is a viable option for smallholder farmers under the prevailing semi-arid conditions in India. Future research needs to elucidate the long-term productivity and profitability, particularly of cotton and wheat, and the ecological impact of the different farming systems. PMID:24324659

Yield and economic performance of organic and conventional cotton-based farming systems--results from a field trial in India.

PubMed

Forster, Dionys; Andres, Christian; Verma, Rajeev; Zundel, Christine; Messmer, Monika M; Mäder, Paul

2013-01-01

The debate on the relative benefits of conventional and organic farming systems has in recent time gained significant interest. So far, global agricultural development has focused on increased productivity rather than on a holistic natural resource management for food security. Thus, developing more sustainable farming practices on a large scale is of utmost importance. However, information concerning the performance of farming systems under organic and conventional management in tropical and subtropical regions is scarce. This study presents agronomic and economic data from the conversion phase (2007-2010) of a farming systems comparison trial on a Vertisol soil in Madhya Pradesh, central India. A cotton-soybean-wheat crop rotation under biodynamic, organic and conventional (with and without Bt cotton) management was investigated. We observed a significant yield gap between organic and conventional farming systems in the 1(st) crop cycle (cycle 1: 2007-2008) for cotton (-29%) and wheat (-27%), whereas in the 2(nd) crop cycle (cycle 2: 2009-2010) cotton and wheat yields were similar in all farming systems due to lower yields in the conventional systems. In contrast, organic soybean (a nitrogen fixing leguminous plant) yields were marginally lower than conventional yields (-1% in cycle 1, -11% in cycle 2). Averaged across all crops, conventional farming systems achieved significantly higher gross margins in cycle 1 (+29%), whereas in cycle 2 gross margins in organic farming systems were significantly higher (+25%) due to lower variable production costs but similar yields. Soybean gross margin was significantly higher in the organic system (+11%) across the four harvest years compared to the conventional systems. Our results suggest that organic soybean production is a viable option for smallholder farmers under the prevailing semi-arid conditions in India. Future research needs to elucidate the long-term productivity and profitability, particularly of cotton and wheat, and the ecological impact of the different farming systems.

Breeding of a new potato variety 'Nagasaki Kogane' with high eating quality, high carotenoid content, and resistance to diseases and pests.

PubMed

Sakamoto, Yu; Mori, Kazuyuki; Matsuo, Yuuki; Mukojima, Nobuhiro; Watanabe, Wataru; Sobaru, Norio; Tamiya, Seiji; Nakao, Takashi; Hayashi, Kazuya; Watanuki, Hitomi; Nara, Kazuhiro; Yamazaki, Kaoru; Chaya, Masataka

2017-06-01

'Nagasaki Kogane' is a new potato variety bred from a cross between 'Saikai 35' as a female parent and 'Saikai 33' as a male. 'Saikai 35' is resistant to bacterial wilt, contains the H1 and Ry chc genes for resistance to the potato cyst nematode (PCN) and potato virus Y (PVY), respectively, and has high carotenoid content, while 'Saikai 33' has large and high-yielding tubers and is resistant to both bacterial wilt and PCN. The carotenoid content of 'Nagasaki Kogane' is higher than that of 'Dejima', a common double cropping variety. The taste quality of steamed 'Nagasaki Kogane' is comparable to that of 'Inca-no-mezame' tubers, which has high levels of carotenoid, and superior to 'Nishiyutaka', another popular double cropping variety. 'Nagasaki Kogane' is suitable for French fries, because its tuber has high starch content. The marketable yield of 'Nagasaki Kogane' was higher than that of 'Inca-no-mezame' in spring cropping, although it was lower than that of 'Nishiyutaka' in double cropping regions. 'Nagasaki Kogane' tubers are larger on average than 'Inca-no-mezame' tubers in spring cropping. Moreover, the 'Nagasaki Kogane' variety is resistant to PCN and PVY, and exhibits a high level of resistance to bacterial wilt.

Plant tolerance to high temperature in a changing environment: scientific fundamentals and production of heat stress-tolerant crops

PubMed Central

Bita, Craita E.; Gerats, Tom

2013-01-01

Global warming is predicted to have a general negative effect on plant growth due to the damaging effect of high temperatures on plant development. The increasing threat of climatological extremes including very high temperatures might lead to catastrophic loss of crop productivity and result in wide spread famine. In this review, we assess the impact of global climate change on the agricultural crop production. There is a differential effect of climate change both in terms of geographic location and the crops that will likely show the most extreme reductions in yield as a result of expected extreme fluctuations in temperature and global warming in general. High temperature stress has a wide range of effects on plants in terms of physiology, biochemistry and gene regulation pathways. However, strategies exist to crop improvement for heat stress tolerance. In this review, we present recent advances of research on all these levels of investigation and focus on potential leads that may help to understand more fully the mechanisms that make plants tolerant or susceptible to heat stress. Finally, we review possible procedures and methods which could lead to the generation of new varieties with sustainable yield production, in a world likely to be challenged both by increasing population, higher average temperatures and larger temperature fluctuations. PMID:23914193

Soil Water Balance and Water Use Efficiency of Dryland Wheat in Different Precipitation Years in Response to Green Manure Approach

PubMed Central

Zhang, Dabin; Yao, Pengwei; Na, Zhao; Cao, Weidong; Zhang, Suiqi; Li, Yangyang; Gao, Yajun

2016-01-01

Winter wheat (Triticum aestivum L.) monoculture is conventionally cultivated followed by two to three months of summer fallow in the Loess Plateau. To develop a sustainable cropping system, we conducted a six-year field experiment to investigate the effect of leguminous green manure (LGM) instead of bare fallow on the yield and water use efficiency (WUE) of winter wheat and the soil water balance (SWB) in different precipitation years in a semi-arid region of northwest China. Results confirmed that planting LGM crop consumes soil water in the fallow season can bring varied effects to the subsequent wheat. The effect is positive or neutral when the annual precipitation is adequate, so that there is no significant reduction in the soil water supplied to wheat. If this is not the case, the effect is negative. On average, the LGM crop increased wheat yield and WUE by 13% and 28%, respectively, and had considerable potential for maintaining the SWB (0–200 cm) compared with fallow management. In conclusion, cultivation of the LGM crop is a better option than fallow to improve the productivity and WUE of the next crop and maintain the soil water balance in the normal and wet years in the Loess Plateau. PMID:27225842

Plant tolerance to high temperature in a changing environment: scientific fundamentals and production of heat stress-tolerant crops.

PubMed

Bita, Craita E; Gerats, Tom

2013-01-01

Global warming is predicted to have a general negative effect on plant growth due to the damaging effect of high temperatures on plant development. The increasing threat of climatological extremes including very high temperatures might lead to catastrophic loss of crop productivity and result in wide spread famine. In this review, we assess the impact of global climate change on the agricultural crop production. There is a differential effect of climate change both in terms of geographic location and the crops that will likely show the most extreme reductions in yield as a result of expected extreme fluctuations in temperature and global warming in general. High temperature stress has a wide range of effects on plants in terms of physiology, biochemistry and gene regulation pathways. However, strategies exist to crop improvement for heat stress tolerance. In this review, we present recent advances of research on all these levels of investigation and focus on potential leads that may help to understand more fully the mechanisms that make plants tolerant or susceptible to heat stress. Finally, we review possible procedures and methods which could lead to the generation of new varieties with sustainable yield production, in a world likely to be challenged both by increasing population, higher average temperatures and larger temperature fluctuations.

Analysis of climate signals in the crop yield record of sub-Saharan Africa.

PubMed

Hoffman, Alexis L; Kemanian, Armen R; Forest, Chris E

2018-01-01

Food security and agriculture productivity assessments in sub-Saharan Africa (SSA) require a better understanding of how climate and other drivers influence regional crop yields. In this paper, our objective was to identify the climate signal in the realized yields of maize, sorghum, and groundnut in SSA. We explored the relation between crop yields and scale-compatible climate data for the 1962-2014 period using Random Forest, a diagnostic machine learning technique. We found that improved agricultural technology and country fixed effects are three times more important than climate variables for explaining changes in crop yields in SSA. We also found that increasing temperatures reduced yields for all three crops in the temperature range observed in SSA, while precipitation increased yields up to a level roughly matching crop evapotranspiration. Crop yields exhibited both linear and nonlinear responses to temperature and precipitation, respectively. For maize, technology steadily increased yields by about 1% (13 kg/ha) per year while increasing temperatures decreased yields by 0.8% (10 kg/ha) per °C. This study demonstrates that although we should expect increases in future crop yields due to improving technology, the potential yields could be progressively reduced due to warmer and drier climates. © 2017 John Wiley & Sons Ltd.

Usability of NASA Satellite Imagery-Based Daily Solar Radiation for Crop Yield Simulation and Management Decisions

NASA Astrophysics Data System (ADS)

Yang, H.; Cassman, K. G.; Stackhouse, P. W.; Hoell, J. M.

2007-12-01

We tested the usability of NASA satellite imagery-based daily solar radiation for farm-specific crop yield simulation and management decisions using the Hybrid-Maize model (www.hybridmaize.unl.edu). Solar radiation is one of the key inputs for crop yield simulation. Farm-specific crop management decisions using simulation models require long-term (i.e., 20 years or longer) daily local weather data including solar radiation for assessing crop yield potential and its variation, optimizing crop planting date, and predicting crop yield in a real time mode. Weather stations that record daily solar radiation have sparse coverage and many of them have record shorter than 15 years. Based on satellite imagery and other remote sensed information, NASA has provided estimates of daily climatic data including solar radiation at a resolution of 1 degree grid over the earth surface from 1983 to 2005. NASA is currently continuing to update the database and has plans to provide near real-time data in the future. This database, which is free to the public at http://power.larc.nasa.gov, is a potential surrogate for ground- measured climatic data for farm-specific crop yield simulation and management decisions. In this report, we quantified (1) the similarities between NASA daily solar radiation and ground-measured data atr 20 US sites and four international sites, and (2) the accuracy and precision of simulated corn yield potential and its variability using NASA solar radiation coupled with other weather data from ground measurements. The 20 US sites are in the western Corn Belt, including Iowa, South Dakota, Nebraska, and Kansas. The four international sites are Los Banos in the Philippines, Beijing in China, Cali in Columbia, and Ibatan in Nigeria. Those sites were selected because of their high quality weather record and long duration (more than 20 years on average). We found that NASA solar radiation was highly significantly correlated (mean r2 =0.88**) with the ground measurements at the 20 US sites, while the correlation was poor (mean r2=0.55**, though significant) at the four international sites. At the 20 US sites, the mean root mean square error (RMSE) between NASA solar radiation and the ground data was 2.7 MJ/m2/d, or 19% of the mean daily ground data. At the four international sites, the mean RMSE was 4.0 MJ/m2/d, or 25% of the mean daily ground value. Large differences between NASA solar radiation and the ground data were likely associated with tropical environment or significant variation in elevation within a short distance. When using NASA solar radiation coupled with other weather data from ground measurements, the simulated corn yields were highly significantly correlated (mean r2=0.85**) with those using complete ground weather data at the 20 US sites, while the correlation (mean r2=0.48**) was poor at the four international sites. The mean RMSE between the simulated corn yields of the two batches was 0.50 Mg/ha, or 3% of the mean absolute value using the ground data. At the four international sites, the RMSE of the simulated yields was 1.5 Mg/ha, or 13% of the mean absolute value using the ground data. We conclude that the NASA satellite imagery-based daily solar radiation is a reasonably reliable surrogate for the ground observations for farm-specific crop yield simulation and management decisions, especially at locations where ground-measured solar radiation is unavailable.

Performance of Vegetation Indices for Wheat Yield Forecasting for Punjab, Pakistan

NASA Astrophysics Data System (ADS)

Dempewolf, J.; Becker-Reshef, I.; Adusei, B.; Barker, B.

2013-12-01

Forecasting wheat yield in major producer countries early in the growing season allows better planning for harvest deficits and surplus with implications for food security, world market transactions, sustaining adequate grain stocks, policy making and other matters. Remote sensing imagery is well suited for yield forecasting over large areas. The Normalized Difference Vegetation Index (NDVI) has been the most-used spectral index derived from remote sensing imagery for assessing crop condition of major crops and forecasting crop yield. Many authors have found that the highest correlation between NDVI and yield of wheat crops occurs at the height of the growing season when NDVI values and photosynthetic activity of the wheat plants are at their relative maximum. At the same time NDVI saturates in very dense and vigorous (healthy, green) canopies such as wheat fields during the seasonal peak and shows significantly reduced sensitivity to further increases in photosynthetic activity. In this study we compare the performance of different vegetation indices derived from space-borne red and near-infrared spectral reflectance measurements for wheat yield forecasting in the Punjab Province, Pakistan. Areas covered by wheat crop each year were determined using a time series of MODIS 8-day composites at 250 m resolution converted to temporal metrics and classified using a bagged decision tree approach, driven by classified multi-temporal Landsat scenes. Within the wheat areas we analyze and compare wheat yield forecasts derived from three different satellite-based vegetation indices at the peak of the growing season. We regressed in turn NDVI, Wide Dynamic Range Vegetation Index (WDRVI) and the Vegetation Condition Index (VCI) from the four years preceding the wheat growing season 2011/12 against reported yield values and applied the regression equations to forecast wheat yield for the 2011/12 season per district for each of 36 Punjab districts. Yield forecasts overall corresponded well with reported values. NDVI-based forecasts showed high correlations of r squared = 0.881 and RMSE 11%. The VCI performed similarly well with r squared = 0.886 and RMSE 11%. WDRVI performed better than either of the other indices with r squared = 0.909 and RMSE 10%, probably due to the increased sensitivity of the index at high values. Wheat yields in Pakistan show on average a slow but steady annual increase but overall are comparatively stable due to the fact that the majority of fields are irrigated. The next steps in this study will be to compare NDVI- with WDRVI-based yield forecasts in other environments dominated by rain-fed agriculture, such as Ukraine, Australia and the United States.

Increasing Crop Diversity Mitigates Weather Variations and Improves Yield Stability

PubMed Central

Gaudin, Amélie C. M.; Tolhurst, Tor N.; Ker, Alan P.; Janovicek, Ken; Tortora, Cristina; Martin, Ralph C.; Deen, William

2015-01-01

Cropping sequence diversification provides a systems approach to reduce yield variations and improve resilience to multiple environmental stresses. Yield advantages of more diverse crop rotations and their synergistic effects with reduced tillage are well documented, but few studies have quantified the impact of these management practices on yields and their stability when soil moisture is limiting or in excess. Using yield and weather data obtained from a 31-year long term rotation and tillage trial in Ontario, we tested whether crop rotation diversity is associated with greater yield stability when abnormal weather conditions occur. We used parametric and non-parametric approaches to quantify the impact of rotation diversity (monocrop, 2-crops, 3-crops without or with one or two legume cover crops) and tillage (conventional or reduced tillage) on yield probabilities and the benefits of crop diversity under different soil moisture and temperature scenarios. Although the magnitude of rotation benefits varied with crops, weather patterns and tillage, yield stability significantly increased when corn and soybean were integrated into more diverse rotations. Introducing small grains into short corn-soybean rotation was enough to provide substantial benefits on long-term soybean yields and their stability while the effects on corn were mostly associated with the temporal niche provided by small grains for underseeded red clover or alfalfa. Crop diversification strategies increased the probability of harnessing favorable growing conditions while decreasing the risk of crop failure. In hot and dry years, diversification of corn-soybean rotations and reduced tillage increased yield by 7% and 22% for corn and soybean respectively. Given the additional advantages associated with cropping system diversification, such a strategy provides a more comprehensive approach to lowering yield variability and improving the resilience of cropping systems to multiple environmental stresses. This could help to sustain future yield levels in challenging production environments. PMID:25658914

Crop yield responses to a hardwood biochar across varied soils and climate conditions

USDA-ARS?s Scientific Manuscript database

Biochars applied to soil for crop yield improvements have produced mixed results. The assorted crop yield responses may be linked to employing biochars with diverse chemical and physical characteristics. To clarify if biochars can improve crop yields, it may be prudent to evaluate one biochar type...

How does spatial and temporal resolution of vegetation index impact crop yield estimation?

USDA-ARS?s Scientific Manuscript database

Timely and accurate estimation of crop yield before harvest is critical for food market and administrative planning. Remote sensing data have long been used in crop yield estimation for decades. The process-based approach uses light use efficiency model to estimate crop yield. Vegetation index (VI) ...

Crop Yield Predictions - High Resolution Statistical Model for Intra-season Forecasts Applied to Corn in the US

NASA Astrophysics Data System (ADS)

Cai, Y.

2017-12-01

Accurately forecasting crop yields has broad implications for economic trading, food production monitoring, and global food security. However, the variation of environmental variables presents challenges to model yields accurately, especially when the lack of highly accurate measurements creates difficulties in creating models that can succeed across space and time. In 2016, we developed a sequence of machine-learning based models forecasting end-of-season corn yields for the US at both the county and national levels. We combined machine learning algorithms in a hierarchical way, and used an understanding of physiological processes in temporal feature selection, to achieve high precision in our intra-season forecasts, including in very anomalous seasons. During the live run, we predicted the national corn yield within 1.40% of the final USDA number as early as August. In the backtesting of the 2000-2015 period, our model predicts national yield within 2.69% of the actual yield on average already by mid-August. At the county level, our model predicts 77% of the variation in final yield using data through the beginning of August and improves to 80% by the beginning of October, with the percentage of counties predicted within 10% of the average yield increasing from 68% to 73%. Further, the lowest errors are in the most significant producing regions, resulting in very high precision national-level forecasts. In addition, we identify the changes of important variables throughout the season, specifically early-season land surface temperature, and mid-season land surface temperature and vegetation index. For the 2017 season, we feed 2016 data to the training set, together with additional geospatial data sources, aiming to make the current model even more precise. We will show how our 2017 US corn yield forecasts converges in time, which factors affect the yield the most, as well as present our plans for 2018 model adjustments.

Productivity of clay tailings from phosphate mining: 3. Grain crops. [Zea mays; Helianthus annuus; Sorghum bicolor; Glycine max

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mislevy, P.; Blue, W.G.; Roessler, C.E.

A split-fold field experiment was conducted to study forage and grain yield, forage quality, plant nutrient concentrations, changes in soil nutrients, and {sup 226}Ra contents of four grain crops in various rotations. The crop rotations (1) corn (Zea mays L. Jacques 247)-sunflower (Helianthus annuus L. Cargil 205), (2) sunflower-grain sorghum (Sorghum bicolor L, Moench Northrup King Savanna 5), (3) soybean (Glycine max L. Merr. Williams 80)-grain sorghum, and (4) grain sorghum-soybean (University of Florida V-1) were grown on a dry phosphatic clay with and without a 50-mm surface layer of quartz-sand tailings. Results show that corn and grain sorghum producedmore » highest forage yields and highest grain yields per harvest, respectively. Soybean harvested for forage (Crop 1) contained the highest crude protein and in vitro organic matter digestibility. Concentrations of P, K, Ca, Mg, and Fe in most of the forages were adequate for the diets of beef cattle, while those of Mn, Cu and Zn were low. Mehlich I-extractable soil, Ca, and Mg were considered very high and changed little over the 4-yr production period. Application of 50 mm of sand tailings tended to increase Mehlich I-extractable P, Ca, Mn, Cu, Zn, and Fe. Radium-226 concentration in the forage of all grain crops averaged 8.5 Bq kg{sup {minus}1}, which was about 17 times higher than that in the grain of the same crops. Concentrations of {sup 226}Ra in the forage and grain were 1.1% and 0.09% of the concentration in clay respectively. These data indicate that phosphatic clays can be a valuable resource for the production of corn and sorghum grain that contain low concentrations of {sup 226}Ra.« less

Airborne and ground-based remote sensing for the estimation of evapotranspiration and yield of bean, potato, and sugar beet crops

NASA Astrophysics Data System (ADS)

Jayanthi, Harikishan

The focus of this research was two-fold: (1) extend the reflectance-based crop coefficient approach to non-grain (potato and sugar beet), and vegetable crops (bean), and (2) develop vegetation index (VI)-yield statistical models for potato and sugar beet crops using high-resolution aerial multispectral imagery. Extensive crop biophysical sampling (leaf area index and aboveground dry biomass sampling) and canopy reflectance measurements formed the backbone of developing of canopy reflectance-based crop coefficients for bean, potato, and sugar beet crops in this study. Reflectance-based crop coefficient equations were developed for the study crops cultivated in Kimberly, Idaho, and subsequently used in water availability simulations in the plant root zone during 1998 and 1999 seasons. The simulated soil water profiles were compared with independent measurements of actual soil water profiles in the crop root zone in selected fields. It is concluded that the canopy reflectance-based crop coefficient technique can be successfully extended to non-grain crops as well. While the traditional basal crop coefficients generally expect uniform growth in a region the reflectance-based crop coefficients represent the actual crop growth pattern (in less than ideal water availability conditions) in individual fields. Literature on crop canopy interactions with sunlight states that there is a definite correspondence between leaf area index progression in the season and the final yield. In case of crops like potato and sugar beet, the yield is influenced not only on how early and how quickly the crop establishes its canopy but also on how long the plant stands on the ground in a healthy state. The integrated area under the crop growth curve has shown excellent correlations with hand-dug samples of potato and sugar beet crops in this research. Soil adjusted vegetation index-yield models were developed, and validated using multispectral aerial imagery. Estimated yield images were compared with the actual yields extracted from the ground. The remote sensing-derived yields compared well with the actual yields sampled on the ground. This research has highlighted the importance of the date of spectral emergence, the need to know the duration for which the crops stand on the ground, and the need to identify critical periods of time when multispectral coverages are essential for reliable tuber yield estimation.

Land agroecological quality assessment in conditions of high spatial soil cover variability at the Pereslavskoye Opolye.

NASA Astrophysics Data System (ADS)

Morev, Dmitriy; Vasenev, Ivan

2015-04-01

The essential spatial variability is mutual feature for most natural and man-changed soils at the Central region of European territory of Russia. The original spatial heterogeneity of forest soils has been further complicated by a specific land-use history and human impacts. For demand-driven land-use planning and decision making the quantitative analysis and agroecological interpretation of representative soil cover spatial variability is an important and challenging task that receives increasing attention from private companies, governmental and environmental bodies. Pereslavskoye Opolye is traditionally actively used in agriculture due to dominated high-quality cultivated soddy-podzoluvisols which are relatively reached in organic matter (especially for conditions of the North part at the European territory of Russia). However, the soil cover patterns are often very complicated even within the field that significantly influences on crop yield variability and have to be considered in farming system development and land agroecological quality evaluation. The detailed investigations of soil regimes and mapping of the winter rye yield have been carried in conditions of two representative fields with slopes sharply contrasted both in aspects and degrees. Rye biological productivity and weed infestation have been measured in elementary plots of 0.25 m2 with the following analysis the quality of the yield. In the same plot soil temperature and moisture have been measured by portable devices. Soil sampling was provided from three upper layers by drilling. The results of ray yield detailed mapping shown high differences both in average values and within-field variability on different slopes. In case of low-gradient slope (field 1) there is variability of ray yield from 39.4 to 44.8 dt/ha. In case of expressed slope (field 2) the same species of winter rye grown with the same technology has essentially lower yield and within-field variability from 20 to 29.6 dt/ha. The variability in crop yield between two fields is determined by their differences in mesorelief, A-horizon average thickness and slightly changes in soil temperature. The within-field crop yield variability is determined by microrelief and connected differences in soil moisture. Higher soil cover variability reflects in higher variability of winter ray yield and its quality that could be predicted and planed in conditions of concrete field and year according to principal limiting factors evaluation.

26 CFR 1.263A-4 - Rules for property produced in a farming business.

Code of Federal Regulations, 2013 CFR

2013-04-01

... period of plants grown in commercial quantities in the United States is based on the nationwide weighted... plants grown in commercial quantities in the United States, the nationwide weighted average preproductive... crop or yield. The plants are grown in commercial quantities in the United States. Farmer A acquires 1...

26 CFR 1.263A-4 - Rules for property produced in a farming business.

Code of Federal Regulations, 2010 CFR

2010-04-01

... period of plants grown in commercial quantities in the United States is based on the nationwide weighted... plants grown in commercial quantities in the United States, the nationwide weighted average preproductive... crop or yield. The plants are grown in commercial quantities in the United States. Farmer A acquires 1...

26 CFR 1.263A-4 - Rules for property produced in a farming business.

Code of Federal Regulations, 2012 CFR

2012-04-01

... period of plants grown in commercial quantities in the United States is based on the nationwide weighted... plants grown in commercial quantities in the United States, the nationwide weighted average preproductive... crop or yield. The plants are grown in commercial quantities in the United States. Farmer A acquires 1...

26 CFR 1.263A-4 - Rules for property produced in a farming business.

Code of Federal Regulations, 2014 CFR

2014-04-01

... period of plants grown in commercial quantities in the United States is based on the nationwide weighted... plants grown in commercial quantities in the United States, the nationwide weighted average preproductive... crop or yield. The plants are grown in commercial quantities in the United States. Farmer A acquires 1...

26 CFR 1.263A-4 - Rules for property produced in a farming business.

Code of Federal Regulations, 2011 CFR

2011-04-01

... period of plants grown in commercial quantities in the United States is based on the nationwide weighted... plants grown in commercial quantities in the United States, the nationwide weighted average preproductive... crop or yield. The plants are grown in commercial quantities in the United States. Farmer A acquires 1...

High resolution crop growth simulation for identification of potential adaptation strategies under climate change

NASA Astrophysics Data System (ADS)

Kim, K. S.; Yoo, B. H.

2016-12-01

Impact assessment of climate change on crop production would facilitate planning of adaptation strategies. Because socio-environmental conditions would differ by local areas, it would be advantageous to assess potential adaptation measures at a specific area. The objectives of this study was to develop a crop growth simulation system at a very high spatial resolution, e.g., 30 m, and to assess different adaptation options including shift of planting date and use of different cultivars. The Decision Support System for Agrotechnology Transfer (DSSAT) model was used to predict yields of soybean and maize in Korea. Gridded data for climate and soil were used to prepare input data for the DSSAT model. Weather input data were prepared at the resolution of 30 m using bilinear interpolation from gridded climate scenario data. Those climate data were obtained from Korean Meteorology Administration. Spatial resolution of temperature and precipitation was 1 km whereas that of solar radiation was 12.5 km. Soil series data at the 30 m resolution were obtained from the soil database operated by Rural Development Administration, Korea. The SOL file, which is a soil input file for the DSSAT model was prepared using physical and chemical properties of a given soil series, which were available from the soil database. Crop yields were predicted by potential adaptation options based on planting date and cultivar. For example, 10 planting dates and three cultivars were used to identify ideal management options for climate change adaptation. In prediction of maize yield, combination of 20 planting dates and two cultivars was used as management options. Predicted crop yields differed by site even within a relatively small region. For example, the maximum of average yields for 2001-2010 seasons differed by sites In a county of which areas is 520 km2 (Fig. 1). There was also spatial variation in the ideal management option in the region (Fig. 2). These results suggested that local assessment of climate change impact on crop production would be useful for planning adaptation options.

Maize yield gaps caused by non-controllable, agronomic, and socioeconomic factors in a changing climate of Northeast China.

PubMed

Liu, Zhijuan; Yang, Xiaoguang; Lin, Xiaomao; Hubbard, Kenneth G; Lv, Shuo; Wang, Jing

2016-01-15

Closing the gap between current and potential yields is one means of increasing agricultural production to feed the globally increasing population. Therefore, investigation of the geographic patterns, trends and causes of crop yield gaps is essential to identifying where yields might be increased and quantifying the contributions of yield-limiting factors that may provide us potentials to enhance crop productivity. In this study, the changes in potential yields, attainable yields, potential farmers' yields, and actual farmers' yields during the past five decades in Northeast China (NEC) were investigated. Additionally the yield gaps caused by non-controllable, agronomic, and socioeconomic factors were determined. Over the period 1961 to 2010 the estimated regional area-weighted mean maize potential yield, attainable yield, and potential farmers' yield were approximately 12.3 t ha(-1), 11.5 t ha(-1), and 6.4 t ha(-1) which showed a decreasing tendency. The actual farmers' yield over NEC was 4.5 t ha(-1), and showed a tendency to increase (p<0.01) by 1.27 t ha(-1) per decade. The regional mean total yield gap (YGt), weighted by the area in each county dedicated to maize crop, was 64% of potential yield. Moreover, 8, 40, and 16% reductions in potential yields were due to non-controllable factors (YGI), agronomic factors (YGII), and socioeconomic factors (YGIII), respectively. Therefore, the exploitable yield gap, considered here as the difference between the potential yield and what one can expect considering non-controllable factors (i.e. YGt-YGI), of maize in NEC was about 56%. The regional area-weighted averages of YGt, and YGIII were found to have significant decreases of 11.0, and 10.7% per decade. At the time horizon 2010, the exploitable yield gaps were estimated to equal 36% of potential yield. This led to the conclusion that the yield gap could be deeply reduced by improving local agronomic management and controlling socioeconomic factors. Copyright © 2015 Elsevier B.V. All rights reserved.

[Carbon footprints of major staple grain crops production in three provinces of Northeast China during 2004-2013.

PubMed

Huang, Xiao Min; Chen, Chang Qing; Chen, Ming Zhou; Song, Zhen Wei; Deng, Ai Xing; Zhang, Jun; Zheng, Cheng Yan; Zhang, Wei Jian

2016-10-01

Northeast China is one of the most important farming regions in China, due to its great contribution to national food security. Crop production is a main source of carbon emission. To assess the differences in carbon footprints of major grain crop production will benefit the achievement of low carbon agriculture. Therefore, this study calculated the regional carbon foot prints of rice (Oryza sativa), maize (Zea mays) and soybean (Glycine max) production in Northeast China du-ring 2004-2013 using the provincial statistical data, including crop yield, sown area and production inputs. The results showed that the highest area-scale carbon footprint was found in rice production, with the average value of (2463±56) kg CE·hm -2 , while the second was found in maize production during 2004-2013. The sharpest rise occurred in maize production, from 1164 kg CE·hm -2 in 2004 to 1768 kg CE·hm -2 in 2013, with the average rate of 67 kg CE·hm -2 ·a -1 . The application of chemical fertilizer contributed to the carbon footprint largely, accounting for 45%, 90% and 83% for rice, maize and soybean, respectively. Moreover, the contribution of electricity for irrigation in rice production ranged from 29% to 42%, which was larger than that in maize and soybean production. The carbon footprints were significantly different among the three provinces of Northeast China. The highest yield-scaled carbon footprints for three crops were found in Jilin Province, while the lowest area-scaled carbon footprints found in Heilongjiang Province. Given to the large transfer of rural labor from agricultural to non-agricultural sections and the development of mechanization, diesel and other mechanical inputs would increase rapidly in the future. Therefore, improving ferti-lizer utilization, mechanical and irrigation efficiencies in crop production would be the main approaches to promoting low-carbon agriculture in Northeast China.

Evaluating the applicability of using daily forecasts from seasonal prediction systems (SPSs) for agriculture: a case study of Nepal's Terai with the NCEP CFSv2

NASA Astrophysics Data System (ADS)

Jha, Prakash K.; Athanasiadis, Panos; Gualdi, Silvio; Trabucco, Antonio; Mereu, Valentina; Shelia, Vakhtang; Hoogenboom, Gerrit

2018-03-01

Ensemble forecasts from dynamic seasonal prediction systems (SPSs) have the potential to improve decision-making for crop management to help cope with interannual weather variability. Because the reliability of crop yield predictions based on seasonal weather forecasts depends on the quality of the forecasts, it is essential to evaluate forecasts prior to agricultural applications. This study analyses the potential of Climate Forecast System version 2 (CFSv2) in predicting the Indian summer monsoon (ISM) for producing meteorological variables relevant to crop modeling. The focus area was Nepal's Terai region, and the local hindcasts were compared with weather station and reanalysis data. The results showed that the CFSv2 model accurately predicts monthly anomalies of daily maximum and minimum air temperature (Tmax and Tmin) as well as incoming total surface solar radiation (Srad). However, the daily climatologies of the respective CFSv2 hindcasts exhibit significant systematic biases compared to weather station data. The CFSv2 is less capable of predicting monthly precipitation anomalies and simulating the respective intra-seasonal variability over the growing season. Nevertheless, the observed daily climatologies of precipitation fall within the ensemble spread of the respective daily climatologies of CFSv2 hindcasts. These limitations in the CFSv2 seasonal forecasts, primarily in precipitation, restrict the potential application for predicting the interannual variability of crop yield associated with weather variability. Despite these limitations, ensemble averaging of the simulated yield using all CFSv2 members after applying bias correction may lead to satisfactory yield predictions.

Assessment of climate change impact on yield of major crops in the Banas River Basin, India.

PubMed

Dubey, Swatantra Kumar; Sharma, Devesh

2018-09-01

Crop growth models like AquaCrop are useful in understanding the impact of climate change on crop production considering the various projections from global circulation models and regional climate models. The present study aims to assess the climate change impact on yield of major crops in the Banas River Basin i.e., wheat, barley and maize. Banas basin is part of the semi-arid region of Rajasthan state in India. AquaCrop model is used to calculate the yield of all the three crops for a historical period of 30years (1981-2010) and then compared with observed yield data. Root Mean Square Error (RMSE) values are calculated to assess the model accuracy in prediction of yield. Further, the calibrated model is used to predict the possible impacts of climate change and CO 2 concentration on crop yield using CORDEX-SA climate projections of three driving climate models (CNRM-CM5, CCSM4 and MPI-ESM-LR) for two different scenarios (RCP4.5 and RCP8.5) for the future period 2021-2050. RMSE values of simulated yield with respect to observed yield of wheat, barley and maize are 11.99, 16.15 and 19.13, respectively. It is predicted that crop yield of all three crops will increase under the climate change conditions for future period (2021-2050). Copyright © 2018 Elsevier B.V. All rights reserved.

Development of estimation method for crop yield using MODIS satellite imagery data and process-based model for corn and soybean in US Corn-Belt region

NASA Astrophysics Data System (ADS)

Lee, J.; Kang, S.; Jang, K.; Ko, J.; Hong, S.

2012-12-01

Crop productivity is associated with the food security and hence, several models have been developed to estimate crop yield by combining remote sensing data with carbon cycle processes. In present study, we attempted to estimate crop GPP and NPP using algorithm based on the LUE model and a simplified respiration model. The state of Iowa and Illinois was chosen as the study site for estimating the crop yield for a period covering the 5 years (2006-2010), as it is the main Corn-Belt area in US. Present study focuses on developing crop-specific parameters for corn and soybean to estimate crop productivity and yield mapping using satellite remote sensing data. We utilized a 10 km spatial resolution daily meteorological data from WRF to provide cloudy-day meteorological variables but in clear-say days, MODIS-based meteorological data were utilized to estimate daily GPP, NPP, and biomass. County-level statistics on yield, area harvested, and productions were used to test model predicted crop yield. The estimated input meteorological variables from MODIS and WRF showed with good agreements with the ground observations from 6 Ameriflux tower sites in 2006. For examples, correlation coefficients ranged from 0.93 to 0.98 for Tmin and Tavg ; from 0.68 to 0.85 for daytime mean VPD; from 0.85 to 0.96 for daily shortwave radiation, respectively. We developed county-specific crop conversion coefficient, i.e. ratio of yield to biomass on 260 DOY and then, validated the estimated county-level crop yield with the statistical yield data. The estimated corn and soybean yields at the county level ranged from 671 gm-2 y-1 to 1393 gm-2 y-1 and from 213 gm-2 y-1 to 421 gm-2 y-1, respectively. The county-specific yield estimation mostly showed errors less than 10%. Furthermore, we estimated crop yields at the state level which were validated against the statistics data and showed errors less than 1%. Further analysis for crop conversion coefficient was conducted for 200 DOY and 280 DOY. For the case of 280 DOY, Crop yield estimation showed better accuracy for soybean at county level. Though the case of 200 DOY resulted in less accuracy (i.e. 20% mean bias), it provides a useful tool for early forecasting of crop yield. We improved the spatial accuracy of estimated crop yield at county level by developing county-specific crop conversion coefficient. Our results indicate that the aboveground crop biomass can be estimated successfully with the simple LUE and respiration models combined with MODIS data and then, county-specific conversion coefficient can be different with each other across different counties. Hence, applying region-specific conversion coefficient is necessary to estimate crop yield with better accuracy.

The Space-Time Variation of Global Crop Yields, Detecting Simultaneous Outliers and Identifying the Teleconnections with Climatic Patterns

NASA Astrophysics Data System (ADS)

Najafi, E.; Devineni, N.; Pal, I.; Khanbilvardi, R.

2017-12-01

An understanding of the climate factors that influence the space-time variability of crop yields is important for food security purposes and can help us predict global food availability. In this study, we address how the crop yield trends of countries globally were related to each other during the last several decades and the main climatic variables that triggered high/low crop yields simultaneously across the world. Robust Principal Component Analysis (rPCA) is used to identify the primary modes of variation in wheat, maize, sorghum, rice, soybeans, and barley yields. Relations between these modes of variability and important climatic variables, especially anomalous sea surface temperature (SSTa), are examined from 1964 to 2010. rPCA is also used to identify simultaneous outliers in each year, i.e. systematic high/low crop yields across the globe. The results demonstrated spatiotemporal patterns of these crop yields and the climate-related events that caused them as well as the connection of outliers with weather extremes. We find that among climatic variables, SST has had the most impact on creating simultaneous crop yields variability and yield outliers in many countries. An understanding of this phenomenon can benefit global crop trade networks.

Evaluating high temporal and spatial resolution vegetation index for crop yield prediction

USDA-ARS?s Scientific Manuscript database

Remote sensing data have been widely used in estimating crop yield. Remote sensing derived parameters such as Vegetation Index (VI) were used either directly in building empirical models or by assimilating with crop growth models to predict crop yield. The abilities of remote sensing VI in crop yiel...

Bioenergy Sorghum Crop Model Predicts VPD-Limited Transpiration Traits Enhance Biomass Yield in Water-Limited Environments

PubMed Central

Truong, Sandra K.; McCormick, Ryan F.; Mullet, John E.

2017-01-01

Bioenergy sorghum is targeted for production in water-limited annual cropland therefore traits that improve plant water capture, water use efficiency, and resilience to water deficit are necessary to maximize productivity. A crop modeling framework, APSIM, was adapted to predict the growth and biomass yield of energy sorghum and to identify potentially useful traits for crop improvement. APSIM simulations of energy sorghum development and biomass accumulation replicated results from field experiments across multiple years, patterns of rainfall, and irrigation schemes. Modeling showed that energy sorghum's long duration of vegetative growth increased water capture and biomass yield by ~30% compared to short season crops in a water-limited production region. Additionally, APSIM was extended to enable modeling of VPD-limited transpiration traits that reduce crop water use under high vapor pressure deficits (VPDs). The response of transpiration rate to increasing VPD was modeled as a linear response until a VPD threshold was reached, at which the slope of the response decreases, representing a range of responses to VPD observed in sorghum germplasm. Simulation results indicated that the VPD-limited transpiration trait is most beneficial in hot and dry regions of production where crops are exposed to extended periods without rainfall during the season or to a terminal drought. In these environments, slower but more efficient transpiration increases biomass yield and prevents or delays the exhaustion of soil water and onset of leaf senescence. The VPD-limited transpiration responses observed in sorghum germplasm increased biomass accumulation by 20% in years with lower summer rainfall, and the ability to drastically reduce transpiration under high VPD conditions could increase biomass by 6% on average across all years. This work indicates that the productivity and resilience of bioenergy sorghum grown in water-limited environments could be further enhanced by development of genotypes with optimized VPD-limited transpiration traits and deployment of these crops in water limited growing environments. The energy sorghum model and VPD-limited transpiration trait implementation are made available to simulate performance in other target environments. PMID:28377779

Bioenergy Sorghum Crop Model Predicts VPD-Limited Transpiration Traits Enhance Biomass Yield in Water-Limited Environments.

PubMed

Truong, Sandra K; McCormick, Ryan F; Mullet, John E

2017-01-01

Bioenergy sorghum is targeted for production in water-limited annual cropland therefore traits that improve plant water capture, water use efficiency, and resilience to water deficit are necessary to maximize productivity. A crop modeling framework, APSIM, was adapted to predict the growth and biomass yield of energy sorghum and to identify potentially useful traits for crop improvement. APSIM simulations of energy sorghum development and biomass accumulation replicated results from field experiments across multiple years, patterns of rainfall, and irrigation schemes. Modeling showed that energy sorghum's long duration of vegetative growth increased water capture and biomass yield by ~30% compared to short season crops in a water-limited production region. Additionally, APSIM was extended to enable modeling of VPD-limited transpiration traits that reduce crop water use under high vapor pressure deficits (VPDs). The response of transpiration rate to increasing VPD was modeled as a linear response until a VPD threshold was reached, at which the slope of the response decreases, representing a range of responses to VPD observed in sorghum germplasm. Simulation results indicated that the VPD-limited transpiration trait is most beneficial in hot and dry regions of production where crops are exposed to extended periods without rainfall during the season or to a terminal drought. In these environments, slower but more efficient transpiration increases biomass yield and prevents or delays the exhaustion of soil water and onset of leaf senescence. The VPD-limited transpiration responses observed in sorghum germplasm increased biomass accumulation by 20% in years with lower summer rainfall, and the ability to drastically reduce transpiration under high VPD conditions could increase biomass by 6% on average across all years. This work indicates that the productivity and resilience of bioenergy sorghum grown in water-limited environments could be further enhanced by development of genotypes with optimized VPD-limited transpiration traits and deployment of these crops in water limited growing environments. The energy sorghum model and VPD-limited transpiration trait implementation are made available to simulate performance in other target environments.

Bioenergy sorghum crop model predicts VPD-limited transpiration traits enhance biomass yield in water-limited environments

DOE PAGES

Truong, Sandra K.; McCormick, Ryan F.; Mullet, John E.

2017-03-21

Bioenergy sorghum is targeted for production in water-limited annual cropland therefore traits that improve plant water capture, water use efficiency, and resilience to water deficit are necessary to maximize productivity. A crop modeling framework, APSIM, was adapted to predict the growth and biomass yield of energy sorghum and to identify potentially useful traits for crop improvement. APSIM simulations of energy sorghum development and biomass accumulation replicated results from field experiments across multiple years, patterns of rainfall, and irrigation schemes. Modeling showed that energy sorghum’s long duration of vegetative growth increased water capture and biomass yield by ~30% compared to shortmore » season crops in a water-limited production region. Additionally, APSIM was extended to enable modeling of VPD-limited transpiration traits that reduce crop water use under high vapor pressure deficits (VPDs). The response of transpiration rate to increasing VPD was modeled as a linear response until a VPD threshold was reached, at which the slope of the response decreases, representing a range of responses to VPD observed in sorghum germplasm. Simulation results indicated that the VPD-limited transpiration trait is most beneficial in hot and dry regions of production where crops are exposed to extended periods without rainfall during the season or to a terminal drought. In these environments, slower but more efficient transpiration increases biomass yield and prevents or delays the exhaustion of soil water and onset of leaf senescence. The VPD-limited transpiration responses observed in sorghum germplasm increased biomass accumulation by 20% in years with lower summer rainfall, and the ability to drastically reduce transpiration under high VPD conditions could increase biomass by 6% on average across all years. This work indicates that the productivity and resilience of bioenergy sorghum grown in water-limited environments could be further enhanced by development of genotypes with optimized VPD-limited transpiration traits and deployment of these crops in water limited growing environments. As a result, the energy sorghum model and VPD-limited transpiration trait implementation aremade available to simulate performance in other target environments.« less

Bioenergy sorghum crop model predicts VPD-limited transpiration traits enhance biomass yield in water-limited environments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Truong, Sandra K.; McCormick, Ryan F.; Mullet, John E.

Bioenergy sorghum is targeted for production in water-limited annual cropland therefore traits that improve plant water capture, water use efficiency, and resilience to water deficit are necessary to maximize productivity. A crop modeling framework, APSIM, was adapted to predict the growth and biomass yield of energy sorghum and to identify potentially useful traits for crop improvement. APSIM simulations of energy sorghum development and biomass accumulation replicated results from field experiments across multiple years, patterns of rainfall, and irrigation schemes. Modeling showed that energy sorghum’s long duration of vegetative growth increased water capture and biomass yield by ~30% compared to shortmore » season crops in a water-limited production region. Additionally, APSIM was extended to enable modeling of VPD-limited transpiration traits that reduce crop water use under high vapor pressure deficits (VPDs). The response of transpiration rate to increasing VPD was modeled as a linear response until a VPD threshold was reached, at which the slope of the response decreases, representing a range of responses to VPD observed in sorghum germplasm. Simulation results indicated that the VPD-limited transpiration trait is most beneficial in hot and dry regions of production where crops are exposed to extended periods without rainfall during the season or to a terminal drought. In these environments, slower but more efficient transpiration increases biomass yield and prevents or delays the exhaustion of soil water and onset of leaf senescence. The VPD-limited transpiration responses observed in sorghum germplasm increased biomass accumulation by 20% in years with lower summer rainfall, and the ability to drastically reduce transpiration under high VPD conditions could increase biomass by 6% on average across all years. This work indicates that the productivity and resilience of bioenergy sorghum grown in water-limited environments could be further enhanced by development of genotypes with optimized VPD-limited transpiration traits and deployment of these crops in water limited growing environments. As a result, the energy sorghum model and VPD-limited transpiration trait implementation aremade available to simulate performance in other target environments.« less

Field warming experiments shed light on the wheat yield response to temperature in China

PubMed Central

Zhao, Chuang; Piao, Shilong; Huang, Yao; Wang, Xuhui; Ciais, Philippe; Huang, Mengtian; Zeng, Zhenzhong; Peng, Shushi

2016-01-01

Wheat growth is sensitive to temperature, but the effect of future warming on yield is uncertain. Here, focusing on China, we compiled 46 observations of the sensitivity of wheat yield to temperature change (SY,T, yield change per °C) from field warming experiments and 102 SY,T estimates from local process-based and statistical models. The average SY,T from field warming experiments, local process-based models and statistical models is −0.7±7.8(±s.d.)% per °C, −5.7±6.5% per °C and 0.4±4.4% per °C, respectively. Moreover, SY,T is different across regions and warming experiments indicate positive SY,T values in regions where growing-season mean temperature is low, and water supply is not limiting, and negative values elsewhere. Gridded crop model simulations from the Inter-Sectoral Impact Model Intercomparison Project appear to capture the spatial pattern of SY,T deduced from warming observations. These results from local manipulative experiments could be used to improve crop models in the future. PMID:27853151

Using Satellite Data to Unpack Causes of Yield Gaps in India's Wheat Belt

NASA Astrophysics Data System (ADS)

Jain, M.; Singh, B.; Srivastava, A.; Malik, R. K.; McDonald, A.; Lobell, D. B.

2016-12-01

India will face significant food security challenges in the coming decades due to climate change, natural resource degradation, and population growth. Yields of wheat, one of India's staple crops, are already stagnating and will be significantly impacted by warming temperatures. Despite these challenges, wheat yields can be enhanced by implementing improved management in regions with existing yield gaps. To identify the magnitude and causes of current yield gaps, we produced 30 m resolution yield maps across India's main wheat belt, the Indo-Gangetic Plains (IGP), from 2000 to 2015. Yield maps were derived using a new method that translates satellite vegetation indices to yield estimates using crop model simulations, bypassing the need for ground calibration data that rarely exist in smallholder systems. We find that yields can be increased by 5% on average and up to 16% in the eastern IGP by improving management to current best practices within a given district. However, if policies and technologies are put in place to improve management to current best practices in Punjab, the highest yielding state, yields can be increased by 29% in the eastern IGP. Considering which factors most influence wheat yields, we find that later sow dates and warmer temperatures are most associated with low yields across the IGP. This suggests that strategies that reduce the negative effects of heat stress, like earlier sowing and planting heat-tolerant wheat varieties, are critical to India's current and future food security.

Impacts of ridge-furrow rainfall concentration systems and mulches on corn growth and yield in the semiarid region of China.

PubMed

Ren, Xiao-Long; Zhang, Peng; Chen, Xiao-Li; Jia, Zhi-Kuan

2016-08-01

Plastic-covered ridge-furrow farming systems for rainfall concentration (RC) improve the water availability for crops and increase the water use efficiency (WUE), thereby stabilizing high yields. In this study, we optimized the mulching patterns for RC planting to mitigate the risks of drought during crop production in semiarid agricultural areas. We conducted a 4-year field study to determine the RC effects on corn production of mulching in furrows with 8% biodegradable films (RCSB ), liquid film (RCSL ), bare furrow (RCSN ) and conventional flat (CF) farming. We found that RC significantly (P > 0.05) increased the soil moisture in the top 0-100 cm layer and the topsoil temperature (0-20 cm) during the corn-growing period. Mulching with different materials in planting furrows further improved the rain-harvesting, moisture-retaining and yield-increasing effects of RC planting. Compared with CF, the 4-year average total dry matter amount per plant for RCSB , RCSL and RCSN treatments increased by 42.1%, 30.8% and 17.2%, respectively. The grain yield increased by 59.7%, 53.4% and 32.6%, respectively. Plastic-covered ridge and furrow mulched with biodegradable film and liquid film is recommended for use in the semiarid Loess Plateau of China to alleviate the effects of drought on crop production. © 2015 Society of Chemical Industry. © 2015 Society of Chemical Industry.

Progress and Challenges in Predicting Crop Responses to Atmospheric [CO2

NASA Astrophysics Data System (ADS)

Kent, J.; Paustian, K.

2017-12-01

Increasing atmospheric [CO2] directly accelerates photosynthesis in C3 crops, and indirectly promotes yields by reducing stomatal conductance and associated water losses in C3 and C4 crops. Several decades of experiments have exposed crops to eCO2 in greenhouses and other enclosures and observed yield increases on the order of 33%. FACE systems were developed in the early 1990s to better replicate open-field growing conditions. Some authors contend that FACE results indicate lower crop yield responses than enclosure studies, while others maintain no significant difference or attribute differences to various methodological factors. The crop CO2 response processes in many crop models were developed using results from enclosure experiments. This work tested the ability of one such model, DayCent, to reproduce crop responses to CO2 enrichment from several FACE experiments. DayCent performed well at simulating yield and transpiration responses in C4 crops, but significantly overestimated yield responses in C3 crops. After adjustment of CO2-response parameters, DayCent was able to reproduce mean yield responses for specific crops. However, crop yield responses from FACE experiments vary widely across years and sites, and likely reflect complex interactions between conditions such as weather, soils, cultivars, and biotic stressors. Further experimental work is needed to identify the secondary variables that explain this variability so that models can more reliably forecast crop yields under climate change. Likewise, CO2 impacts on crop outcomes such as belowground biomass allocation and grain N content have implications for agricultural C fluxes and human nutrition, respectively, but are poorly understood and thus difficult to simulate with confidence.

Climate Change and ENSO Effects on Southeastern US Climate Patterns and Maize Yield.

PubMed

Mourtzinis, Spyridon; Ortiz, Brenda V; Damianidis, Damianos

2016-07-19

Climate change has a strong influence on weather patterns and significantly affects crop yields globally. El Niño Southern Oscillation (ENSO) has a strong influence on the U.S. climate and is related to agricultural production variability. ENSO effects are location-specific and in southeastern U.S. strongly connect with climate variability. When combined with climate change, the effects on growing season climate patterns and crop yields might be greater than expected. In our study, historical monthly precipitation and temperature data were coupled with non-irrigated maize yield data (33-43 years depending on the location) to show a potential yield suppression of ~15% for one °C increase in southeastern U.S. growing season maximum temperature. Yield suppression ranged between -25 and -2% among locations suppressing the southeastern U.S. average yield trend since 1981 by 17 kg ha(-1)year(-1) (~25%), mainly due to year-to-year June temperature anomalies. Yields varied among ENSO phases from 1971-2013, with greater yields observed during El Niño phase. During La Niña years, maximum June temperatures were higher than Neutral and El Niño, whereas June precipitation was lower than El Niño years. Our data highlight the importance of developing location-specific adaptation strategies quantifying both, climate change and ENSO effects on month-specific growing season climate conditions.

Drought-related vulnerability and risk assessment of groundwater in Belgium: estimation of the groundwater recharge and crop yield vulnerability with the B-CGMS

NASA Astrophysics Data System (ADS)

Jacquemin, Ingrid; Verbeiren, Boud; Vanderhaegen, Sven; Canters, Frank; Vermeiren, Karolien; Engelen, Guy; Huysmans, Marijke; Batelaan, Okke; Tychon, Bernard

2016-04-01

Due to common belief that regions under temperate climate are not affected by (meteorological and groundwater) drought, these events and their impacts remain poorly studied: in the GroWaDRISK, we propose to take stock of this question. We aim at providing a better understanding of the influencing factors (land use and land cover changes, water demand and climate) and the drought-related impacts on the environment, water supply and agriculture. The study area is located in the North-East of Belgium, corresponding approximatively to the Dijle and Demer catchments. To establish an overview of the groundwater situation, we assess the system input: the recharge. To achieve this goal, two models, B-CGMS and WetSpass are used to evaluate the recharge, respectively, over agricultural land and over the remaining areas, as a function of climate and for various land uses and land covers. B-CGMS, which is an adapted version for Belgium of the European Crop Growth Monitoring System, is used for assessing water recharge at a daily timestep and under different agricultural lands: arable land (winter wheat, maize...), orchards, horticulture and floriculture and for grassland. B-CGMS is designed to foresee crop yield and obviously it studies the impact of drought on crop yield and raises issues for the potential need of irrigation. For both yields and water requirements, the model proposes a potential mode, driven by temperature and solar radiation, and a water-limited mode for which water availability can limit crop growth. By this way, we can identify where and when water consumption and yield are not optimal, in addition to the Crop Water Stress Index. This index is calculated for a given crop, as the number of days affected by water stress during the growth sensitive period. Both recharge and crop yield are assessed for the current situation (1980 - 2012), taking into account the changing land use/land cover, in terms of areas and localization of the agricultural land and where the proportion of the different crops had considerably evolved through time (e.g., increase of grain maize and potatoes while winter cereals decrease). The preliminary results of the recharge lead to an average value in the area showing a significant negative trend, in both simulations with fixed (base = 1980) and changing land cover. In the same time, we could observe an increasing number of water stress periods, especially for maize, one of the main crops in the area. Finally, a preliminary test will be presented for the horizon 2040, for which we use meteorological time series (for high and low hydrologic impacts) given by the CCI-HYDR Perturbation Tool (Ntegeka V. and Willems P., 2009). This preliminary test aims to (1) evaluate the amplitude of the potential recharge deficit and, (2) especially, to define vulnerability zones, affected by frequent water stress, in connection with irrigation needs which could possibly increase the groundwater extraction.

Global growth and stability of agricultural yield decrease with pollinator dependence

PubMed Central

Garibaldi, Lucas A.; Aizen, Marcelo A.; Klein, Alexandra M.; Cunningham, Saul A.; Harder, Lawrence D.

2011-01-01

Human welfare depends on the amount and stability of agricultural production, as determined by crop yield and cultivated area. Yield increases asymptotically with the resources provided by farmers’ inputs and environmentally sensitive ecosystem services. Declining yield growth with increased inputs prompts conversion of more land to cultivation, but at the risk of eroding ecosystem services. To explore the interdependence of agricultural production and its stability on ecosystem services, we present and test a general graphical model, based on Jensen's inequality, of yield–resource relations and consider implications for land conversion. For the case of animal pollination as a resource influencing crop yield, this model predicts that incomplete and variable pollen delivery reduces yield mean and stability (inverse of variability) more for crops with greater dependence on pollinators. Data collected by the Food and Agriculture Organization of the United Nations during 1961–2008 support these predictions. Specifically, crops with greater pollinator dependence had lower mean and stability in relative yield and yield growth, despite global yield increases for most crops. Lower yield growth was compensated by increased land cultivation to enhance production of pollinator-dependent crops. Area stability also decreased with pollinator dependence, as it correlated positively with yield stability among crops. These results reveal that pollen limitation hinders yield growth of pollinator-dependent crops, decreasing temporal stability of global agricultural production, while promoting compensatory land conversion to agriculture. Although we examined crop pollination, our model applies to other ecosystem services for which the benefits to human welfare decelerate as the maximum is approached. PMID:21422295

Estimating the impact of mineral aerosols on crop yields in food insecure regions using statistical crop models

NASA Astrophysics Data System (ADS)

Hoffman, A.; Forest, C. E.; Kemanian, A.

2016-12-01

A significant number of food-insecure nations exist in regions of the world where dust plays a large role in the climate system. While the impacts of common climate variables (e.g. temperature, precipitation, ozone, and carbon dioxide) on crop yields are relatively well understood, the impact of mineral aerosols on yields have not yet been thoroughly investigated. This research aims to develop the data and tools to progress our understanding of mineral aerosol impacts on crop yields. Suspended dust affects crop yields by altering the amount and type of radiation reaching the plant, modifying local temperature and precipitation. While dust events (i.e. dust storms) affect crop yields by depleting the soil of nutrients or by defoliation via particle abrasion. The impact of dust on yields is modeled statistically because we are uncertain which impacts will dominate the response on national and regional scales considered in this study. Multiple linear regression is used in a number of large-scale statistical crop modeling studies to estimate yield responses to various climate variables. In alignment with previous work, we develop linear crop models, but build upon this simple method of regression with machine-learning techniques (e.g. random forests) to identify important statistical predictors and isolate how dust affects yields on the scales of interest. To perform this analysis, we develop a crop-climate dataset for maize, soybean, groundnut, sorghum, rice, and wheat for the regions of West Africa, East Africa, South Africa, and the Sahel. Random forest regression models consistently model historic crop yields better than the linear models. In several instances, the random forest models accurately capture the temperature and precipitation threshold behavior in crops. Additionally, improving agricultural technology has caused a well-documented positive trend that dominates time series of global and regional yields. This trend is often removed before regression with traditional crop models, but likely at the cost of removing climate information. Our random forest models consistently discover the positive trend without removing any additional data. The application of random forests as a statistical crop model provides insight into understanding the impact of dust on yields in marginal food producing regions.

Growing sensitivity of maize to water scarcity under climate change.

PubMed

Meng, Qingfeng; Chen, Xinping; Lobell, David B; Cui, Zhenling; Zhang, Yi; Yang, Haishun; Zhang, Fusuo

2016-01-25

Climate change can reduce crop yields and thereby threaten food security. The current measures used to adapt to climate change involve avoiding crops yield decrease, however, the limitations of such measures due to water and other resources scarcity have not been well understood. Here, we quantify how the sensitivity of maize to water availability has increased because of the shift toward longer-maturing varieties during last three decades in the Chinese Maize Belt (CMB). We report that modern, longer-maturing varieties have extended the growing period by an average of 8 days and have significantly offset the negative impacts of climate change on yield. However, the sensitivity of maize production to water has increased: maize yield across the CMB was 5% lower with rainfed than with irrigated maize in the 1980s and was 10% lower (and even >20% lower in some areas) in the 2000s because of both warming and the increased requirement for water by the longer-maturing varieties. Of the maize area in China, 40% now fails to receive the precipitation required to attain the full yield potential. Opportunities for water saving in maize systems exist, but water scarcity in China remains a serious problem.

Is current irrigation sustainable in the United States? An integrated assessment of climate change impact on water resources and irrigated crop yields

NASA Astrophysics Data System (ADS)

Blanc, Elodie; Caron, Justin; Fant, Charles; Monier, Erwan

2017-08-01

While climate change impacts on crop yields has been extensively studied, estimating the impact of water shortages on irrigated crop yields is challenging because the water resources management system is complex. To investigate this issue, we integrate a crop yield reduction module and a water resources model into the MIT Integrated Global System Modeling framework, an integrated assessment model linking a global economic model to an Earth system model. We assess the effects of climate and socioeconomic changes on water availability for irrigation in the U.S. as well as subsequent impacts on crop yields by 2050, while accounting for climate change projection uncertainty. We find that climate and socioeconomic changes will increase water shortages and strongly reduce irrigated yields for specific crops (i.e., cotton and forage), or in specific regions (i.e., the Southwest) where irrigation is not sustainable. Crop modeling studies that do not represent changes in irrigation availability can thus be misleading. Yet, since the most water-stressed basins represent a relatively small share of U.S. irrigated areas, the overall reduction in U.S. crop yields is small. The response of crop yields to climate change and water stress also suggests that some level of adaptation will be feasible, like relocating croplands to regions with sustainable irrigation or switching to less irrigation intensive crops. Finally, additional simulations show that greenhouse gas (GHG) mitigation can alleviate the effect of water stress on irrigated crop yields, enough to offset the reduced CO2 fertilization effect compared to an unconstrained GHG emission scenario.

Is current irrigation sustainable in the United States? An integrated assessment of climate change impact on water resources and irrigated crop yields.

PubMed

Blanc, Elodie; Caron, Justin; Fant, Charles; Monier, Erwan

2017-08-01

While climate change impacts on crop yields has been extensively studied, estimating the impact of water shortages on irrigated crop yields is challenging because the water resources management system is complex. To investigate this issue, we integrate a crop yield reduction module and a water resources model into the MIT Integrated Global System Modeling framework, an integrated assessment model linking a global economic model to an Earth system model. We assess the effects of climate and socioeconomic changes on water availability for irrigation in the U.S. as well as subsequent impacts on crop yields by 2050, while accounting for climate change projection uncertainty. We find that climate and socioeconomic changes will increase water shortages and strongly reduce irrigated yields for specific crops (i.e., cotton and forage), or in specific regions (i.e., the Southwest) where irrigation is not sustainable. Crop modeling studies that do not represent changes in irrigation availability can thus be misleading. Yet, since the most water-stressed basins represent a relatively small share of U.S. irrigated areas, the overall reduction in U.S. crop yields is small. The response of crop yields to climate change and water stress also suggests that some level of adaptation will be feasible, like relocating croplands to regions with sustainable irrigation or switching to less irrigation intensive crops. Finally, additional simulations show that greenhouse gas (GHG) mitigation can alleviate the effect of water stress on irrigated crop yields, enough to offset the reduced CO 2 fertilization effect compared to an unconstrained GHG emission scenario.

Assessing gaps in irrigated agricultural productivity through satellite earth observations-A case study of the Fergana Valley, Central Asia

NASA Astrophysics Data System (ADS)

Löw, Fabian; Biradar, Chandrashekhar; Fliemann, Elisabeth; Lamers, John P. A.; Conrad, Christopher

2017-07-01

Improving crop area and/or crop yields in agricultural regions is one of the foremost scientific challenges for the next decades. This is especially true in irrigated areas because sustainable intensification of irrigated crop production is virtually the sole means to enhance food supply and contribute to meeting food demands of a growing population. Yet, irrigated crop production worldwide is suffering from soil degradation and salinity, reduced soil fertility, and water scarcity rendering the performance of irrigation schemes often below potential. On the other hand, the scope for improving irrigated agricultural productivity remains obscure also due to the lack of spatial data on agricultural production (e.g. crop acreage and yield). To fill this gap, satellite earth observations and a replicable methodology were used to estimate crop yields at the field level for the period 2010/2014 in the Fergana Valley, Central Asia, to understand the response of agricultural productivity to factors related to the irrigation and drainage infrastructure and environment. The results showed that cropping pattern, i.e. the presence or absence of multi-annual crop rotations, and spatial diversity of crops had the most persistent effects on crop yields across observation years suggesting the need for introducing sustainable cropping systems. On the other hand, areas with a lower crop diversity or abundance of crop rotation tended to have lower crop yields, with differences of partly more than one t/ha yield. It is argued that factors related to the infrastructure, for example, the distance of farms to the next settlement or the density of roads, had a persistent effect on crop yield dynamics over time. The improvement potential of cotton and wheat yields were estimated at 5%, compared to crop yields of farms in the direct vicinity of settlements or roads. In this study it is highlighted how remotely sensed estimates of crop production in combination with geospatial technologies provide a unique perspective that, when combined with field surveys, can support planners to identify management priorities for improving regional production and/or reducing environmental impacts.

Crop monitoring & yield forecasting system based on Synthetic Aperture Radar (SAR) and process-based crop growth model: Development and validation in South and South East Asian Countries

NASA Astrophysics Data System (ADS)

Setiyono, T. D.

2014-12-01

Accurate and timely information on rice crop growth and yield helps governments and other stakeholders adapting their economic policies and enables relief organizations to better anticipate and coordinate relief efforts in the wake of a natural catastrophe. Such delivery of rice growth and yield information is made possible by regular earth observation using space-born Synthetic Aperture Radar (SAR) technology combined with crop modeling approach to estimate yield. Radar-based remote sensing is capable of observing rice vegetation growth irrespective of cloud coverage, an important feature given that in incidences of flooding the sky is often cloud-covered. The system allows rapid damage assessment over the area of interest. Rice yield monitoring is based on a crop growth simulation and SAR-derived key information, particularly start of season and leaf growth rate. Results from pilot study sites in South and South East Asian countries suggest that incorporation of SAR data into crop model improves yield estimation for actual yields. Remote-sensing data assimilation into crop model effectively capture responses of rice crops to environmental conditions over large spatial coverage, which otherwise is practically impossible to achieve. Such improvement of actual yield estimates offers practical application such as in a crop insurance program. Process-based crop simulation model is used in the system to ensure climate information is adequately captured and to enable mid-season yield forecast.

A 5-year analysis of crop phenologies from the United States Heartland (Invited)

NASA Astrophysics Data System (ADS)

Johnson, D. M.

2010-12-01

Time series imagery data from the National Aeronautics and Space Administration (NASA) Moderate Resolution Imaging Spectroradiometer (MODIS) was intersected with annually updated field-level crop data from the United States Department of Agriculture (USDA) Farm Service Agency (FSA). Phenological metrics were derived for major crop types found in the United States (US) Heartland region. The specific MODIS data consisted of the 16-day composited Normalized Difference Vegetation Index (NDVI) 250 meter spatial resolution imagery from the Terra satellite. Crops evaluated included corn, soybeans, wheat, cotton, sorghum, rice, and other small grains. Charts showing the annual average state-level NDVI phenologies by crop were constructed for the five years between 2006 and 2010. The states of interest covered the intensively cultivated regions in the US Great Plains, Corn Belt, and Mississippi River Alluvial Plain. Results demonstrated the recent biophysical growth cycles of prevalent and widespread US crops and how they varied by geography and year. Linkages between the time series data and planting practices, weather impacts, crop progress reports, and yields were also investigated.

Impacts of El Nino Southern Oscillation on the Global Yields of Major Crops

NASA Technical Reports Server (NTRS)

Iizumi, Toshichika; Luo, Jing-Jia; Challinor, Andrew J.; Sakurai, Gen; Yokozawa, Masayuki; Sakuma, Hirofumi; Brown, Molly Elizabeth; Yamagata, Toshio

2014-01-01

The monitoring and prediction of climate-induced variations in crop yields, production and export prices in major food-producing regions have become important to enable national governments in import-dependent countries to ensure supplies of affordable food for consumers. Although the El Nino/Southern Oscillation (ENSO) often affects seasonal temperature and precipitation, and thus crop yields in many regions, the overall impacts of ENSO on global yields are uncertain. Here we present a global map of the impacts of ENSO on the yields of major crops and quantify its impacts on their global-mean yield anomalies. Results show that El Nino likely improves the global-mean soybean yield by 2.15.4 but appears to change the yields of maize, rice and wheat by -4.3 to +0.8. The global-mean yields of all four crops during La Nina years tend to be below normal (-4.5 to 0.0).Our findings highlight the importance of ENSO to global crop production.

Investment risk in bioenergy crops

DOE PAGES

Skevas, Theodoros; Swinton, Scott M.; Tanner, Sophia; ...

2015-11-18

Here, perennial, cellulosic bioenergy crops represent a risky investment. The potential for adoption of these crops depends not only on mean net returns, but also on the associated probability distributions and on the risk preferences of farmers. Using 6-year observed crop yield data from highly productive and marginally productive sites in the southern Great Lakes region and assuming risk neutrality, we calculate expected breakeven biomass yields and prices compared to corn ( Zea mays L.) as a benchmark. Next we develop Monte Carlo budget simulations based on stochastic crop prices and yields. The crop yield simulations decompose yield risk intomore » three components: crop establishment survival, time to maturity, and mature yield variability. Results reveal that corn with harvest of grain and 38% of stover (as cellulosic bioenergy feedstock) is both the most profitable and the least risky investment option. It dominates all perennial systems considered across a wide range of farmer risk preferences. Although not currently attractive for profit-oriented farmers who are risk neutral or risk averse, perennial bioenergy crops.« less

Investment risk in bioenergy crops

DOE Office of Scientific and Technical Information (OSTI.GOV)

Skevas, Theodoros; Swinton, Scott M.; Tanner, Sophia

Here, perennial, cellulosic bioenergy crops represent a risky investment. The potential for adoption of these crops depends not only on mean net returns, but also on the associated probability distributions and on the risk preferences of farmers. Using 6-year observed crop yield data from highly productive and marginally productive sites in the southern Great Lakes region and assuming risk neutrality, we calculate expected breakeven biomass yields and prices compared to corn ( Zea mays L.) as a benchmark. Next we develop Monte Carlo budget simulations based on stochastic crop prices and yields. The crop yield simulations decompose yield risk intomore » three components: crop establishment survival, time to maturity, and mature yield variability. Results reveal that corn with harvest of grain and 38% of stover (as cellulosic bioenergy feedstock) is both the most profitable and the least risky investment option. It dominates all perennial systems considered across a wide range of farmer risk preferences. Although not currently attractive for profit-oriented farmers who are risk neutral or risk averse, perennial bioenergy crops.« less

Tradeoffs between vigor and yield for crops grown under different management systems

NASA Astrophysics Data System (ADS)

Simic Milas, Anita; Keller Vincent, Robert; Romanko, Matthew; Feitl, Melina; Rupasinghe, Prabha

2016-04-01

Remote sensing can provide an effective means for rapid and non-destructive monitoring of crop status and biochemistry. Monitoring pattern of traditional vigor algorithms generated from Landsat 8 OLI satellite data represents a robust method that can be widely used to differentiate the status of crops, as well as to monitor nutrient uptake functionality of differently treated seeds grown under different managements. This study considers 24 factorial parcels of winter wheat in 2013, corn in 2014, and soybeans in 2015, grown under four different types of agricultural management. The parcels are located at the Kellogg Biological Station, Long-Term Ecological Research site in the State of Michigan USA. At maturity, the organic crops exhibit significantly higher vigor and significantly lower yield than conventionally managed crops under different treatments. While organic crops invest in their metabolism at the expense of their yield, the conventional crops manage to increase their yield at the expense of their vigor. Landsat 8 OLI is capable of 1) differentiating the biochemical status of crops under different treatments at maturity, and 2) monitoring the tradeoff between crop yield and vigor that can be controlled by the seed treatments and proper conventional applications, with the ultimate goal of increasing food yield and food availability, and 3) distinguishing between organic and conventionally treated crops. Timing, quantity and types of herbicide applications have a great impact on early and pre-harvest vigor, maturity and yield of conventionally treated crops. Satellite monitoring using Landsat 8 is an optimal tool for coordinating agricultural applications, soil practices and genetic coding of the crop to produce higher yield as well as have early crop maturity, desirable in northern climates.

Effects of enhancing soil organic carbon sequestration in the topsoil by fertilization on crop productivity and stability: Evidence from long-term experiments with wheat-maize cropping systems in China.

PubMed

Zhang, Xubo; Sun, Nan; Wu, Lianhai; Xu, Minggang; Bingham, Ian J; Li, Zhongfang

2016-08-15

Although organic carbon sequestration in agricultural soils has been recommended as a 'win-win strategy' for mitigating climate change and ensuring food security, great uncertainty still remains in identifying the relationships between soil organic carbon (SOC) sequestration and crop productivity. Using data from 17 long-term experiments in China we determined the effects of fertilization strategies on SOC stocks at 0-20cm depth in the North, North East, North West and South. The impacts of changes in topsoil SOC stocks on the yield and yield stability of winter wheat (Triticum aestivum L.) and maize (Zea mays L.) were determined. Results showed that application of inorganic fertilizers (NPK) plus animal manure over 20-30years significantly increased SOC stocks to 20-cm depth by 32-87% whilst NPK plus wheat/maize straw application increased it by 26-38% compared to controls. The efficiency of SOC sequestration differed between regions with 7.4-13.1% of annual C input into the topsoil being retained as SOC over the study periods. In the northern regions, application of manure had little additional effect on yield compared to NPK over a wide range of topsoil SOC stocks (18->50MgCha(-1)). In the South, average yield from manure applied treatments was 2.5 times greater than that from NPK treatments. Moreover, the yield with NPK plus manure increased until SOC stocks (20-cm depth) increased to ~35MgCha(-1). In the northern regions, yield stability was not increased by application of NPK plus manure compared to NPK, whereas in the South there was a significant improvement. We conclude that manure application and straw incorporation could potentially lead to SOC sequestration in topsoil in China, but beneficial effects of this increase in SOC stocks to 20-cm depth on crop yield and yield stability may only be achieved in the South. Copyright © 2016 Elsevier B.V. All rights reserved.

Quantifying the risks of winter damage on overwintering crops under future climates: Will low-temperature damage be more likely in warmer climates?

NASA Astrophysics Data System (ADS)

Vico, G.; Weih, M.

2014-12-01

Autumn-sown crops act as winter cover crop, reducing soil erosion and nutrient leaching, while potentially providing higher yields than spring varieties in many environments. Nevertheless, overwintering crops are exposed for longer periods to the vagaries of weather conditions. Adverse winter conditions, in particular, may negatively affect the final yield, by reducing crop survival or its vigor. The net effect of the projected shifts in climate is unclear. On the one hand, warmer temperatures may reduce the frequency of low temperatures, thereby reducing damage risk. On the other hand, warmer temperatures, by reducing plant acclimation level and the amount and duration of snow cover, may increase the likelihood of damage. Thus, warmer climates may paradoxically result in more extensive low temperature damage and reduced viability for overwintering plants. The net effect of a shift in climate is explored by means of a parsimonious probabilistic model, based on a coupled description of air temperature, snow cover, and crop tolerable temperature. Exploiting an extensive dataset of winter wheat responses to low temperature exposure, the risk of winter damage occurrence is quantified under conditions typical of northern temperate latitudes. The full spectrum of variations expected with climate change is explored, quantifying the joint effects of alterations in temperature averages and their variability as well as shifts in precipitation. The key features affecting winter wheat vulnerability to low temperature damage under future climates are singled out.

Adaptive nitrogen and integrated weed management in conservation agriculture: impacts on agronomic productivity, greenhouse gas emissions, and herbicide residues.

PubMed

Oyeogbe, Anthony Imoudu; Das, T K; Bhatia, Arti; Singh, Shashi Bala

2017-04-01

Increasing nitrogen (N) immobilization and weed interference in the early phase of implementation of conservation agriculture (CA) affects crop yields. Yet, higher fertilizer and herbicide use to improve productivity influences greenhouse gase emissions and herbicide residues. These tradeoffs precipitated a need for adaptive N and integrated weed management in CA-based maize (Zea mays L.)-wheat [Triticum aestivum (L.) emend Fiori & Paol] cropping system in the Indo-Gangetic Plains (IGP) to optimize N availability and reduce weed proliferation. Adaptive N fertilization was based on soil test value and normalized difference vegetation index measurement (NDVM) by GreenSeeker™ technology, while integrated weed management included brown manuring (Sesbania aculeata L. co-culture, killed at 25 days after sowing), herbicide mixture, and weedy check (control, i.e., without weed management). Results indicated that the 'best-adaptive N rate' (i.e., 50% basal + 25% broadcast at 25 days after sowing + supplementary N guided by NDVM) increased maize and wheat grain yields by 20 and 14% (averaged for 2 years), respectively, compared with whole recommended N applied at sowing. Weed management by brown manuring (during maize) and herbicide mixture (during wheat) resulted in 10 and 21% higher grain yields (averaged for 2 years), respectively, over the weedy check. The NDVM in-season N fertilization and brown manuring affected N 2 O and CO 2 emissions, but resulted in improved carbon storage efficiency, while herbicide residuals in soil were significantly lower in the maize season than in wheat cropping. This study concludes that adaptive N and integrated weed management enhance synergy between agronomic productivity, fertilizer and herbicide efficiency, and greenhouse gas mitigation.

Effect of a Terminated Cover Crop and Aldicarb on Cotton Yield and Meloidogyne incognita Population Density

PubMed Central

Wheeler, T. A.; Leser, J. F.; Keeling, J. W.; Mullinix, B.

2008-01-01

Terminated small grain cover crops are valuable in light textured soils to reduce wind and rain erosion and for protection of young cotton seedlings. A three-year study was conducted to determine the impact of terminated small grain winter cover crops, which are hosts for Meloidogyne incognita, on cotton yield, root galling and nematode midseason population density. The small plot test consisted of the cover treatment as the main plots (winter fallow, oats, rye and wheat) and rate of aldicarb applied in-furrow at-plant (0, 0.59 and 0.84 kg a.i./ha) as subplots in a split-plot design with eight replications, arranged in a randomized complete block design. Roots of 10 cotton plants per plot were examined at approximately 35 days after planting. Root galling was affected by aldicarb rate (9.1, 3.8 and 3.4 galls/root system for 0, 0.59 and 0.84 kg aldicarb/ha), but not by cover crop. Soil samples were collected in mid-July and assayed for nematodes. The winter fallow plots had a lower density of M. incognita second-stage juveniles (J2) (transformed to Log10 (J2 + 1)/500 cm3 soil) than any of the cover crops (0.88, 1.58, 1.67 and 1.75 Log10(J2 + 1)/500 cm3 soil for winter fallow, oats, rye and wheat, respectively). There were also fewer M. incognita eggs at midseason in the winter fallow (3,512, 7,953, 8,262 and 11,392 eggs/500 cm3 soil for winter fallow, oats, rye and wheat, respectively). Yield (kg lint per ha) was increased by application of aldicarb (1,544, 1,710 and 1,697 for 0, 0.59 and 0.84 kg aldicarb/ha), but not by any cover crop treatments. These results were consistent over three years. The soil temperature at 15 cm depth, from when soils reached 18°C to termination of the grass cover crop, averaged 9,588, 7,274 and 1,639 centigrade hours (with a minimum threshold of 10°C), in 2005, 2006 and 2007, respectively. Under these conditions, potential reproduction of M. incognita on the cover crop did not result in a yield penalty. PMID:19259531

Effect of a Terminated Cover Crop and Aldicarb on Cotton Yield and Meloidogyne incognita Population Density.

PubMed

Wheeler, T A; Leser, J F; Keeling, J W; Mullinix, B

2008-06-01

Terminated small grain cover crops are valuable in light textured soils to reduce wind and rain erosion and for protection of young cotton seedlings. A three-year study was conducted to determine the impact of terminated small grain winter cover crops, which are hosts for Meloidogyne incognita, on cotton yield, root galling and nematode midseason population density. The small plot test consisted of the cover treatment as the main plots (winter fallow, oats, rye and wheat) and rate of aldicarb applied in-furrow at-plant (0, 0.59 and 0.84 kg a.i./ha) as subplots in a split-plot design with eight replications, arranged in a randomized complete block design. Roots of 10 cotton plants per plot were examined at approximately 35 days after planting. Root galling was affected by aldicarb rate (9.1, 3.8 and 3.4 galls/root system for 0, 0.59 and 0.84 kg aldicarb/ha), but not by cover crop. Soil samples were collected in mid-July and assayed for nematodes. The winter fallow plots had a lower density of M. incognita second-stage juveniles (J2) (transformed to Log(10) (J2 + 1)/500 cm(3) soil) than any of the cover crops (0.88, 1.58, 1.67 and 1.75 Log(10)(J2 + 1)/500 cm(3) soil for winter fallow, oats, rye and wheat, respectively). There were also fewer M. incognita eggs at midseason in the winter fallow (3,512, 7,953, 8,262 and 11,392 eggs/500 cm(3) soil for winter fallow, oats, rye and wheat, respectively). Yield (kg lint per ha) was increased by application of aldicarb (1,544, 1,710 and 1,697 for 0, 0.59 and 0.84 kg aldicarb/ha), but not by any cover crop treatments. These results were consistent over three years. The soil temperature at 15 cm depth, from when soils reached 18 degrees C to termination of the grass cover crop, averaged 9,588, 7,274 and 1,639 centigrade hours (with a minimum threshold of 10 degrees C), in 2005, 2006 and 2007, respectively. Under these conditions, potential reproduction of M. incognita on the cover crop did not result in a yield penalty.

Diverse rotations and poultry litter improves soybean yield

USDA-ARS?s Scientific Manuscript database

Continuous cropping systems without rotations or cover crops are perceived as unsustainable for long-term yield and soil health. Continuous systems, defined as continually producing a crop on the same parcel of land for more than three years, is thought to reduce yields. Given that crop rotations a...

Is current irrigation sustainable in the United States? An integrated assessment of climate change impact on water resources and irrigated crop yields

DOE PAGES

Blanc, Elodie; Caron, Justin; Fant, Charles; ...

2017-06-27

While climate change impacts on crop yields has been extensively studied, estimating the impact of water shortages on irrigated crop yields is challenging because the water resources management system is complex. To investigate this issue, we integrate a crop yield reduction module and a water resources model into the MIT Integrated Global System Modeling framework, an integrated assessment model linking a global economic model to an Earth system model. We assess the effects of climate and socioeconomic changes on water availability for irrigation in the U.S. as well as subsequent impacts on crop yields by 2050, while accounting for climatemore » change projection uncertainty. We find that climate and socioeconomic changes will increase water shortages and strongly reduce irrigated yields for specific crops (i.e., cotton and forage), or in specific regions (i.e., the Southwest) where irrigation is not sustainable. Crop modeling studies that do not represent changes in irrigation availability can thus be misleading. Yet, since the most water-stressed basins represent a relatively small share of U.S. irrigated areas, the overall reduction in U.S. crop yields is small. The response of crop yields to climate change and water stress also suggests that some level of adaptation will be feasible, like relocating croplands to regions with sustainable irrigation or switching to less irrigation intensive crops. Finally, additional simulations show that greenhouse gas (GHG) mitigation can alleviate the effect of water stress on irrigated crop yields, enough to offset the reduced CO 2 fertilization effect compared to an unconstrained GHG emission scenario.« less

Is current irrigation sustainable in the United States? An integrated assessment of climate change impact on water resources and irrigated crop yields

DOE Office of Scientific and Technical Information (OSTI.GOV)

Blanc, Elodie; Caron, Justin; Fant, Charles

While climate change impacts on crop yields has been extensively studied, estimating the impact of water shortages on irrigated crop yields is challenging because the water resources management system is complex. To investigate this issue, we integrate a crop yield reduction module and a water resources model into the MIT Integrated Global System Modeling framework, an integrated assessment model linking a global economic model to an Earth system model. We assess the effects of climate and socioeconomic changes on water availability for irrigation in the U.S. as well as subsequent impacts on crop yields by 2050, while accounting for climatemore » change projection uncertainty. We find that climate and socioeconomic changes will increase water shortages and strongly reduce irrigated yields for specific crops (i.e., cotton and forage), or in specific regions (i.e., the Southwest) where irrigation is not sustainable. Crop modeling studies that do not represent changes in irrigation availability can thus be misleading. Yet, since the most water-stressed basins represent a relatively small share of U.S. irrigated areas, the overall reduction in U.S. crop yields is small. The response of crop yields to climate change and water stress also suggests that some level of adaptation will be feasible, like relocating croplands to regions with sustainable irrigation or switching to less irrigation intensive crops. Finally, additional simulations show that greenhouse gas (GHG) mitigation can alleviate the effect of water stress on irrigated crop yields, enough to offset the reduced CO 2 fertilization effect compared to an unconstrained GHG emission scenario.« less

Cowpeas and pinto beans: yields and light efficiency of candidate space crops in the Laboratory Biosphere closed ecological system

NASA Astrophysics Data System (ADS)

Nelson, M.; Dempster, W. F.; Silverstone, S.; Alling, A.; Allen, J. P.; van Thillo, M.

An experiment utilizing cowpeas Vigna unguiculata pinto beans Phaseolus vulgaris L and Apogee ultra-dwarf wheat was conducted in the soil-based closed ecological facility Laboratory Biosphere from February to May 2005 The lighting regime was 13 hours light 11 hours dark at a light intensity of 960 mu mol m -2 s -1 45 moles m -2 day -1 supplied by high-pressure sodium lamps The pinto beans and cowpeas were grown at two different plant densities The pinto bean produced 710 g m -2 total aboveground biomass and 341 g m -2 at 33 5 plants per m 2 and at 37 5 plants per m 2 produced 1092 g m -2 total biomass and 537 g m -2 of dry seed an increase of almost 50 Cowpeas at 28 plants m -2 yielded 1060 g m -2 of total biomass and 387 g seed m -2 outproducing the less dense planting by more than double 209 in biomass and 86 more seed as the planting of 21 plants m -2 produced 508 g m-2 of total biomass and 209 g m-2 of seed Edible yield rate EYR for the denser cowpea bean was 4 6 g m -2 day -1 vs 2 5 g m -2 day -1 for the less dense stand average yield was 3 5 g m -2 day -1 EYR for the denser pinto bean was 8 5 g m -2 day -1 vs 5 3 g m -2 day -1 average EYR for the pinto beans was 7 0 g m -2 day -1 Yield efficiency rate YER the ratio of edible to non-edible biomass was 0 97 for the dense pinto bean 0 92 for the less dense pinto bean and average 0 94 for the entire crop The cowpeas

Benefits of increasing transpiration efficiency in wheat under elevated CO2 for rainfed regions.

PubMed

Christy, Brendan; Tausz-Posch, Sabine; Tausz, Michael; Richards, Richard; Rebetzke, Greg; Condon, Anthony; McLean, Terry; Fitzgerald, Glenn; Bourgault, Maryse; O'Leary, Garry

2018-05-01

Higher transpiration efficiency (TE) has been proposed as a mechanism to increase crop yields in dry environments where water availability usually limits yield. The application of a coupled radiation and TE simulation model shows wheat yield advantage of a high-TE cultivar (cv. Drysdale) over its almost identical low-TE parent line (Hartog), from about -7 to 558 kg/ha (mean 187 kg/ha) over the rainfed cropping region in Australia (221-1,351 mm annual rainfall), under the present-day climate. The smallest absolute yield response occurred in the more extreme drier and wetter areas of the wheat belt. However, under elevated CO 2 conditions, the response of Drysdale was much greater overall, ranging from 51 to 886 kg/ha (mean 284 kg/ha) with the greatest response in the higher rainfall areas. Changes in simulated TE under elevated CO 2 conditions are seen across Australia with notable increased areas of higher TE under a drier climate in Western Australia, Queensland and parts of New South Wales and Victoria. This improved efficiency is subtly deceptive, with highest yields not necessarily directly correlated with highest TE. Nevertheless, the advantage of Drysdale over Hartog is clear with the benefit of the trait advantage attributed to TE ranging from 102% to 118% (mean 109%). The potential annual cost-benefits of this increased genetic TE trait across the wheat growing areas of Australia (5 year average of area planted to wheat) totaled AUD 631 MIL (5-year average wheat price of AUD/260 t) with an average of 187 kg/ha under the present climate. The benefit to an individual farmer will depend on location but elevated CO 2 raises this nation-wide benefit to AUD 796 MIL in a 2°C warmer climate, slightly lower (AUD 715 MIL) if rainfall is also reduced by 20%. © 2018 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.

An end-to-end assessment of extreme weather impacts on food security

NASA Astrophysics Data System (ADS)

Chavez, Erik; Conway, Gordon; Ghil, Michael; Sadler, Marc

2015-11-01

Both governments and the private sector urgently require better estimates of the likely incidence of extreme weather events, their impacts on food crop production and the potential consequent social and economic losses. Current assessments of climate change impacts on agriculture mostly focus on average crop yield vulnerability to climate and adaptation scenarios. Also, although new-generation climate models have improved and there has been an exponential increase in available data, the uncertainties in their projections over years and decades, and at regional and local scale, have not decreased. We need to understand and quantify the non-stationary, annual and decadal climate impacts using simple and communicable risk metrics that will help public and private stakeholders manage the hazards to food security. Here we present an `end-to-end’ methodological construct based on weather indices and machine learning that integrates current understanding of the various interacting systems of climate, crops and the economy to determine short- to long-term risk estimates of crop production loss, in different climate and adaptation scenarios. For provinces north and south of the Yangtze River in China, we have found that risk profiles for crop yields that translate climate into economic variability follow marked regional patterns, shaped by drivers of continental-scale climate. We conclude that to be cost-effective, region-specific policies have to be tailored to optimally combine different categories of risk management instruments.

Breeding of a new potato variety ‘Nagasaki Kogane’ with high eating quality, high carotenoid content, and resistance to diseases and pests

PubMed Central

Sakamoto, Yu; Mori, Kazuyuki; Matsuo, Yuuki; Mukojima, Nobuhiro; Watanabe, Wataru; Sobaru, Norio; Tamiya, Seiji; Nakao, Takashi; Hayashi, Kazuya; Watanuki, Hitomi; Nara, Kazuhiro; Yamazaki, Kaoru; Chaya, Masataka

2017-01-01

‘Nagasaki Kogane’ is a new potato variety bred from a cross between ‘Saikai 35’ as a female parent and ‘Saikai 33’ as a male. ‘Saikai 35’ is resistant to bacterial wilt, contains the H1 and Rychc genes for resistance to the potato cyst nematode (PCN) and potato virus Y (PVY), respectively, and has high carotenoid content, while ‘Saikai 33’ has large and high-yielding tubers and is resistant to both bacterial wilt and PCN. The carotenoid content of ‘Nagasaki Kogane’ is higher than that of ‘Dejima’, a common double cropping variety. The taste quality of steamed ‘Nagasaki Kogane’ is comparable to that of ‘Inca-no-mezame’ tubers, which has high levels of carotenoid, and superior to ‘Nishiyutaka’, another popular double cropping variety. ‘Nagasaki Kogane’ is suitable for French fries, because its tuber has high starch content. The marketable yield of ‘Nagasaki Kogane’ was higher than that of ‘Inca-no-mezame’ in spring cropping, although it was lower than that of ‘Nishiyutaka’ in double cropping regions. ‘Nagasaki Kogane’ tubers are larger on average than ‘Inca-no-mezame’ tubers in spring cropping. Moreover, the ‘Nagasaki Kogane’ variety is resistant to PCN and PVY, and exhibits a high level of resistance to bacterial wilt. PMID:28744186

Adaptation Measures Evaliation on Agriculture Under Future Climate and Land Use Scenarios in Central Chile

NASA Astrophysics Data System (ADS)

Henriquez Dole, L. E.; Vicuna, S.; Gironas, J. A.; Meza, F. J.

2016-12-01

Future climate change scenarios threaten current practices in agriculture and therefore adaptation measures have been proposed to overcome this possible situation. Regional to local ideas apply for all kind of adaptation measures and can be found among literature for Central Chile, but their quantitative efficiency is rarely evaluated. Furthermore, land uses changes are commonly neglected in such evaluations. This research use the Water Evaluation and Planning (WEAP) model and the Plant Growth Model (PGM) to simulate weekly water distribution and consumption in Chile's rural areas up to 2050. Using information directly provided by the Water User Organizations (WUO), the developed model assesses possible future impacts on 2 crops (corn and plum) under 15 climate scenarios and land use trends. Results show that WEAP-PGM tool can represent satisfactorily crop sensitiveness to historic and future circumstances. Nine scenarios satisfy average crop water demands, but all of them present a diminished yield (1%-14%) and production (8%-20%). Just six scenarios cannot meet crop water demands (40-70% of reliability) if adaptation measures are not applied. Given this need, two adaptation measures were evaluated: a) using all water rights and b) irrigation improvements. The second option showed to be the most effective measure leading to the satisfaction of crop water demands under all the scenarios, but still a diminished yield and production remained.

Linking Field and Satellite Observations to Reveal Differences in Single vs. Double-Cropped Soybean Yields in Central Brazil

NASA Astrophysics Data System (ADS)

Jeffries, G. R.; Cohn, A.

2016-12-01

Soy-corn double cropping (DC) has been widely adopted in Central Brazil alongside single cropped (SC) soybean production. DC involves different cropping calendars, soy varieties, and may be associated with different crop yield patterns and volatility than SC. Study of the performance of the region's agriculture in a changing climate depends on tracking differences in the productivity of SC vs. DC, but has been limited by crop yield data that conflate the two systems. We predicted SC and DC yields across Central Brazil, drawing on field observations and remotely sensed data. We first modeled field yield estimates as a function of remotely sensed DC status and vegetation index (VI) metrics, and other management and biophysical factors. We then used the statistical model estimated to predict SC and DC soybean yields at each 500 m2 grid cell of Central Brazil for harvest years 2001 - 2015. The yield estimation model was constructed using 1) a repeated cross-sectional survey of soybean yields and management factors for years 2007-2015, 2) a custom agricultural land cover classification dataset which assimilates earlier datasets for the region, and 3) 500m 8-day MODIS image composites used to calculate the wide dynamic range vegetation index (WDRVI) and derivative metrics such as area under the curve for WDRVI values in critical crop development periods. A statistical yield estimation model which primarily entails WDRVI metrics, DC status, and spatial fixed effects was developed on a subset of the yield dataset. Model validation was conducted by predicting previously withheld yield records, and then assessing error and goodness-of-fit for predicted values with metrics including root mean squared error (RMSE), mean squared error (MSE), and R2. We found a statistical yield estimation model which incorporates WDRVI and DC status to be way to estimate crop yields over the region. Statistical properties of the resulting gridded yield dataset may be valuable for understanding linkages between crop yields, farm management factors, and climate.

Simulating the effects of climate and agricultural management practices on global crop yield

NASA Astrophysics Data System (ADS)

Deryng, D.; Sacks, W. J.; Barford, C. C.; Ramankutty, N.

2011-06-01

Climate change is expected to significantly impact global food production, and it is important to understand the potential geographic distribution of yield losses and the means to alleviate them. This study presents a new global crop model, PEGASUS 1.0 (Predicting Ecosystem Goods And Services Using Scenarios) that integrates, in addition to climate, the effect of planting dates and cultivar choices, irrigation, and fertilizer application on crop yield for maize, soybean, and spring wheat. PEGASUS combines carbon dynamics for crops with a surface energy and soil water balance model. It also benefits from the recent development of a suite of global data sets and analyses that serve as model inputs or as calibration data. These include data on crop planting and harvesting dates, crop-specific irrigated areas, a global analysis of yield gaps, and harvested area and yield of major crops. Model results for present-day climate and farm management compare reasonably well with global data. Simulated planting and harvesting dates are within the range of crop calendar observations in more than 75% of the total crop-harvested areas. Correlation of simulated and observed crop yields indicates a weighted coefficient of determination, with the weighting based on crop-harvested area, of 0.81 for maize, 0.66 for soybean, and 0.45 for spring wheat. We found that changes in temperature and precipitation as predicted by global climate models for the 2050s lead to a global yield reduction if planting and harvesting dates remain unchanged. However, adapting planting dates and cultivar choices increases yield in temperate regions and avoids 7-18% of global losses.

From field to region yield predictions in response to pedo-climatic variations in Eastern Canada

NASA Astrophysics Data System (ADS)

JÉGO, G.; Pattey, E.; Liu, J.

2013-12-01

The increase in global population coupled with new pressures to produce energy and bioproducts from agricultural land requires an increase in crop productivity. However, the influence of climate and soil variations on crop production and environmental performance is not fully understood and accounted for to define more sustainable and economical management strategies. Regional crop modeling can be a great tool for understanding the impact of climate variations on crop production, for planning grain handling and for assessing the impact of agriculture on the environment, but it is often limited by the availability of input data. The STICS ("Simulateur mulTIdisciplinaire pour les Cultures Standard") crop model, developed by INRA (France) is a functional crop model which has a built-in module to optimize several input parameters by minimizing the difference between calculated and measured output variables, such as Leaf Area Index (LAI). STICS crop model was adapted to the short growing season of the Mixedwood Plains Ecozone using field experiments results, to predict biomass and yield of soybean, spring wheat and corn. To minimize the numbers of inference required for regional applications, 'generic' cultivars rather than specific ones have been calibrated in STICS. After the calibration of several model parameters, the root mean square error (RMSE) of yield and biomass predictions ranged from 10% to 30% for the three crops. A bit more scattering was obtained for LAI (20%

Integrated Modeling of Crop Growth and Water Resource Management to Project Climate Change Impacts on Crop Production and Irrigation Water Supply and Demand in African Nations

NASA Astrophysics Data System (ADS)

Dale, A. L.; Boehlert, B.; Reisenauer, M.; Strzepek, K. M.; Solomon, S.

2017-12-01

Climate change poses substantial risks to African agriculture. These risks are exacerbated by concurrent risks to water resources, with water demand for irrigation comprising 80 to 90% of water withdrawals across the continent. Process-based crop growth models are able to estimate both crop demand for irrigation water and crop yields, and are therefore well-suited to analyses of climate change impacts at the food-water nexus. Unfortunately, impact assessments based on these models generally focus on either yields or water demand, rarely both. For this work, we coupled a crop model to a water resource management model in order to predict national trends in the impact of climate change on crop production, irrigation water demand, and the availability of water for irrigation across Africa. The crop model FAO AquaCrop-OS was run at 2ox2o resolution for 17 different climate futures from the CMIP5 archive, nine for Representative Concentration Pathway (RCP) 4.5 and eight for RCP8.5. Percent changes in annual rainfed and irrigated crop production and temporal shifts in monthly irrigation water demand were estimated for the years 2030, 2050, 2070, and 2090 for maize, sorghum, rice, wheat, cotton, sugarcane, fruits & vegetables, roots & tubers, and legumes & soybeans. AquaCrop was then coupled to a water management model (WEAP) in order to project changes in the ability of seven major river basins (the Congo, Niger, Nile, Senegal, Upper Orange, Volta, and Zambezi) to meet irrigation water demand out to 2050 in both average and dry years in the face of both climate change and irrigation expansion. Spatial and temporal trends were identified and interpreted through the lens of potential risk management strategies. Uncertainty in model estimates is reported and discussed.

Heterologous Expression of ATG8c from Soybean Confers Tolerance to Nitrogen Deficiency and Increases Yield in Arabidopsis

PubMed Central

Liu, Dong; Chai, Wenting; Gong, Qingqiu; Wang, Ning Ning

2012-01-01

Nitrogen is an essential element for plant growth and yield. Improving Nitrogen Use Efficiency (NUE) of crops could potentially reduce the application of chemical fertilizer and alleviate environmental damage. To identify new NUE genes is therefore an important task in molecular breeding. Macroautophagy (autophagy) is an intracellular process in which damaged or obsolete cytoplasmic components are encapsulated in double membraned vesicles termed autophagosomes, then delivered to the vacuole for degradation and nutrient recycling. One of the core components of autophagosome formation, ATG8, has been shown to directly mediate autophagosome expansion, and the transcript of which is highly inducible upon starvation. Therefore, we postulated that certain homologs of Saccharomyces cerevisiae ATG8 (ScATG8) from crop species could have potential for NUE crop breeding. A soybean (Glycine max, cv. Zhonghuang-13) ATG8, GmATG8c, was selected from the 11 family members based on transcript analysis upon nitrogen deprivation. GmATG8c could partially complement the yeast atg8 mutant. Constitutive expression of GmATG8c in soybean callus cells not only enhanced nitrogen starvation tolerance of the cells but accelerated the growth of the calli. Transgenic Arabidopsis over-expressing GmATG8c performed better under extended nitrogen and carbon starvation conditions. Meanwhile, under optimum growth conditions, the transgenic plants grew faster, bolted earlier, produced larger primary and axillary inflorescences, eventually produced more seeds than the wild-type. In average, the yield was improved by 12.9%. We conclude that GmATG8c may serve as an excellent candidate for breeding crops with enhanced NUE and better yield. PMID:22629371

Replacing fallow with continuous cropping reduces crop water productivity of semiarid wheat

USDA-ARS?s Scientific Manuscript database

Water supply frequently limits crop yield in semiarid cropping systems; water deficits can restrict yields in drought-affected subhumid regions. In semiarid wheat (Triticum aestivumL.)-based cropping systems, replacing an uncropped fallow period with a crop can increase precipitation use efficiency ...

A regionally-adapted implementation of conservation agriculture delivers rapid improvements to soil properties associated with crop yield stability.

PubMed

Williams, Alwyn; Jordan, Nicholas R; Smith, Richard G; Hunter, Mitchell C; Kammerer, Melanie; Kane, Daniel A; Koide, Roger T; Davis, Adam S

2018-05-31

Climate models predict increasing weather variability, with negative consequences for crop production. Conservation agriculture (CA) may enhance climate resilience by generating certain soil improvements. However, the rate at which these improvements accrue is unclear, and some evidence suggests CA can lower yields relative to conventional systems unless all three CA elements are implemented: reduced tillage, sustained soil cover, and crop rotational diversity. These cost-benefit issues are important considerations for potential adopters of CA. Given that CA can be implemented across a wide variety of regions and cropping systems, more detailed and mechanistic understanding is required on whether and how regionally-adapted CA can improve soil properties while minimizing potential negative crop yield impacts. Across four US states, we assessed short-term impacts of regionally-adapted CA systems on soil properties and explored linkages with maize and soybean yield stability. Structural equation modeling revealed increases in soil organic matter generated by cover cropping increased soil cation exchange capacity, which improved soybean yield stability. Cover cropping also enhanced maize minimum yield potential. Our results demonstrate individual CA elements can deliver rapid improvements in soil properties associated with crop yield stability, suggesting that regionally-adapted CA may play an important role in developing high-yielding, climate-resilient agricultural systems.

Forecasting wheat and barley crop production in arid and semi-arid regions using remotely sensed primary productivity and crop phenology: A case study in Iraq.

PubMed

Qader, Sarchil Hama; Dash, Jadunandan; Atkinson, Peter M

2018-02-01

Crop production and yield estimation using remotely sensed data have been studied widely, but such information is generally scarce in arid and semi-arid regions. In these regions, inter-annual variation in climatic factors (such as rainfall) combined with anthropogenic factors (such as civil war) pose major risks to food security. Thus, an operational crop production estimation and forecasting system is required to help decision-makers to make early estimates of potential food availability. Data from NASA's MODIS with official crop statistics were combined to develop an empirical regression-based model to forecast winter wheat and barley production in Iraq. The study explores remotely sensed indices representing crop productivity over the crop growing season to find the optimal correlation with crop production. The potential of three different remotely sensed indices, and information related to the phenology of crops, for forecasting crop production at the governorate level was tested and their results were validated using the leave-one-year-out approach. Despite testing several methodological approaches, and extensive spatio-temporal analysis, this paper depicts the difficulty in estimating crop yield on an annual base using current satellite low-resolution data. However, more precise estimates of crop production were possible. The result of the current research implies that the date of the maximum vegetation index (VI) offered the most accurate forecast of crop production with an average R 2 =0.70 compared to the date of MODIS EVI (Avg R 2 =0.68) and a NPP (Avg R 2 =0.66). When winter wheat and barley production were forecasted using NDVI, EVI and NPP and compared to official statistics, the relative error ranged from -20 to 20%, -45 to 28% and -48 to 22%, respectively. The research indicated that remotely sensed indices could characterize and forecast crop production more accurately than simple cropping area, which was treated as a null model against which to evaluate the proposed approach. Copyright © 2017 Elsevier B.V. All rights reserved.

Biomass production of 12 winter cereal cover crop cultivars and their effect on subsequent no-till corn yield

USDA-ARS?s Scientific Manuscript database

Cover crops can improve the sustainability and resilience of corn and soybean production systems. However, there have been isolated reports of corn yield reductions following winter rye cover crops. Although there are many possible causes of corn yield reductions following winter cereal cover crops,...

Long-term Tillage and Cropping Sequence Effect on Dryland Crop Yields and Carbon and Nitrogen Cycling

USDA-ARS?s Scientific Manuscript database

Improved management practices are needed to increase dryland crop yields and soil organic matter compared with conventional farming practices in the northern Great Plains. We evaluated the 21-yr effect of tillage and cropping sequence on dryland grain and biomass (stems + leaves) yields and N uptake...

Development of a European Ensemble System for Seasonal Prediction: Application to crop yield

NASA Astrophysics Data System (ADS)

Terres, J. M.; Cantelaube, P.

2003-04-01

Western European agriculture is highly intensive and the weather is the main source of uncertainty for crop yield assessment and for crop management. In the current system, at the time when a crop yield forecast is issued, the weather conditions leading up to harvest time are unknown and are therefore a major source of uncertainty. The use of seasonal weather forecast would bring additional information for the remaining crop season and has valuable benefit for improving the management of agricultural markets and environmentally sustainable farm practices. An innovative method for supplying seasonal forecast information to crop simulation models has been developed in the frame of the EU funded research project DEMETER. It consists in running a crop model on each individual member of the seasonal hindcasts to derive a probability distribution of crop yield. Preliminary results of cumulative probability function of wheat yield provides information on both the yield anomaly and the reliability of the forecast. Based on the spread of the probability distribution, the end-user can directly quantify the benefits and risks of taking weather-sensitive decisions.

Changes in crop yields and their variability at different levels of global warming

NASA Astrophysics Data System (ADS)

Ostberg, Sebastian; Schewe, Jacob; Childers, Katelin; Frieler, Katja

2018-05-01

An assessment of climate change impacts at different levels of global warming is crucial to inform the policy discussion about mitigation targets, as well as for the economic evaluation of climate change impacts. Integrated assessment models often use global mean temperature change (ΔGMT) as a sole measure of climate change and, therefore, need to describe impacts as a function of ΔGMT. There is already a well-established framework for the scalability of regional temperature and precipitation changes with ΔGMT. It is less clear to what extent more complex biological or physiological impacts such as crop yield changes can also be described in terms of ΔGMT, even though such impacts may often be more directly relevant for human livelihoods than changes in the physical climate. Here we show that crop yield projections can indeed be described in terms of ΔGMT to a large extent, allowing for a fast estimation of crop yield changes for emissions scenarios not originally covered by climate and crop model projections. We use an ensemble of global gridded crop model simulations for the four major staple crops to show that the scenario dependence is a minor component of the overall variance of projected yield changes at different levels of ΔGMT. In contrast, the variance is dominated by the spread across crop models. Varying CO2 concentrations are shown to explain only a minor component of crop yield variability at different levels of global warming. In addition, we find that the variability in crop yields is expected to increase with increasing warming in many world regions. We provide, for each crop model, geographical patterns of mean yield changes that allow for a simplified description of yield changes under arbitrary pathways of global mean temperature and CO2 changes, without the need for additional climate and crop model simulations.

Climate change and maize yield in southern Africa: what can farm management do?

PubMed

Rurinda, Jairos; van Wijk, Mark T; Mapfumo, Paul; Descheemaeker, Katrien; Supit, Iwan; Giller, Ken E

2015-12-01

There is concern that food insecurity will increase in southern Africa due to climate change. We quantified the response of maize yield to projected climate change and to three key management options - planting date, fertilizer use and cultivar choice - using the crop simulation model, agricultural production systems simulator (APSIM), at two contrasting sites in Zimbabwe. Three climate periods up to 2100 were selected to cover both near- and long-term climates. Future climate data under two radiative forcing scenarios were generated from five global circulation models. The temperature is projected to increase significantly in Zimbabwe by 2100 with no significant change in mean annual total rainfall. When planting before mid-December with a high fertilizer rate, the simulated average grain yield for all three maize cultivars declined by 13% for the periods 2010-2039 and 2040-2069 and by 20% for 2070-2099 compared with the baseline climate, under low radiative forcing. Larger declines in yield of up to 32% were predicted for 2070-2099 with high radiative forcing. Despite differences in annual rainfall, similar trends in yield changes were observed for the two sites studied, Hwedza and Makoni. The yield response to delay in planting was nonlinear. Fertilizer increased yield significantly under both baseline and future climates. The response of maize to mineral nitrogen decreased with progressing climate change, implying a decrease in the optimal fertilizer rate in the future. Our results suggest that in the near future, improved crop and soil fertility management will remain important for enhanced maize yield. Towards the end of the 21st century, however, none of the farm management options tested in the study can avoid large yield losses in southern Africa due to climate change. There is a need to transform the current cropping systems of southern Africa to offset the negative impacts of climate change. © 2015 John Wiley & Sons Ltd.

Analysis of factors which limited the spatial variation of barley yield on the forest-steppe chernozems of Kursk region

NASA Astrophysics Data System (ADS)

Belik, Anton; Vasenev, Ivan; Jablonskikh, Lidia; Bozhko, Svetlana

2017-04-01

The crop yield is the most important indicator of the efficiency of agricultural production. It is the function that depends on a large number of groups of independent variables, such as the weather, soil fertility and overall culture agriculture. A huge number of combinations of these factors contribute to the formation of high spatial variety of crop yields within small areas, includes the slope agrolandscapes in Kursk region. Spatial variety of yield leads to a significant reduction in the efficiency of agriculture. In this connection, evaluation and analysis of the factors, which limits the yield of field crops is a very urgent proble in agroecology. The research was conducted in the period of 2003-2004 on a representative field. The typical and leached chernozems with the varying thickness and of erosion degree are dominated in soil cover. At the time of field research studied areas were busy by barley. The reseached soils have an average and increased fertility level. Chernozem typical full-face, and the leached contain an average of 4.5-6% humus, close to neutral pH, favorable values of physico-chemical parameters, medium and high content of nutrients. The eroded chernozems differs agrogenic marked declining in fertility parameters. The diversity of meso- and micro-relief in the fields and soil cover influence to significant spatial variety of fertility. For example the content of nutrients in the soil variation can be up to 5-fold level. High spatial heterogeneity of soils fertility ifluence to barley yield variety. During research on the productivity of the field varied in the range of 20-43 c/ha, and 7-44 c/ha (2004). Analysis of the factors, which limited the yield of barley, showed that the first priorities occupy unregulated characterises: slope angle and the classification of soils (subtype and race of chernozem and the difference in the degree of erosion), which determines the development of erosion processes and redistribution available to plants form of moisture. As a rule, the maximum yield of barley is marked on most flat areas covered with chernozem leached and typical with the full profile. The contain of nutrients usually takes 3-4 levels of limitation. The significance of a particular element is determined by the characteristics of the particular agro-ecological homogeneous area. Most, however, the value in the 2003 - 2004's. plants were available forms of phosphorus and potassium Thus, in terms of slope agricultural landscapes of the Kursk region, there is increased spatial varety of fertility and barley yields. This priority among the limiting factors are soils and agro-ecological conditions. Significant influence of agrochemical parameters are shown within the homogeneous agroecological regions. In this regard system of precision agriculture has a great prospects for acquiring practical, and must to imply the adaptation of existing agricultural technologies to change the conditions of cultivation of field crops within fields.

Wildlife-friendly farming increases crop yield: evidence for ecological intensification.

PubMed

Pywell, Richard F; Heard, Matthew S; Woodcock, Ben A; Hinsley, Shelley; Ridding, Lucy; Nowakowski, Marek; Bullock, James M

2015-10-07

Ecological intensification has been promoted as a means to achieve environmentally sustainable increases in crop yields by enhancing ecosystem functions that regulate and support production. There is, however, little direct evidence of yield benefits from ecological intensification on commercial farms growing globally important foodstuffs (grains, oilseeds and pulses). We replicated two treatments removing 3 or 8% of land at the field edge from production to create wildlife habitat in 50-60 ha patches over a 900 ha commercial arable farm in central England, and compared these to a business as usual control (no land removed). In the control fields, crop yields were reduced by as much as 38% at the field edge. Habitat creation in these lower yielding areas led to increased yield in the cropped areas of the fields, and this positive effect became more pronounced over 6 years. As a consequence, yields at the field scale were maintained--and, indeed, enhanced for some crops--despite the loss of cropland for habitat creation. These results suggested that over a 5-year crop rotation, there would be no adverse impact on overall yield in terms of monetary value or nutritional energy. This study provides a clear demonstration that wildlife-friendly management which supports ecosystem services is compatible with, and can even increase, crop yields. © 2015 The Authors.

Added-values of high spatiotemporal remote sensing data in crop yield estimation

NASA Astrophysics Data System (ADS)

Gao, F.; Anderson, M. C.

2017-12-01

Timely and accurate estimation of crop yield before harvest is critical for food market and administrative planning. Remote sensing derived parameters have been used for estimating crop yield by using either empirical or crop growth models. The uses of remote sensing vegetation index (VI) in crop yield modeling have been typically evaluated at regional and country scales using coarse spatial resolution (a few hundred to kilo-meters) data or assessed over a small region at field level using moderate resolution spatial resolution data (10-100m). Both data sources have shown great potential in capturing spatial and temporal variability in crop yield. However, the added value of data with both high spatial and temporal resolution data has not been evaluated due to the lack of such data source with routine, global coverage. In recent years, more moderate resolution data have become freely available and data fusion approaches that combine data acquired from different spatial and temporal resolutions have been developed. These make the monitoring crop condition and estimating crop yield at field scale become possible. Here we investigate the added value of the high spatial and temporal VI for describing variability of crop yield. The explanatory ability of crop yield based on high spatial and temporal resolution remote sensing data was evaluated in a rain-fed agricultural area in the U.S. Corn Belt. Results show that the fused Landsat-MODIS (high spatial and temporal) VI explains yield variability better than single data source (Landsat or MODIS alone), with EVI2 performing slightly better than NDVI. The maximum VI describes yield variability better than cumulative VI. Even though VI is effective in explaining yield variability within season, the inter-annual variability is more complex and need additional information (e.g. weather, water use and management). Our findings augment the importance of high spatiotemporal remote sensing data and supports new moderate resolution satellite missions for agricultural applications.

Responses of root physiological characteristics and yield of sweet potato to humic acid urea fertilizer

PubMed Central

Kou, Meng; Tang, Zhonghou; Zhang, Aijun; Li, Hongmin; Wei, Meng

2017-01-01

Humic acid (HA), not only promote the growth of crop roots, they can be combined with nitrogen (N) to increase fertilizer use efficiency and yield. However, the effects of HA urea fertilizer (HA-N) on root growth and yield of sweet potato has not been widely investigated. Xushu 28 was used as the experimental crop to investigate the effects of HA-N on root morphology, active oxygen metabolism and yield under field conditions. Results showed that nitrogen application alone was not beneficial for root growth and storage root formation during the early growth stage. HA-N significantly increased the dry weight of the root system, promoted differentiation from adventitious root to storage root, and increased the overall root activity, total root length, root diameter, root surface area, as well as root volume. HA-N thus increased the activity of superoxide dismutase (SOD), peroxidase (POD), and Catalase (CAT) as well as increasing the soluble protein content of roots and decreasing the malondialdehyde (MDA) content. HA-N significantly increased both the number of storage roots per plant increased by 14.01%, and the average fresh weight per storage root increased by 13.7%, while the yield was also obviously increased by 29.56%. In this study, HA-N increased yield through a synergistic increase of biological yield and harvest index. PMID:29253886

Decadal analysis of impact of future climate on wheat production in dry Mediterranean environment: A case of Jordan.

PubMed

Dixit, Prakash N; Telleria, Roberto; Al Khatib, Amal N; Allouzi, Siham F

2018-01-01

Different aspects of climate change, such as increased temperature, changed rainfall and higher atmospheric CO 2 concentration, all have different effects on crop yields. Process-based crop models are the most widely used tools for estimating future crop yield responses to climate change. We applied APSIM crop simulation model in a dry Mediterranean climate with Jordan as sentinel site to assess impact of climate change on wheat production at decadal level considering two climate change scenarios of representative concentration pathways (RCP) viz., RCP4.5 and RCP8.5. Impact of climatic variables alone was negative on grain yield but this adverse effect was negated when elevated atmospheric CO 2 concentrations were also considered in the simulations. Crop cycle of wheat was reduced by a fortnight for RCP4.5 scenario and by a month for RCP8.5 scenario at the approach of end of the century. On an average, a grain yield increase of 5 to 11% in near future i.e., 2010s-2030s decades, 12 to 16% in mid future i.e., 2040s-2060s decades and 9 to 16% in end of century period can be expected for moderate climate change scenario (RCP4.5) and 6 to 15% in near future, 13 to 19% in mid future and 7 to 20% increase in end of century period for a drastic climate change scenario (RCP8.5) based on different soils. Positive impact of elevated CO 2 is more pronounced in soils with lower water holding capacity with moderate increase in temperatures. Elevated CO 2 had greater positive effect on transpiration use efficiency (TUE) than negative effect of elevated mean temperatures. The change in TUE was in near perfect direct relationship with elevated CO 2 levels (R 2 >0.99) and every 100-ppm atmospheric CO 2 increase resulted in TUE increase by 2kgha -1 mm -1 . Thereby, in this environment yield gains are expected in future and farmers can benefit from growing wheat. Copyright © 2017 Elsevier B.V. All rights reserved.

Contribution of crop model structure, parameters and climate projections to uncertainty in climate change impact assessments.

PubMed

Tao, Fulu; Rötter, Reimund P; Palosuo, Taru; Gregorio Hernández Díaz-Ambrona, Carlos; Mínguez, M Inés; Semenov, Mikhail A; Kersebaum, Kurt Christian; Nendel, Claas; Specka, Xenia; Hoffmann, Holger; Ewert, Frank; Dambreville, Anaelle; Martre, Pierre; Rodríguez, Lucía; Ruiz-Ramos, Margarita; Gaiser, Thomas; Höhn, Jukka G; Salo, Tapio; Ferrise, Roberto; Bindi, Marco; Cammarano, Davide; Schulman, Alan H

2018-03-01

Climate change impact assessments are plagued with uncertainties from many sources, such as climate projections or the inadequacies in structure and parameters of the impact model. Previous studies tried to account for the uncertainty from one or two of these. Here, we developed a triple-ensemble probabilistic assessment using seven crop models, multiple sets of model parameters and eight contrasting climate projections together to comprehensively account for uncertainties from these three important sources. We demonstrated the approach in assessing climate change impact on barley growth and yield at Jokioinen, Finland in the Boreal climatic zone and Lleida, Spain in the Mediterranean climatic zone, for the 2050s. We further quantified and compared the contribution of crop model structure, crop model parameters and climate projections to the total variance of ensemble output using Analysis of Variance (ANOVA). Based on the triple-ensemble probabilistic assessment, the median of simulated yield change was -4% and +16%, and the probability of decreasing yield was 63% and 31% in the 2050s, at Jokioinen and Lleida, respectively, relative to 1981-2010. The contribution of crop model structure to the total variance of ensemble output was larger than that from downscaled climate projections and model parameters. The relative contribution of crop model parameters and downscaled climate projections to the total variance of ensemble output varied greatly among the seven crop models and between the two sites. The contribution of downscaled climate projections was on average larger than that of crop model parameters. This information on the uncertainty from different sources can be quite useful for model users to decide where to put the most effort when preparing or choosing models or parameters for impact analyses. We concluded that the triple-ensemble probabilistic approach that accounts for the uncertainties from multiple important sources provide more comprehensive information for quantifying uncertainties in climate change impact assessments as compared to the conventional approaches that are deterministic or only account for the uncertainties from one or two of the uncertainty sources. © 2017 John Wiley & Sons Ltd.

Climate variation explains a third of global crop yield variability

PubMed Central

Ray, Deepak K.; Gerber, James S.; MacDonald, Graham K.; West, Paul C.

2015-01-01

Many studies have examined the role of mean climate change in agriculture, but an understanding of the influence of inter-annual climate variations on crop yields in different regions remains elusive. We use detailed crop statistics time series for ~13,500 political units to examine how recent climate variability led to variations in maize, rice, wheat and soybean crop yields worldwide. While some areas show no significant influence of climate variability, in substantial areas of the global breadbaskets, >60% of the yield variability can be explained by climate variability. Globally, climate variability accounts for roughly a third (~32–39%) of the observed yield variability. Our study uniquely illustrates spatial patterns in the relationship between climate variability and crop yield variability, highlighting where variations in temperature, precipitation or their interaction explain yield variability. We discuss key drivers for the observed variations to target further research and policy interventions geared towards buffering future crop production from climate variability. PMID:25609225

Quantifying the impacts of climatic trend and fluctuation on crop yields in northern China.

PubMed

Qiao, Jianmin; Yu, Deyong; Liu, Yupeng

2017-10-01

Climate change plays a critical role in crop yield variations, which has attracted a great deal of concern worldwide. However, the mechanisms of how climatic trend and fluctuations affect crop yields are not well understood and need to be further investigated. Thus, using the GIS-based Environmental Policy Integrated Climate (EPIC) model, we simulated the yields of major crops (i.e., wheat, maize, and rice) and evaluated the impacts of climatic factors on crop yields in the Agro-Pastoral Transitional Zone (APTZ) of northern China between 1980 and 2010. The partial least squares regression model was used to assess the contribution rates of climatic factors (i.e., precipitation, photosynthetically active radiation (PAR), minimum temperature (T min ), maximum temperature (T max )) to the variation of crop yields. The Breaks for Additive Season and Trend (BFAST) model was adopted to decompose the climate factors into trend and fluctuation components, and the relative contributions of climate trend and fluctuation were then evaluated. The results indicated that the contributions of climatic factors to yield variations of wheat, maize, and rice were 31.7, 37.7, and 23.1%, respectively. That is, climate change had larger impacts on maize than wheat and rice. More cultivated areas were significantly and positively correlated with precipitation than with other climatic factors due to the limited precipitation in the APTZ. Also, climatic trend component had positive impacts on crop yields in the whole region, whereas the climate fluctuation was associated mainly with the areas where the crop yields decreased. This study helps improve our understanding of the mechanisms of climate change impacts on crop yields, and provides useful scientific information for designing regional-scale strategies of adaptation to climate change.

Effect of diversified crop rotations on groundwater levels and crop water productivity in the North China Plain

NASA Astrophysics Data System (ADS)

Yang, Xiaolin; Chen, Yuanquan; Pacenka, Steven; Gao, Wangsheng; Ma, Li; Wang, Guangya; Yan, Peng; Sui, Peng; Steenhuis, Tammo S.

2015-03-01

Water shortage is the major bottleneck that limits sustainable yield of agriculture in the North China Plain. Due to the over-exploitation of groundwater for irrigating the winter wheat-summer maize double cropping systems, a groundwater crisis is becoming increasingly serious. To help identify more efficient and sustainable utilization of the limited water resources, the water consumption and water use efficiency of five irrigated cropping systems were calculated and the effect of cropping systems on groundwater table changes was estimated based on a long term field experiment from 2003 to 2013 in the North China Plain interpreted using a soil-water-balance model. The five cropping systems included sweet potato → cotton → sweet potato → winter wheat-summer maize (SpCSpWS, 4-year cycle), ryegrass-cotton → peanuts → winter wheat-summer maize (RCPWS, 3-year cycle), peanuts → winter wheat-summer maize (PWS, 2-year cycle), winter wheat-summer maize (WS, 1-year cycle), and continuous cotton (Cont C). The five cropping systems had a wide range of annual average actual evapotranspiration (ETa): Cont C (533 mm/year) < SpCSpWS (556 mm/year) < PWS (615 mm/year) < RCPWS (650 mm/year) < WS rotation (734 mm/year). The sequence of the simulated annual average groundwater decline due to the five cropping systems was WS (1.1 m/year) > RCPWS (0.7 m/year) > PWS (0.6 m/year) > SPCSPWS and Cont C (0.4 m/year). The annual average economic output water use efficiency (WUEe) increased in the order SpCSpWS (11.6 yuan ¥ m-3) > RCPWS (9.0 ¥ m-3) > PWS (7.3 ¥ m-3) > WS (6.8 ¥ m-3) > Cont C (5.6 ¥ m-3) from 2003 to 2013. Results strongly suggest that diversifying crop rotations could play a critically important role in mitigating the over-exploitation of the groundwater, while ensuring the food security or boosting the income of farmers in the North China Plain.

Identification of saline soils with multi-year remote sensing of crop yields

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lobell, D; Ortiz-Monasterio, I; Gurrola, F C

2006-10-17

Soil salinity is an important constraint to agricultural sustainability, but accurate information on its variation across agricultural regions or its impact on regional crop productivity remains sparse. We evaluated the relationships between remotely sensed wheat yields and salinity in an irrigation district in the Colorado River Delta Region. The goals of this study were to (1) document the relative importance of salinity as a constraint to regional wheat production and (2) develop techniques to accurately identify saline fields. Estimates of wheat yield from six years of Landsat data agreed well with ground-based records on individual fields (R{sup 2} = 0.65).more » Salinity measurements on 122 randomly selected fields revealed that average 0-60 cm salinity levels > 4 dS m{sup -1} reduced wheat yields, but the relative scarcity of such fields resulted in less than 1% regional yield loss attributable to salinity. Moreover, low yield was not a reliable indicator of high salinity, because many other factors contributed to yield variability in individual years. However, temporal analysis of yield images showed a significant fraction of fields exhibited consistently low yields over the six year period. A subsequent survey of 60 additional fields, half of which were consistently low yielding, revealed that this targeted subset had significantly higher salinity at 30-60 cm depth than the control group (p = 0.02). These results suggest that high subsurface salinity is associated with consistently low yields in this region, and that multi-year yield maps derived from remote sensing therefore provide an opportunity to map salinity across agricultural regions.« less

[Comparison of potential yield and resource utilization efficiency of main food crops in three provinces of Northeast China under climate change].

PubMed

Wang, Xiao-yu; Yang, Xiao-guang; Sun, Shuang; Xie, Wen-juan

2015-10-01

Based on the daily data of 65 meteorological stations from 1961 to 2010 and the crop phenology data in the potential cultivation zones of thermophilic and chimonophilous crops in Northeast China, the crop potential yields were calculated through step-by-step correction method. The spatio-temporal distribution of the crop potential yields at different levels was analyzed. And then we quantified the limitations of temperature and precipitation on the crop potential yields and compared the differences in the climatic resource utilization efficiency. The results showed that the thermal potential yields of six crops (including maize, rice, spring wheat, sorghum, millet and soybean) during the period 1961-2010 deceased from west to east. The climatic potential yields of the five crops (spring wheat not included) were higher in the south than in the north. The potential yield loss rate due to temperature limitations of the six crops presented a spatial distribution pattern and was higher in the east than in the west. Among the six main crops, the yield potential loss rate due to temperature limitation of the soybean was the highest (51%), and those of the other crops fluctuated within the range of 33%-41%. The potential yield loss rate due to water limitation had an obvious regional difference, and was high in Songnen Plain and Changbai Mountains. The potential yield loss rate of spring wheat was the highest (50%), and those of the other four rainfed crops fluctuated within the range of 8%-10%. The solar energy utilization efficiency of the six main crops ranged from 0.9% to 2.7%, in the order of maize> sorghum>rice>millet>spring wheat>soybean. The precipitation utilization efficiency of the maize, sorghum, spring wheat, millet and soybean under rainfed conditions ranged from 8 to 35 kg . hm-2 . mm-1, in the order of maize>sorghum>spring wheat>millet>soybean. In those areas with lower efficiency of solar energy utilization and precipitation utilization, such as Changbai Mountains and the south of Lesser Khingan Mountains, measures could be taken to increase the efficiency of resource utilization such as rational close-planting, selection of droughtresistant varieties, proper and timely fertilization, farming for soil water storage, optimization of crop layout and so on.

Statistical Analysis of Large Simulated Yield Datasets for Studying Climate Effects

NASA Technical Reports Server (NTRS)

Makowski, David; Asseng, Senthold; Ewert, Frank; Bassu, Simona; Durand, Jean-Louis; Martre, Pierre; Adam, Myriam; Aggarwal, Pramod K.; Angulo, Carlos; Baron, Chritian;

Spatial and Temporal Uncertainty of Crop Yield Aggregations

NASA Technical Reports Server (NTRS)

Porwollik, Vera; Mueller, Christoph; Elliott, Joshua; Chryssanthacopoulos, James; Iizumi, Toshichika; Ray, Deepak K.; Ruane, Alex C.; Arneth, Almut; Balkovic, Juraj; Ciais, Philippe;

Towards a Solid Foundation of Using Remotely Sensed Solar-Induced Chlorophyll Fluorescence for Crop Monitoring and Yield Forecast

NASA Astrophysics Data System (ADS)

Chen, Y.; Sun, Y.; You, L.; Liu, Y.

2017-12-01

The growing demand for food production due to population increase coupled with high vulnerability to volatile environmental changes poses a paramount challenge for mankind in the coming century. Real-time crop monitoring and yield forecasting must be a key part of any solution to this challenge as these activities provide vital information needed for effective and efficient crop management and for decision making. However, traditional methods of crop growth monitoring (e.g., remotely sensed vegetation indices) do not directly relate to the most important function of plants - photosynthesis and therefore crop yield. The recent advance in the satellite remote sensing of Solar-Induced chlorophyll Fluorescence (SIF), an integrative photosynthetic signal from molecular origin and a direct measure of plant functions holds great promise for real-time monitoring of crop growth conditions and forecasting yields. In this study, we use satellite measurements of SIF from both the Global Ozone Monitoring Experiment-2 (GOME-2) onboard MetOp-A and the Orbiting Carbon Observatory-2 (OCO-2) satellites to estimate crop yield using both process-based and statistical models. We find that SIF-based crop yield well correlates with the global yield product Spatial Production Allocation Model (SPAM) derived from ground surveys for all major crops including maize, soybean, wheat, sorghum, and rice. The potential and challenges of using upcoming SIF satellite missions for crop monitoring and prediction will also be discussed.

Differential Impacts of Climate Change on Crops and Agricultural Regions in India

NASA Astrophysics Data System (ADS)

Sharma, A. N.

2015-12-01

As India's farmers and policymakers consider potential adaptation strategies to climate change, some questions loom large: - Which climate variables best explain the variability of crop yields? - How does the vulnerability of crop yields to climate vary regionally? - How are these risks likely to change in the future? While process-based crop modelling has started to answer many of these questions, we believe statistical approaches can complement these in improving our understanding of climate vulnerabilities and appropriate responses. We use yield data collected over three decades for more than ten food crops grown in India along with a variety of statistical approaches to answer the above questions. The ability of climate variables to explain yield variation varies greatly by crop and season, which is expected. Equally important, the ability of models to predict crop yields as well as their coefficients varies greatly by district even for districts which are relatively close to each other and similar in their agricultural practices. We believe these results encourage caution and nuance when making projections about climate impacts on crop yields in the future. Most studies about climate impacts on crop yields focus on a handful of major food crops. By extending our analysis to all the crops with long-term district level data in India as well as two growing seasons we gain a more comprehensive picture. Our results indicate that there is a great deal of variability even at relatively small scales, and that this must be taken into account if projections are to be made useful to policymakers.

Effect of Nutrient Management Planning on Crop Yield, Nitrate Leaching and Sediment Loading in Thomas Brook Watershed

NASA Astrophysics Data System (ADS)

Amon-Armah, Frederick; Yiridoe, Emmanuel K.; Ahmad, Nafees H. M.; Hebb, Dale; Jamieson, Rob; Burton, David; Madani, Ali

2013-11-01

Government priorities on provincial Nutrient Management Planning (NMP) programs include improving the program effectiveness for environmental quality protection, and promoting more widespread adoption. Understanding the effect of NMP on both crop yield and key water-quality parameters in agricultural watersheds requires a comprehensive evaluation that takes into consideration important NMP attributes and location-specific farming conditions. This study applied the Soil and Water Assessment Tool (SWAT) to investigate the effects of crop and rotation sequence, tillage type, and nutrient N application rate on crop yield and the associated groundwater leaching and sediment loss. The SWAT model was applied to the Thomas Brook Watershed, located in the most intensively managed agricultural region of Nova Scotia, Canada. Cropping systems evaluated included seven fertilizer application rates and two tillage systems (i.e., conventional tillage and no-till). The analysis reflected cropping systems commonly managed by farmers in the Annapolis Valley region, including grain corn-based and potato-based cropping systems, and a vegetable-horticulture system. ANOVA models were developed and used to assess the effects of crop management choices on crop yield and two water-quality parameters (i.e., leaching and sediment loading). Results suggest that existing recommended N-fertilizer rate can be reduced by 10-25 %, for grain crop production, to significantly lower leaching ( P > 0.05) while optimizing the crop yield. The analysis identified the nutrient N rates in combination with specific crops and rotation systems that can be used to manage leaching while balancing impacts on crop yields within the watershed.

Large Area Crop Inventory Experiment (LACIE). Feasibility of assessing crop condition and yield from LANDSAT data

NASA Technical Reports Server (NTRS)

1978-01-01

The author has identified the following significant results. Yield modelling for crop production estimation derived a means of predicting the within-a-year yield and the year-to-year variability of yield over some fixed or randomly located unit of area. Preliminary studies indicated that the requirements for interpreting LANDSAT data for yield may be sufficiently similar to those of signature extension that it is feasible to investigate the automated estimation of production. The concept of an advanced yield model consisting of both spectral and meteorological components was endorsed. Rationale for using meteorological parameters originated from known between season and near harvest dynamics in crop environmental-condition-yield relationships.

Yield model development project implementation plan

NASA Technical Reports Server (NTRS)

Ambroziak, R. A.

1982-01-01

Tasks remaining to be completed are summarized for the following major project elements: (1) evaluation of crop yield models; (2) crop yield model research and development; (3) data acquisition processing, and storage; (4) related yield research: defining spectral and/or remote sensing data requirements; developing input for driving and testing crop growth/yield models; real time testing of wheat plant process models) and (5) project management and support.

Reducing nitrate loss in tile drainage water with cover crops and water-table management systems.

PubMed

Drury, C F; Tan, C S; Welacky, T W; Reynolds, W D; Zhang, T Q; Oloya, T O; McLaughlin, N B; Gaynor, J D

2014-03-01

Nitrate lost from agricultural soils is an economic cost to producers, an environmental concern when it enters rivers and lakes, and a health risk when it enters wells and aquifers used for drinking water. Planting a winter wheat cover crop (CC) and/or use of controlled tile drainage-subirrigation (CDS) may reduce losses of nitrate (NO) relative to no cover crop (NCC) and/or traditional unrestricted tile drainage (UTD). A 6-yr (1999-2005) corn-soybean study was conducted to determine the effectiveness of CC+CDS, CC+UTD, NCC+CDS, and NCC+UTD treatments for reducing NO loss. Flow volume and NO concentration in surface runoff and tile drainage were measured continuously, and CC reduced the 5-yr flow-weighted mean (FWM) NO concentration in tile drainage water by 21 to 38% and cumulative NO loss by 14 to 16% relative to NCC. Controlled tile drainage-subirrigation reduced FWM NO concentration by 15 to 33% and cumulative NO loss by 38 to 39% relative to UTD. When CC and CDS were combined, 5-yr cumulative FWM NO concentrations and loss in tile drainage were decreased by 47% (from 9.45 to 4.99 mg N L and from 102 to 53.6 kg N ha) relative to NCC+UTD. The reductions in runoff and concomitant increases in tile drainage under CC occurred primarily because of increases in near-surface soil hydraulic conductivity. Cover crops increased corn grain yields by 4 to 7% in 2004 increased 3-yr average soybean yields by 8 to 15%, whereas CDS did not affect corn or soybean yields over the 6 yr. The combined use of a cover crop and water-table management system was highly effective for reducing NO loss from cool, humid agricultural soils. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

Regional crop yield forecasting: a probabilistic approach

NASA Astrophysics Data System (ADS)

de Wit, A.; van Diepen, K.; Boogaard, H.

2009-04-01

Information on the outlook on yield and production of crops over large regions is essential for government services dealing with import and export of food crops, for agencies with a role in food relief, for international organizations with a mandate in monitoring the world food production and trade, and for commodity traders. Process-based mechanistic crop models are an important tool for providing such information, because they can integrate the effect of crop management, weather and soil on crop growth. When properly integrated in a yield forecasting system, the aggregated model output can be used to predict crop yield and production at regional, national and continental scales. Nevertheless, given the scales at which these models operate, the results are subject to large uncertainties due to poorly known weather conditions and crop management. Current yield forecasting systems are generally deterministic in nature and provide no information about the uncertainty bounds on their output. To improve on this situation we present an ensemble-based approach where uncertainty bounds can be derived from the dispersion of results in the ensemble. The probabilistic information provided by this ensemble-based system can be used to quantify uncertainties (risk) on regional crop yield forecasts and can therefore be an important support to quantitative risk analysis in a decision making process.

The limits of crop productivity: validating theoretical estimates and determining the factors that limit crop yields in optimal environments

NASA Technical Reports Server (NTRS)

Bugbee, B.; Monje, O.

1992-01-01

Plant scientists have sought to maximize the yield of food crops since the beginning of agriculture. There are numerous reports of record food and biomass yields (per unit area) in all major crop plants, but many of the record yield reports are in error because they exceed the maximal theoretical rates of the component processes. In this article, we review the component processes that govern yield limits and describe how each process can be individually measured. This procedure has helped us validate theoretical estimates and determine what factors limit yields in optimal environments.

Spatial Sampling of Weather Data for Regional Crop Yield Simulations

NASA Technical Reports Server (NTRS)

Van Bussel, Lenny G. J.; Ewert, Frank; Zhao, Gang; Hoffmann, Holger; Enders, Andreas; Wallach, Daniel; Asseng, Senthold; Baigorria, Guillermo A.; Basso, Bruno; Biernath, Christian;

Methane production through anaerobic digestion of various energy crops grown in sustainable crop rotations.

PubMed

Amon, Thomas; Amon, Barbara; Kryvoruchko, Vitaliy; Machmüller, Andrea; Hopfner-Sixt, Katharina; Bodiroza, Vitomir; Hrbek, Regina; Friedel, Jürgen; Pötsch, Erich; Wagentristl, Helmut; Schreiner, Matthias; Zollitsch, Werner

2007-12-01

Biogas production is of major importance for the sustainable use of agrarian biomass as renewable energy source. Economic biogas production depends on high biogas yields. The project aimed at optimising anaerobic digestion of energy crops. The following aspects were investigated: suitability of different crop species and varieties, optimum time of harvesting, specific methane yield and methane yield per hectare. The experiments covered 7 maize, 2 winter wheat, 2 triticale varieties, 1 winter rye, and 2 sunflower varieties and 6 variants with permanent grassland. In the course of the vegetation period, biomass yield and biomass composition were measured. Anaerobic digestion was carried out in eudiometer batch digesters. The highest methane yields of 7500-10200 m(N)(3)ha(-1) were achieved from maize varieties with FAO numbers (value for the maturity of the maize) of 300 to 600 harvested at "wax ripeness". Methane yields of cereals ranged from 3200 to 4500 m(N)(3)ha(-1). Cereals should be harvested at "grain in the milk stage" to "grain in the dough stage". With sunflowers, methane yields between 2600 and 4550 m(N)(3)ha(-1) were achieved. There were distinct differences between the investigated sunflower varieties. Alpine grassland can yield 2700-3500 m(N)(3)CH(4)ha(-1). The methane energy value model (MEVM) was developed for the different energy crops. It estimates the specific methane yield from the nutrient composition of the energy crops. Energy crops for biogas production need to be grown in sustainable crop rotations. The paper outlines possibilities for optimising methane yield from versatile crop rotations that integrate the production of food, feed, raw materials and energy. These integrated crop rotations are highly efficient and can provide up to 320 million t COE which is 96% of the total energy demand of the road traffic of the EU-25 (the 25 Member States of the European Union).

Crop yields response to water pressures in the Ebro basin in Spain: risk and water policy implications

NASA Astrophysics Data System (ADS)

Quiroga, S.; Fernández-Haddad, Z.; Iglesias, A.

2011-02-01

The increasing pressure on water systems in the Mediterranean enhances existing water conflicts and threatens water supply for agriculture. In this context, one of the main priorities for agricultural research and public policy is the adaptation of crop yields to water pressures. This paper focuses on the evaluation of hydrological risk and water policy implications for food production. Our methodological approach includes four steps. For the first step, we estimate the impacts of rainfall and irrigation water on crop yields. However, this study is not limited to general crop production functions since it also considers the linkages between those economic and biophysical aspects which may have an important effect on crop productivity. We use statistical models of yield response to address how hydrological variables affect the yield of the main Mediterranean crops in the Ebro river basin. In the second step, this study takes into consideration the effects of those interactions and analyzes gross value added sensitivity to crop production changes. We then use Montecarlo simulations to characterize crop yield risk to water variability. Finally we evaluate some policy scenarios with irrigated area adjustments that could cope in a context of increased water scarcity. A substantial decrease in irrigated land, of up to 30% of total, results in only moderate losses of crop productivity. The response is crop and region specific and may serve to prioritise adaptation strategies.

Land-surface initialisation improves seasonal climate prediction skill for maize yield forecast.

PubMed

Ceglar, Andrej; Toreti, Andrea; Prodhomme, Chloe; Zampieri, Matteo; Turco, Marco; Doblas-Reyes, Francisco J

2018-01-22

Seasonal crop yield forecasting represents an important source of information to maintain market stability, minimise socio-economic impacts of crop losses and guarantee humanitarian food assistance, while it fosters the use of climate information favouring adaptation strategies. As climate variability and extremes have significant influence on agricultural production, the early prediction of severe weather events and unfavourable conditions can contribute to the mitigation of adverse effects. Seasonal climate forecasts provide additional value for agricultural applications in several regions of the world. However, they currently play a very limited role in supporting agricultural decisions in Europe, mainly due to the poor skill of relevant surface variables. Here we show how a combined stress index (CSI), considering both drought and heat stress in summer, can predict maize yield in Europe and how land-surface initialised seasonal climate forecasts can be used to predict it. The CSI explains on average nearly 53% of the inter-annual maize yield variability under observed climate conditions and shows how concurrent heat stress and drought events have influenced recent yield anomalies. Seasonal climate forecast initialised with realistic land-surface achieves better (and marginally useful) skill in predicting the CSI than with climatological land-surface initialisation in south-eastern Europe, part of central Europe, France and Italy.

Sensitivity and uncertainty in crop water footprint accounting: a case study for the Yellow River basin

NASA Astrophysics Data System (ADS)

Zhuo, L.; Mekonnen, M. M.; Hoekstra, A. Y.

2014-06-01

Water Footprint Assessment is a fast-growing field of research, but as yet little attention has been paid to the uncertainties involved. This study investigates the sensitivity of and uncertainty in crop water footprint (in m3 t-1) estimates related to uncertainties in important input variables. The study focuses on the green (from rainfall) and blue (from irrigation) water footprint of producing maize, soybean, rice, and wheat at the scale of the Yellow River basin in the period 1996-2005. A grid-based daily water balance model at a 5 by 5 arcmin resolution was applied to compute green and blue water footprints of the four crops in the Yellow River basin in the period considered. The one-at-a-time method was carried out to analyse the sensitivity of the crop water footprint to fractional changes of seven individual input variables and parameters: precipitation (PR), reference evapotranspiration (ET0), crop coefficient (Kc), crop calendar (planting date with constant growing degree days), soil water content at field capacity (Smax), yield response factor (Ky) and maximum yield (Ym). Uncertainties in crop water footprint estimates related to uncertainties in four key input variables: PR, ET0, Kc, and crop calendar were quantified through Monte Carlo simulations. The results show that the sensitivities and uncertainties differ across crop types. In general, the water footprint of crops is most sensitive to ET0 and Kc, followed by the crop calendar. Blue water footprints were more sensitive to input variability than green water footprints. The smaller the annual blue water footprint is, the higher its sensitivity to changes in PR, ET0, and Kc. The uncertainties in the total water footprint of a crop due to combined uncertainties in climatic inputs (PR and ET0) were about ±20% (at 95% confidence interval). The effect of uncertainties in ET0was dominant compared to that of PR. The uncertainties in the total water footprint of a crop as a result of combined key input uncertainties were on average ±30% (at 95% confidence level).

Connections Between Soil Fertility Declines, Land Use, Ethnicity, Education, and Wealth In Uganda

NASA Astrophysics Data System (ADS)

Tiemann, L. K.; Hartter, J.; Grandy, S.

2016-12-01

Food security issues are particularly acute in Uganda, where the world's 8th highest population growth rate will lead to cultivation of all land available for agriculture by 2022. Agricultural intensification in Uganda, which includes continuous cropping, mono-cropping and expansion of agriculture into marginal areas, has put unprecedented pressure on soils. In western Uganda, we surveyed 474 households, collecting demographic data, information on land use practices and perceptions of risk to crop yields and food security. We also sampled soils from maize fields associated with each surveyed household and measured total organic C and nutrients such as nitrogen (N) and phosphorus (P). Using these data, we sought to determine how risk perceptions, ethnicity, household wealth and education combine to determine land use decisions and ultimately, declines in soil organic matter and soil nutrients. We conducted our study within 5 km of an un-cultivated native tropical forest reserve, Kibale National Park (KNP), which serves as a reference point for potential soil fertility. Of 470 respondents, only 29 answered `no' when asked if they noticed year to year declines in crop yields. Across all maize fields we found soil C has been reduced by 30% and soil N by 45% relative to KNP soils and declines were more pronounced when survey respondents were Bakiga rather than Batooro. Households that indicated they were "very much" dependent upon profits from maize had a 31% increase in soil C:N while those indicating no dependence on maize profits had a significantly lower increase in soil C:N of 21%. Ethnicity and education influenced land use decisions; the Batooro and people with a lower level of education were more likely to burn their fields or crop residues. Additionally, the Bakiga were more likely to use rock P in their fields and in consequence had 108% while Batooro soils had 65% of the P found in KNP soils. Across all respondents, the top two ranked risks to crop yields and food security were weather related, with soil fertility ranked third on average, regardless of ethnicity, education or wealth. While crop yields are being noticeably affected by declining soil organic matter and soil nutrients, in particular soil N, people in this region continue to be worried more about changing weather patterns than soil fertility.

Yield and Economic Responses of Peanut to Crop Rotation Sequence

USDA-ARS?s Scientific Manuscript database

National Peanut Research Laboratory, Dawson, GA 39842. Proper crop rotation is essential to maintaining high peanut yield and quality. However, the economic considerations of maintaining or altering crop rotation sequences must incorporate the commodity prices, production costs, and yield responses...

Hyperspectral imagery for mapping crop yield for precision agriculture

USDA-ARS?s Scientific Manuscript database

Crop yield is perhaps the most important piece of information for crop management in precision agriculture. It integrates the effects of various spatial variables such as soil properties, topographic attributes, tillage, plant population, fertilization, irrigation, and pest infestations. A yield map...

Multimodel ensembles of wheat growth: many models are better than one.

PubMed

Martre, Pierre; Wallach, Daniel; Asseng, Senthold; Ewert, Frank; Jones, James W; Rötter, Reimund P; Boote, Kenneth J; Ruane, Alex C; Thorburn, Peter J; Cammarano, Davide; Hatfield, Jerry L; Rosenzweig, Cynthia; Aggarwal, Pramod K; Angulo, Carlos; Basso, Bruno; Bertuzzi, Patrick; Biernath, Christian; Brisson, Nadine; Challinor, Andrew J; Doltra, Jordi; Gayler, Sebastian; Goldberg, Richie; Grant, Robert F; Heng, Lee; Hooker, Josh; Hunt, Leslie A; Ingwersen, Joachim; Izaurralde, Roberto C; Kersebaum, Kurt Christian; Müller, Christoph; Kumar, Soora Naresh; Nendel, Claas; O'leary, Garry; Olesen, Jørgen E; Osborne, Tom M; Palosuo, Taru; Priesack, Eckart; Ripoche, Dominique; Semenov, Mikhail A; Shcherbak, Iurii; Steduto, Pasquale; Stöckle, Claudio O; Stratonovitch, Pierre; Streck, Thilo; Supit, Iwan; Tao, Fulu; Travasso, Maria; Waha, Katharina; White, Jeffrey W; Wolf, Joost

2015-02-01

Crop models of crop growth are increasingly used to quantify the impact of global changes due to climate or crop management. Therefore, accuracy of simulation results is a major concern. Studies with ensembles of crop models can give valuable information about model accuracy and uncertainty, but such studies are difficult to organize and have only recently begun. We report on the largest ensemble study to date, of 27 wheat models tested in four contrasting locations for their accuracy in simulating multiple crop growth and yield variables. The relative error averaged over models was 24-38% for the different end-of-season variables including grain yield (GY) and grain protein concentration (GPC). There was little relation between error of a model for GY or GPC and error for in-season variables. Thus, most models did not arrive at accurate simulations of GY and GPC by accurately simulating preceding growth dynamics. Ensemble simulations, taking either the mean (e-mean) or median (e-median) of simulated values, gave better estimates than any individual model when all variables were considered. Compared to individual models, e-median ranked first in simulating measured GY and third in GPC. The error of e-mean and e-median declined with an increasing number of ensemble members, with little decrease beyond 10 models. We conclude that multimodel ensembles can be used to create new estimators with improved accuracy and consistency in simulating growth dynamics. We argue that these results are applicable to other crop species, and hypothesize that they apply more generally to ecological system models. © 2014 John Wiley & Sons Ltd.

Multimodel Ensembles of Wheat Growth: More Models are Better than One

NASA Technical Reports Server (NTRS)

Martre, Pierre; Wallach, Daniel; Asseng, Senthold; Ewert, Frank; Jones, James W.; Rotter, Reimund P.; Boote, Kenneth J.; Ruane, Alex C.; Thorburn, Peter J.; Cammarano, Davide;

Multimodel Ensembles of Wheat Growth: Many Models are Better than One

NASA Technical Reports Server (NTRS)

Martre, Pierre; Wallach, Daniel; Asseng, Senthold; Ewert, Frank; Jones, James W.; Rotter, Reimund P.; Boote, Kenneth J.; Ruane, Alexander C.; Thorburn, Peter J.; Cammarano, Davide;

Cover crops support ecological intensification of arable cropping systems

NASA Astrophysics Data System (ADS)

Wittwer, Raphaël A.; Dorn, Brigitte; Jossi, Werner; van der Heijden, Marcel G. A.

2017-02-01

A major challenge for agriculture is to enhance productivity with minimum impact on the environment. Several studies indicate that cover crops could replace anthropogenic inputs and enhance crop productivity. However, so far, it is unclear if cover crop effects vary between different cropping systems, and direct comparisons among major arable production systems are rare. Here we compared the short-term effects of various cover crops on crop yield, nitrogen uptake, and weed infestation in four arable production systems (conventional cropping with intensive tillage and no-tillage; organic cropping with intensive tillage and reduced tillage). We hypothesized that cover cropping effects increase with decreasing management intensity. Our study demonstrated that cover crop effects on crop yield were highest in the organic system with reduced tillage (+24%), intermediate in the organic system with tillage (+13%) and in the conventional system with no tillage (+8%) and lowest in the conventional system with tillage (+2%). Our results indicate that cover crops are essential to maintaining a certain yield level when soil tillage intensity is reduced (e.g. under conservation agriculture), or when production is converted to organic agriculture. Thus, the inclusion of cover crops provides additional opportunities to increase the yield of lower intensity production systems and contribute to ecological intensification.

Linking ecophysiological modelling with quantitative genetics to support marker-assisted crop design for improved yields of rice (Oryza sativa) under drought stress

PubMed Central

Gu, Junfei; Yin, Xinyou; Zhang, Chengwei; Wang, Huaqi; Struik, Paul C.

2014-01-01

Background and Aims Genetic markers can be used in combination with ecophysiological crop models to predict the performance of genotypes. Crop models can estimate the contribution of individual markers to crop performance in given environments. The objectives of this study were to explore the use of crop models to design markers and virtual ideotypes for improving yields of rice (Oryza sativa) under drought stress. Methods Using the model GECROS, crop yield was dissected into seven easily measured parameters. Loci for these parameters were identified for a rice population of 94 introgression lines (ILs) derived from two parents differing in drought tolerance. Marker-based values of ILs for each of these parameters were estimated from additive allele effects of the loci, and were fed to the model in order to simulate yields of the ILs grown under well-watered and drought conditions and in order to design virtual ideotypes for those conditions. Key Results To account for genotypic yield differences, it was necessary to parameterize the model for differences in an additional trait ‘total crop nitrogen uptake’ (Nmax) among the ILs. Genetic variation in Nmax had the most significant effect on yield; five other parameters also significantly influenced yield, but seed weight and leaf photosynthesis did not. Using the marker-based parameter values, GECROS also simulated yield variation among 251 recombinant inbred lines of the same parents. The model-based dissection approach detected more markers than the analysis using only yield per se. Model-based sensitivity analysis ranked all markers for their importance in determining yield differences among the ILs. Virtual ideotypes based on markers identified by modelling had 10–36 % more yield than those based on markers for yield per se. Conclusions This study outlines a genotype-to-phenotype approach that exploits the potential value of marker-based crop modelling in developing new plant types with high yields. The approach can provide more markers for selection programmes for specific environments whilst also allowing for prioritization. Crop modelling is thus a powerful tool for marker design for improved rice yields and for ideotyping under contrasting conditions. PMID:24984712

Climatically driven yield variability of major crops in Khakassia (South Siberia)

NASA Astrophysics Data System (ADS)

Babushkina, Elena A.; Belokopytova, Liliana V.; Zhirnova, Dina F.; Shah, Santosh K.; Kostyakova, Tatiana V.

2018-06-01

We investigated the variability of yield of the three main crop cultures in the Khakassia Republic: spring wheat, spring barley, and oats. In terms of yield values, variability characteristics, and climatic response, the agricultural territory of Khakassia can be divided into three zones: (1) the Northern Zone, where crops yield has a high positive response to the amount of precipitation, May-July, and a moderately negative one to the temperatures of the same period; (2) the Central Zone, where crops yield depends mainly on temperatures; and (3) the Southern Zone, where climate has the least expressed impact on yield. The dominant pattern in the crops yield is caused by water stress during periods of high temperatures and low moisture supply with heat stress as additional reason. Differences between zones are due to combinations of temperature latitudinal gradient, precipitation altitudinal gradient, and the presence of a well-developed hydrological network and the irrigational system as moisture sources in the Central Zone. More detailed analysis shows differences in the climatic sensitivity of crops during phases of their vegetative growth and grain development and, to a lesser extent, during harvesting period. Multifactor linear regression models were constructed to estimate climate- and autocorrelation-induced variability of the crops yield. These models allowed prediction of the possibility of yield decreasing by at least 2-11% in the next decade due to increasing of the regional summer temperatures.

Climatically driven yield variability of major crops in Khakassia (South Siberia)

NASA Astrophysics Data System (ADS)

Babushkina, Elena A.; Belokopytova, Liliana V.; Zhirnova, Dina F.; Shah, Santosh K.; Kostyakova, Tatiana V.

2017-12-01

We investigated the variability of yield of the three main crop cultures in the Khakassia Republic: spring wheat, spring barley, and oats. In terms of yield values, variability characteristics, and climatic response, the agricultural territory of Khakassia can be divided into three zones: (1) the Northern Zone, where crops yield has a high positive response to the amount of precipitation, May-July, and a moderately negative one to the temperatures of the same period; (2) the Central Zone, where crops yield depends mainly on temperatures; and (3) the Southern Zone, where climate has the least expressed impact on yield. The dominant pattern in the crops yield is caused by water stress during periods of high temperatures and low moisture supply with heat stress as additional reason. Differences between zones are due to combinations of temperature latitudinal gradient, precipitation altitudinal gradient, and the presence of a well-developed hydrological network and the irrigational system as moisture sources in the Central Zone. More detailed analysis shows differences in the climatic sensitivity of crops during phases of their vegetative growth and grain development and, to a lesser extent, during harvesting period. Multifactor linear regression models were constructed to estimate climate- and autocorrelation-induced variability of the crops yield. These models allowed prediction of the possibility of yield decreasing by at least 2-11% in the next decade due to increasing of the regional summer temperatures.

Future possible crop yield scenarios under multiple SSP and RCP scenarios.

NASA Astrophysics Data System (ADS)

Sakurai, G.; Yokozawa, M.; Nishimori, M.; Okada, M.

2016-12-01

Understanding the effect of future climate change on global crop yields is one of the most important tasks for global food security. Future crop yields would be influenced by climatic factors such as the changes of temperature, precipitation and atmospheric carbon dioxide concentration. On the other hand, the effect of the changes of agricultural technologies such as crop varieties, pesticide and fertilizer input on crop yields have large uncertainty. However, not much is available on the contribution ratio of each factor under the future climate change scenario. We estimated the future global yields of four major crops (maize, soybean, rice and wheat) under three Shared Socio Economic Pathways (SSPs) and four Representative Concentration Pathways (RCPs). For this purpose, firstly, we estimated a parameter of a process based model (PRYSBI2) using a Bayesian method for each 1.125 degree spatial grid. The model parameter is relevant to the agricultural technology (we call "technological parameter" here after). Then, we analyzed the relationship between the values of technological parameter and GDP values. We found that the estimated values of the technological parameter were positively correlated with the GDP. Using the estimated relationship, we predicted future crop yield during 2020 and 2100 under SSP1, SSP2 and SSP3 scenarios and RCP 2.6, 4.5, 6.0 and 8.5. The estimated crop yields were different among SSP scenarios. However, we found that the yield difference attributable to SSPs were smaller than those attributable to CO2 fertilization effects and climate change. Particularly, the estimated effect of the change of atmospheric carbon dioxide concentration on global yields was more than four times larger than that of GDP for C3 crops.

Regional crop gross primary production and yield estimation using fused Landsat-MODIS data

NASA Astrophysics Data System (ADS)

He, M.; Kimball, J. S.; Maneta, M. P.; Maxwell, B. D.; Moreno, A.

2017-12-01

Accurate crop yield assessments using satellite-based remote sensing are of interest for the design of regional policies that promote agricultural resiliency and food security. However, the application of current vegetation productivity algorithms derived from global satellite observations are generally too coarse to capture cropland heterogeneity. Merging information from sensors with reciprocal spatial and temporal resolution can improve the accuracy of these retrievals. In this study, we estimate annual crop yields for seven important crop types -alfalfa, barley, corn, durum wheat, peas, spring wheat and winter wheat over Montana, United States (U.S.) from 2008 to 2015. Yields are estimated as the product of gross primary production (GPP) and a crop-specific harvest index (HI) at 30 m spatial resolution. To calculate GPP we used a modified form of the MOD17 LUE algorithm driven by a 30 m 8-day fused NDVI dataset constructed by blending Landsat (5 or 7) and MODIS Terra reflectance data. The fused 30-m NDVI record shows good consistency with the original Landsat and MODIS data, but provides better spatiotemporal information on cropland vegetation growth. The resulting GPP estimates capture characteristic cropland patterns and seasonal variations, while the estimated annual 30 m crop yield results correspond favorably with county-level crop yield data (r=0.96, p<0.05). The estimated crop yield performance was generally lower, but still favorable in relation to field-scale crop yield surveys (r=0.42, p<0.01). Our methods and results are suitable for operational applications at regional scales.

Analysis of the trade-off between high crop yield and low yield instability at the global scale

NASA Astrophysics Data System (ADS)

Ben-Ari, Tamara; Makowski, David

2016-10-01

Yield dynamics of major crops species vary remarkably among continents. Worldwide distribution of cropland influences both the expected levels and the interannual variability of global yields. An expansion of cultivated land in the most productive areas could theoretically increase global production, but also increase global yield instability if the most productive regions are characterized by high interannual yield variability. In this letter, we use portfolio analysis to quantify the tradeoff between the expected values and the interannual variance of global yield. We compute optimal frontiers for four crop species i.e., maize, rice, soybean and wheat and show how the distribution of cropland among large world regions can be optimized to either increase expected global crop production or decrease its interannual variability. We also show that a preferential allocation of cropland in the most productive regions can increase global expected yield at the expense of yield stability. Theoretically, optimizing the distribution of a small fraction of total cultivated areas can help find a good compromise between low instability and high crop yields at the global scale.

Food price seasonality in Africa: Measurement and extent.

PubMed

Gilbert, Christopher L; Christiaensen, Luc; Kaminski, Jonathan

2017-02-01

Everyone knows about seasonality. But what exactly do we know? This study systematically measures seasonal price gaps at 193 markets for 13 food commodities in seven African countries. It shows that the commonly used dummy variable or moving average deviation methods to estimate the seasonal gap can yield substantial upward bias. This can be partially circumvented using trigonometric and sawtooth models, which are more parsimonious. Among staple crops, seasonality is highest for maize (33 percent on average) and lowest for rice (16½ percent). This is two and a half to three times larger than in the international reference markets. Seasonality varies substantially across market places but maize is the only crop in which there are important systematic country effects. Malawi, where maize is the main staple, emerges as exhibiting the most acute seasonal differences. Reaching the Sustainable Development Goal of Zero Hunger requires renewed policy attention to seasonality in food prices and consumption.

Remote-sensing-based rapid assessment of flood crop loss to support USDA flooding decision-making

NASA Astrophysics Data System (ADS)

Di, L.; Yu, G.; Yang, Z.; Hipple, J.; Shrestha, R.

2016-12-01

Floods often cause significant crop loss in the United States. Timely and objective assessment of flood-related crop loss is very important for crop monitoring and risk management in agricultural and disaster-related decision-making in USDA. Among all flood-related information, crop yield loss is particularly important. Decision on proper mitigation, relief, and monetary compensation relies on it. Currently USDA mostly relies on field surveys to obtain crop loss information and compensate farmers' loss claim. Such methods are expensive, labor intensive, and time consumptive, especially for a large flood that affects a large geographic area. Recent studies have demonstrated that Earth observation (EO) data are useful in post-flood crop loss assessment for a large geographic area objectively, timely, accurately, and cost effectively. There are three stages of flood damage assessment, including rapid assessment, early recovery assessment, and in-depth assessment. EO-based flood assessment methods currently rely on the time-series of vegetation index to assess the yield loss. Such methods are suitable for in-depth assessment but are less suitable for rapid assessment since the after-flood vegetation index time series is not available. This presentation presents a new EO-based method for the rapid assessment of crop yield loss immediately after a flood event to support the USDA flood decision making. The method is based on the historic records of flood severity, flood duration, flood date, crop type, EO-based both before- and immediate-after-flood crop conditions, and corresponding crop yield loss. It hypotheses that a flood of same severity occurring at the same pheonological stage of a crop will cause the similar damage to the crop yield regardless the flood years. With this hypothesis, a regression-based rapid assessment algorithm can be developed by learning from historic records of flood events and corresponding crop yield loss. In this study, historic records of MODIS-based flood and vegetation products and USDA/NASS crop type and crop yield data are used to train the regression-based rapid assessment algorithm. Validation of the rapid assessment algorithm indicates it can predict the yield loss at 90% accuracy, which is accurate enough to support USDA on flood-related quick response and mitigation.

Fusion of multi-source remote sensing data for agriculture monitoring tasks

NASA Astrophysics Data System (ADS)

Skakun, S.; Franch, B.; Vermote, E.; Roger, J. C.; Becker Reshef, I.; Justice, C. O.; Masek, J. G.; Murphy, E.

2016-12-01

Remote sensing data is essential source of information for enabling monitoring and quantification of crop state at global and regional scales. Crop mapping, state assessment, area estimation and yield forecasting are the main tasks that are being addressed within GEO-GLAM. Efficiency of agriculture monitoring can be improved when heterogeneous multi-source remote sensing datasets are integrated. Here, we present several case studies of utilizing MODIS, Landsat-8 and Sentinel-2 data along with meteorological data (growing degree days - GDD) for winter wheat yield forecasting, mapping and area estimation. Archived coarse spatial resolution data, such as MODIS, VIIRS and AVHRR, can provide daily global observations that coupled with statistical data on crop yield can enable the development of empirical models for timely yield forecasting at national level. With the availability of high-temporal and high spatial resolution Landsat-8 and Sentinel-2A imagery, course resolution empirical yield models can be downscaled to provide yield estimates at regional and field scale. In particular, we present the case study of downscaling the MODIS CMG based generalized winter wheat yield forecasting model to high spatial resolution data sets, namely harmonized Landsat-8 - Sentinel-2A surface reflectance product (HLS). Since the yield model requires corresponding in season crop masks, we propose an automatic approach to extract winter crop maps from MODIS NDVI and MERRA2 derived GDD using Gaussian mixture model (GMM). Validation for the state of Kansas (US) and Ukraine showed that the approach can yield accuracies > 90% without using reference (ground truth) data sets. Another application of yearly derived winter crop maps is their use for stratification purposes within area frame sampling for crop area estimation. In particular, one can simulate the dependence of error (coefficient of variation) on the number of samples and strata size. This approach was used for estimating the area of winter crops in Ukraine for 2013-2016. The GMM-GDD approach is further extended for HLS data to provide automatic winter crop mapping at 30 m resolution for crop yield model and area estimation. In case of persistent cloudiness, addition of Sentinel-1A synthetic aperture radar (SAR) images is explored for automatic winter crop mapping.

Changes in rainfed and irrigated crop yield response to climate in the western US

NASA Astrophysics Data System (ADS)

Li, X.; Troy, T. J.

2018-06-01

As the global population increases and the climate changes, ensuring a secure food supply is increasingly important. One strategy is irrigation, which allows for crops to be grown outside their optimal climate growing regions and which buffers against climate variability. Although irrigation is a positive climate adaptation mechanism for agriculture, it has a potentially negative effect on water resources as it can lead to groundwater depletion and diminished surface water supplies. This study quantifies how crop yields are affected by climate variability and extremes and the impact of irrigation on crop yield increases under various growing-season climate conditions. To do this, we use historical climate data and county-level rainfed and irrigated crop yields for maize, soybean, winter and spring wheat over the US to analyze the relationship between climate, crop yields, and irrigation. We find that there are optimal climates, specific to each crop, where irrigation provides a benefit and other conditions where irrigation proves to have marginal, if any, benefits. Furthermore, the relationship between crop yields and climate has changed over the last decades, with a changing sensitivity in the relationship of soybean and winter wheat yields to certain climate variables, like crop reference evapotranspiration. These two conclusions have important implications for agricultural and water resource system planning, as it implies there are more optimal climate conditions where irrigation is particularly productive and regions where irrigation should be reconsidered as there is not a significant agricultural benefit and the water could be used more productively.

The implication of irrigation in climate change impact assessment: a European-wide study.

PubMed

Zhao, Gang; Webber, Heidi; Hoffmann, Holger; Wolf, Joost; Siebert, Stefan; Ewert, Frank

2015-11-01

This study evaluates the impacts of projected climate change on irrigation requirements and yields of six crops (winter wheat, winter barley, rapeseed, grain maize, potato, and sugar beet) in Europe. Furthermore, the uncertainty deriving from consideration of irrigation, CO2 effects on crop growth and transpiration, and different climate change scenarios in climate change impact assessments is quantified. Net irrigation requirement (NIR) and yields of the six crops were simulated for a baseline (1982-2006) and three SRES scenarios (B1, B2 and A1B, 2040-2064) under rainfed and irrigated conditions, using a process-based crop model, SIMPLACE . We found that projected climate change decreased NIR of the three winter crops in northern Europe (up to 81 mm), but increased NIR of all the six crops in the Mediterranean regions (up to 182 mm yr(-1) ). Climate change increased yields of the three winter crops and sugar beet in middle and northern regions (up to 36%), but decreased their yields in Mediterranean countries (up to 81%). Consideration of CO2 effects can alter the direction of change in NIR for irrigated crops in the south and of yields for C3 crops in central and northern Europe. Constraining the model to rainfed conditions for spring crops led to a negative bias in simulating climate change impacts on yields (up to 44%), which was proportional to the irrigation ratio of the simulation unit. Impacts on NIR and yields were generally consistent across the three SRES scenarios for the majority of regions in Europe. We conclude that due to the magnitude of irrigation and CO2 effects, they should both be considered in the simulation of climate change impacts on crop production and water availability, particularly for crops and regions with a high proportion of irrigated crop area. © 2015 John Wiley & Sons Ltd.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kyle, G. Page; Mueller, C.; Calvin, Katherine V.

This study assesses how climate impacts on agriculture may change the evolution of the agricultural and energy systems in meeting the end-of-century radiative forcing targets of the Representative Concentration Pathways (RCPs). We build on the recently completed ISI-MIP exercise that has produced global gridded estimates of future crop yields for major agricultural crops using climate model projections of the RCPs from the Coupled Model Intercomparison Project Phase 5 (CMIP5). For this study we use the bias-corrected outputs of the HadGEM2-ES climate model as inputs to the LPJmL crop growth model, and the outputs of LPJmL to modify inputs to themore » GCAM integrated assessment model. Our results indicate that agricultural climate impacts generally lead to an increase in global cropland, as compared with corresponding emissions scenarios that do not consider climate impacts on agricultural productivity. This is driven mostly by negative impacts on wheat, rice, other grains, and oil crops. Still, including agricultural climate impacts does not significantly increase the costs or change the technological strategies of global, whole-system emissions mitigation. In fact, to meet the most aggressive climate change mitigation target (2.6 W/m2 in 2100), the net mitigation costs are slightly lower when agricultural climate impacts are considered. Key contributing factors to these results are (a) low levels of climate change in the low-forcing scenarios, (b) adaptation to climate impacts, simulated in GCAM through inter-regional shifting in the production of agricultural goods, and (c) positive average climate impacts on bioenergy crop yields.« less

Increasing crop production in Russia and Ukraine—regional and global impacts from intensification and recultivation

NASA Astrophysics Data System (ADS)

Deppermann, Andre; Balkovič, Juraj; Bundle, Sophie-Charlotte; Di Fulvio, Fulvio; Havlik, Petr; Leclère, David; Lesiv, Myroslava; Prishchepov, Alexander V.; Schepaschenko, Dmitry

2018-02-01

Russia and Ukraine are countries with relatively large untapped agricultural potentials, both in terms of abandoned agricultural land and substantial yield gaps. Here we present a comprehensive assessment of Russian and Ukrainian crop production potentials and we analyze possible impacts of their future utilization, on a regional as well as global scale. To this end, the total amount of available abandoned land and potential yields in Russia and Ukraine are estimated and explicitly implemented in an economic agricultural sector model. We find that cereal (barley, corn, and wheat) production in Russia and Ukraine could increase by up to 64% in 2030 to 267 million tons, compared to a baseline scenario. Oilseeds (rapeseed, soybean, and sunflower) production could increase by 84% to 50 million tons, respectively. In comparison to the baseline, common net exports of Ukraine and Russia could increase by up to 86.3 million tons of cereals and 18.9 million tons of oilseeds in 2030, representing 4% and 3.6% of the global production of these crops, respectively. Furthermore, we find that production potentials due to intensification are ten times larger than potentials due to recultivation of abandoned land. Consequently, we also find stronger impacts from intensification at the global scale. A utilization of crop production potentials in Russia and Ukraine could globally save up to 21 million hectares of cropland and reduce average global crop prices by more than 3%.

Quantifying yield gaps in wheat production in Russia

NASA Astrophysics Data System (ADS)

Schierhorn, Florian; Faramarzi, Monireh; Prishchepov, Alexander V.; Koch, Friedrich J.; Müller, Daniel

2014-08-01

Crop yields must increase substantially to meet the increasing demands for agricultural products. Crop yield increases are particularly important for Russia because low crop yields prevail across Russia’s widespread and fertile land resources. However, reliable data are lacking regarding the spatial distribution of potential yields in Russia, which can be used to determine yield gaps. We used a crop growth model to determine the yield potentials and yield gaps of winter and spring wheat at the provincial level across European Russia. We modeled the annual yield potentials from 1995 to 2006 with optimal nitrogen supplies for both rainfed and irrigated conditions. Overall, the results suggest yield gaps of 1.51-2.10 t ha-1, or 44-52% of the yield potential under rainfed conditions. Under irrigated conditions, yield gaps of 3.14-3.30 t ha-1, or 62-63% of the yield potential, were observed. However, recurring droughts cause large fluctuations in yield potentials under rainfed conditions, even when the nitrogen supply is optimal, particularly in the highly fertile black soil areas of southern European Russia. The highest yield gaps (up to 4 t ha-1) under irrigated conditions were detected in the steppe areas in southeastern European Russia along the border of Kazakhstan. Improving the nutrient and water supply and using crop breeds that are adapted to the frequent drought conditions are important for reducing yield gaps in European Russia. Our regional assessment helps inform policy and agricultural investors and prioritize research that aims to increase crop production in this important region for global agricultural markets.

Monitoring Crop Yield in USA Using a Satellite-Based Climate-Variability Impact Index

NASA Technical Reports Server (NTRS)

Zhang, Ping; Anderson, Bruce; Tan, Bin; Barlow, Mathew; Myneni, Ranga

2011-01-01

A quantitative index is applied to monitor crop growth and predict agricultural yield in continental USA. The Climate-Variability Impact Index (CVII), defined as the monthly contribution to overall anomalies in growth during a given year, is derived from 1-km MODIS Leaf Area Index. The growing-season integrated CVII can provide an estimate of the fractional change in overall growth during a given year. In turn these estimates can provide fine-scale and aggregated information on yield for various crops. Trained from historical records of crop production, a statistical model is used to produce crop yield during the growing season based upon the strong positive relationship between crop yield and the CVII. By examining the model prediction as a function of time, it is possible to determine when the in-season predictive capability plateaus and which months provide the greatest predictive capacity.

The impact of Global Warming on global crop yields due to changes in pest pressure

NASA Astrophysics Data System (ADS)

Battisti, D. S.; Tewksbury, J. J.; Deutsch, C. A.

2011-12-01

A billion people currently lack reliable access to sufficient food and almost half of the calories feeding these people come from just three crops: rice, maize, wheat. Insect pests are among the largest factors affecting the yield of these three crops, but models assessing the effects of global warming on crops rarely consider changes in insect pest pressure on crop yields. We use well-established relationships between temperature and insect physiology to project climate-driven changes in pest pressure, defined as integrated population metabolism, for the three major crops. By the middle of this century, under most scenarios, insect pest pressure is projected to increase by more than 50% in temperate areas, while increases in tropical regions will be more modest. Yield relationships indicate that the largest increases in insect pest pressure are likely to occur in areas where yield is greatest, suggesting increased strain on global food markets.

The important but weakening maize yield benefit of grain filling prolongation in the US Midwest.

PubMed

Zhu, Peng; Jin, Zhenong; Zhuang, Qianlai; Ciais, Philippe; Bernacchi, Carl; Wang, Xuhui; Makowski, David; Lobell, David

2018-06-14

A better understanding of recent crop yield trends is necessary for improving the yield and maintaining food security. Several possible mechanisms have been investigated recently in order to explain the steady growth in maize yield over the US Corn-Belt, but a substantial fraction of the increasing trend remains elusive. In this study, trends in grain filling period (GFP) were identified and their relations with maize yield increase were further analyzed. By using satellite data from 2000 to 2015, an average lengthening of GFP of 0.37 days per year was found over the region, which probably results from variety renewal. Statistical analysis suggests that longer GFP accounted for roughly one-quarter (23%) of the yield increase trend by promoting kernel dry matter accumulation, yet had less yield benefit in hotter counties. Both official survey data and crop model simulations estimated a similar contribution of GFP trend to yield. If growing degree days that determines the GFP continues to prolong at the current rate for the next 50 years, yield reduction will be lessened with 25% and 18% longer GFP under Representative Concentration Pathway 2.6 (RCP 2.6) and RCP 6.0, respectively. However, this level of progress is insufficient to offset yield losses in future climates, because drought and heat stress during the GFP will become more prevalent and severe. This study highlights the need to devise multiple effective adaptation strategies to withstand the upcoming challenges in food security. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Testing an Irrigation Decision Support Tool for California Specialty Crops

NASA Astrophysics Data System (ADS)

Johnson, L.; Cahn, M.; Benzen, S.; Zaragoza, I.; Murphy, L.; Melton, F. S.; Martin, F.; Quackenbush, A.; Lockhart, T.

2015-12-01

Estimation of crop evapotranspiration supports efficiency of irrigation water management, which in turn can mitigate nitrate leaching, groundwater depletion, and provide energy savings. Past research in California and elsewhere has revealed strong relationships between photosynthetically active vegetation fraction (Fc) and crop evapotranspiration (ETc). Additional research has shown the potential of monitoring Fc by satellite remote sensing. The U.C. Cooperative Extension developed and operates CropManage (CM) as on-line database irrigation (and nitrogen) scheduling tool. CM accounts for the rapid growth and typically brief cycle of cool-season vegetables, where Fc and fraction of reference ET can change daily during canopy development. The model automates crop water requirement calculations based on reference ET data collected by California Dept. Water Resources. Empirically-derived equations are used to estimate daily Fc time-series for a given crop type primarily as a function of planting date and expected harvest date. An application programming interface (API) is under development to provide a check on modeled Fc of current crops and facilitate CM expansion to new crops. The API will enable CM to extract field scale Fc observations from NASA's Satellite Irrigation Management Support (SIMS). SIMS is mainly Landsat based and currently monitors Fc over about 8 million irrigation acres statewide, with potential for adding data from ESA/Sentinel for improved temporal resolution. In the current study, a replicated irrigation trial was performed on romaine lettuce at the USDA Agricultural Research Station in Salinas, CA. CropManage recommendations were used to guide water treatments by drip irrigation at 50%, 75%, 100% ETc replacement levels, with an added treatment at 150% ET representing grower standard practice. Experimental results indicate that yields from the 100% and 150% treatments were not significantly different and were in-line with industry average, while yields from the 75% and 50% treatments were significantly lower. Additional results will be presented with respect to a subsequent cabbage trial harvested October 2015.

Impacts of extreme heat and drought on crop yields in China: an assessment by using the DLEM-AG2 model

NASA Astrophysics Data System (ADS)

Zhang, J.; Yang, J.; Pan, S.; Tian, H.

2016-12-01

China is not only one of the major agricultural production countries with the largest population in the world, but it is also the most susceptible to climate change and extreme events. Much concern has been raised about how extreme climate has affected crop yield, which is crucial for China's food supply security. However, the quantitative assessment of extreme heat and drought impacts on crop yield in China has rarely been investigated. By using the Dynamic Land Ecosystem Model (DLEM-AG2), a highly integrated process-based ecosystem model with crop-specific simulation, here we quantified spatial and temporal patterns of extreme climatic heat and drought stress and their impacts on the yields of major food crops (rice, wheat, maize, and soybean) across China during 1981-2015, and further investigated the underlying mechanisms. Simulated results showed that extreme heat and drought stress significantly reduced national cereal production and increased the yield gaps between potential yield and rain-fed yield. The drought stress was the primary factor to reduce crop yields in the semi-arid and arid regions, and extreme heat stress slightly aggravated the yield loss. The yield gap between potential yield and rain-fed yield was larger at locations with lower precipitation. Our results suggest that a large exploitable yield gap in response to extreme climatic heat-drought stress offers an opportunity to increase productivity in China by optimizing agronomic practices, such as irrigation, fertilizer use, sowing density, and sowing date.

Crop yield response to increasing biochar rates

USDA-ARS?s Scientific Manuscript database

The benefit or detriment to crop yield from biochar application varies with biochar type/rate, soil, crop, or climate. The objective of this research was to identify yield response of cotton (Gossypium hirsutum L.), corn (Zea mayes L.), and peanut (Arachis hypogaea L.) to hardwood biochar applied at...

Impacts of ozone air pollution and temperature extremes on crop yields: Spatial variability, adaptation and implications for future food security

NASA Astrophysics Data System (ADS)

Tai, Amos P. K.; Val Martin, Maria

2017-11-01

Ozone air pollution and climate change pose major threats to global crop production, with ramifications for future food security. Previous studies of ozone and warming impacts on crops typically do not account for the strong ozone-temperature correlation when interpreting crop-ozone or crop-temperature relationships, or the spatial variability of crop-to-ozone sensitivity arising from varietal and environmental differences, leading to potential biases in their estimated crop losses. Here we develop an empirical model, called the partial derivative-linear regression (PDLR) model, to estimate the spatial variations in the sensitivities of wheat, maize and soybean yields to ozone exposures and temperature extremes in the US and Europe using a composite of multidecadal datasets, fully correcting for ozone-temperature covariation. We find generally larger and more spatially varying sensitivities of all three crops to ozone exposures than are implied by experimentally derived concentration-response functions used in most previous studies. Stronger ozone tolerance is found in regions with high ozone levels and high consumptive crop water use, reflecting the existence of spatial adaptation and effect of water constraints. The spatially varying sensitivities to temperature extremes also indicate stronger heat tolerance in crops grown in warmer regions. The spatial adaptation of crops to ozone and temperature we find can serve as a surrogate for future adaptation. Using the PDLR-derived sensitivities and 2000-2050 ozone and temperature projections by the Community Earth System Model, we estimate that future warming and unmitigated ozone pollution can combine to cause an average decline in US wheat, maize and soybean production by 13%, 43% and 28%, respectively, and a smaller decline for European crops. Aggressive ozone regulation is shown to offset such decline to various extents, especially for wheat. Our findings demonstrate the importance of considering ozone regulation as well as ozone and climate change adaptation (e.g., selecting heat- and ozone-tolerant cultivars, irrigation) as possible strategies to enhance future food security in response to imminent environmental threats.

Simulating large-scale crop yield by using perturbed-parameter ensemble method

NASA Astrophysics Data System (ADS)

Iizumi, T.; Yokozawa, M.; Sakurai, G.; Nishimori, M.

2010-12-01

Toshichika Iizumi, Masayuki Yokozawa, Gen Sakurai, Motoki Nishimori Agro-Meteorology Division, National Institute for Agro-Environmental Sciences, Japan Abstract One of concerning issues of food security under changing climate is to predict the inter-annual variation of crop production induced by climate extremes and modulated climate. To secure food supply for growing world population, methodology that can accurately predict crop yield on a large scale is needed. However, for developing a process-based large-scale crop model with a scale of general circulation models (GCMs), 100 km in latitude and longitude, researchers encounter the difficulties in spatial heterogeneity of available information on crop production such as cultivated cultivars and management. This study proposed an ensemble-based simulation method that uses a process-based crop model and systematic parameter perturbation procedure, taking maize in U.S., China, and Brazil as examples. The crop model was developed modifying the fundamental structure of the Soil and Water Assessment Tool (SWAT) to incorporate the effect of heat stress on yield. We called the new model PRYSBI: the Process-based Regional-scale Yield Simulator with Bayesian Inference. The posterior probability density function (PDF) of 17 parameters, which represents the crop- and grid-specific features of the crop and its uncertainty under given data, was estimated by the Bayesian inversion analysis. We then take 1500 ensemble members of simulated yield values based on the parameter sets sampled from the posterior PDF to describe yearly changes of the yield, i.e. perturbed-parameter ensemble method. The ensemble median for 27 years (1980-2006) was compared with the data aggregated from the county yield. On a country scale, the ensemble median of the simulated yield showed a good correspondence with the reported yield: the Pearson’s correlation coefficient is over 0.6 for all countries. In contrast, on a grid scale, the correspondence is still high in most grids regardless of the countries. However, the model showed comparatively low reproducibility in the slope areas, such as around the Rocky Mountains in South Dakota, around the Great Xing'anling Mountains in Heilongjiang, and around the Brazilian Plateau. As there is a wide-ranging local climate conditions in the complex terrain, such as the slope of mountain, the GCM grid-scale weather inputs is likely one of major sources of error. The results of this study highlight the benefits of the perturbed-parameter ensemble method in simulating crop yield on a GCM grid scale: (1) the posterior PDF of parameter could quantify the uncertainty of parameter value of the crop model associated with the local crop production aspects; (2) the method can explicitly account for the uncertainty of parameter value in the crop model simulations; (3) the method achieve a Monte Carlo approximation of probability of sub-grid scale yield, accounting for the nonlinear response of crop yield to weather and management; (4) the method is therefore appropriate to aggregate the simulated sub-grid scale yields to a grid-scale yield and it may be a reason for high performance of the model in capturing inter-annual variation of yield.

Tuber yield and quality characteristics of potatoes for off-season crops in a Mediterranean environment.

PubMed

Ierna, Anita

2010-01-15

There is little research on evaluating the compatibility of potatoes for double cropping in southern Italy. The aim of this investigation was to assess tuber yield and some qualitative traits of tubers such as skin colour, tuber dry matter content and tuber nitrate content, both in winter-spring and in summer-autumn crops, as influenced by genotype and harvest time. Yield, skin colour and dry matter content of tubers were higher in the winter-spring crop than in the summer-autumn crop, attributable to the advantageous lag time in spring between solar radiation and temperatures and the disadvantageous lag in autumn. Spunta and Arinda performed well within each crop season, whereas Ninfa showed an important yield loss in autumn. In both off-season crops, delaying tuber harvest until leaf senescence increased yield and improved quality attributes such as tuber dry matter content and skin colour, whereas nitrate contents significantly decreased in the winter-spring crop and increased in the summer-autumn crop. Ninfa showed less tendency than Arinda and Spunta to accumulate nitrate in tubers in both off-season crops. It might be advantageous to examine in further research which mechanisms sustain compatibility to the autumn and assess other quality characteristics for the fresh market in the contrasting climatic conditions of the two off-season crops. Copyright (c) 2009 Society of Chemical Industry.

Water Footprint of a Super-intensive Olive Grove Under Mediterranean Climate using Ground-based Evapotranspiration Measurements and Remote Sensing

NASA Astrophysics Data System (ADS)

Nogueira, A. M.; Paço, T. A.; Silvestre, J. C.; Gonzalez, L. F.; Santos, F. L.; Pereira, L. S.

2012-04-01

The water footprint of a crop is the volume of water that is necessary to produce it, therefore relating crop water requirements and yield. The components of water footprint, blue, green and grey water footprints, refer to the volumes of respectively, surface and groundwater, rainfall, and water required to assimilate pollution, that are used to produce the crop yield. Determining blue and green water footprints is generally achieved using estimates of evapotranspiration obtained with a crop coefficient approach and of a water use ratio. In the present study we have used evapotranspiration measurements to estimate the water footprint of a super-intensive olive grove in southern Portugal (cv. Arbequina, drip irrigated, 1975 trees ha-1), during 2011. The crop water requirements were measured using a heat dissipation sap flow technique, to determine transpiration and using the eddy covariance method that allowed the direct measurement of evapotranspiration, applied to non-flat terrain conditions. This technique was used for a short period, from end of July till the end of August, while the sap flow measurements were performed from May to December, hence allowing the extension of the data series; for other periods estimates were used. Evapotranspiration measured directly with the eddy covariance method was in average close to 3 mm d-1 and the ratio of evapotranspiration to reference evapotranspiration approached 0.6 for the same period. Plants were under a moderate water stress, as confirmed with predawn leaf water potential measurements. The water footprint of the olive crop under study was lower than the water footprint simulations reported in literature. A possible reason relates to the density of plantation, yield and irrigation crops management. The irrigated olive grove under study had a high yield, which compensates for a high water consumption, leading to a water footprint lower than the ones of rainfed or less dense groves. Furthermore, as evapotranspiration measurements were used to calculate water footprint instead of the common procedure (using evapotranspiration estimates), this might have also introduced some differences. The potential of using remote sensing techniques for the assessment of water footprint of crops has been discussed in recent literature. It can provide estimates of actual evapotranspiration, of precipitation, of surface runoff and of irrigation needs when associated with modelling. In this study we further compare the water footprint estimates using in situ evapotranspiration measurements and water footprint estimates using remote sensing techniques. A comparison with the irrigation records for this particular olive orchard will be used to validate the approaches.

Sensitivity of simulated maize crop yields to regional climate in the Southwestern United States

NASA Astrophysics Data System (ADS)

Kim, S.; Myoung, B.; Stack, D.; Kim, J.; Hatzopoulos, N.; Kafatos, M.

2013-12-01

The sensitivity of maize yield to the regional climate in the Southwestern United States (SW US) has been investigated by using a crop-yield simulation model (APSIM) in conjunction with meteorological forcings (daily minimum and maximum temperature, precipitation, and radiation) from the North American Regional Reanalysis (NARR) dataset. The primary focus of this study is to look at the effects of interannual variations of atmospheric components on the crop productivity in the SW US over the 21-year period (1991 to 2011). First of all, characteristics and performance of APSIM was examined by comparing simulated maize yields with observed yields from United States Department of Agriculture (USDA) and the leaf-area index (LAI) from MODIS satellite data. Comparisons of the simulated maize yield with the available observations show that the crop model can reasonably reproduce observed maize yields. Sensitivity tests were performed to assess the relative contribution of each climate driver to regional crop yield. Sensitivity experiments show that potential crop production responds nonlinearly to climate drivers and the yield sensitivity varied among geographical locations depending on their mean climates. Lastly, a detailed analysis of both the spatial and temporal variations of each climate driver in the regions where maize is actually grown in three states (CA, AZ, and NV) in the SW US was performed.

Agricultural Management Practices Explain Variation in Global Yield Gaps of Major Crops

NASA Astrophysics Data System (ADS)

Mueller, N. D.; Gerber, J. S.; Ray, D. K.; Ramankutty, N.; Foley, J. A.

2010-12-01

The continued expansion and intensification of agriculture are key drivers of global environmental change. Meeting a doubling of food demand in the next half-century will further induce environmental change, requiring either large cropland expansion into carbon- and biodiversity-rich tropical forests or increasing yields on existing croplands. Closing the “yield gaps” between the most and least productive farmers on current agricultural lands is a necessary and major step towards preserving natural ecosystems and meeting future food demand. Here we use global climate, soils, and cropland datasets to quantify yield gaps for major crops using equal-area climate analogs. Consistent with previous studies, we find large yield gaps for many crops in Eastern Europe, tropical Africa, and parts of Mexico. To analyze the drivers of yield gaps, we collected sub-national agricultural management data and built a global dataset of fertilizer application rates for over 160 crops. We constructed empirical crop yield models for each climate analog using the global management information for 17 major crops. We find that our climate-specific models explain a substantial amount of the global variation in yields. These models could be widely applied to identify management changes needed to close yield gaps, analyze the environmental impacts of agricultural intensification, and identify climate change adaptation techniques.

Wildlife-friendly farming increases crop yield: evidence for ecological intensification

PubMed Central

Pywell, Richard F.; Heard, Matthew S.; Woodcock, Ben A.; Hinsley, Shelley; Ridding, Lucy; Nowakowski, Marek; Bullock, James M.

2015-01-01

Ecological intensification has been promoted as a means to achieve environmentally sustainable increases in crop yields by enhancing ecosystem functions that regulate and support production. There is, however, little direct evidence of yield benefits from ecological intensification on commercial farms growing globally important foodstuffs (grains, oilseeds and pulses). We replicated two treatments removing 3 or 8% of land at the field edge from production to create wildlife habitat in 50–60 ha patches over a 900 ha commercial arable farm in central England, and compared these to a business as usual control (no land removed). In the control fields, crop yields were reduced by as much as 38% at the field edge. Habitat creation in these lower yielding areas led to increased yield in the cropped areas of the fields, and this positive effect became more pronounced over 6 years. As a consequence, yields at the field scale were maintained—and, indeed, enhanced for some crops—despite the loss of cropland for habitat creation. These results suggested that over a 5-year crop rotation, there would be no adverse impact on overall yield in terms of monetary value or nutritional energy. This study provides a clear demonstration that wildlife-friendly management which supports ecosystem services is compatible with, and can even increase, crop yields. PMID:26423846

Closing the Yield Gap of Sugar Beet in the Netherlands-A Joint Effort.

PubMed

Hanse, Bram; Tijink, Frans G J; Maassen, Jurgen; van Swaaij, Noud

2018-01-01

The reform of the European Union's sugar regime caused potential decreasing beet prices. Therefore, the Speeding Up Sugar Yield (SUSY) project was initiated. At the start, a 3 × 15 target was formulated: in 2015 the national average sugar yield in the Netherlands equals 15 t/ha (60% of the sugar beet potential) and the total variable costs 15 euro/t sugar beet, aspiring a saving on total variable costs and a strong increase in sugar yield. Based on their average sugar yield in 2000-2004, 26 pairs of "type top" (high yielding) and "type average" (average yielding) growers were selected from all sugar beet growing regions in the Netherlands. On the fields of those farmers, all measures of sugar beet cultivation were investigated, including cost calculation and recording phytopathological, agronomical and soil characteristics in 2006 and 2007. Although there was no significant difference in total variable costs, the "type top" growers yielded significantly 20% more sugar in each year compared to the "type average" growers. Therefore, the most profitable strategy for the growers is maximizing sugar yield and optimizing costs. The difference in sugar yield between growers could be explained by pests and diseases (50%), weed control (30%), soil structure (25%) and sowing date (14%), all interacting with each other. The SUSY-project revealed the effect of the grower's management on sugar yield. As a follow up for the SUSY-project, a growers' guide "Suikerbietsignalen" was published, Best Practice study groups of growers were formed and trainings and workshops were given and field days organized. Further, the benchmarking and feedback on the crop management recordings and the extension on variety choice, sowing performance, foliar fungi control and harvest losses were intensified. On the research part, a resistance breaking strain of the Beet Necrotic Yellow Vein Virus (BNYVV) and a new foliar fungus, Stemphylium beticola , were identified and options for control were tested, and implemented in growers practices. The joint efforts of sugar industry, sugar beet research and growers resulted in a raise in sugar yield from 10.6 t/ha in 2002-2006 to 13.8 t/ha in 2012-2016.

7 CFR 400.651 - Definitions.

Code of Federal Regulations, 2012 CFR

2012-01-01

... unadjusted transitional yields and dividing the sum by the number of yields contained in the database, which will always contain at least four yields. The database may contain up to 10 consecutive crop years of... catastrophic risk protection. Crop of economic significance. A crop that has either contributed in the previous...

7 CFR 400.651 - Definitions.

Code of Federal Regulations, 2014 CFR

2014-01-01

... unadjusted transitional yields and dividing the sum by the number of yields contained in the database, which will always contain at least four yields. The database may contain up to 10 consecutive crop years of... catastrophic risk protection. Crop of economic significance. A crop that has either contributed in the previous...

7 CFR 400.651 - Definitions.

Code of Federal Regulations, 2013 CFR

2013-01-01

... unadjusted transitional yields and dividing the sum by the number of yields contained in the database, which will always contain at least four yields. The database may contain up to 10 consecutive crop years of... catastrophic risk protection. Crop of economic significance. A crop that has either contributed in the previous...

7 CFR 400.651 - Definitions.

Code of Federal Regulations, 2010 CFR

2010-01-01

... unadjusted transitional yields and dividing the sum by the number of yields contained in the database, which will always contain at least four yields. The database may contain up to 10 consecutive crop years of... catastrophic risk protection. Crop of economic significance. A crop that has either contributed in the previous...

7 CFR 400.651 - Definitions.

Code of Federal Regulations, 2011 CFR

2011-01-01

... unadjusted transitional yields and dividing the sum by the number of yields contained in the database, which will always contain at least four yields. The database may contain up to 10 consecutive crop years of... catastrophic risk protection. Crop of economic significance. A crop that has either contributed in the previous...

What's holding us back? Raising the alfalfa yield bar

USDA-ARS?s Scientific Manuscript database

Measuring yield of commodity crops is easy – weight and moisture content are determined on delivery. Consequently, reports of production or yield for grain crops can be made reliably to the agencies that track crop production, such as the USDA-National Agricultural Statistics Service (NASS). The s...

Temporally dependent pollinator competition and facilitation with mass flowering crops affects yield in co-blooming crops

PubMed Central

Grab, Heather; Blitzer, Eleanor J.; Danforth, Bryan; Loeb, Greg; Poveda, Katja

2017-01-01

One of the greatest challenges in sustainable agricultural production is managing ecosystem services, such as pollination, in ways that maximize crop yields. Most efforts to increase services by wild pollinators focus on management of natural habitats surrounding farms or non-crop habitats within farms. However, mass flowering crops create resource pulses that may be important determinants of pollinator dynamics. Mass bloom attracts pollinators and it is unclear how this affects the pollination and yields of other co-blooming crops. We investigated the effects of mass flowering apple on the pollinator community and yield of co-blooming strawberry on farms spanning a gradient in cover of apple orchards in the landscape. The effect of mass flowering apple on strawberry was dependent on the stage of apple bloom. During early and peak apple bloom, pollinator abundance and yield were reduced in landscapes with high cover of apple orchards. Following peak apple bloom, pollinator abundance was greater on farms with high apple cover and corresponded with increased yields on these farms. Spatial and temporal overlap between mass flowering and co-blooming crops alters the strength and direction of these dynamics and suggests that yields can be optimized by designing agricultural systems that avoid competition while maximizing facilitation. PMID:28345653

African crop yield reductions due to increasingly unbalanced Nitrogen and Phosphorus consumption

NASA Astrophysics Data System (ADS)

van der Velde, Marijn; Folberth, Christian; Balkovič, Juraj; Ciais, Philippe; Fritz, Steffen; Janssens, Ivan A.; Obersteiner, Michael; See, Linda; Skalský, Rastislav; Xiong, Wei; Peñuealas, Josep

2014-05-01

The impact of soil nutrient depletion on crop production has been known for decades, but robust assessments of the impact of increasingly unbalanced nitrogen (N) and phosphorus (P) application rates on crop production are lacking. Here, we use crop response functions based on 741 FAO maize crop trials and EPIC crop modeling across Africa to examine maize yield deficits resulting from unbalanced N:P applications under low, medium, and high input scenarios, for past (1975), current, and future N:P mass ratios of respectively, 1:0.29, 1:0.15, and 1:0.05. At low N inputs (10 kg/ha), current yield deficits amount to 10% but will increase up to 27% under the assumed future N:P ratio, while at medium N inputs (50 kg N/ha), future yield losses could amount to over 40%. The EPIC crop model was then used to simulate maize yields across Africa. The model results showed relative median future yield reductions at low N inputs of 40%, and 50% at medium and high inputs, albeit with large spatial variability. Dominant low-quality soils such as Ferralsols, which are strongly adsorbing P, and Arenosols with a low nutrient retention capacity, are associated with a strong yield decline, although Arenosols show very variable crop yield losses at low inputs. Optimal N:P ratios, i.e. those where the lowest amount of applied P produces the highest yield (given N input) where calculated with EPIC to be as low as 1:0.5. Finally, we estimated the additional P required given current N inputs, and given N inputs that would allow Africa to close yield gaps (ca. 70%). At current N inputs, P consumption would have to increase 2.3-fold to be optimal, and to increase 11.7-fold to close yield gaps. The P demand to overcome these yield deficits would provide a significant additional pressure on current global extraction of P resources.

Land Use, Yield and Quality Changes of Minor Field Crops: Is There Superseded Potential to Be Reinvented in Northern Europe?

PubMed

Peltonen-Sainio, Pirjo; Jauhiainen, Lauri; Lehtonen, Heikki

2016-01-01

Diversification of agriculture was one of the strengthened aims of the greening payment of European Agricultural Policy (CAP) as diversification provides numerous ecosystems services compared to cereal-intensive crop rotations. This study focuses on current minor crops in Finland that have potential for expanded production and considers changes in their cropping areas, yield trends, breeding gains, roles in crop rotations and potential for improving resilience. Long-term datasets of Natural Resources Institute Finland and farmers' land use data from the Agency of Rural Affairs were used to analyze the above-mentioned trends and changes. The role of minor crops in rotations declined when early and late CAP periods were compared and that of cereal monocultures strengthened. Genetic yield potentials of minor crops have increased as also genetic improvements in quality traits, although some typical trade-offs with improved yields have also appeared. However, the gap between potential and attained yields has expanded, depending on the minor crop, as national yield trends have either stagnated or declined. When comparing genetic improvements of minor crops to those of the emerging major crop, spring wheat, breeding achievements in minor crops were lower. It was evident that the current agricultural policies in the prevailing market and the price environment have not encouraged cultivation of minor crops but further strengthened the role of cereal monocultures. We suggest optimization of agricultural land use, which is a core element of sustainable intensification, as a future means to couple long-term environmental sustainability with better success in economic profitability and social acceptability. This calls for development of effective policy instruments to support farmer's diversification actions.

Land Use, Yield and Quality Changes of Minor Field Crops: Is There Superseded Potential to Be Reinvented in Northern Europe?

PubMed Central

Peltonen-Sainio, Pirjo; Jauhiainen, Lauri; Lehtonen, Heikki

2016-01-01

Diversification of agriculture was one of the strengthened aims of the greening payment of European Agricultural Policy (CAP) as diversification provides numerous ecosystems services compared to cereal-intensive crop rotations. This study focuses on current minor crops in Finland that have potential for expanded production and considers changes in their cropping areas, yield trends, breeding gains, roles in crop rotations and potential for improving resilience. Long-term datasets of Natural Resources Institute Finland and farmers’ land use data from the Agency of Rural Affairs were used to analyze the above-mentioned trends and changes. The role of minor crops in rotations declined when early and late CAP periods were compared and that of cereal monocultures strengthened. Genetic yield potentials of minor crops have increased as also genetic improvements in quality traits, although some typical trade-offs with improved yields have also appeared. However, the gap between potential and attained yields has expanded, depending on the minor crop, as national yield trends have either stagnated or declined. When comparing genetic improvements of minor crops to those of the emerging major crop, spring wheat, breeding achievements in minor crops were lower. It was evident that the current agricultural policies in the prevailing market and the price environment have not encouraged cultivation of minor crops but further strengthened the role of cereal monocultures. We suggest optimization of agricultural land use, which is a core element of sustainable intensification, as a future means to couple long-term environmental sustainability with better success in economic profitability and social acceptability. This calls for development of effective policy instruments to support farmer’s diversification actions. PMID:27870865

Differences, or lack thereof, in wheat and maize yields under three low-warming scenarios

NASA Astrophysics Data System (ADS)

Tebaldi, Claudia; Lobell, David

2018-06-01

The availability of climate model experiments under three alternative scenarios stabilizing at warming targets inspired by the COP21 agreements (a 1.5 °C not exceed, a 1.5 °C with overshoot and a 2.0 °C) makes it possible to assess future expected changes in global yields for two staple crops, wheat and maize. In this study an empirical model of the relation between crop yield anomalies and temperature and precipitation changes, with or without the inclusion of CO2 fertilization effects, is used to produce ensembles of time series of yield outcomes on a yearly basis over the course of the 21st century, for each scenario. The 21st century is divided into 10 year windows starting from 2020, within which the statistical significance and the magnitude of the differences in yield changes between pairs of scenarios are assessed, thus evaluating if and when benefits of mitigations appear, and how substantial they are. Additionally, a metric of extreme heat tailored to the individual crops (number of days during the growing season above a crop-specific threshold) is used to measure exposure to harmful temperatures under the different scenarios. If CO2 effects are not included, statistically significant differences in yields of both crops appear as early as the 2030s but the magnitude of the differences remains below 3% of the historical baseline in all cases until the second part of the century. In the later decades of the 21st century, differences remain small and eventually stop being statistically significant between the two scenarios stabilizing at 1.5 °C, while differences between these two lower scenarios and the 2.0 °C scenario grow to about 4%. The inclusion of CO2 effects erases all significant benefits of mitigation for wheat, while the significance of differences is maintained for maize yields between the higher and the two lower scenarios, albeit with smaller benefits in magnitude. Changes in extremes are significant within each of the scenarios but the differences between any pair of them, even by the end of the century are only on the order of a few days per growing season, and these small changes appear limited to a few localized areas of the growing regions. These results seem to suggest that for globally averaged yields of these two grains the lower targets put forward by the Paris agreement does not change substantially the expected impacts on yields that are caused by warming temperatures under the pre-existing 2.0 °C target.

National Variation in Crop Yield Production Functions

NASA Astrophysics Data System (ADS)

Devineni, N.; Rising, J. A.

2017-12-01

A new multilevel model for yield prediction at the county scale using regional climate covariates is presented in this paper. A new crop specific water deficit index, growing degree days, extreme degree days, and time-trend as an approximation of technology improvements are used as predictors to estimate annual crop yields for each county from 1949 to 2009. Every county in the United States is allowed to have unique parameters describing how these weather predictors are related to yield outcomes. County-specific parameters are further modeled as varying according to climatic characteristics, allowing the prediction of parameters in regions where crops are not currently grown and into the future. The structural relationships between crop yield and regional climate as well as trends are estimated simultaneously. All counties are modeled in a single multilevel model with partial pooling to automatically group and reduce estimation uncertainties. The model captures up to 60% of the variability in crop yields after removing the effect of technology, does well in out of sample predictions and is useful in relating the climate responses to local bioclimatic factors. We apply the predicted growing models in a cost-benefit analysis to identify the most economically productive crop in each county.

Assessing the environmental impacts of soil compaction in Life Cycle Assessment.

PubMed

Stoessel, Franziska; Sonderegger, Thomas; Bayer, Peter; Hellweg, Stefanie

2018-07-15

Maintaining biotic capacity is of key importance with regard to global food and biomass provision. One reason for productivity loss is soil compaction. In this paper, we use a statistical empirical model to assess long-term yield losses through soil compaction in a regionalized manner, with global coverage and for different agricultural production systems. To facilitate the application of the model, we provide an extensive dataset including crop production data (with 81 crops and corresponding production systems), related machinery application, as well as regionalized soil texture and soil moisture data. Yield loss is modeled for different levels of soil depth (0-25cm, 25-40cm and >40cm depth). This is of particular relevance since compaction in topsoil is classified as reversible in the short term (approximately four years), while recovery of subsoil layers takes much longer. We derive characterization factors quantifying the future average annual yield loss as a fraction of the current yield for 100years and applicable in Life Cycle Assessment studies of agricultural production. The results show that crops requiring enhanced machinery inputs, such as potatoes, have a major influence on soil compaction and yield losses, while differences between mechanized production systems (organic and integrated production) are small. The spatial variations of soil moisture and clay content are reflected in the results showing global hotspot regions especially susceptible to soil compaction, e.g. the South of Brazil, the Caribbean Islands, Central Africa, and the Maharashtra district of India. The impacts of soil compaction can be substantial, with highest annual yield losses in the range of 0.5% (95% percentile) due to one year of potato production (cumulated over 100y this corresponds to a one-time loss of 50% of the present yield). These modeling results demonstrate the necessity for including soil compaction effects in Life Cycle Impact Assessment. Copyright © 2018 Elsevier B.V. All rights reserved.

Influence of poultry litter and double cropping on soybean yield

USDA-ARS?s Scientific Manuscript database

Continuous cultivation of mono-cropping systems coupled with inorganic fertilizer consumption has led to a decline in soil fertility, negatively influencing crop yields. Poultry litter application and double cropping are two management practices that could be used with conservation tillage to increa...

Soil total carbon and crop yield affected by crop rotation and cultural practice

USDA-ARS?s Scientific Manuscript database

Stacked crop rotation and improved cultural practice have been used to control pests, but their impact on soil organic C (SOC) and crop yield are lacking. We evaluated the effects of stacked vs. alternate-year rotations and cultural practices on SOC at the 0- to 125-cm depth and annualized crop yiel...

Adapt-N: A Cloud-Based Computational Tool for Crop Nitrogen Management that Improves Production and Environmental Outcomes

NASA Astrophysics Data System (ADS)

van Es, Harold; Sela, Shai; Marjerison, Rebecca; Melkonian, Jeff

2016-04-01

Maize production accounts for the largest share of crop land area in the US and is the largest consumer of nitrogen (N) fertilizers, while also having low N use efficiency. Routine application of N fertilizer has led to well-documented environmental problems and social costs. Adapt-N is a computational tool that combines soil, crop and management information with near-real-time weather data to estimate optimum N application rates for maize. Its cloud-based implementation allows for tracking and timely management of the dynamic gains and losses of N in cropping systems. This presentation will provide an overview of the tool and its implementation of farms. We also evaluated Adapt-N tool during five growing seasons (2011-to-2015) using a large dataset of both side-by-side (SBS) strip trials and multi-N rate experiments. The SBS trials consisted of 115 on-farm strip trials in Iowa and New York, each trial including yield results from replicated field-scale plots involving two sidedress N rate treatments: Adapt-N-estimated and Grower-selected (conventional). The Adapt-N rates were on average 53 and 30 kg ha-1 lower than Grower rates for NY and IA, respectively (-34% overall), with no statistically significant difference in yields. On average, Adapt-N rates increased grower profits by 63.9 ha-1 and resulted in an Adapt-N estimated decrease of 28 kg ha-1 (38%) in environmental N losses. A second set of strip trials involved multiple N-rate experiments in Wisconsin, Indiana, Ohio and NY, which allowed for the comparison of Adapt-N and conventional static recommendations to an Economic Optimum N Rate (determined through response model fitting). These trials demonstrated that Adapt-N can achieve the same profitability with greatly reduced average N inputs of 20 lbs N/ac for the Midwest and 65 lbs N/ac for the Northeast, resulting in significantly lower environmental losses. In conclusion, Adapt-N recommendations resulted in both increased growers profits and decreased environmental N losses by accounting for variable site and weather conditions.

Cura Annonae-Chemically Boosting Crop Yields Through Metabolic Feeding of a Plant Signaling Precursor.

PubMed

Vocadlo, David J

2017-05-22

The cream of the crop: With the world facing a projected shortfall of crops by 2050, new approaches are needed to boost crop yields. Metabolic feeding of plants with photocaged trehalose-6-phosphate (Tre6P) can increase levels of the signaling metabolite Tre6P in the plant. Reprogramming of cellular metabolism by Tre6P stimulates a program of plant growth and enhanced crop yields, while boosting starch content. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Spatial variability in nutrient transport by HUC8, state, and subbasin based on Mississippi/Atchafalaya River Basin SPARROW models

USGS Publications Warehouse

Robertson, Dale M.; Saad, David A.; Schwarz, Gregory E.

2014-01-01

Nitrogen (N) and phosphorus (P) loading from the Mississippi/Atchafalaya River Basin (MARB) has been linked to hypoxia in the Gulf of Mexico. With geospatial datasets for 2002, including inputs from wastewater treatment plants (WWTPs), and monitored loads throughout the MARB, SPAtially Referenced Regression On Watershed attributes (SPARROW) watershed models were constructed specifically for the MARB, which reduced simulation errors from previous models. Based on these models, N loads/yields were highest from the central part (centered over Iowa and Indiana) of the MARB (Corn Belt), and the highest P yields were scattered throughout the MARB. Spatial differences in yields from previous studies resulted from different descriptions of the dominant sources (N yields are highest with crop-oriented agriculture and P yields are highest with crop and animal agriculture and major WWTPs) and different descriptions of downstream transport. Delivered loads/yields from the MARB SPARROW models are used to rank subbasins, states, and eight-digit Hydrologic Unit Code basins (HUC8s) by N and P contributions and then rankings are compared with those from other studies. Changes in delivered yields result in an average absolute change of 1.3 (N) and 1.9 (P) places in state ranking and 41 (N) and 69 (P) places in HUC8 ranking from those made with previous national-scale SPARROW models. This information may help managers decide where efforts could have the largest effects (highest ranked areas) and thus reduce hypoxia in the Gulf of Mexico.

Management of Lesion Nematodes and Potato Early Dying with Rotation Crops

PubMed Central

LaMondia, J.A.

2006-01-01

Soil-incorporated rotation/green manure crops were evaluated for management of potato early dying caused by Verticillium dahliae and Pratylenchus penetrans. After two years of rotation/green manure and a subsequent potato crop, P. penetrans numbers were less after ‘Saia’ oat/‘Polynema’ marigold, ‘Triple S’ sorghum-sudangrass, or ‘Garry’ oat than ‘Superior’ potato or ‘Humus’ rapeseed. The area under the disease progress curve (AUDPC) for early dying was lowest after Saia oat/marigold, and tuber yields were greater than continuous potato after all crops except sorghum-sudangrass. Saia oat/marigold crops resulted in the greatest tuber yields. After one year of rotation/green manure, a marigold crop increased tuber yields and reduced AUDPC and P. penetrans. In the second potato crop after a single year of rotation, plots previously planted to marigolds had reduced P. penetrans densities and AUDPC and increased tuber yield. Rapeseed supported more P. penetrans than potato, but had greater yields. After two years of rotation/green manure crops and a subsequent potato crop, continuous potato had the highest AUDPC and lowest tuber weight. Rotation with Saia oats (2 yr) and Rudbeckia hirta (1 yr) reduced P. penetrans and increased tuber yields. AUDPC was lowest after R. hirta. Two years of sorghum-sudangrass did not affect P. penetrans, tuber yield or AUDPC. These results demonstrate that P. penetrans may be reduced by one or two years of rotation to non-host or antagonistic plants such as Saia oat, Polynema marigold, or R. hirta and that nematode control may reduce the severity of potato early dying. PMID:19259461

Crop yield response to climate change varies with crop spatial distribution pattern

DOE PAGES

Leng, Guoyong; Huang, Maoyi

2017-05-03

The linkage between crop yield and climate variability has been confirmed in numerous studies using statistical approaches. A crucial assumption in these studies is that crop spatial distribution pattern is constant over time. Here, we explore how changes in county-level corn spatial distribution pattern modulate the response of its yields to climate change at the state level over the Contiguous United States. Our results show that corn yield response to climate change varies with crop spatial distribution pattern, with distinct impacts on the magnitude and even the direction at the state level. Corn yield is predicted to decrease by 20~40%more » by 2050s when considering crop spatial distribution pattern changes, which is 6~12% less than the estimates with fixed cropping pattern. The beneficial effects are mainly achieved by reducing the negative impacts of daily maximum temperature and strengthening the positive impacts of precipitation. Our results indicate that previous empirical studies could be biased in assessing climate change impacts by ignoring the changes in crop spatial distribution pattern. As a result, this has great implications for understanding the increasing debates on whether climate change will be a net gain or loss for regional agriculture.« less

Crop yield response to climate change varies with crop spatial distribution pattern

DOE Office of Scientific and Technical Information (OSTI.GOV)

Leng, Guoyong; Huang, Maoyi

The linkage between crop yield and climate variability has been confirmed in numerous studies using statistical approaches. A crucial assumption in these studies is that crop spatial distribution pattern is constant over time. Here, we explore how changes in county-level corn spatial distribution pattern modulate the response of its yields to climate change at the state level over the Contiguous United States. Our results show that corn yield response to climate change varies with crop spatial distribution pattern, with distinct impacts on the magnitude and even the direction at the state level. Corn yield is predicted to decrease by 20~40%more » by 2050s when considering crop spatial distribution pattern changes, which is 6~12% less than the estimates with fixed cropping pattern. The beneficial effects are mainly achieved by reducing the negative impacts of daily maximum temperature and strengthening the positive impacts of precipitation. Our results indicate that previous empirical studies could be biased in assessing climate change impacts by ignoring the changes in crop spatial distribution pattern. As a result, this has great implications for understanding the increasing debates on whether climate change will be a net gain or loss for regional agriculture.« less

Food and Water Gaps to 2050

NASA Astrophysics Data System (ADS)

Grafton, Q.

2014-12-01

This presentation reviews the pressures, threats and risks to food availability and water based on projected global population growth to 2050. An original model, the Global Food and Water System (GWFS) Platform, is introduced and used to explore food deficits under various scenarios and also the implications for future water gaps. The GWFS platform can assess the effects of crop productivity on food production and incorporates data from 19 major food producing nations to generate a global projection of food and water gaps. Preliminary results indicate that while crop food supply is able to meet global crop food demand by 2050, this is possible only with 'input intensification' that includes increased average rates of water and fertiliser use per hectare and at least a 20% increase in average yield productivity (once and for all). Increased water withdrawals for agriculture with input intensification would, absent any increases in withdrawals in the manufacturing or household uses, would place the world very close to the limits of a safe operating space in terms overall water use by 2050. While global crop food supply can meet projected global demand with input intensification, this still results in large and growing crop food deficits to 2050 in some countries, especially in South Asia, where climate change is expected to increase variability of rainfall and, in some places, reduce overall freshwater availability. While beyond the confines of the GWFS Platform the implications of expected water withdrawals on the environment in particular locations are also briefly reviewed.

Factors Affecting the Biology and Pathogenicity of Heterodera schachtii on Sugarbeet.

PubMed

Griffin, G D

1988-07-01

A direct relationship exists between soil temperature and Heterodera schachtii development. The average developmental period of two nematode populations from Lewiston, Utah, and Rupert, Idaho, from J2 to J3, J4, adult, and the next generation J2 at soil temperatures of 18-28 C were 100, 140,225, and 399 degree-days (base 8 C), respectively. There was a positive relationship (P < 0.05) between nematode Pi, nematode generations, and sugarbeet yields. The greatest sugarbeet growth inhibition (87%) occurred when sugarbeets were exposed to a Pi of 12 eggs/cm(3) soil for five generations (1,995 degree-days), compared with a 47% inhibition when plants were exposed to the same Pi for two generations. There was a negative correlation (P < 0.05) between the Pi, Pf, and sugarbeet yield for each population threshold. The smaller the Pi, the greater the sugarbeet yields and the greater the Pf. Root yields were 80 and 29 t /ha and Pf were 8.4 and 3.6 eggs/cm(3) soil when sugarbeet seeds were planted at Pi of 0.4 and 7.9 eggs/cm(3). respectively, at a soil temperature of 8 C. The number of years rotation with a nonhost crop required to reduce the nematode population density below a damage threshold level of 2 eggs/cm(3) depends on the Pi. A Pi of 33.8 eggs/cm(3) soil required a 5-year crop rotation, whereas a Pi of 8.4 eggs/cm(3) soil required a 2-year crop rotation.

Factors Affecting the Biology and Pathogenicity of Heterodera schachtii on Sugarbeet

PubMed Central

Griffin, G. D.

1988-01-01

A direct relationship exists between soil temperature and Heterodera schachtii development. The average developmental period of two nematode populations from Lewiston, Utah, and Rupert, Idaho, from J2 to J3, J4, adult, and the next generation J2 at soil temperatures of 18-28 C were 100, 140,225, and 399 degree-days (base 8 C), respectively. There was a positive relationship (P < 0.05) between nematode Pi, nematode generations, and sugarbeet yields. The greatest sugarbeet growth inhibition (87%) occurred when sugarbeets were exposed to a Pi of 12 eggs/cm³ soil for five generations (1,995 degree-days), compared with a 47% inhibition when plants were exposed to the same Pi for two generations. There was a negative correlation (P < 0.05) between the Pi, Pf, and sugarbeet yield for each population threshold. The smaller the Pi, the greater the sugarbeet yields and the greater the Pf. Root yields were 80 and 29 t /ha and Pf were 8.4 and 3.6 eggs/cm³ soil when sugarbeet seeds were planted at Pi of 0.4 and 7.9 eggs/cm³. respectively, at a soil temperature of 8 C. The number of years rotation with a nonhost crop required to reduce the nematode population density below a damage threshold level of 2 eggs/cm³ depends on the Pi. A Pi of 33.8 eggs/cm³ soil required a 5-year crop rotation, whereas a Pi of 8.4 eggs/cm³ soil required a 2-year crop rotation. PMID:19290229

Linking ecophysiological modelling with quantitative genetics to support marker-assisted crop design for improved yields of rice (Oryza sativa) under drought stress.

PubMed

Gu, Junfei; Yin, Xinyou; Zhang, Chengwei; Wang, Huaqi; Struik, Paul C

2014-09-01

Genetic markers can be used in combination with ecophysiological crop models to predict the performance of genotypes. Crop models can estimate the contribution of individual markers to crop performance in given environments. The objectives of this study were to explore the use of crop models to design markers and virtual ideotypes for improving yields of rice (Oryza sativa) under drought stress. Using the model GECROS, crop yield was dissected into seven easily measured parameters. Loci for these parameters were identified for a rice population of 94 introgression lines (ILs) derived from two parents differing in drought tolerance. Marker-based values of ILs for each of these parameters were estimated from additive allele effects of the loci, and were fed to the model in order to simulate yields of the ILs grown under well-watered and drought conditions and in order to design virtual ideotypes for those conditions. To account for genotypic yield differences, it was necessary to parameterize the model for differences in an additional trait 'total crop nitrogen uptake' (Nmax) among the ILs. Genetic variation in Nmax had the most significant effect on yield; five other parameters also significantly influenced yield, but seed weight and leaf photosynthesis did not. Using the marker-based parameter values, GECROS also simulated yield variation among 251 recombinant inbred lines of the same parents. The model-based dissection approach detected more markers than the analysis using only yield per se. Model-based sensitivity analysis ranked all markers for their importance in determining yield differences among the ILs. Virtual ideotypes based on markers identified by modelling had 10-36 % more yield than those based on markers for yield per se. This study outlines a genotype-to-phenotype approach that exploits the potential value of marker-based crop modelling in developing new plant types with high yields. The approach can provide more markers for selection programmes for specific environments whilst also allowing for prioritization. Crop modelling is thus a powerful tool for marker design for improved rice yields and for ideotyping under contrasting conditions. © The Author 2014. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

A Landscape View of Agricultural Insecticide Use across the Conterminous US from 1997 through 2012

DOE PAGES

Meehan, Timothy D.; Gratton, Claudio; Zhang, Youjun

2016-11-30

Simplification of agricultural landscapes is expected to have positive effects on many crop pests and negative effects on their natural enemies, potentially leading to increased pest pressure, decreased crop yield, and increased insecticide use. While many intermediate links in this causal chain have empirical support, there is mixed evidence for ultimate relationships between landscape simplification, crop yield, and insecticide use, especially at large spatial and temporal scales. We explored relationships between landscape simplification (proportion of a county in harvested cropland) and insecticide use (proportion of harvested cropland treated with insecticides), using county-level data from the US Census of Agriculture andmore » a variety of standard and spatiotemporal regression techniques. The best model indicated that insecticide use across the US has increased between 1997 and 2012, was strongly dependent on the crops grown in a county, increased with average farm income and size, and increased with annual growing degree days. After accounting for those variables, and other unidentified spatial and temporal structure in the data, there remained a statistically significant, moderate, positive relationship between insecticide use and landscape simplification. Finally, these results lend general support to the causal chain outlined above, and to the notion that a landscape perspective is useful for managing ecosystem services that are provided by mobile organisms and valuable to agriculture.« less

A Landscape View of Agricultural Insecticide Use across the Conterminous US from 1997 through 2012

DOE Office of Scientific and Technical Information (OSTI.GOV)

Meehan, Timothy D.; Gratton, Claudio; Zhang, Youjun

Simplification of agricultural landscapes is expected to have positive effects on many crop pests and negative effects on their natural enemies, potentially leading to increased pest pressure, decreased crop yield, and increased insecticide use. While many intermediate links in this causal chain have empirical support, there is mixed evidence for ultimate relationships between landscape simplification, crop yield, and insecticide use, especially at large spatial and temporal scales. We explored relationships between landscape simplification (proportion of a county in harvested cropland) and insecticide use (proportion of harvested cropland treated with insecticides), using county-level data from the US Census of Agriculture andmore » a variety of standard and spatiotemporal regression techniques. The best model indicated that insecticide use across the US has increased between 1997 and 2012, was strongly dependent on the crops grown in a county, increased with average farm income and size, and increased with annual growing degree days. After accounting for those variables, and other unidentified spatial and temporal structure in the data, there remained a statistically significant, moderate, positive relationship between insecticide use and landscape simplification. Finally, these results lend general support to the causal chain outlined above, and to the notion that a landscape perspective is useful for managing ecosystem services that are provided by mobile organisms and valuable to agriculture.« less

Statistical modeling of yield and variance instability in conventional and organic cropping systems

USDA-ARS?s Scientific Manuscript database

Cropping systems research was undertaken to address declining crop diversity and verify competitiveness of alternatives to the predominant conventional cropping system in the northern Corn Belt. To understand and capitalize on temporal yield variability within corn and soybean fields, we quantified ...

Simulating canopy temperature for modelling heat stress in cereals

USDA-ARS?s Scientific Manuscript database

Crop models must be improved to account for the large effects of heat stress effects on crop yields. To date, most approaches in crop models use air temperature despite evidence that crop canopy temperature better explains yield reductions associated with high temperature events. This study presents...

Long-term variation of Surface Ozone, NO2, temperature and relative humidity on crop yield over Andhra Pradesh (AP), India

NASA Astrophysics Data System (ADS)

Arunachalam, M. S.; Obili, Manjula; Srimurali, M.

2016-07-01

Long-term variation of Surface Ozone, NO2, Temperature, Relative humidity and crop yield datasets over thirteen districts of Andhra Pradesh(AP) has been studied with the help of OMI, MODIS, AIRS, ERA-Interim re-analysis and Directorate of Economics and Statistics (DES) of AP. Inter comparison of crop yield loss estimates according to exposure metrics such as AOT40 (accumulated ozone exposure over a threshold of 40) and non-linear variation of surface temperature for twenty and eighteen varieties of two major crop growing seasons namely, kharif (April-September) and rabi (October-March), respectively has been made. Study is carried to establish a new crop-yield-exposure relationship for different crop cultivars of AP. Both ozone and temperature are showing a correlation coefficient of 0.66 and 0.87 with relative humidity; and 0.72 and 0.80 with NO2. Alleviation of high surface ozone results in high food security and improves the economy thereby reduces the induced warming of the troposphere caused by ozone. Keywords: Surface Ozone, NO2, Temperature, Relative humidity, Crop yield, AOT 40.

Mapping Crop Yield and Sow Date Using High Resolution Imagery

NASA Astrophysics Data System (ADS)

Royal, K.

2015-12-01

Keitasha Royal, Meha Jain, Ph.D., David Lobell, Ph.D Mapping Crop Yield and Sow Date Using High Resolution ImageryThe use of satellite imagery in agriculture is becoming increasingly more significant and valuable. Due to the emergence of new satellites, such as Skybox, these satellites provide higher resolution imagery (e.g 1m) therefore improving the ability to map smallholder agriculture. For the smallholder farm dominated area of northern India, Skybox high-resolution satellite imagery can aid in understanding how to improve farm yields. In particular, we are interested in mapping winter wheat in India, as this region produces approximately 80% of the country's wheat crop, which is important given that wheat is a staple crop that provides approximately 20% of household calories. In northeast India, the combination of increased heat stress, limited irrigation access, and the difficulty for farmers to access advanced farming technologies results in farmers only producing about 50% of their potential crop yield. The use of satellite imagery can aid in understanding wheat yields through time and help identify ways to increase crop yields in the wheat belt of India. To translate Skybox satellite data into meaningful information about wheat fields, we examine vegetation indices, such as the normalized difference vegetation index (NDVI), to measure the "greenness" of plants to help determine the health of the crops. We test our ability to predict crop characteristics, like sow date and yield, using vegetation indices of 59 fields for which we have field data in Bihar, India.

Tropical rotation crops influence nematode densities and vegetable yields.

PubMed

McSorley, R; Dickson, D W; de Brito, J A; Hochmuth, R C

1994-09-01

The effects of eight summer rotation crops on nematode densities and yields of subsequent spring vegetable crops were determined in field studies conducted in north Florida from 1991 to 1993. The crop sequence was as follows: (i) rotation crops during summer 1991; (ii) cover crop of rye (Secale cereale) during winter 1991-92; (iii) 'Lemondrop L' squash (Cucurbita pepo) during spring 1992; (iv) rotation crops during summer 1992; (v) rye during winter 1992-93; (vi) 'Classic' eggplant (Solanum melongena) during spring 1993. The eight summer crop rotation treatments were as follows: 'Hale' castor (Ricinus communis), velvetbean (Mucuna deeringiana), sesame (Sesamum indicum), American jointvetch (Aeschynomene americana), weed fallow, 'SX- 17' sorghum-sudangrass (Sorghum bicolor x S. sudanense), 'Kirby' soybean (Glycine max), and 'Clemson Spineless' okra (Hibiscus esculentus) as a control. Rotations with castor, velvetbean, American jointvetch, and sorghum-sudangrass were most effective in maintaining the lowest population densities of Meloidogyne spp. (a mixture of M. incognita race 1 and M. arenaria race 1), but Paratrichodorus minor built up in the sorghum-sudangrass rotation. Yield of squash was lower (P

Risk of water scarcity and water policy implications for crop production in the Ebro Basin in Spain

NASA Astrophysics Data System (ADS)

Quiroga, S.; Fernández-Haddad, Z.; Iglesias, A.

2010-08-01

The increasing pressure on water systems in the Mediterranean enhances existing water conflicts and threatens water supply for agriculture. In this context, one of the main priorities for agricultural research and public policy is the adaptation of crop yields to water pressures. This paper focuses on the evaluation of hydrological risk and water policy implications for food production. Our methodological approach includes four steps. For the first step, we estimate the impacts of rainfall and irrigation water on crop yields. However, this study is not limited to general crop production functions since it also considers the linkages between those economic and biophysical aspects which may have an important effect on crop productivity. We use statistical models of yield response to address how hydrological variables affect the yield of the main Mediterranean crops in the Ebro River Basin. In the second step, this study takes into consideration the effects of those interactions and analyzes gross value added sensitivity to crop production changes. We then use Montecarlo simulations to characterize crop yield risk to water variability. Finally we evaluate some policy scenarios with irrigated area adjustments that could cope in a context of increased water scarcity. A substantial decrease in irrigated land, of up to 30% of total, results in only moderate losses of crop productivity. The response is crop and region specific and may serve to prioritise adaptation strategies.

What limits photosynthetic energy conversion efficiency in nature? Lessons from the oceans.

PubMed

Falkowski, Paul G; Lin, Hanzhi; Gorbunov, Maxim Y

2017-09-26

Constraining photosynthetic energy conversion efficiency in nature is challenging. In principle, two yield measurements must be made simultaneously: photochemistry, fluorescence and/or thermal dissipation. We constructed two different, extremely sensitive and precise active fluorometers: one measures the quantum yield of photochemistry from changes in variable fluorescence, the other measures fluorescence lifetimes in the picosecond time domain. By deploying the pair of instruments on eight transoceanic cruises over six years, we obtained over 200 000 measurements of fluorescence yields and lifetimes from surface waters in five ocean basins. Our results revealed that the average quantum yield of photochemistry was approximately 0.35 while the average quantum yield of fluorescence was approximately 0.07. Thus, closure on the energy budget suggests that, on average, approximately 58% of the photons absorbed by phytoplankton in the world oceans are dissipated as heat. This extraordinary inefficiency is associated with the paucity of nutrients in the upper ocean, especially dissolved inorganic nitrogen and iron. Our results strongly suggest that, in nature, most of the time, most of the phytoplankton community operates at approximately half of its maximal photosynthetic energy conversion efficiency because nutrients limit the synthesis or function of essential components in the photosynthetic apparatus.This article is part of the themed issue 'Enhancing photosynthesis in crop plants: targets for improvement'. © 2017 The Author(s).

Application of agrometeorological spectral model in rice area in southern Brazil

NASA Astrophysics Data System (ADS)

Leivas, Janice F.; de C. Teixeira, Antonio Heriberto; Andrade, Ricardo G.; de C. Victoria, Daniel; Bayma-Silva, Gustavo; Bolfe, Edson L.

2015-10-01

The southern region is responsible for 70% of rice production in Brazil. In this study, rice areas of Rio Grande do Sul were selected, using the land use classification, scale 1: 100,000, provided by Brazilian Institute of Geography and Statistics (IBGE). MODIS Images were used and meteorological data, available by National Institute of Meteorology (INMET). The period of analysis was crop season 2011/2012, October to March. To obtain evapotranspiration was applied agrometeorological-spectral model SAFER (Simple Algorithm For Retrieving Evapotranspiration). From the analysis of the results, on planting and cultivation period , the average evapotranspiration (ET) daily was 1.93 +/- 0.96 mm.day-1. In the vegetative development period of rice, the daily ET has achieved 4.94 mm.day-1, with average value 2,31+/- 0.97 mm.day-1. In the period of harvest, evapotranspiration daily average was 1.84 +/- 0.80 mm.day-1. From results obtained, the estimation of evapotranspiration from satellite images may assist in monitoring the culture during the cycle, assisting in estimates of water productivity and crop yield.

Monitoring interannual variation in global crop yield using long-term AVHRR and MODIS observations

NASA Astrophysics Data System (ADS)

Zhang, Xiaoyang; Zhang, Qingyuan

2016-04-01

Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) data have been extensively applied for crop yield prediction because of their daily temporal resolution and a global coverage. This study investigated global crop yield using daily two band Enhanced Vegetation Index (EVI2) derived from AVHRR (1981-1999) and MODIS (2000-2013) observations at a spatial resolution of 0.05° (∼5 km). Specifically, EVI2 temporal trajectory of crop growth was simulated using a hybrid piecewise logistic model (HPLM) for individual pixels, which was used to detect crop phenological metrics. The derived crop phenology was then applied to calculate crop greenness defined as EVI2 amplitude and EVI2 integration during annual crop growing seasons, which was further aggregated for croplands in each country, respectively. The interannual variations in EVI2 amplitude and EVI2 integration were combined to correlate to the variation in cereal yield from 1982-2012 for individual countries using a stepwise regression model, respectively. The results show that the confidence level of the established regression models was higher than 90% (P value < 0.1) in most countries in the northern hemisphere although it was relatively poor in the southern hemisphere (mainly in Africa). The error in the yield predication was relatively smaller in America, Europe and East Asia than that in Africa. In the 10 countries with largest cereal production across the world, the prediction error was less than 9% during past three decades. This suggests that crop phenology-controlled greenness from coarse resolution satellite data has the capability of predicting national crop yield across the world, which could provide timely and reliable crop information for global agricultural trade and policymakers.

High-resolution, regional-scale crop yield simulations for the Southwestern United States

NASA Astrophysics Data System (ADS)

Stack, D. H.; Kafatos, M.; Medvigy, D.; El-Askary, H. M.; Hatzopoulos, N.; Kim, J.; Kim, S.; Prasad, A. K.; Tremback, C.; Walko, R. L.; Asrar, G. R.

2012-12-01

Over the past few decades, there have been many process-based crop models developed with the goal of better understanding the impacts of climate, soils, and management decisions on crop yields. These models simulate the growth and development of crops in response to environmental drivers. Traditionally, process-based crop models have been run at the individual farm level for yield optimization and management scenario testing. Few previous studies have used these models over broader geographic regions, largely due to the lack of gridded high-resolution meteorological and soil datasets required as inputs for these data intensive process-based models. In particular, assessment of regional-scale yield variability due to climate change requires high-resolution, regional-scale, climate projections, and such projections have been unavailable until recently. The goal of this study was to create a framework for extending the Agricultural Production Systems sIMulator (APSIM) crop model for use at regional scales and analyze spatial and temporal yield changes in the Southwestern United States (CA, AZ, and NV). Using the scripting language Python, an automated pipeline was developed to link Regional Climate Model (RCM) output with the APSIM crop model, thus creating a one-way nested modeling framework. This framework was used to combine climate, soil, land use, and agricultural management datasets in order to better understand the relationship between climate variability and crop yield at the regional-scale. Three different RCMs were used to drive APSIM: OLAM, RAMS, and WRF. Preliminary results suggest that, depending on the model inputs, there is some variability between simulated RCM driven maize yields and historical yields obtained from the United States Department of Agriculture (USDA). Furthermore, these simulations showed strong non-linear correlations between yield and meteorological drivers, with critical threshold values for some of the inputs (e.g. minimum and maximum temperature), beyond which the yields were negatively affected. These results are now being used for further regional-scale yield analysis as the aforementioned framework is adaptable to multiple geographic regions and crop types.

Land Husbandry: Biochar application to reduce land degradation and erosion on cassava production

NASA Astrophysics Data System (ADS)

Yuniwati, E. D.

2017-12-01

This field experiment was carried out to examine the effect of increasing crop yield on land degradation and erosion in cassava-based cropping systems. The experiment was also aimed at showing that with proper crop management, the planting of cassava does not result in land degradation, and therefore, a sustainable production system can be obtained. The experiment was done in a farmer's fields in Batu, about 15 km south east of Malang, East Java, Indonesia. The soils are Alfisols with a surface slope of about 8%. There were 8 experimental treatments with two replications. The experiment results show that biochar applications reduce of soil erosion rate of the cassava field were not necessarily higher than those of maize in terms of crop yield and crop management. At low-to-medium yield, also observed the nutrient uptake of cassava was lower than that of maize. At high yield, only the K uptake of cassava was higher than that of maize, whereas the N and P uptake was more or less similar. Soil erosion on the cassava field was significantly higher than that on the maize field; however, this only occurred when there was no suitable crop management. Simple crop managements, such as ridging, biochar application, or manure application could significantly reduce soil erosion. The results also revealed that proper management could prevent land degradation and increase crop yield. In turn, the increase in crop yield could decrease soil erosion and plant nutrient depletion.

Effects of fragmentation, supplementation and the addition of phase II compost to 2nd break compost on mushroom (Agaricus bisporus) yield.

PubMed

Royse, Daniel J

2010-01-01

Double-cropping offers growers an opportunity to increase production efficiency while reducing costs. We evaluated degree of fragmentation, supplementation, and addition of phase II compost (PIIC) to 2nd break compost (2BkC) on mushroom yield and biological efficiency (BE%). One crop was extended as a triple crop in which we evaluated effect of compost type, and addition of phase II compost and supplement. All crops involved removing the casing layer after 2nd break and then using 2BkC for the various treatments. Simple fragmentation of the compost increased mushroom yield by 30% compared to non-fragmented compost. Addition of a commercial supplement to fragmented compost increased mushroom yield by 53-56% over non-supplemented, fragmented 2BkC. Fragmented, supplemented 2BkC resulted in a 99% and 108% yield increase over the non-fragmented control depending on degree of fragmentation (3x, 1x, respectively). A 3rd crop of mushrooms was produced from 2BkC, but yields were about one-half that of the 1st and 2nd crops. Double-cropping (and even triple-cropping) offers growers an opportunity to increase bio-efficiency, reduce production costs, and increase profitability. The cost of producing Agaricus bisporus continues to rise due to increasing expenses including materials, energy, and labor. Optimizing production practices, through double- or triple-cropping, could help growers become more efficient and competitive, and ensure the availability of mushrooms for consumers.

Wheat yield and yield stability of eight dryland crop rotations

USDA-ARS?s Scientific Manuscript database

The winter wheat (Triticum aestivum L.)-fallow (WF) dryland production system employed in the Central Great Plains has evolved in the past 40 years to include a diversity of other crops, with a reduction in fallow frequency. Wheat remains the base crop for essentially all cropping systems. Decisions...

Effects of Management Practices on Meloidogyne incognita and Snap Bean Yield.

PubMed

Smittle, D A; Johnson, A W

1982-01-01

Phenamiphos applied at 6.7 kg ai/ha through a solid set or a center pivot irrigation system with 28 mm of water effectively controlled root-knot nematodes, Meloidogyne incognita, and resulted in greater snap bean growth and yields irrespective of growing season, tillage method, or cover crop system. The percentage yield increases attributed to this method of M. incognita control over nontreated controls were 45% in the spring crop, and 90% and 409% in the fall crops following winter rye and fallow, respectively. Root galling was not affected by tillage systems or cover crop, but disk tillage resulted in over 50% reduction in bean yield compared with yields from the subsoil-bed tillage system.

Projections of Biofuel Growth Patterns Reveal the Potential Importance of Nitrogen Fixation for Miscanthus Productivity

NASA Astrophysics Data System (ADS)

Davis, S. C.; Parton, W. J.; Dohleman, F. G.; Gottel, N. R.; Smith, C. M.; Kent, A. D.; Delucia, E. H.

2008-12-01

Demand for liquid biofuels is increasing because of the disparity between fuel demand and supply. Relative to grain crops, the more intensive harvest required for second generation liquid biofuel production leads to the removal of significantly more carbon and nitrogen from the soil. These elements are conventionally litter products of crops that are returned to the soil and can accumulate over time. This loss of organic matter represents a management challenge because the energy cost associated with fertilizers or external sources of organic matter reduce the net energy value of the biofuel crops. Plants that have exceptional strategies for exploiting nutrients may be the most viable options for sustainable biofuel yields because of low management and energy cost. Miscanthus x giganteus has high N retranslocation rates, maintains high photosynthetic rates over a large temperature range, exploits a longer-than-average growing season, and yields at least twice the biomass of other candidate biofuel grass crops (i.e. switchgrass). We employed the DAYCENT model to project potential productivity of Miscanthus, corn, switchgrass, and mixed prairie communities based on our current knowledge of these species. Ecosystem process descriptions that have been validated for many crop species did not accurately predict Miscanthus yields and lead to new hypotheses about unknown N cycling mechanisms for this species. We tested the hypothesis that Miscanthus hosts N-fixing bacteria in several ways. First, we used enrichment culture and molecular methods to detect N-fixing bacteria in Miscanthus. Then, we demonstrated the plant-growth promoting effect of diazotrophs isolated from Miscanthus rhizomes on a model grass. And finally, we applied 15N2 to the soil and rooting zone of field grown Miscanthus plants to determine if atmospheric N2 was incorporated into plant tissue, a process that requires N-fixation. These experiments are the first tests of N-fixation in Miscanthus x giganteus, and the ecosystem model allowed us to project how much nitrogen may be obtained from N-fixation to support sustainable high biomass yields.

Meeting the demand for crop production: the challenge of yield decline in crops grown in short rotations.

PubMed

Bennett, Amanda J; Bending, Gary D; Chandler, David; Hilton, Sally; Mills, Peter

2012-02-01

There is a trend world-wide to grow crops in short rotation or in monoculture, particularly in conventional agriculture. This practice is becoming more prevalent due to a range of factors including economic market trends, technological advances, government incentives, and retailer and consumer demands. Land-use intensity will have to increase further in future in order to meet the demands of growing crops for both bioenergy and food production, and long rotations may not be considered viable or practical. However, evidence indicates that crops grown in short rotations or monoculture often suffer from yield decline compared to those grown in longer rotations or for the first time. Numerous factors have been hypothesised as contributing to yield decline, including biotic factors such as plant pathogens, deleterious rhizosphere microorganisms, mycorrhizas acting as pathogens, and allelopathy or autotoxicity of the crop, as well as abiotic factors such as land management practices and nutrient availability. In many cases, soil microorganisms have been implicated either directly or indirectly in yield decline. Although individual factors may be responsible for yield decline in some cases, it is more likely that combinations of factors interact to cause the problem. However, evidence confirming the precise role of these various factors is often lacking in field studies due to the complex nature of cropping systems and the numerous interactions that take place within them. Despite long-term knowledge of the yield-decline phenomenon, there are few tools to counteract it apart from reverting to longer crop rotations or break crops. Alternative cropping and management practices such as double-cropping or inter-cropping, tillage and organic amendments may prove valuable for combating some of the negative effects seen when crops are grown in short rotation. Plant breeding continues to be important, although this does require a specific breeding target to be identified. This review identifies gaps in our understanding of yield decline, particularly with respect to the complex interactions occurring between the different components of agro-ecosystems, which may well influence food security in the 21(st) Century. © 2011 The Authors. Biological Reviews © 2011 Cambridge Philosophical Society.

Global Gridded Crop Model Evaluation: Benchmarking, Skills, Deficiencies and Implications.

NASA Technical Reports Server (NTRS)

Muller, Christoph; Elliott, Joshua; Chryssanthacopoulos, James; Arneth, Almut; Balkovic, Juraj; Ciais, Philippe; Deryng, Delphine; Folberth, Christian; Glotter, Michael; Hoek, Steven;

Understanding the weather signal in national crop-yield variability

NASA Astrophysics Data System (ADS)

Frieler, Katja; Schauberger, Bernhard; Arneth, Almut; Balkovič, Juraj; Chryssanthacopoulos, James; Deryng, Delphine; Elliott, Joshua; Folberth, Christian; Khabarov, Nikolay; Müller, Christoph; Olin, Stefan; Pugh, Thomas A. M.; Schaphoff, Sibyll; Schewe, Jacob; Schmid, Erwin; Warszawski, Lila; Levermann, Anders

2017-06-01

Year-to-year variations in crop yields can have major impacts on the livelihoods of subsistence farmers and may trigger significant global price fluctuations, with severe consequences for people in developing countries. Fluctuations can be induced by weather conditions, management decisions, weeds, diseases, and pests. Although an explicit quantification and deeper understanding of weather-induced crop-yield variability is essential for adaptation strategies, so far it has only been addressed by empirical models. Here, we provide conservative estimates of the fraction of reported national yield variabilities that can be attributed to weather by state-of-the-art, process-based crop model simulations. We find that observed weather variations can explain more than 50% of the variability in wheat yields in Australia, Canada, Spain, Hungary, and Romania. For maize, weather sensitivities exceed 50% in seven countries, including the United States. The explained variance exceeds 50% for rice in Japan and South Korea and for soy in Argentina. Avoiding water stress by simulating yields assuming full irrigation shows that water limitation is a major driver of the observed variations in most of these countries. Identifying the mechanisms leading to crop-yield fluctuations is not only fundamental for dampening fluctuations, but is also important in the context of the debate on the attribution of loss and damage to climate change. Since process-based crop models not only account for weather influences on crop yields, but also provide options to represent human-management measures, they could become essential tools for differentiating these drivers, and for exploring options to reduce future yield fluctuations.

Patterns of Cereal Yield Growth across China from 1980 to 2010 and Their Implications for Food Production and Food Security

PubMed Central

Li, Xiaoyun; Liu, Nianjie; You, Liangzhi; Ke, Xinli; Liu, Haijun; Huang, Malan; Waddington, Stephen R.

2016-01-01

After a remarkable 86% increase in cereal production from 1980 to 2005, recent crop yield growth in China has been slow. County level crop production data between 1980 and 2010 from eastern and middle China were used to analyze spatial and temporal patterns of rice, wheat and maize yield in five major farming systems that include around 90% of China's cereal production. Site-specific yield trends were assessed in areas where those crops have experienced increasing yield or where yields have stagnated or declined. We find that rice yields have continued to increase on over 12.3 million hectares (m. ha) or 41.8% of the rice area in China between 1980 and 2010. However, yields stagnated on 50% of the rice area (around 14.7 m. ha) over this time period. Wheat yields increased on 13.8 m. ha (58.2% of the total harvest area), but stagnated on around 3.8 m. ha (15.8% of the harvest area). Yields increased on a smaller proportion of the maize area (17.7% of harvest area, 5.3 m. ha), while yields have stagnated on over 54% (16.3 m. ha). Many parts of the lowland rice and upland intensive sub-tropical farming systems were more prone to stagnation with rice, the upland intensive sub-tropical system with wheat, and maize in the temperate mixed system. Large areas where wheat yield continues to rise were found in the lowland rice and temperate mixed systems. Land and water constraints, climate variability, and other environmental limitations undermine increased crop yield and agricultural productivity in these systems and threaten future food security. Technology and policy innovations must be implemented to promote crop yields and the sustainable use of agricultural resources to maintain food security in China. In many production regions it is possible to better match the crop with input resources to raise crop yields and benefits. Investments may be especially useful to intensify production in areas where yields continue to improve. For example, increased support to maize production in southern China, where yields are still rising, seems justified. PMID:27404110

Eating on an interconnected planet

NASA Astrophysics Data System (ADS)

MacDonald, Graham K.

2013-06-01

Calls to boost agricultural production in order to meet the demands of a growing global population are now commonplace. Yet, depending on where productivity changes and population growth occur, international trade could be increasingly necessary in the transfer of food from farms to consumers. Fader et al (2013) offer a nuanced view of this spatial disconnect and its food security implications by considering a valuable thought experiment: what countries could foreseeably meet their food requirements from internal production alone circa 2000 and for contrasting scenarios in 2050? They investigate the extent to which available renewable water and land resources constrain domestic per capita crop production, assuming current as well as broadly improved yields. The findings convey an intuitive, though often overlooked, point that population growth is likely to increase the reliance of certain regions on food imports unless substantial productivity improvements are realized. It is unlikely that any nation would be compelled to produce all of its food domestically, but reflecting on potential food self-sufficiency is a worthwhile endeavor. Importing crops may be matter of choice, but also one of necessity if available land, water, and yields limit production. Dependence on food imports can involve uncertainty: production shortfalls arising from drought and other factors have been associated with price volatility—or even restrictions on crop exports—posing challenges to countries anticipating consistent import arrangements (Headey 2011). Compounding this uncertainty is that a relatively small number of countries produce the bulk of staple crops for global markets. Just eight countries comprising 11% of the global population produced, on average, 70% of cereal exports during the past decade (FAO 2013). Although trade networks are dynamic, some net-importing countries have developed entrenched relationships with particular producers that entail very large crop transfers (Carr et al 2012). A central finding of Fader et al 's study is that domestic crop production could theoretically replace imports and allow food self-sufficiency in many countries. Embracing this potential could lessen the need to increase imports as populations grow. Yet, in their extreme scenario—assuming no yield improvements, no agricultural expansion and high population growth rates—roughly 51% of the global population would be import dependent by 2050. While improbable, this case raises the question of how such a spike in crop demands might ricochet across producing countries. Exporters could alter their production and export rates in response to various internal or external drivers, such as land-use policies, concerns over grain stocks, or climate change impacts (Hertel et al 2010, Lambin and Meyfroidt 2011, Headey 2011). Suweis et al (2013) suggest that water-rich nations are unlikely to maintain their current crop export rates amidst global change, questioning the persistence of global food trade relationships in the absence of mitigative actions. The uneven role of a relatively small number of nations to the food security of many is apparent when considering the origins of key crops imported by countries that Fader et al estimate have already crossed a resource boundary limiting food self-sufficiency (figure 1). Figure 1. Figure 1. The origins of key crops (maize, milled/paddy rice, soybean, and wheat) imported by 49 countries that have exceeded a land or water constraint boundary currently limiting food self-sufficiency. The map of countries exceeding at least one boundary circa 2000, shaded in black, is based on figure 1(B) in Fader et al (2013). The size of the lines indicate the relative quantity of kilocalories imported, calculated using FAO (2013) import matrices and crop kilocalorie contents (FAO 2001) averaged for the period 2000-2010. Internal trade among countries that had exceeded a land or water boundary totaled ~6%. Small island nations and 11 countries not reporting import origin data were omitted here. Fader et al 's potential crop production estimates are derived from a comprehensive global model, but several factors could compound import dependence or shift yield trajectories. Growing meat consumption that typically coincides with rising average incomes will drive increased demand for crops across some regions surpassing that of population growth (Delgado 2003, Kastner et al 2012). Such trends would exacerbate direct or indirect reliance on foreign land and water resources. Comparison of global crop productivity simulations with regional crop response models would help to better understand how management interventions (Lobell et al 2009) and changing climate (Thornton et al 2009) positively or negatively impact attainable per capita production across regions. Moreover, the cropland expansion scenarios used in Fader et al 's study are optimistic in that they draw on a sizable land base of 13.2 million km2, which, if fully utilized, would be an almost doubling of the 15.1 million km2 under production in 2000 (FAO 2013). We already use much of the world's prime arable lands, with stagnating yield trends for key crops in some locations, so realizing equivalent yields from a vast new area is unlikely (Foley et al 2011, Ray et al 2012). Considering how specific farm management and demand-driven feedbacks alter trade patterns would provide valuable juxtaposition to Fader et al 's benchmark study. Ultimately, equity and cooperation among countries may be increasingly critical to regional food security if locations of food production and consumption continue to diverge. Even with large increases in yields and widespread cropland expansion, Fader et al (2013) project that up to 30 countries—largely low-income economies—will remain import dependent due to resource constraints. Food security in poorer countries most vulnerable to productivity shocks and price volatility depends on the ability of certain populations to afford imports (Naylor and Falcon 2010). Future changes in agricultural commodity prices tied to yield variations could disproportionately impact the welfare of specific households, while possibly benefiting other lower income countries that produce exports (Hertel et al 2010). In the event that import dependence rises markedly from 16% of the global population circa 2000 (Fader et al 2013), cooperative trade policies may be pivotal to alleviating food insecurity of the most vulnerable net-food importing countries (Bouët and Debucquet 2012). Quantifying the capacity of countries to meet their per capita crop requirements underpins the importance of truly widespread yield improvements, particularly given the already concentrated nature of export production. Fader et al 's study offers new insight on how the growing spatial disconnect between where people live and where food is grown may dictate either increasingly entrenched dependence on foreign production or immense cropland expansion throughout net-importing countries. Framing this challenge in terms of potential domestic crop production reveals that even small yield improvements could go a long way toward easing both. Acknowledgments I thank K Carlson, J Foley, P West, M Schipanski, and N Mueller for comments. References Bouët A and Debucquet D 2012 Food crisis and export taxation: the cost of non-cooperative trade policies Rev. World Econom. 148 209-33 Carr J A, D'Odorico P, Laio F and Ridolfi L 2012 On the temporal variability of the virtual water network Geophys. Res. Lett. 39 L06404 Delgado C L 2003 Rising consumption of meat and milk in developing countries has created a new food revolution J. Nutr. 133 3907S-10S Fader M, Gerten D, Krause M, Lucht W and Cramer W 2013 Spatial decoupling of agricultural production and consumption: quantifying dependence of countries on food imports due to domestic land and water constraints Environ. Res. Lett. 8 014046 FAO (Food and Agriculture Organization) 2001 Food Balance Sheets: A Handbook (Rome: United Nations Food and Agriculture Organization) FAO (Food and Agriculture Organization) 2013 FAOSTAT: FAO Statistical Databases (Rome: United Nations Food and Agriculture Organization) Foley J A et al 2011 Solutions for a cultivated planet Nature 478 337-42 Headey D 2011 Rethinking the global food crisis: the role of trade shocks Food Policy 36 136-46 Hertel T W, Burke M B and Lobell D B 2010 The poverty implications of climate-induced crop yield changes by 2030 Glob. Environ. Change 20 577-85 Kastner T, Rivas M J I, Koch W and Nonhebel S 2012 Global changes in diets and the consequences for land requirements for food Proc. Natl Acad. Sci. 109 6868-72 Lambin E F and Meyfroidt P 2011 Global land use change, economic globalization, and the looming land scarcity Proc. Natl Acad. Sci. 108 3465-72 Lobell D B, Cassman K G and Field C B 2009 Crop yield gaps: their importance, magnitudes, and causes Annu. Rev. Environ. Resour. 34 179 Naylor R L and Falcon W P 2010 Food security in an era of economic volatility Popul. Dev. Rev. 36 693-723 Ray D K, Ramankutty N, Mueller N D, West P C and Foley J A 2012 Recent patterns of crop yield growth and stagnation Nature Commun. 3 1293 Suweis S, Rinaldo A, Maritan A and D'Odorico P 2013 Water-controlled wealth of nations Proc. Natl Acad. Sci. 110 4230-3 Thornton P K, Jones P G, Alagarswamy G and Andresen J 2009 Spatial variation of crop yield response to climate change in East Africa Glob. Environ. Change 19 54-65

Correlation Between Precipitation and Crop Yield for Corn and Cotton Produced in Alabama

NASA Technical Reports Server (NTRS)

Hayes, Carol E.; Perkey, Donald J.

1998-01-01

In this study, variations in precipitation during the time of corn silking are compared to Alabama corn yields. Also, this study compares precipitation variations during bloom to Alabama cotton yield. The goal is to obtain mathematical correlations between rainfall during the crop's critical period and the crop amount harvested per acre.

Recent Genetic Gains in Nitrogen Use Efficiency in Oilseed Rape

PubMed Central

Stahl, Andreas; Pfeifer, Mara; Frisch, Matthias; Wittkop, Benjamin; Snowdon, Rod J.

2017-01-01

Nitrogen is essential for plant growth, and N fertilization allows farmers to obtain high yields and produce sufficient agricultural commodities. On the other hand, nitrogen losses potentially cause adverse effects to ecosystems and to human health. Increasing nitrogen use efficiency (NUE) is vital to solve the conflict between productivity, to secure the demand of a growing world population, and the protection of the environment. To ensure this, genetic improvement is considered to be a paramount aspect toward ecofriendly crop production. Winter oilseed rape (Brassica napus L.) is the second most important oilseed crop in the world and is cultivated in many regions across the temperate zones. To our knowledge, this study reports the most comprehensive field-based data generated to date for an empirical evaluation of genetic improvement in winter oilseed rape varieties under two divergent nitrogen fertilization levels (NFLs). A collection of 30 elite varieties registered between 1989 and 2014, including hybrids and open pollinated varieties, was tested in a 2-year experiment in 10 environments across Germany for changes in seed yield and seed quality traits. Furthermore, NUE was calculated. We observed a highly significant genetics-driven increase in seed yield per-se and, thus, increased NUE at both NFLs. On average, seed yield from modern open-pollinated varieties and modern hybrids was higher than from old open-pollinated varieties and old hybrids. The annual yield progress across all tested varieties was ~35 kg ha−1 year−1 at low nitrogen and 45 kg ha−1 year−1 under high nitrogen fertilization. Furthermore, in modern varieties an increased oil concentration and decreased protein concentration was observed. Despite, the significant effects of nitrogen fertilization, a surprisingly low average seed yield gap of 180 kg N ha−1 was noted between high and low nitrogen fertilization. Due to contrary effects of N fertilization on seed yield per-se and seed oil concentration an oil yield of 2.04 t ha−1 was measured at both N levels. Collectively, the data reveal that genetic improvement through modern breeding techniques in conjunction with reduced N fertilizer inputs has a tremendous potential to increase NUE of oilseed rape. PMID:28638399

Soil response to biodynamic farming practices in estevia -Stevia Rebaudiana- (Extremadura, Spain)

NASA Astrophysics Data System (ADS)

Labrador, Juana; Colmenares, Ricardo; Sánchez, Eduardo; Creus, Juan; García, Nieves; Blázquez, Jaime; Moreno, Marta M.

2014-05-01

The first results of the evolution of an organic-biodynamic cultivation of stevia (Stevia rebaudiana) in Extremadura (Spain) are shown here. The organic-biodynamic approach permits experimentally for a more holistic view of the crop development process what means the understanding and quantification of its evolution at different scales. The research methodology applied includes not only quantitative individual parameters of the crop development but also global parameters which make a contribution of very relevant information concerning unbalances between growth and differentiation processes, as well as other aspects linked to the product intrinsic quality. The crop cultivation has been done over a plot of 2.5 has, on acid soils (pH 5.18) and very poor organic matter content (0.5 %). On this first year of cultivation two cuts were given to the plant with an average total yield of 4,500 kg/ha without any supply of solid organic matter, only with the application of the biodynamic preparations. So far results regarding soil improvement and crop productivity, taking into consideration the practices used, let us introduce this pioneer crop in Extremadura, not only as an alternative crop to the current tobacco crop in this area, but also as a development resource for the rural environment of this region. Key words: Agroecology, Organic Biodynamic Agriculture, Stevia Rebaudiana

A network-based approach for semi-quantitative knowledge mining and its application to yield variability

NASA Astrophysics Data System (ADS)

Schauberger, Bernhard; Rolinski, Susanne; Müller, Christoph

2016-12-01

Variability of crop yields is detrimental for food security. Under climate change its amplitude is likely to increase, thus it is essential to understand the underlying causes and mechanisms. Crop models are the primary tool to project future changes in crop yields under climate change. A systematic overview of drivers and mechanisms of crop yield variability (YV) can thus inform crop model development and facilitate improved understanding of climate change impacts on crop yields. Yet there is a vast body of literature on crop physiology and YV, which makes a prioritization of mechanisms for implementation in models challenging. Therefore this paper takes on a novel approach to systematically mine and organize existing knowledge from the literature. The aim is to identify important mechanisms lacking in models, which can help to set priorities in model improvement. We structure knowledge from the literature in a semi-quantitative network. This network consists of complex interactions between growing conditions, plant physiology and crop yield. We utilize the resulting network structure to assign relative importance to causes of YV and related plant physiological processes. As expected, our findings confirm existing knowledge, in particular on the dominant role of temperature and precipitation, but also highlight other important drivers of YV. More importantly, our method allows for identifying the relevant physiological processes that transmit variability in growing conditions to variability in yield. We can identify explicit targets for the improvement of crop models. The network can additionally guide model development by outlining complex interactions between processes and by easily retrieving quantitative information for each of the 350 interactions. We show the validity of our network method as a structured, consistent and scalable dictionary of literature. The method can easily be applied to many other research fields.

Crop yield risk analysis and mitigation of smallholder farmers at quaternary catchment level: Case study of B72A in Olifants river basin, South Africa

NASA Astrophysics Data System (ADS)

Magombeyi, Manuel S.; Taigbenu, Akpofure E.

Currently, Sub-Sahara is experiencing increased frequency of disasters either as floods or droughts which depletes the scarce resources available to sustain increasing populations. Success in preventing food shortages in the African continent can only be achieved by understanding the vulnerability and risk of the majority of smallholder farmers under rainfed and supplementary irrigation coupled with appropriate interventions. Increased frequency of floods, droughts and dry spells pose an increasing threat to the smallholder farmers’ food security and water resources availability in B72A quaternary catchment of the Olifants river basin in South Africa. This paper links maize crop yield risk and smallholder farmer vulnerability arising from droughts by applying a set of interdisciplinary indicators (physical and socio-economic) encompassing gender and institutional vulnerabilities. For the study area, the return period of droughts and dry spells was 2 years. The growing season for maize crop was 121 days on average. Soil water deficit during critical growth stages may reduce potential yields by up to 62%, depending on the length and severity of the moisture deficit. To minimize grain yield loss and avoid total crop failures from intra-seasonal dry spells, farmers applied supplementary irrigation either from river water or rainwater harvested into small reservoirs. Institutional vulnerability was evidenced by disjointed water management institutions with lack of comprehension of roles of higher level institutions by lower level ones. Women are most hit by droughts as they derived more than 90% of their family income from agriculture activities. An enhanced understanding of the vulnerability and risk exposure will assist in developing technologies and policies that conform to the current livelihood strategies of smallholder, resource-constrained farmers. Development of such knowledge base for a catchment opens avenues for computational modeling of the impacts of different types of disasters under different scenarios.

What is soil organic matter worth?

PubMed

Sparling, G P; Wheeler, D; Vesely, E-T; Schipper, L A

2006-01-01

The conservation and restoration of soil organic matter are often advocated because of the generally beneficial effects on soil attributes for plant growth and crop production. More recently, organic matter has become important as a terrestrial sink and store for C and N. We have attempted to derive a monetary value of soil organic matter for crop production and storage functions in three contrasting New Zealand soil orders (Gley, Melanic, and Granular Soils). Soil chemical and physical characteristics of real-life examples of three pairs of matched soils with low organic matter contents (after long-term continuous cropping for vegetables or maize) or high organic matter content (continuous pasture) were used as input data for a pasture (grass-clover) production model. The differences in pasture dry matter yields (non-irrigated) were calculated for three climate scenarios (wet, dry, and average years) and the yields converted to an equivalent weight and financial value of milk solids. We also estimated the hypothetical value of the C and N sequestered during the recovery phase of the low organic matter content soils assuming trading with C and N credits. For all three soil orders, and for the three climate scenarios, pasture dry matter yields were decreased in the soils with lower organic matter contents. The extra organic matter in the high C soils was estimated to be worth NZ$27 to NZ$150 ha(-1) yr(-1) in terms of increased milk solids production. The decreased yields from the previously cropped soils were predicted to persist for 36 to 125 yr, but with declining effect as organic matter gradually recovered, giving an accumulated loss in pastoral production worth around NZ$518 to NZ$1239 ha(-1). This was 42 to 73 times lower than the hypothetical value of the organic matter as a sequestering agent for C and N, which varied between NZ$22,963 to NZ$90,849 depending on the soil, region, discount rates, and values used for carbon and nitrogen credits.

An integrated crop model and GIS decision support system for assisting agronomic decision making under climate change.

PubMed

Kadiyala, M D M; Nedumaran, S; Singh, Piara; S, Chukka; Irshad, Mohammad A; Bantilan, M C S

2015-07-15

The semi-arid tropical (SAT) regions of India are suffering from low productivity which may be further aggravated by anticipated climate change. The present study analyzes the spatial variability of climate change impacts on groundnut yields in the Anantapur district of India and examines the relative contribution of adaptation strategies. For this purpose, a web based decision support tool that integrates crop simulation model and Geographical Information System (GIS) was developed to assist agronomic decision making and this tool can be scalable to any location and crop. The climate change projections of five global climate models (GCMs) relative to the 1980-2010 baseline for Anantapur district indicates an increase in rainfall activity to the tune of 10.6 to 25% during Mid-century period (2040-69) with RCP 8.5. The GCMs also predict warming exceeding 1.4 to 2.4°C by 2069 in the study region. The spatial crop responses to the projected climate indicate a decrease in groundnut yields with four GCMs (MPI-ESM-MR, MIROC5, CCSM4 and HadGEM2-ES) and a contrasting 6.3% increase with the GCM, GFDL-ESM2M. The simulation studies using CROPGRO-Peanut model reveals that groundnut yields can be increased on average by 1.0%, 5.0%, 14.4%, and 20.2%, by adopting adaptation options of heat tolerance, drought tolerant cultivars, supplemental irrigation and a combination of drought tolerance cultivar and supplemental irrigation respectively. The spatial patterns of relative benefits of adaptation options were geographically different and the greatest benefits can be achieved by adopting new cultivars having drought tolerance and with the application of one supplemental irrigation at 60days after sowing. Copyright © 2015 Elsevier B.V. All rights reserved.

Climate change impacts on coffee rust disease

NASA Astrophysics Data System (ADS)

Alfonsi, W. M. V.; Koga-Vicente, A.; Pinto, H. S.; Alfonsi, E. L., Sr.; Coltri, P. P.; Zullo, J., Jr.; Patricio, F. R.; Avila, A. M. H. D.; Gonçalves, R. R. D. V.

2016-12-01

Changes in climate conditions and in extreme weather events may affect the food security due to impacts in agricultural production. Despite several researches have been assessed the impacts of extremes in yield crops in climate change scenarios, there is the need to consider the effects in pests and diseases which increase losses in the sector. Coffee Arabica is an important commodity in world and plays a key role in Brazilian agricultural exports. Although the coffee crop has a world highlight, its yield is affected by several factors abiotic or biotic. The weather as well pests and diseases directly influence the development and coffee crop yield. These problems may cause serious damage with significant economic impacts. The coffee rust, caused by the fungus Hemileia vastarix,is among the diseases of greatest impact for the crop. The disease emerged in Brazil in the 70s and is widely spread in all producing regions of coffee in Brazil, and in the world. Regions with favorable weather conditions for the pathogen may exhibit losses ranging from 30% to 50% of the total grain production. The evaluation of extreme weather events of coffee rust disease in futures scenarios was carried out using the climatic data from CMIP5 models, data field of coffee rust disease incidence and, incubation period simulation data for Brazilian municipalities. Two Regional Climate Models were selected, Eta-HadGEM2-ES and Eta-MIROC5, and the Representative Concentration Pathways 8.5 w/m2 was adopted. The outcomes pointed out that in these scenarios the period of incubation tends to decrease affecting the coffee rust disease incidence, which tends to increase. Nevertheless, the changing in average trends tends to benefit the reproduction of the pathogen. Once the temperature threshold for the disease reaches the adverse conditions it may be unfavorable for the incidence.

The impact of soil moisture extremes and their spatiotemporal variability on Zambian maize yields

NASA Astrophysics Data System (ADS)

Zhao, Y.; Estes, L. D.; Vergopolan, N.

2017-12-01

Food security in sub-Saharan Africa is highly sensitive to climate variability. While it is well understood that extreme heat has substantial negative impacts on crop yield, the impacts of precipitation extremes, particularly over large spatial extents, are harder to quantify. There are three primary reasons for this difficulty, which are (1) lack of high quality, high resolution precipitation data, (2) rainfall data provide incomplete information on plant water availability, the variable that most directly affects crop performance, and (3) the type of rainfall extreme that most affects crop yields varies throughout the crop development stage. With respect to the first reason, the spatial and temporal variation of precipitation is much greater than that of temperature, yet the spatial resolution of rainfall data is typically even coarser than it is for temperature, particularly within Africa. Even if there were high-resolution rainfall data, the amount of water available to crops also depends on other physical factors that affect evapotranspiration, which are strongly influenced by heterogeneity in the land surface related to topography, soil properties, and land cover. In this context, soil moisture provides a better measure of crop water availability than rainfall. Furthermore, soil moisture has significantly different influences on crop yield depending on the crop's growth stage. The goal of this study is to understand how the spatiotemporal scales of soil moisture extremes interact with crops, more specifically, the timing and the spatial scales of extreme events like droughts and flooding. In this study, we simulate daily-1km soil moisture using HydroBlocks - a physically based land surface model - and compare it with precipitation and remote sensing derived maize yields between 2000 and 2016 in Zambia. We use a novel combination of the SCYM (scalable satellite-based yield mapper) method with DSSAT crop model, which is a mechanistic model responsive to water stress. Understanding the relationships between soil moisture spatiotemporal variability and yields can help to improve agricultural drought risk assessment and seasonal crop yield forecasting as well as early season warning of potential famines.

Possible changes to arable crop yields by 2050

PubMed Central

Jaggard, Keith W.; Qi, Aiming; Ober, Eric S.

2010-01-01

By 2050, the world population is likely to be 9.1 billion, the CO2 concentration 550 ppm, the ozone concentration 60 ppb and the climate warmer by ca 2°C. In these conditions, what contribution can increased crop yield make to feeding the world? CO2 enrichment is likely to increase yields of most crops by approximately 13 per cent but leave yields of C4 crops unchanged. It will tend to reduce water consumption by all crops, but this effect will be approximately cancelled out by the effect of the increased temperature on evaporation rates. In many places increased temperature will provide opportunities to manipulate agronomy to improve crop performance. Ozone concentration increases will decrease yields by 5 per cent or more. Plant breeders will probably be able to increase yields considerably in the CO2-enriched environment of the future, and most weeds and airborne pests and diseases should remain controllable, so long as policy changes do not remove too many types of crop-protection chemicals. However, soil-borne pathogens are likely to be an increasing problem when warmer weather will increase their multiplication rates; control is likely to need a transgenic approach to breeding for resistance. There is a large gap between achievable yields and those delivered by farmers, even in the most efficient agricultural systems. A gap is inevitable, but there are large differences between farmers, even between those who have used the same resources. If this gap is closed and accompanied by improvements in potential yields then there is a good prospect that crop production will increase by approximately 50 per cent or more by 2050 without extra land. However, the demands for land to produce bio-energy have not been factored into these calculations. PMID:20713388

Possible changes to arable crop yields by 2050.

PubMed

Jaggard, Keith W; Qi, Aiming; Ober, Eric S

2010-09-27

By 2050, the world population is likely to be 9.1 billion, the CO(2) concentration 550 ppm, the ozone concentration 60 ppb and the climate warmer by ca 2 degrees C. In these conditions, what contribution can increased crop yield make to feeding the world? CO(2) enrichment is likely to increase yields of most crops by approximately 13 per cent but leave yields of C4 crops unchanged. It will tend to reduce water consumption by all crops, but this effect will be approximately cancelled out by the effect of the increased temperature on evaporation rates. In many places increased temperature will provide opportunities to manipulate agronomy to improve crop performance. Ozone concentration increases will decrease yields by 5 per cent or more. Plant breeders will probably be able to increase yields considerably in the CO(2)-enriched environment of the future, and most weeds and airborne pests and diseases should remain controllable, so long as policy changes do not remove too many types of crop-protection chemicals. However, soil-borne pathogens are likely to be an increasing problem when warmer weather will increase their multiplication rates; control is likely to need a transgenic approach to breeding for resistance. There is a large gap between achievable yields and those delivered by farmers, even in the most efficient agricultural systems. A gap is inevitable, but there are large differences between farmers, even between those who have used the same resources. If this gap is closed and accompanied by improvements in potential yields then there is a good prospect that crop production will increase by approximately 50 per cent or more by 2050 without extra land. However, the demands for land to produce bio-energy have not been factored into these calculations.

Drought effects on US maize and soybean production: spatiotemporal patterns and historical changes

NASA Astrophysics Data System (ADS)

Zipper, Samuel C.; Qiu, Jiangxiao; Kucharik, Christopher J.

2016-09-01

Maximizing agricultural production on existing cropland is one pillar of meeting future global food security needs. To close crop yield gaps, it is critical to understand how climate extremes such as drought impact yield. Here, we use gridded, daily meteorological data and county-level annual yield data to quantify meteorological drought sensitivity of US maize and soybean production from 1958 to 2007. Meteorological drought negatively affects crop yield over most US crop-producing areas, and yield is most sensitive to short-term (1-3 month) droughts during critical development periods from July to August. While meteorological drought is associated with 13% of overall yield variability, substantial spatial variability in drought effects and sensitivity exists, with central and southeastern US becoming increasingly sensitive to drought over time. Our study illustrates fine-scale spatiotemporal patterns of drought effects, highlighting where variability in crop production is most strongly associated with drought, and suggests that management strategies that buffer against short-term water stress may be most effective at sustaining long-term crop productivity.

Plant species evaluated for new crop potential

DOE Office of Scientific and Technical Information (OSTI.GOV)

Carr, M.E.

1985-01-01

Ninety-two plant species from various regions of the USA were screened for their energy-producing potential. Samples were analysed for oil, polyphenol, hydrocarbon and protein. Oil fractions of some species were analysed for classes of lipid constituents and yields of unsaponifiable matter and fatty acids were determined. Hydrocarbon fractions of some species were analysed for rubber, gutta and waxes. Average MW and MW distribution of rubber and gutta were determined. Complete analytical data for 16 species is presented. Large quantities of oil were obtained from Philadelphus coronarius, Cacalia muhlenbergii, Lindera benzoin and Koelreuteria paniculata. High yields of polyphenols came from Acermore » ginnala, Cornus obliqua and Salix caprea and maximum yields of hydrocarbon and protein were from Elymus virginicus and Lindera benzoin, respectively.« less

What aspects of future rainfall changes matter for crop yields in West Africa?

NASA Astrophysics Data System (ADS)

Guan, Kaiyu; Sultan, Benjamin; Biasutti, Michela; Baron, Christian; Lobell, David B.

2015-10-01

How rainfall arrives, in terms of its frequency, intensity, the timing and duration of rainy season, may have a large influence on rainfed agriculture. However, a thorough assessment of these effects is largely missing. This study combines a new synthetic rainfall model and two independently validated crop models (APSIM and SARRA-H) to assess sorghum yield response to possible shifts in seasonal rainfall characteristics in West Africa. We find that shifts in total rainfall amount primarily drive the rainfall-related crop yield change, with less relevance to intraseasonal rainfall features. However, dry regions (total annual rainfall below 500 mm/yr) have a high sensitivity to rainfall frequency and intensity, and more intense rainfall events have greater benefits for crop yield than more frequent rainfall. Delayed monsoon onset may negatively impact yields. Our study implies that future changes in seasonal rainfall characteristics should be considered in designing specific crop adaptations in West Africa.

Yield estimation of sugarcane based on agrometeorological-spectral models

NASA Technical Reports Server (NTRS)

Rudorff, Bernardo Friedrich Theodor; Batista, Getulio Teixeira

1990-01-01

This work has the objective to assess the performance of a yield estimation model for sugarcane (Succharum officinarum). The model uses orbital gathered spectral data along with yield estimated from an agrometeorological model. The test site includes the sugarcane plantations of the Barra Grande Plant located in Lencois Paulista municipality in Sao Paulo State. Production data of four crop years were analyzed. Yield data observed in the first crop year (1983/84) were regressed against spectral and agrometeorological data of that same year. This provided the model to predict the yield for the following crop year i.e., 1984/85. The model to predict the yield of subsequent years (up to 1987/88) were developed similarly, incorporating all previous years data. The yield estimations obtained from these models explained 69, 54, and 50 percent of the yield variation in the 1984/85, 1985/86, and 1986/87 crop years, respectively. The accuracy of yield estimations based on spectral data only (vegetation index model) and on agrometeorological data only (agrometeorological model) were also investigated.

A Pilot Study Assesing Climate Change Impacts on Cereals

NASA Astrophysics Data System (ADS)

Topcu, Sevilay; Sen, Burak; Turkes, Murat

2010-05-01

The spatial and temporal impacts of climate change on the growth and yield of major cereals (first and second-crop corn) as well as wheat grown in Cukurova Region in the southern Turkey have been assessed, by combining the outputs from a regional climate model with a crop growth simulation model. With its 1.1 million ha of agricultural land, the Cukurova Region is one of the major agricultural production regions in Turkey. Wheat dominates in rain-fed areas while corn crops are grown in more than 50 % of the irrigated land in the region. Thus, the Region is providing half of the country's total cereal production. Since the region has a typical Mediterranean climate with almost no rain and high temperatures during the summer months, agricultural production is vulnerable to changes in climate in terms of decreasing rainfall and increasing temperatures and consequently shortage of water resources. To predict the future climate for the period 2070-2100, the regional climate model RegCM3 conditions was performed using IPCC's SRESS-A2 scenario, and climatic parameter such as daily mean, maximum and minimum temperatures, radiation as well as total annual precipitation were selected for the simulation study. Data for the period 1961 to 1990 were used as historical reference. The WOFOST model was used to simulate cereal growths and yields for two different water availability senarios: 1) potential production and 2) water-limited production conditions. Potential growth represents the conditions where no limiting factor such as water and nutrients is present, however due to the water-limited production situation, water for irrigation is limited as a consequence of water shortage. The detailed results of previous field experiments carried out with three cereal crops in different locations with different regional soil and climate conditions were used for the verification of the WOFOST model. According to the verification results, the model simulated the yield with less than 5% deviation for all three cereal crops. According to projections of the regional climate model RegCM3, the annual average temperature will likely increase by 3.4 to 4.8 °C, while approximately a 25% decrease in rainfall amounts is expected in the Cukurova Region during the period 2071-2100. Similar results for temperatures were estimated for entire country, however predicted changes in rainfall varies in a wide range for the country. The study showed that with climate change, wheat yield could decrease drastically in rainfed areas, however supplemental irrigation could help to sustain the yield on the current level. Yields of first and second-crop corn are expected to decrease by 58% and 43.4%, respectively, compared to the reference value under water shortages.

Oil palm natural diversity and the potential for yield improvement

PubMed Central

Barcelos, Edson; Rios, Sara de Almeida; Cunha, Raimundo N. V.; Lopes, Ricardo; Motoike, Sérgio Y.; Babiychuk, Elena; Skirycz, Aleksandra; Kushnir, Sergei

2015-01-01

African oil palm has the highest productivity amongst cultivated oleaginous crops. Species can constitute a single crop capable to fulfill the growing global demand for vegetable oils, which is estimated to reach 240 million tons by 2050. Two types of vegetable oil are extracted from the palm fruit on commercial scale. The crude palm oil and kernel palm oil have different fatty acid profiles, which increases versatility of the crop in industrial applications. Plantations of the current varieties have economic life-span around 25–30 years and produce fruits around the year. Thus, predictable annual palm oil supply enables marketing plans and adjustments in line with the economic forecasts. Oil palm cultivation is one of the most profitable land uses in the humid tropics. Oil palm fruits are the richest plant source of pro-vitamin A and vitamin E. Hence, crop both alleviates poverty, and could provide a simple practical solution to eliminate global pro-vitamin A deficiency. Oil palm is a perennial, evergreen tree adapted to cultivation in biodiversity rich equatorial land areas. The growing demand for the palm oil threatens the future of the rain forests and has a large negative impact on biodiversity. Plant science faces three major challenges to make oil palm the key element of building the future sustainable world. The global average yield of 3.5 tons of oil per hectare (t) should be raised to the full yield potential estimated at 11–18t. The tree architecture must be changed to lower labor intensity and improve mechanization of the harvest. Oil composition should be tailored to the evolving needs of the food, oleochemical and fuel industries. The release of the oil palm reference genome sequence in 2013 was the key step toward this goal. The molecular bases of agronomically important traits can be and are beginning to be understood at the single base pair resolution, enabling gene-centered breeding and engineering of this remarkable crop. PMID:25870604

Oil palm natural diversity and the potential for yield improvement.

PubMed

Barcelos, Edson; Rios, Sara de Almeida; Cunha, Raimundo N V; Lopes, Ricardo; Motoike, Sérgio Y; Babiychuk, Elena; Skirycz, Aleksandra; Kushnir, Sergei

2015-01-01

African oil palm has the highest productivity amongst cultivated oleaginous crops. Species can constitute a single crop capable to fulfill the growing global demand for vegetable oils, which is estimated to reach 240 million tons by 2050. Two types of vegetable oil are extracted from the palm fruit on commercial scale. The crude palm oil and kernel palm oil have different fatty acid profiles, which increases versatility of the crop in industrial applications. Plantations of the current varieties have economic life-span around 25-30 years and produce fruits around the year. Thus, predictable annual palm oil supply enables marketing plans and adjustments in line with the economic forecasts. Oil palm cultivation is one of the most profitable land uses in the humid tropics. Oil palm fruits are the richest plant source of pro-vitamin A and vitamin E. Hence, crop both alleviates poverty, and could provide a simple practical solution to eliminate global pro-vitamin A deficiency. Oil palm is a perennial, evergreen tree adapted to cultivation in biodiversity rich equatorial land areas. The growing demand for the palm oil threatens the future of the rain forests and has a large negative impact on biodiversity. Plant science faces three major challenges to make oil palm the key element of building the future sustainable world. The global average yield of 3.5 tons of oil per hectare (t) should be raised to the full yield potential estimated at 11-18t. The tree architecture must be changed to lower labor intensity and improve mechanization of the harvest. Oil composition should be tailored to the evolving needs of the food, oleochemical and fuel industries. The release of the oil palm reference genome sequence in 2013 was the key step toward this goal. The molecular bases of agronomically important traits can be and are beginning to be understood at the single base pair resolution, enabling gene-centered breeding and engineering of this remarkable crop.

Aerobic Decomposition and Organic Amendments Effects on Grain Yield of Triple-Cropped Rice in the Mekong Delta, Vietnam

USDA-ARS?s Scientific Manuscript database

Soil aeration during decomposition of incorporated crop residues and application of organic amendments might help improve soil quality and rice yield for sustainable intensive rice production. A field experiment was conducted on triple-cropped rice during three consecutive crops with five treatments...

Effects of Tropical Rotation Crops on Meloidogyne arenaria Population Densities and Vegetable Yields in Microplots.

PubMed

McSorley, R; Dickson, D W; de Brito, J A; Hewlett, T E; Frederick, J J

1994-06-01

The effects of 12 summer crop rotation treatments on population densities of Meloidogyne arenaria race 1 and on yields of subsequent spring vegetable crops were determined in microplots. The crop sequence was: (i) rotation crops during summer 1991 ; (ii) cover crop of rye (Secale cereale) during winter 1991-92; (iii) squash (Cucurbita pepo) during spring 1992; (iv) rotation crops during summer 1992; (v) rye during winter 1992-93; (vi) eggplant (Solanum melongena) during spring 1993. The 12 rotation treatments were castor (Ricinus communis), cotton (Gossypium hirsutum), velvetbean (Mucuna deeringiana), crotalaria (Crotalaria spectabilis), fallow, hairy indigo (Indigofera hirsuta), American jointvetch (Aeschynomene americana), sorghum-sudangrass (Sorghum bicolor x S. sudanense), soybean (Glycine max), horsebean (Canavalia ensiformis), sesame (Sesamum indicum), and peanut (Arachis hypogaea). Compared to peanut, the first eight rotation treatments resulted in lower (P

Sensitivity and requirement of improvements of four soybean crop simulation models for climate change studies in Southern Brazil

NASA Astrophysics Data System (ADS)

Battisti, R.; Sentelhas, P. C.; Boote, K. J.

2017-12-01

Crop growth models have many uncertainties that affect the yield response to climate change. Based on that, the aim of this study was to evaluate the sensitivity of crop models to systematic changes in climate for simulating soybean attainable yield in Southern Brazil. Four crop models were used to simulate yields: AQUACROP, MONICA, DSSAT, and APSIM, as well as their ensemble. The simulations were performed considering changes of air temperature (0, + 1.5, + 3.0, + 4.5, and + 6.0 °C), [CO2] (380, 480, 580, 680, and 780 ppm), rainfall (- 30, - 15, 0, + 15, and + 30%), and solar radiation (- 15, 0, + 15), applied to daily values. The baseline climate was from 1961 to 2014, totalizing 53 crop seasons. The crop models simulated a reduction of attainable yield with temperature increase, reaching 2000 kg ha-1 for the ensemble at + 6 °C, mainly due to shorter crop cycle. For rainfall, the yield had a higher rate of reduction when it was diminished than when rainfall was increased. The crop models increased yield variability when solar radiation was changed from - 15 to + 15%, whereas [CO2] rise resulted in yield gains, following an asymptotic response, with a mean increase of 31% from 380 to 680 ppm. The models used require further attention to improvements in optimal and maximum cardinal temperature for development rate; runoff, water infiltration, deep drainage, and dynamic of root growth; photosynthesis parameters related to soil water availability; and energy balance of soil-plant system to define leaf temperature under elevated CO2.

Sensitivity and requirement of improvements of four soybean crop simulation models for climate change studies in Southern Brazil

NASA Astrophysics Data System (ADS)

Battisti, R.; Sentelhas, P. C.; Boote, K. J.

2018-05-01

Crop growth models have many uncertainties that affect the yield response to climate change. Based on that, the aim of this study was to evaluate the sensitivity of crop models to systematic changes in climate for simulating soybean attainable yield in Southern Brazil. Four crop models were used to simulate yields: AQUACROP, MONICA, DSSAT, and APSIM, as well as their ensemble. The simulations were performed considering changes of air temperature (0, + 1.5, + 3.0, + 4.5, and + 6.0 °C), [CO2] (380, 480, 580, 680, and 780 ppm), rainfall (- 30, - 15, 0, + 15, and + 30%), and solar radiation (- 15, 0, + 15), applied to daily values. The baseline climate was from 1961 to 2014, totalizing 53 crop seasons. The crop models simulated a reduction of attainable yield with temperature increase, reaching 2000 kg ha-1 for the ensemble at + 6 °C, mainly due to shorter crop cycle. For rainfall, the yield had a higher rate of reduction when it was diminished than when rainfall was increased. The crop models increased yield variability when solar radiation was changed from - 15 to + 15%, whereas [CO2] rise resulted in yield gains, following an asymptotic response, with a mean increase of 31% from 380 to 680 ppm. The models used require further attention to improvements in optimal and maximum cardinal temperature for development rate; runoff, water infiltration, deep drainage, and dynamic of root growth; photosynthesis parameters related to soil water availability; and energy balance of soil-plant system to define leaf temperature under elevated CO2.

African agricultural subsidy impacts food security, poverty, drought tolerance, and environmental quality

NASA Astrophysics Data System (ADS)

Galford, G. L.; Palm, C.; DeFries, R. S.; Nziguheba, G.; Droppelmann, K.; Nkonya, E.; Michelson, H.; Clark, C.; Kathewera, F.; Walsh, M.

2011-12-01

Malawi has spearheaded an unprecedented policy change in sub-Saharan Africa (SSA) since 2005 when it started a widespread agricultural inputs subsidy program (AISP) targeting small farmer maize production with mineral fertilizer and improved seeds. Since then, the mean N fertilizer load has increased significantly, from ~ 0 to a modest 35 kg N/ha or 7 times greater than SSA's average 5 kg N/ha average. During the tenure of AISP, Malawi has transitioned from a food aid recipient to an exporter. Maize yields each year of AISP are double the long-term average (0.8 tons/ha/yr, 1960-2005). In 2007, subsidy inputs combined with good rains led to of an unprecedented increase in national average yields of 2.7 tons/ha. National-scale assessments covering, agriculture, poverty, and environment such as this one are required to understand the trade-offs between development, climate and the environment. Environmentally, N2O emissions from fertilizer are a concern. First order estimates put emissions from AISP fertilizers at 2,600 Mg N2O/year (0.81 Tg CO2-e). While globally insignificant, these emissions may be equivalent to 16% of Malawi's annual fossil fuel and deforestation emissions. However, our partial nutrient budgets indicate that crop removal is still higher than N applied and therefore little loss of N to the environment is expected. Mineral fertilizers are a rapid first step to increase soil N after 40 years of serious depletion. Once restored, the soils will support robust agroforestry and other forms of organic inputs produced on-farm. Fertilizer use increases carbon sequestration on agricultural soils and reduces pressure to clear forests, which may partially compensate for the N2O emissions. We find evidence that AISP significantly increases food security and mitigates the impacts of drought on maize production. This is the first work linking the distribution of fertilizer subsidies to local crop yields using government records, remotely-sensed time series of green vegetation (10-year time series MODIS EVI), and rainfall (TRMM). Skeptics speculated that climate has improved crop yields, yet our findings robustly show vegetation changes attributable to AISP and distinguishable from precipitation. On the macro-economic side, the sustainability of AISP has been questioned for a long time due to strain on Government budgets. This research examines the relationship between regional food prices and poverty and the distribution of AISP allocation. We also study the correlations of AISP allocations and local changes in poverty. We explore future methods for increasing AISP returns through provisions requiring a farmer use additional land management practice that sequesters more carbon.

A Novel Approach for Forecasting Crop Production and Yield Using Remotely Sensed Satellite Images

NASA Astrophysics Data System (ADS)

Singh, R. K.; Budde, M. E.; Senay, G. B.; Rowland, J.

2017-12-01

Forecasting crop production in advance of crop harvest plays a significant role in drought impact management, improved food security, stabilizing food grain market prices, and poverty reduction. This becomes essential, particularly in Sub-Saharan Africa, where agriculture is a critical source of livelihoods, but lacks good quality agricultural statistical data. With increasing availability of low cost satellite data, faster computing power, and development of modeling algorithms, remotely sensed images are becoming a common source for deriving information for agricultural, drought, and water management. Many researchers have shown that the Normalized Difference Vegetation Index (NDVI), based on red and near-infrared reflectance, can be effectively used for estimating crop production and yield. Similarly, crop production and yield have been closely related to evapotranspiration (ET) also as there are strong linkages between production/yield and transpiration based on plant physiology. Thus, we combined NDVI and ET information from remotely sensed images for estimating total production and crop yield prior to crop harvest for Niger and Burkina Faso in West Africa. We identified the optimum time (dekads 23-29) for cumulating NDVI and ET and developed a new algorithm for estimating crop production and yield. We used the crop data from 2003 to 2008 to calibrate our model and the data from 2009 to 2013 for validation. Our results showed that total crop production can be estimated within 5% of actual production (R2 = 0.98) about 30-45 days before end of the harvest season. This novel approach can be operationalized to provide a valuable tool to decision makers for better drought impact management in drought-prone regions of the world.

Climate Change and Projected Impacts in Agriculture: an Example on Mediterranean Crops

NASA Astrophysics Data System (ADS)

Ferrise, R.; Moriondo, M.; Bindi, M.

2009-04-01

Recently, the availability of multi-model ensemble prediction methods has permitted the assignment of likelihoods to future climate projections. This allowed moving from the scenario-based approach to the risk-based approach in assessing the effects of climate change, thus providing more useful information for decision-makers that, as reported by Schneider (2001), need probability estimates to assess the seriousness of the projected impacts. The probabilistic approach to evaluate crop response to climate change mainly consists in applying an impact model (such as crop growth model) to a very large number of climate projections so to provide a probabilistic distribution of the variable selected to evaluate the impact. By comparing the outputs of the multi-simulation with a critical threshold (such as minimum yield below which it is not admissible to fall), it is possible to evaluate the risk related to future climate conditions. Unfortunately, such an approach is a time-consuming process due to the large number of model runs needed for such a procedure. An alternative method relies on the set up of impact response surfaces (RS) with respect to key climatic variables on which a probabilistic representation of projected changes in the same climatic variables may be overlaid (Fronzek et al. 2008). This approach was exploited within the ENSEMBLES EU Project aiming at assessing climate change impact on typical Mediterranean crops. This work presents the results of the project with a particular concerning about the assessment of risk, of durum wheat (T. turgidum L. subsp. durum (Desf.) Husn) and grapevine (Vitis vinifera L.) yield falling below fixed thresholds, using probabilistic information about future climate. Methodology The simple mechanistic crop growth models, SIRIUS Quality (Jamieson et al., 1998) and VITE-model (Bindi et al., 1997a,b), were selected to respectively simulate durum wheat and grapevine yields in present and future scenarios. SIRIUS Quality is a wheat simulation model that calculates biomass production from photosynthetically active radiation and grain growth from simple partition rules. VITE-model is a model that uses a simplified mechanistic approach based on the accumulated degree days, the radiation use efficiency and the fruit biomass index to simulate the main processes regulating grapevine development, growth and yield. The selected crop growth models were adopted to create yield RSs of both crops over the suitable cultivated area in the Mediterranean Basin. Yield RSs were calculated performing a scenario sensitivity analysis by altering the baseline climate with respect to temperature and precipitation changes. The baseline climate consisted of 30 years (1975-2005) of daily minimum and maximum temperatures, rainfall and global radiation. Meteorological data were extracted from the MARS JRC Archive and are referred to a grid with a spatial resolution of 50 Km x 50 Km covering the whole European area. The sensitivity analysis was performed for precipitation changes (from -40% to 20%) and temperature changes (from 0°C to +8°C), uniformly applied across all the year. To take in account for the effect of rising CO2, the yield RSs for future periods, were produced considering CO2 air concentration level according to the A1B SRES emission scenario. For each rainfall and temperature combination the average yield over the 30-years period was calculated. The probabilistic distribution of future yields was estimated by applying a bilinear interpolative method to overlap, onto the RSs, the data from perturbed physics experiment of Hadley Centre for future scenarios (joint distribution of annual temperature and rainfall changes). Critical thresholds of impact were determined by calculating, for each grid cell, the distribution of the 30-years average yield according to the joint distribution data for present period (1990-2010) and selecting the values that correspond to the 20th percentile of the cumulative distribution. Finally, future yields were compared with yield threshold to assess the risk of yield shortfall that, in each time period, was defined as the percentage of projected yields that not overcome the selected threshold. Results Maps of durum wheat and grapevine low productivity risk were generated for the next century over the Mediterranean Basin. For durum wheat, with the exception of Portugal and Southern Spain, in the next 30 years risk of low crop productivity shows an overall reduction, due to the fertilizing effect of CO2 increase that counterbalances for the negative impact of rising temperature and reducing rainfall. Thereafter, these latter negative effects become greater and the risk progressively increases starting from lower latitudes. Maximum risk was estimated in 2060 when strong reductions in yield were accounted all over the study area. The smaller reductions in risk, estimated for the end of the next century, may be explained by the greater uncertainty in climate projections. South Portugal, South Spain and Peloponnesus resulted the most vulnerable areas showing increase in risk probability up to 50%, while risk in Galicia, Slovenia, Croatia and central-southern France always resulted lower then present time. As regard grapevine, in the great part of the case study area, the yield seems to have beneficial effect from future climate change. In Central-Western Europe and at lower latitudes the projected yields never fall below the risk threshold, indicating a prevailing effect of CO2 fertilisation. By the other hand, Central-Northern Italy and North of Greece result the most vulnerable areas. In these regions the likelihood of reduced yields quickly rises and remains very high (>50%) until the end of the century, denoting a greater negative effect of temperature and rainfall. Conclusions From these results it may be argued that the impact of future climate change on crop yields is the resultant of the contrasting effects of changes in temperature and precipitation, CO2 increase and uncertainty in climate projections. The intensity of these effects is very site and crop dependent and may vary with time, differently affecting the assessment of risk. As a consequence, the patterns of risk of low crop productivity will change depending on which of these effects will prevail. References Bindi M. et al., 1997a "A simple model for simulation of growth and development in grapevine (Vitis vinifera L.). I. Model description". Vitis 36:67-71 Bindi M. et al., 1997b "A simple model for simulation of growth and development in grapevine (Vitis vinifera L.). II. Model validation". Vitis 36:73-76 Carter T. et al., 2006 "". Fronzek S. et al 2008 "Applying probabilistic projections of climate change with impact models: a case study for sub-arctic palsa mires in Fennoscandia". Climatic Change (submitted) Jamieson et al., 1998 "Sirius: a mechanistic model of wheat response to environmental variation". Eur. J. Agron. 8:161-179. Schneider S. 2001 "What is ‘dangerous' climate change?". Nature 411:17-19

Simulating maize yield and bomass with spatial variability of soil field capacity

USGS Publications Warehouse

Ma, Liwang; Ahuja, Lajpat; Trout, Thomas; Nolan, Bernard T.; Malone, Robert W.

2015-01-01

Spatial variability in field soil properties is a challenge for system modelers who use single representative values, such as means, for model inputs, rather than their distributions. In this study, the root zone water quality model (RZWQM2) was first calibrated for 4 yr of maize (Zea mays L.) data at six irrigation levels in northern Colorado and then used to study spatial variability of soil field capacity (FC) estimated in 96 plots on maize yield and biomass. The best results were obtained when the crop parameters were fitted along with FCs, with a root mean squared error (RMSE) of 354 kg ha–1 for yield and 1202 kg ha–1 for biomass. When running the model using each of the 96 sets of field-estimated FC values, instead of calibrating FCs, the average simulated yield and biomass from the 96 runs were close to measured values with a RMSE of 376 kg ha–1 for yield and 1504 kg ha–1 for biomass. When an average of the 96 FC values for each soil layer was used, simulated yield and biomass were also acceptable with a RMSE of 438 kg ha–1 for yield and 1627 kg ha–1 for biomass. Therefore, when there are large numbers of FC measurements, an average value might be sufficient for model inputs. However, when the ranges of FC measurements were known for each soil layer, a sampled distribution of FCs using the Latin hypercube sampling (LHS) might be used for model inputs.

Climate and N-Mineral Fertilization Changes on Triticale (XTriticosecale W.) Yield

NASA Astrophysics Data System (ADS)

László, Márton, ,, Dr.

2010-05-01

Ecological quality has a well established dependence on climate-rainfall changes because the water problems are pressing. There is, therefore, growing concern about the potentially wide ranging risks that climate change would have on these key industries as the nature and extent of anticipated changes have become more evident. It also includes changes in land use and in plant production and their management. These changes are unprecedented in terms of both their rate and their spatial extent. Changes in land use (agrotechnics, soil, cultivation, fertility, quality, protection etc.) and in plant production (plant nutrition-, rotation-, protection-, etc.) are currently the main manifestations. As an interdisciplinary problem it is necessary to study such a complex matter in terms of agricultural production. Generally among natural catastrophes, droughts and floods cause the greatest problems in field crop production. The droughts and the floods that were experienced in Hungary in the early 1980's have drawn renewed attention to the analyses of these problems. New research on climate change-soil-plant systems are focused on yield and yield quality. This paper reports the climate change (rainfall) x soil (acidic sandy brown forest) x mineral N-fertilisation x plant interactions on triticale yields in a long term field experiment set up at Nyírlugos in north-eastern Hungary under temperate climate conditions in 1962. The agrochemical parameters of the soil were as follows: pH (H2O) 5.9, pH (KCl) 4.7, hydrolytic acidity 8.4, hy1 0.3, humus 0.7%, CEC 5-10 mgeq 100*g-1, total N 34 mg*kg-1, AL-P2O5 43 mg*kg-1, AL-K2O 60 mg*kg-1. From 1962 to 1980 the experiment consisted of 2x16x4x4=512 plots and from 1980 of 32x4=128 plots in split-split plot and factorial random block design. The gross plot size was 10x5=50 m2. The average fertiliser rates in kg*ha-1*year-1 were nitrogen 45, phosphorus 24 (P2O5), potassium 40 (K2O), magnesium 7.5 (MgO) until 1980 and nitrogen 75, phosphorus 90 (P2O5), potassium 90 (K2O), calcium 175 (Ca) and magnesium 40 (Mg) after 1980. Nitrogen results are summarised from 1990 to 2001. Main conclusions were as follows: 1. On the basis of "general" (Harnos 1993) and triticale-specific rainfall deficiency values (Márton 2003) the years could be classified as average (1991, 1995, 2000), dry (1993), droughty (1992, 1994, 1996), wet (1997, 1998, 2001) and over wet (1999). 2. In average years the yield of the control plots became stabilised at the 1.4 t*ha-1 level. In the fertilised treatments the highest yield (4.0 t*ha-1) was more than two times the lowest yield (1.9 t*ha-1). N fertilisation resulted in an increase of around 1.0 t*ha-1 in the main yield compared with the control. The triticale yields could only be enhanced economically by full treatment with NPK (3.3 t*ha-1) or NPKCa-, NPKMg-, NPKCaMg (3.9 t*ha-1). 3. Without fertilisation the yield in the dry and drought years was decreased 14% and 36% to that in the average year. In case of the nitrogen treatmets the yield was decreased 45% and 24%. 4. In the wet years on the unfertilised plots the yield declined 14% and in the case of the nitrogen fertilisation the yield no changed than in the average years. In the over wet year the plots yielded similar than in the average years. 5. The relationships between rainfall during the vegetation period, N, P, K, Ca and Mg fertilisation and yield were characterised by second-degree correlation depending on the level of nutrition (R: 0=0.3455**, N=0.2779+, NP=0.4722***, NK=0.3739***, NPK=0.6311***, NPKCa=0.6673***, NPKMg=0.6734***, NPKCaMg=0.6232***). The maximum yield (5.0-6.0 t*ha-1) was yielded at 550-600 mm growth period rainfall. This paper summarises quantified results of triticale research with regarding to interaction effects and relationships between climate (rainfall)-mineral nutrition-crop production changes in Hungary during a long term field experiment to agricultural sustainability. Introduction "Climate Change" are recognized as a serious environmental issues (Johnston, 2000). Presently the build up of greenhouse gases in the atmosphere and the inertia in trends in emissions means that we can expect significant changes for at least the next few decades and probably for the 21th century as well (Márton, 2001a., b). It would badly need to understand what might be involved in adapting to the new climates. A decade ago, researchers asked the "what if" question. For example, what will be the impact if climate changes. Now, we must increasingly address the following question: how do we respond effectivelly to prevent damaging impacts and take advantage of new climatic opportunities. This question requires detailed in information regarding expected impacts and effectíve adaptive measures. Information on adaptation is required for governments, landscape planners, stakeholders, farmers, producers, processors, supermarkets and consumers. Not only the local effects and options, but also the spatial implications must be understood. Will yields be maintained on the present range of farms. Where will new crops be grown. Will new processing plants be required. Will there be competition for water. Most recent agricultural impact studies have concentrated on the effects of mean changes in climate on crop production, whilst only limited investigations into the effects of climate variability on agriculture have been undertaken. The paucity of studies in this area is not least due to the considerable uncertainty regarding how climate variability may change in the future in response to greenhouse gas induced warming but also as a result of the uncertainty in the response of agricultural crops to changes in climate variability, effected most probably through changes in the frequency of extreme climatic events. Showed that changes in variance have a greater effect on the frequency of extreme climatic events than do changes in the mean values. Hence, it is important to attempt to include changes in variability in scenarios of climate change. Weather change at Hungary was started about of 1850. Among the natural catastrophes, drought and flooding caused by over-abundant rainfall cause the greatest problem in plant nutrition and in field crop production nowadays too (José et al., 2001). It is why we found it necessary to revise and to analyse this problem. The triticale is most important crop of many World countries (Márton and Pekli, 2003) but little research in the field of climate change impact assessment has been undertaken. These plant is sensitive to the prevailing weather conditions (rainfall) and, hence, it is important to evaluate the effects of anthropogenic climate change on her production. The crop is demanding indicator of soil nutrient status also. Have a particularly high requirement for supply of soil nitrogen, phosphorus, potassium, calcium and magnesium. From 1990 to 2001 this paper describes climate-rainfall-change and N-mineral fertilisation effects on triticale yield on a acidic sandy brown forest soil at long term experiment scale under temperate climate conditions at Hungary. Material and Method The effect of rainfall quantity and distribution on certain crop fertilisation factors (N, P, K, Ca, Mg and yield) were studied in a long- term field experiment on acidic sandy brown forest soil at North- Eastern Hungary set up in 1962 and 2003. The agrochemical parameters of the soil were as follows: pH (H2O) 5.9, pH (KCl) 4.7, hydrolytic acidity 8.4, hy1 0.3, humus 0.7%, CEC 5-10 mgeq 100*g-1, total N 34 mg*kg-1, AL-P2O5 43 mg*kg-1, AL-K2O 60 mg*kg-1. From 1962 to 1980 the experiment consisted of 2x16x4x4=512 plots and from 1980 of 32x4=128 plots in split-split plot and factorial random block design. The gross plot size was 10x5=50 m2. The average fertiliser rates in kg*ha-1*year-1 were nitrogen 45, phosphorus 24 (P2O5), potassium 40 (K2O), magnesium 7.5 (MgO) until 1980 and nitrogen 75, phosphorus 90 (P2O5), potassium 90 (K2O), calcium 175 (Ca) and magnesium 40 (Mg) after 1980 in the form of 25 % calcium ammonium nitrate, 18 % superphosphate, 40 % potassium chloride, calcium carbonate and magnesium sulphate. The groundwater table was at a depth of 2 - 3 m. Ecological (rainfall) and experimental data bases were estimated by Hungarian traditional (Harnos, 1993) and RISSAC-HAS (Márton, 2003) standards, MANOVA (SPSS) and regression analysis (SPSS). Results and Discussion Nitrogen results are summarised from 1990 to 2001. 1. On the basis of "general" (Harnos, 1993) and triticale-specific rainfall deficiency values (Márton, 2003) the years could be classified as average (1991, 1995, 2000), dry (1993), droughty (1992, 1994, 1996), wet (1997, 1998, 2001) and over wet (1999). 2. In average years the yield of the control plots became stabilised at the 1.4 t*ha-1 level. In the fertilised treatments the highest yield (4.0 t*ha-1) was more than two times the lowest yield (1.9 t*ha-1). N fertilisation resulted in an increase of around 1.0 t*ha-1 in the main yield compared with the control. The triticale yields could only be enhanced economically by full treatment with NPK (3.3 t*ha-1) or NPKCa-, NPKMg-, NPKCaMg (3.9 t*ha-1). 3. Without fertilisation the yield in the dry and drought years was decreased 14% and 36% to that in the average year. In case of the nitrogen treatmets the yield was decreased 45% and 24%. 4. In the wet years on the unfertilised plots the yield declined 14% and in the case of the nitrogen fertilisation the yield no changed than in the average years. In the over wet year the plots yielded similar than in the average years. 5. The relationships between rainfall during the vegetation period, N, P, K, Ca and Mg fertilisation and yield were characterised by second-degree correlation depending on the level of nutrition (R: 0=0.3455**, N=0.2779+, NP=0.4722***, NK=0.3739***, NPK=0.6311***, NPKCa=0.6673***, NPKMg=0.6734***, NPKCaMg=0.6232***). The maximum yield (5.0-6.0 t*ha-1) was yielded at 550-600 mm growth period rainfall. References Harnos, Zs. 1993. Időjárás és időjárás-termés összefüggéseinek idősoros elemzése. In: Aszály 1983 (Szerk.: Baráth, Cs-né., Győrffy, B., és Harnos, Zs.). KÉE. Budapest Johnston, A. E. 2000. Some aspects of nitrogen use efficiency in arable agriculture. K. Scogs-o. Lantbr. Akad. Tidskr. 139: 8. José, A. B., Estáquio, M. J., and Márton, L. 2001. Results of Crotalaria ssp. effects on soil conservation. In: Congress on Conservation Agriculture, (Eds Armando, M. V.), ECAF., Madrid, 5, pp 1-4. Márton, L. 2001a. Climate change and N, P, K, Mg fertilization effect analysis at Tisza-river basin in a long term field experiment. Szent István University, Gödöllő, p. 9. Márton, L. 2001b. Climate change, N-fertilisation effect on rye (Secale cereale L.) yield in a long term field experiment. In: Rural development-Ecologically farming-Agriculture, (Eds Palkovics, M.), University Veszprém, Keszthely, pp 924-929. Márton, L. 2002a. Climate-Rainfall Change (CRC) and mineral fertilisation (MF) effects on different crop production. In: Challenges of the new millennium our joint responsibility. (Eds A. Borhidi). MTA ÖBKI. Budapest. 1, pp 110-111. Márton, L. 2002b. Relationships between rainfall, nutrient supplies and the yield of winter wheat (Triticum aestivum L.). Plant Production 51: 529-542. Márton, L. 2003. Relationships between rainfall, nutrient supplies and the yield of triticale. Plant Production. In press Márton, L., and Pekli, J. 2003. Plant production under sub-arctical and temperate climate conditions. SZIU. Gödöllő Acknowledgement This research was supported by Hungarian Academy of Sciences, H-Budapest Adderss of the author Dr. Márton László Ph.D Research Institute for Soil Science and Agricultural Chemistry of the Hungarian Academy of Sciences, 1022 H-Budapest, Herman O. u. 15. E-mail:marton@rissac.hu

Development of transgenic crops based on photo-biotechnology.

PubMed

Ganesan, Markkandan; Lee, Hyo-Yeon; Kim, Jeong-Il; Song, Pill-Soon

2017-11-01

The phenotypes associated with plant photomorphogenesis such as the suppressed shade avoidance response and de-etiolation offer the potential for significant enhancement of crop yields. Of many light signal transducers and transcription factors involved in the photomorphogenic responses of plants, this review focuses on the transgenic overexpression of the photoreceptor genes at the uppermost stream of the signalling events, particularly phytochromes, crytochromes and phototropins as the transgenes for the genetic engineering of crops with improved harvest yields. In promoting the harvest yields of crops, the photoreceptors mediate the light regulation of photosynthetically important genes, and the improved yields often come with the tolerance to abiotic stresses such as drought, salinity and heavy metal ions. As a genetic engineering approach, the term photo-biotechnology has been coined to convey the idea that the greater the photosynthetic efficiency that crop plants can be engineered to possess, the stronger the resistance to biotic and abiotic stresses. Development of GM crops based on photoreceptor transgenes (mainly phytochromes, crytochromes and phototropins) is reviewed with the proposal of photo-biotechnology that the photoreceptors mediate the light regulation of photosynthetically important genes, and the improved yields often come with the added benefits of crops' tolerance to environmental stresses. © 2016 John Wiley & Sons Ltd.

An assessment of irrigation needs and crop yield for the United States under potential climate changes

USGS Publications Warehouse

Brumbelow, Kelly; Georgakakos, Aris P.

2000-01-01

Past assessments of climate change on U.S. agriculture have mostly focused on changes in crop yield. Few studies have included the entire conterminous U.S., and few studies have assessed changing irrigation requirements. None have included the effects of changing soil moisture characteristics as determined by changing climatic forcing. This study assesses changes in irrigation requirements and crop yields for five crops in the areas of the U.S. where they have traditionally been grown. Physiologically-based crop models are used to incorporate inputs of climate, soils, agricultural management, and drought stress tolerance. Soil moisture values from a macroscale hydrologic model run under a future climate scenario are used to initialize soil moisture content at the beginning of each growing season. Historical crop yield data is used to calibrate model parameters and determine locally acceptable drought stress as a management parameter. Changes in irrigation demand and crop yield are assessed for both means and extremes by comparing results for atmospheric forcing close to the present climate with those for a future climate scenario. Assessments using the Canadian Center for Climate Modeling and Analysis General Circulation Model (CGCM1) indicate greater irrigation demands in the southern U.S. and decreased irrigation demands in the northern and western U.S. Crop yields typically increase except for winter wheat in the southern U.S. and corn. Variability in both irrigation demands and crop yields increases in most cases. Assessment results for the CGCM1 climate scenario are compared to those for the Hadley Centre for Climate Prediction and Research GCM (HadCM2) scenario for southwestern Georgia. The comparison shows significant differences in irrigation and yield trends, both in magnitude and direction. The differences reflect the high forecast uncertainty of current GCMs. Nonetheless, both GCMs indicate higher variability in future climatic forcing and, consequently, in the response of agricultural systems.

Educational Software for Illustration of Drainage, Evapotranspiration, and Crop Yield.

ERIC Educational Resources Information Center

Khan, A. H.; And Others

1996-01-01

Describes a study that developed a software package for illustrating drainage, evapotranspiration, and crop yield as influenced by water conditions. The software is a tool for depicting water's influence on crop production in western Kansas. (DDR)

Projected changes in crop yield mean and variability over West Africa in a world 1.5 K warmer than the pre-industrial era

NASA Astrophysics Data System (ADS)

Parkes, Ben; Defrance, Dimitri; Sultan, Benjamin; Ciais, Philippe; Wang, Xuhui

2018-02-01

The ability of a region to feed itself in the upcoming decades is an important issue. The West African population is expected to increase significantly in the next 30 years. The responses of crops to short-term climate change is critical to the population and the decision makers tasked with food security. This leads to three questions: how will crop yields change in the near future? What influence will climate change have on crop failures? Which adaptation methods should be employed to ameliorate undesirable changes? An ensemble of near-term climate projections are used to simulate maize, millet and sorghum in West Africa in the recent historic period (1986-2005) and a near-term future when global temperatures are 1.5 K above pre-industrial levels to assess the change in yield, yield variability and crop failure rate. Four crop models were used to simulate maize, millet and sorghum in West Africa in the historic and future climates. Across the majority of West Africa the maize, millet and sorghum yields are shown to fall. In the regions where yields increase, the variability also increases. This increase in variability increases the likelihood of crop failures, which are defined as yield negative anomalies beyond 1 standard deviation during the historic period. The increasing variability increases the frequency of crop failures across West Africa. The return time of crop failures falls from 8.8, 9.7 and 10.1 years to 5.2, 6.3 and 5.8 years for maize, millet and sorghum respectively. The adoption of heat-resistant cultivars and the use of captured rainwater have been investigated using one crop model as an idealized sensitivity test. The generalized doption of a cultivar resistant to high-temperature stress during flowering is shown to be more beneficial than using rainwater harvesting.

Striga Biocontrol on a Toothpick: A Readily Deployable and Inexpensive Method for Smallholder Farmers.

PubMed

Nzioki, Henry S; Oyosi, Florence; Morris, Cindy E; Kaya, Eylul; Pilgeram, Alice L; Baker, Claire S; Sands, David C

2016-01-01

Striga hermonthica (witchweed) is a parasitic weed that attacks and significantly reduces the yields of maize, sorghum, millet, and sugarcane throughout sub-Saharan Africa. Low cost management methods such as hand weeding, short crop rotations, trap cropping, or conventional biocontrol have not been effective. Likewise, Striga-tolerant or herbicide-resistant maize cultivars are higher yielding, but are often beyond the economic means of sustenance farmers. The fungal pathogen, Fusarium oxysporum f.sp. strigae, has been the object of numerous studies to develop Striga biocontrol. Under experimental conditions this pathogen can reduce the incidence of Striga infestation but field use is not extensive, perhaps because it has not been sufficiently effective in restoring crop yield and reducing the soil Striga seed bank. Here we brought together Kenyan and US crop scientists with smallholder farmers to develop and validate an effective biocontrol strategy for management of Striga on smallholder farms. Key components of this research project were the following: (1) Development of a two-step method of fungal delivery, including laboratory coating of primary inoculum on toothpicks, followed by on-farm production of secondary field inoculum in boiled rice enabling delivery of vigorous, fresh inoculum directly to the seedbed; (2) Training of smallholder farmers (85% women), to produce the biocontrol agent and incorporate it into their maize plantings in Striga-infested soils and collect agronomic data. The field tests expanded from 30 smallholder farmers to a two-season, 500-farmer plot trial including paired plus and minus biocontrol plots with fertilizer and hybrid seed in both plots and; (3) Concerted selection of variants of the pathogen identified for enhanced virulence, as has been demonstrated in other host parasite systems were employed here on Striga via pathogen excretion of the amino acids L-leucine and L-tyrosine that are toxic to Striga but innocuous to maize. This overall strategy resulted in an average of >50% increased maize yield in the March to June rains season and >40% in the September to December rains season. Integration of this enhanced plant pathogen to Striga management in maize can significantly increase the maize yield of smallholder farmers in Kenya.

Striga Biocontrol on a Toothpick: A Readily Deployable and Inexpensive Method for Smallholder Farmers

PubMed Central

Nzioki, Henry S.; Oyosi, Florence; Morris, Cindy E.; Kaya, Eylul; Pilgeram, Alice L.; Baker, Claire S.; Sands, David C.

2016-01-01

Striga hermonthica (witchweed) is a parasitic weed that attacks and significantly reduces the yields of maize, sorghum, millet, and sugarcane throughout sub-Saharan Africa. Low cost management methods such as hand weeding, short crop rotations, trap cropping, or conventional biocontrol have not been effective. Likewise, Striga-tolerant or herbicide-resistant maize cultivars are higher yielding, but are often beyond the economic means of sustenance farmers. The fungal pathogen, Fusarium oxysporum f.sp. strigae, has been the object of numerous studies to develop Striga biocontrol. Under experimental conditions this pathogen can reduce the incidence of Striga infestation but field use is not extensive, perhaps because it has not been sufficiently effective in restoring crop yield and reducing the soil Striga seed bank. Here we brought together Kenyan and US crop scientists with smallholder farmers to develop and validate an effective biocontrol strategy for management of Striga on smallholder farms. Key components of this research project were the following: (1) Development of a two-step method of fungal delivery, including laboratory coating of primary inoculum on toothpicks, followed by on-farm production of secondary field inoculum in boiled rice enabling delivery of vigorous, fresh inoculum directly to the seedbed; (2) Training of smallholder farmers (85% women), to produce the biocontrol agent and incorporate it into their maize plantings in Striga-infested soils and collect agronomic data. The field tests expanded from 30 smallholder farmers to a two-season, 500-farmer plot trial including paired plus and minus biocontrol plots with fertilizer and hybrid seed in both plots and; (3) Concerted selection of variants of the pathogen identified for enhanced virulence, as has been demonstrated in other host parasite systems were employed here on Striga via pathogen excretion of the amino acids L-leucine and L-tyrosine that are toxic to Striga but innocuous to maize. This overall strategy resulted in an average of >50% increased maize yield in the March to June rains season and >40% in the September to December rains season. Integration of this enhanced plant pathogen to Striga management in maize can significantly increase the maize yield of smallholder farmers in Kenya. PMID:27551284

Production of biomass/energy crops on phosphatic clay soils in central Florida

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stricker, J.A.; Prine, G.M.; Woodard, K.R.

1993-12-31

Phosphatic clay is a byproduct of phosphate mining. Presently more than 40,470 ha have been created, most in central Florida, and about 810 ha are being added each year. Phosphatic clays have high fertility and high water holding capacity, reducing fertilization costs and producing high yields without irrigation. Based on 10 years of research, scientists have selected tall annual-regenerating perennial C-4 grasses as having the greatest potential for biomass production in Florida. The purpose of this work was to determine the feasibility of growing these tall perennial grasses for biomass on phosphatic clay. Elephantgrass, sugarcane and energycane, and erianthus weremore » planted in duplicate replications on phosphatic clay soil in late August, 1986. yield was measured by one harvest in December or January each year for four years. Nitrogen fertilization included 112 kg ha{sup {minus}1} the first year followed by 134 kg ha{sup {minus}1} for the next three years. Nitrogen is the only supplemental nutrient needed to grow all tall grass crops on phosphatic clay. The average annual oven dry matter yield over the 4-yr period was 36.3 Mg ha{sup {minus}1} for PI 300086 elephantgrass, 45.2 for N51 elephantgrass, 42.5 for L79-1002 energycane, 49.0 for US72-1153 energycane, 49.7 for US78-1009 sugarcane, 52.2 for US56-9 sugarcane, 56.2 for CP72-1210 sugarcane, and 48.8 for 1K-7647 erianthus. More recent work has utilized domestic sewage sludge as a nitrogen source for the tall grasses. Preliminary sugar yields of selected sugarcane accessions & sweet sorghum were 4.7 Mg ha{sup {minus}1} for CP72-1210, 12.5 for US67-2022, 3.4 for US78-1009 and 1.3 Mg ha{sup {minus}1} for sweet sorghum. The high yields of the tall grasses grown on phosphatic clay with low inputs indicate a great potential for these crops as a source of renewable energy. A sustainable cropping system may be maintained by utilizing municipal sewage sludge as a nitrogen source with tall grasses on phosphatic clay.« less

Societal resilience to hydroclimatic change in the Roman World

NASA Astrophysics Data System (ADS)

Dermody, Brian; van Beek, Rens; Bierkens, Marc; Dekker, Stefan

2016-04-01

The Romans were masters of water resource management. They employed sophisticated irrigation techniques alongside a highly integrated food redistribution system that provided stable food supplies under the variable hydroclimatic regime within the Roman World. However, a number of paleoclimate studies have demonstrated hydroclimatic changes during the Roman Period that exceeded the amplitude and persistence of normal climate variability. In particular, there was a shift from warmer and more stable hydroclimatic conditions in the Roman Warm Period (c.250 BC - 250 AD) to cooler and more variable conditions in Late Roman Period (after c.250 AD). In this study we use a socio-hydrological model of the Roman world to explore the impact of hydroclimatic changes between the Roman Warm Period and Late Roman Period on the Roman food production and redistribution system. We calculate crop yields based on temperature and water resource availability using PC Raster Global Water Balance model (PCR-GLOBWB). PCR-GLOBWB is forced with reanalysis climate fields reflecting reconstructions of Roman Warm Period to the Late Roman climate patterns. Cropland areas and settlement patterns are derived from a database of 14,700 Roman settlement sites and crop suitability maps. We simulate food redistribution using a multi-agent food redistribution network with link weights based on Orbis: The Stanford Geospatial Network of the Roman World. Our analysis indicates a reduction in crop yields during the Late Roman Period compared with the Roman Warm Period owing to cooler temperatures. In addition, our simulations indicate that increased hydroclimatic variability decreased the stability of yields in the Late Roman period. Crop yields in the Western Empire are simulated to have been impacted most by the change in climate owing to cooler average temperatures and greater hydroclimatic variability compared with the Eastern part of the Empire. The food redistribution network was essential to buffer against lower and less stable yields in the Late Roman Period. However, the Late Roman Period coincided with a breakdown in the food redistribution network, making the Western Roman Empire particularly vulnerable to changing climate conditions. Our analysis demonstrates a number of important processes that have general implications for water resource management in food production and redistribution systems.

Contributions of long-term tillage systems on crop production and soil properties in the semi-arid Loess Plateau of China.

PubMed

Niu, Yining; Zhang, Renzhi; Luo, Zhuzhu; Li, Lingling; Cai, Liqun; Li, Guang; Xie, Junhong

2016-06-01

This study determined the long-term effect of tillage systems on soil properties and crop yields in a semi-arid environment. Field pea (Pisum sativum L.) and spring wheat (Triticum aestivum L.) were alternately grown in six tillage systems at Dingxi (35° 28' N, 104° 44' E), north-west China starting in 2001. After the first 6 years of experiments, conventional tillage with stubble incorporating (TS) and no-till with stubble cover (NTS) increased soil organic matter by 9.9% and 13.0%, respectively, compared to the conventional tillage with stubble removed (T); both TS and NTS also increased soil microbial counts, available K and P, and total N. No-till with stubble removed (NT), NTS and NTP (no-till with plastic mulching) had 20.7%, 62.6% and 43.7% greater alkaline phosphatase activity compared to the T treatment. Soil catalase, urease and invertase activities were all greater in the no-till treatments than in the T treatment. Averaged across 6 years, both wheat and pea achieved highest grain yields under NTS treatment. No-till with stubble retention is the most promising system for improving soil physical, biological and chemical properties, and increasing crop yields, and thus, this system can be adopted in areas with conditions similar to the semi-arid north-west China. © 2015 Society of Chemical Industry. © 2015 Society of Chemical Industry.

Climate-Agriculture-Modeling and Decision Tool for Disease (CAMDT-Disease) for seasonal climate forecast-based crop disease risk management in agriculture

NASA Astrophysics Data System (ADS)

Kim, K. H.; Lee, S.; Han, E.; Ines, A. V. M.

2017-12-01

Climate-Agriculture-Modeling and Decision Tool (CAMDT) is a decision support system (DSS) tool that aims to facilitate translations of probabilistic seasonal climate forecasts (SCF) to crop responses such as yield and water stress. Since CAMDT is a software framework connecting different models and algorithms with SCF information, it can be easily customized for different types of agriculture models. In this study, we replaced the DSSAT-CSM-Rice model originally incorporated in CAMDT with a generic epidemiological model, EPIRICE, to generate a seasonal pest outlook. The resulting CAMDT-Disease generates potential risks for selected fungal, viral, and bacterial diseases of rice over the next months by translating SCFs into agriculturally-relevant risk information. The integrated modeling procedure of CAMDT-Disease first disaggregates a given SCF using temporal downscaling methods (predictWTD or FResampler1), runs EPIRICE with the downscaled weather inputs, and finally visualizes the EPIRICE outputs as disease risk compared to that of the previous year and the 30-year-climatological average. In addition, the easy-to-use graphical user interface adopted from CAMDT allows users to simulate "what-if" scenarios of disease risks over different planting dates with given SCFs. Our future work includes the simulation of the effect of crop disease on yields through the disease simulation models with the DSSAT-CSM-Rice model, as disease remains one of the most critical yield-reducing factors in the field.

Variability in soybean yield in Brazil stemming from the interaction of heterogeneous management and climate variability

NASA Astrophysics Data System (ADS)

Cohn, A.; Bragança, A.; Jeffries, G. R.

2017-12-01

An increasing share of global agricultural production can be found in the humid tropics. Therefore, an improved understanding of the mechanisms governing variability in the output of tropical agricultural systems is of increasing importance for food security including through climate change adaptation. Yet, the long window over which many tropical crops can be sown, the diversity of crop varieties and management practices combine to challenge inference into climate risk to cropping output in analyses of tropical crop-climate sensitivity employing administrative data. In this paper, we leverage a newly developed spatially explicit dataset of soybean yields in Brazil to combat this problem. The dataset was built by training a model of remotely-sensed vegetation index data and land cover classification data using a rich in situ dataset of soybean yield and management variables collected over the period 2006 to 2016. The dataset contains soybean yields by plant date, cropping frequency, and maturity group for each 5km grid cell in Brazil. We model variation in these yields using an approach enabling the estimation of the influence of management factors on the sensitivity of soybean yields to variability in: cumulative solar radiation, extreme degree days, growing degree days, flooding rain in the harvest period, and dry spells in the rainy season. We find strong variation in climate sensitivity by management class. Planting date and maturity group each explained a great deal more variation in yield sensitivity than did cropping frequency. Brazil collects comparatively fine spatial resolution yield data. But, our attempt to replicate our results using administrative soy yield data revealed substantially lesser crop-climate sensitivity; suggesting that previous analyses employing administrative data may have underestimated climate risk to tropical soy production.

Seeing is believing I: The use of thermal sensing from satellite imagery to predict crop yield

NASA Astrophysics Data System (ADS)

B, Potgieter A.; D, Rodriguez; B, Power; J, Mclean; P, Davis

2014-02-01

Volatility in crop production has been part of the Australian environment since cropping began with the arrival of the first European settlers. Climate variability is the main factor affecting crop production at national, state and local scales. At field level spatial patterns on yield production are also determined by spatially changing soil properties in interaction with seasonal climate conditions and weather patterns at critical stages in the crop development. Here we used a combination of field level weather records, canopy characteristics, and satellite information to determine the spatial performance of a large field of wheat. The main objective of this research is to determine the ability of remote sensing technologies to capture yield losses due to water stress at the canopy level. The yield, canopy characteristics (i.e. canopy temperature and ground cover) and seasonal conditions of a field of wheat (~1400ha) (-29.402° South and 149.508°, New South Wales, Australia) were continuously monitored during the winter of 2011. Weather and crop variables were continuously monitored by installing three automatic weather stations in a transect covering different positions and soils in the landscape. Weather variables included rainfall, minimum and maximum temperatures and relative humidity, and crop characteristics included ground cover and canopy temperature. Satellite imagery Landsat TM 5 and 7 was collected at five different stages in the crop cycle. Weather variables and crop characteristics were used to calculate a crop stress index (CSI) at point and field scale (39 fields). Field data was used to validate a spatial satellite image derived index. Spatial yield data was downloaded from the harvester at the different locations in the field. We used the thermal band (land surface temperature, LST) and enhanced vegetation index (EVI) bands from the MODIS (250 m for visible bands and 1km for thermal band) and a derived EVI from Landsat TM 7 (25 m for visible and 90m for thermal) satellite platforms. Results showed that spatial variations in crop yield were related to a satellite derived canopy stress index (CSIsat) and a moisture stress index (MSIsat). A weather station level canopy stress index (CSIws) calculated at midday was correlated to the CSIsat at late morning. In addition, a strong linear relationship was observed between EVI and LST at point scale throughout the crop growth period. Differences were smallest at anthesis when the canopy closure was highest. This suggests that LST imagery data around flowering could be used to calculate crop stress over large areas of the crop. The harvested yield was related (R2 = 0.67) to CSIsat using a fix date across all fields. This relationship improved (R2 = 0.92) using both indices from all five dates across all fields during the crop growth period. Here we successfully showed that satellite derived crop attributes (CSIsat and MSIsat) can account for most of the variability in final crop yield and that they can be used to predict crop yield at field scales. Applications of these results could enhance the ability of producers to hedge their financial on -farm crop production losses due to in-season water stress by taking crop insurance. This is likely to further improve their adaptive capacity and thus strengthening the long-term viability of the industry domestically and elsewhere.

Design and analysis of mixed cropping experiments for indigenous Pacific Islands

Treesearch

Mareko P. Tofinga

1993-01-01

Mixed cropping (including agroforestry) often gives yield advan-tages as opposed to monocropping. Many criteria have been used to assess yield advantage in crop mixtures. Some of these are presented. In addition, the relative merits of replacement, additive and bivariate factorial designs are discussed. The concepts of analysis of mixed cropping are applied to an...

How changes of climate extremes affect summer and winter crop yields and water productivity in the southeast USA

NASA Astrophysics Data System (ADS)

Tian, D.; Cammarano, D.

2017-12-01

Modeling changes of crop production at regional scale is important to make adaptation measures for sustainably food supply under global change. In this study, we explore how changing climate extremes in the 20th and 21st century affect maize (summer crop) and wheat (winter crop) yields in an agriculturally important region: the southeast United States. We analyze historical (1950-1999) and projected (2006-2055) precipitation and temperature extremes by calculating the changes of 18 climate extreme indices using the statistically downscaled CMIP5 data from 10 general circulation models (GCMs). To evaluate how these climate extremes affect maize and wheat yields, historical baseline and projected maize and wheat yields under RCP4.5 and RCP8.5 scenarios are simulated using the DSSAT-CERES maize and wheat models driven by the same downscaled GCMs data. All of the changes are examined at 110 locations over the study region. The results show that most of the precipitation extreme indices do not have notable change; mean precipitation, precipitation intensity, and maximum 1-day precipitation are generally increased; the number of rainy days is decreased. The temperature extreme indices mostly showed increased values on mean temperature, number of high temperature days, diurnal temperature range, consecutive high temperature days, maximum daily maximum temperature, and minimum daily minimum temperature; the number of low temperature days and number of consecutive low temperature days are decreased. The conditional probabilistic relationships between changes in crop yields and changes in extreme indices suggested different responses of crop yields to climate extremes during sowing to anthesis and anthesis to maturity periods. Wheat yields and crop water productivity for wheat are increased due to an increased CO2 concentration and minimum temperature; evapotranspiration, maize yields, and crop water productivity for wheat are decreased owing to the increased temperature extremes. We found the effects of precipitation changes on both yields are relatively uncertain.

Projecting climate change impacts on the stability of productivities of maize and soybean in terms of probability of concurrent failure

NASA Astrophysics Data System (ADS)

Yokozawa, M.; Sakurai, G.; Iizumi, T.

2012-12-01

The globalization of the trade of food commodities has arranged agricultural production areas in the world. Current main production areas of maize and soybean, which are major cereal crops for human food and animal diet, are localized in the United States, China and Brazil. The amounts of production of maize and soybean from these three countries reached 70% and 74% of total production in the world in 2009, respectively. These three countries are hubs for the world food supply network. Simultaneous external disturbances to the localized hubs can make the network system unstable. Here, we projected the changes in stability of the productivities of maize and soybean under climate change. We used a process-based model for evaluating crop yield at a large scale for maize and soybean. The parameters are determined based on the historical agricultural statistics issued by administrative agencies during a period of 1981 to 2006 and a reanalysis data JRA25 provided by Japan Meteorological Agency. We used the climate change scenarios from outputs of MIROC5.0 simulations. We projected the time changes in maize and soybean yields of three countries under four climate change scenarios: RCP 2.6, 4.5, 6.0 and 8.5 for a period of 2010 to 2070. The significant declining trend of maize yield with time was projected in RCP 8.5 for all countries, while the yield appeared to decrease after 2050 in other RCP scenarios. The extents to which maize yield decrease in 2060s compared to the average over 1980 to 2006 were projected to be about 20% for the United States, 10% for Brazil and China in RCP 2.6, 4.5 and 6.0; 30% for the United States and Brazil, 40% for China in RCP 8.5. On the other hand, the projected changes in soybean yield were complicated. The projected extent to which soybean yield decrease in 2060s compared to the average over 1980 to 2006 was about 30% for the United States and Brazil and 20% for China in RCP 2.6. In RCP 4.5 and 6.0, the yield was projected to be constant or slightly increase compared to the average over 1980 to 2006 in Brazil and China, while the yield decrease by 20% in the United States. Yields of all the countries were projected to decrease up to 50% in RCP 8.5. We estimated the probability of concurrent failure, which is defined as function of the extent to which yields of three countries at a year decreased compared to the average yield over the past three years. We applied copula to measure the probability, which describe the relationship among multivariate probability distribution functions. For maize, the probability was projected to significantly increase in RCP 2.6 and 8.5, while that was projected to significantly increase only in RCP8.5 for soybean. The change in the probability was attributed to the increase of yearly yield variation and decreasing trend of yield over time. We extracted the trend component due to the improvements on agricultural technologies, therefore, the yearly variation and time trend in yield examined here can be attributed to climate change. From the sensitivity analyses, we found that the time trends in yields for maize and soybean were brought about mainly by the increase trend of mean temperature during the growing season.

Nation-wide assessment of climate change impacts on crops in the Philippines and Peru as part of multi-disciplinary modelling framework

NASA Astrophysics Data System (ADS)

Fujisawa, Mariko; Kanamaru, Hideki

2016-04-01

Agriculture is vulnerable to environmental changes, and climate change has been recognized as one of the most devastating factors. In many developing countries, however, few studies have focused on nation-wide assessment of crop yield and crop suitability in the future, and hence there is a large pressure on science to provide policy makers with solid predictions for major crops in the countries in support of climate risk management policies and programmes. FAO has developed the tool MOSAICC (Modelling System for Agricultural Impacts of Climate Change) where statistical climate downscaling is combined with crop yield projections under climate change scenarios. Three steps are required to get the results: 1. The historical meteorological data such as temperature and precipitation for about 30 years were collected, and future climates were statistically downscaled to the local scale, 2. The historical crop yield data were collected and regression functions were made to estimate the yield by using observed climatic data and water balance during the growing period for each crop, and 3. The yield changes in the future were estimated by using the future climate data, produced by the first step, as an input to the yield regression functions. The yield was first simulated at sub-national scale and aggregated to national scale, which is intended to provide national policies with adaptation options. The methodology considers future changes in characteristics of extreme weather events as the climate projections are on daily scale while crop simulations are on 10-daily scale. Yields were simulated with two greenhouse gas concentration pathways (RCPs) for three GCMs per crop to account for uncertainties in projections. The crop assessment constitutes a larger multi-disciplinary assessment of climate change impacts on agriculture and vulnerability of livelihoods in terms of food security (e.g. water resources, agriculture market, household-level food security from socio-economic perspective). In our presentation we will show the cases of Peru and the Philippines, and discuss the implications for agriculture policies and risk management.

[Influence of paddy rice-upland crop rotation of cold-waterlogged paddy field on crops produc- tion and soil characteristics].

PubMed

Wang, Fei; Li, Qing-hua; Lin, Cheng; He, Chun-mei; Zhong, Shao-jie; Li, Yu; Lin, Xin-jian; Huang, Jian-cheng

2015-05-01

Two consecutive years (4-crop) experiments were conducted to study the influence of different paddy rice-upland crop rotation in cold-waterlogged paddy field on the growth of crops and soil characteristics. The result showed that compared with the rice-winter fallow (CK) pattern, the two-year average yield of paddy rice under four rotation modes, including rape-rice (R-R), spring corn-rice (C-R), Chinese milk vetch-rice (M-R) and bean-rice (B-R), were increased by 5.3%-26.7%, with significant difference observed in C-R and R-R patterns. Except for M-R pattern, the annual average total economic benefits were improved by 79.0%-392.4% in all rotation pattern compared with the CK, and the ration of output/input was enhanced by 0.06-0.72 unit, with the most significant effect found in the C-R pattern. Likewise, compared with the CK, the contents of chlorophyll and carotenoid, and net photosynthetic rate (Pn) of rice plant were all increased during the full-tillering stage of rice in all rotation patterns. The rusty lines and rusty spots of soils were more obvious compared with the CK during the rice harvest, particularly in R-R, C-R and B-R patterns. The ratio of water-stable soil macro aggregates of plough layer of soil (> 2 mm) decreased at different levels in all rotation patterns while the ratios of middle aggregate (0.25-2 mm, expect for M-R) and micro aggregate of soil (< 0.25 mm) were opposite. There was a decreasing trend for soil active reducing agents in all rotation patterns, whereas the available nutrient increased. The amounts of soil bacteria in C-R and B-R patterns, fungi in B-R rotation pattern, cellulose bacteria in R-R, C-R and B-R patterns and N-fixing bacteria in B-R pattern were improved by 285.7%-403.0%, 221.7%, 64.6-92.2% and 162.2%, respectively. Moreover, the differences in all microorganisms were significant. Thus, based on the experimental results of cold-waterlogged paddy field, it was concluded that changing from single cropping rice system to C-R, R-R and B-R rotation patterns had good effect in terms of improving total yield and economic benefits, and soil physical and chemical properties were improved.

Farmers Extension Program Effects on Yield Gap in North China Plain

NASA Astrophysics Data System (ADS)

Sum, N.; Zhao, Y.

2015-12-01

Improving crop yield of the lowest yielding smallholder farmers in developing countries is essential to both food security of the country and the farmers' livelihood. Although wheat and maize production in most developed countries have reached 80% or greater of yield potential determined by simulated models, yield gap remains high in the developing world. One of these cases is the yield gap of maize in the North China Plain (NCP), where the average farmer's yield is 41% of his or her potential yield. This large yield gap indicates opportunity to raise yields substantially by improving agronomy, especially in nutrition management, irrigation facility, and mechanization issues such as technical services. Farmers' agronomic knowledge is essential to yield performance. In order to propagate such knowledge to farmers, agricultural extension programs, especially in-the-field guidance with training programs at targeted demonstration fields, have become prevalent in China. Although traditional analyses of the effects of the extension program are done through surveys, they are limited to only one to two years and to a small area. However, the spatial analysis tool Google Earth Engine (GEE) and its extensive satellite imagery data allow for unprecedented spatial temporal analysis of yield variation. We used GEE to analyze maize yield in Quzhou county in the North China Plain from 2007 to 2013. We based our analysis on the distance from a demonstration farm plot, the source of the farmers' agronomic knowledge. Our hypothesis was that the farther the farmers' fields were from the demonstration plot, the less access they would have to the knowledge, and the less increase in yield over time. Testing this hypothesis using GEE helps us determine the effectiveness of the demonstration plot in disseminating optimal agronomic practices in addition to evaluating yield performance of the demonstration field itself. Furthermore, we can easily extend this methodology to analyze the whole NCP and any other parts of the world for any type of crop.

Using observed warming to identify hazards to Mozambique maize production

USGS Publications Warehouse

Funk, Christopher C.; Harrison, Laura; Eilerts, Gary

2011-01-01

New Perspectives on Crop Yield Constraints because of Climate Change. Climate change impact assessments usually focus on changes to precipitation because most global food production is from rainfed cropping systems; however, other aspects of climate change may affect crop growth and potential yields.A recent (2011) study by the University of California, Santa Barbara (UCSB) Climate Hazards Group, determined that climate change may be affecting Mozambique's primary food crop in a usually overlooked, but potentially significant way (Harrison and others, 2011). The study focused on the direct relation between maize crop development and growing season temperature. It determined that warming during the past three decades in Mozambique may be causing more frequent crop stress and yield reductions in that country's maize crop, independent of any changes occurring in rainfall. This report summarizes the findings and conclusions of that study.

Trading carbon for food: global comparison of carbon stocks vs. crop yields on agricultural land.

PubMed

West, Paul C; Gibbs, Holly K; Monfreda, Chad; Wagner, John; Barford, Carol C; Carpenter, Stephen R; Foley, Jonathan A

2010-11-16

Expanding croplands to meet the needs of a growing population, changing diets, and biofuel production comes at the cost of reduced carbon stocks in natural vegetation and soils. Here, we present a spatially explicit global analysis of tradeoffs between carbon stocks and current crop yields. The difference among regions is striking. For example, for each unit of land cleared, the tropics lose nearly two times as much carbon (∼120 tons·ha(-1) vs. ∼63 tons·ha(-1)) and produce less than one-half the annual crop yield compared with temperate regions (1.71 tons·ha(-1)·y(-1) vs. 3.84 tons·ha(-1)·y(-1)). Therefore, newly cleared land in the tropics releases nearly 3 tons of carbon for every 1 ton of annual crop yield compared with a similar area cleared in the temperate zone. By factoring crop yield into the analysis, we specify the tradeoff between carbon stocks and crops for all areas where crops are currently grown and thereby, substantially enhance the spatial resolution relative to previous regional estimates. Particularly in the tropics, emphasis should be placed on increasing yields on existing croplands rather than clearing new lands. Our high-resolution approach can be used to determine the net effect of local land use decisions.

Network Candidate Genes in Breeding for Drought Tolerant Crops

PubMed Central

Krannich, Christoph Tim; Maletzki, Lisa; Kurowsky, Christina; Horn, Renate

2015-01-01

Climate change leading to increased periods of low water availability as well as increasing demands for food in the coming years makes breeding for drought tolerant crops a high priority. Plants have developed diverse strategies and mechanisms to survive drought stress. However, most of these represent drought escape or avoidance strategies like early flowering or low stomatal conductance that are not applicable in breeding for crops with high yields under drought conditions. Even though a great deal of research is ongoing, especially in cereals, in this regard, not all mechanisms involved in drought tolerance are yet understood. The identification of candidate genes for drought tolerance that have a high potential to be used for breeding drought tolerant crops represents a challenge. Breeding for drought tolerant crops has to focus on acceptable yields under water-limited conditions and not on survival. However, as more and more knowledge about the complex networks and the cross talk during drought is available, more options are revealed. In addition, it has to be considered that conditioning a crop for drought tolerance might require the production of metabolites and might cost the plants energy and resources that cannot be used in terms of yield. Recent research indicates that yield penalty exists and efficient breeding for drought tolerant crops with acceptable yields under well-watered and drought conditions might require uncoupling yield penalty from drought tolerance. PMID:26193269

Network Candidate Genes in Breeding for Drought Tolerant Crops.

PubMed

Krannich, Christoph Tim; Maletzki, Lisa; Kurowsky, Christina; Horn, Renate

2015-07-17

Climate change leading to increased periods of low water availability as well as increasing demands for food in the coming years makes breeding for drought tolerant crops a high priority. Plants have developed diverse strategies and mechanisms to survive drought stress. However, most of these represent drought escape or avoidance strategies like early flowering or low stomatal conductance that are not applicable in breeding for crops with high yields under drought conditions. Even though a great deal of research is ongoing, especially in cereals, in this regard, not all mechanisms involved in drought tolerance are yet understood. The identification of candidate genes for drought tolerance that have a high potential to be used for breeding drought tolerant crops represents a challenge. Breeding for drought tolerant crops has to focus on acceptable yields under water-limited conditions and not on survival. However, as more and more knowledge about the complex networks and the cross talk during drought is available, more options are revealed. In addition, it has to be considered that conditioning a crop for drought tolerance might require the production of metabolites and might cost the plants energy and resources that cannot be used in terms of yield. Recent research indicates that yield penalty exists and efficient breeding for drought tolerant crops with acceptable yields under well-watered and drought conditions might require uncoupling yield penalty from drought tolerance.

Climate Effects on Corn Yield in Missouri(.

NASA Astrophysics Data System (ADS)

Hu, Qi; Buyanovsky, Gregory

2003-11-01

Understanding climate effects on crop yield has been a continuous endeavor aiming at improving farming technology and management strategy, minimizing negative climate effects, and maximizing positive climate effects on yield. Many studies have examined climate effects on corn yield in different regions of the United States. However, most of those studies used yield and climate records that were shorter than 10 years and were for different years and localities. Although results of those studies showed various influences of climate on corn yield, they could be time specific and have been difficult to use for deriving a comprehensive understanding of climate effects on corn yield. In this study, climate effects on corn yield in central Missouri are examined using unique long-term (1895 1998) datasets of both corn yield and climate. Major results show that the climate effects on corn yield can only be explained by within-season variations in rainfall and temperature and cannot be distinguished by average growing-season conditions. Moreover, the growing-season distributions of rainfall and temperature for high-yield years are characterized by less rainfall and warmer temperature in the planting period, a rapid increase in rainfall, and more rainfall and warmer temperatures during germination and emergence. More rainfall and cooler-than-average temperatures are key features in the anthesis and kernel-filling periods from June through August, followed by less rainfall and warmer temperatures during the September and early October ripening time. Opposite variations in rainfall and temperature in the growing season correspond to low yield. Potential applications of these results in understanding how climate change may affect corn yield in the region also are discussed.

Reducing dissolved inorganic nitrogen in surface runoff water from sugarcane production systems.

PubMed

Webster, A J; Bartley, R; Armour, J D; Brodie, J E; Thorburn, P J

2012-01-01

Nitrogen (N) lost from farms, especially as the highly bioavailable dissolved inorganic form, may be damaging Australia's Great Barrier Reef (GBR). As sugarcane is the dominant cropping system in GBR catchments, its N management practises are coming under increasing scrutiny. This study measured dissolved inorganic N lost in surface runoff water and sugarcane productivity over 3 years. The experiment compared the conventional fertiliser N application rate to sugarcane (average 180kg N/ha/year) and a rate based on replacing N exported in the previous crop (average 94kg N/ha/year). Dissolved inorganic N losses in surface water were 72%, 48% and 66% lower in the three monitored years in the reduced N fertiliser treatment. There was no significant difference in sugarcane yield between the two fertiliser N treatments, nor any treatment difference in soil mineral N - both of these results are indicators of the sustainability of the lower fertiliser N applications. Copyright © 2012 Elsevier Ltd. All rights reserved.

Modelling crop yield in Iberia under drought conditions

NASA Astrophysics Data System (ADS)

Ribeiro, Andreia; Páscoa, Patrícia; Russo, Ana; Gouveia, Célia

2017-04-01

The improved assessment of the cereal yield and crop loss under drought conditions are essential to meet the increasing economy demands. The growing frequency and severity of the extreme drought conditions in the Iberian Peninsula (IP) has been likely responsible for negative impacts on agriculture, namely on crop yield losses. Therefore, a continuous monitoring of vegetation activity and a reliable estimation of drought impacts is crucial to contribute for the agricultural drought management and development of suitable information tools. This works aims to assess the influence of drought conditions in agricultural yields over the IP, considering cereal yields from mainly rainfed agriculture for the provinces with higher productivity. The main target is to develop a strategy to model drought risk on agriculture for wheat yield at a province level. In order to achieve this goal a combined assessment was made using a drought indicator (Standardized Precipitation Evapotranspiration Index, SPEI) to evaluate drought conditions together with a widely used vegetation index (Normalized Difference Vegetation Index, NDVI) to monitor vegetation activity. A correlation analysis between detrended wheat yield and SPEI was performed in order to assess the vegetation response to each time scale of drought occurrence and also identify the moment of the vegetative cycle when the crop yields are more vulnerable to drought conditions. The time scales and months of SPEI, together with the months of NDVI, better related with wheat yield were chosen to perform a multivariate regression analysis to simulate crop yield. Model results are satisfactory and highlighted the usefulness of such analysis in the framework of developing a drought risk model for crop yields. In terms of an operational point of view, the results aim to contribute to an improved understanding of crop yield management under dry conditions, particularly adding substantial information on the advantages of combining vegetation and hydro-meteorological drought indices for the assessment of cereal yield. Moreover, the present study will provide some guidance on user's decision making process in agricultural practices in the IP, assisting farmers in deciding whether to purchase crop insurance. Acknowledgements: This work was partially supported by national funds through FCT (Fundação para a Ciência e a Tecnologia, Portugal) under project IMDROFLOOD (WaterJPI/0004/2014). Ana Russo thanks FCT for granted support (SFRH/BPD/99757/2014). Andreia Ribeiro also thanks FCT for grant PD/BD/114481/2016.

Closing the N-use efficiency gap to achieve food and environmental security.

PubMed

Cui, Zhenling; Wang, Guiliang; Yue, Shanchao; Wu, Liang; Zhang, Weifeng; Zhang, Fusuo; Chen, Xinping

2014-05-20

To achieve food and environmental security, closing the gap between actual and attainable N-use efficiency should be as important as closing yield gaps. Using a meta-analysis of 205 published studies from 317 study sites, including 1332 observations from rice, wheat, and maize system in China, reactive N (Nr) losses, and total N2O emissions from N fertilization both increased exponentially with increasing N application rate. On the basis of the N loss response curves from the literature meta-analysis, the direct N2O emission, NH3 volatilization, N leaching, and N runoff, and total N2O emission (direct + indirect) were calculated using information from the survey of farmers. The PFP-N (kilogram of harvested product per kilogram of N applied (kg (kg of N)(-1))) for 6259 farmers were relative low with only 37, 23, and 32 kg (kg of N)(-1) for rice, wheat, and maize systems, respectively. In comparison, the PFP-N for highest yield and PFP-N group (refers to fields where the PFP-N was within the 80-100th percentile among those fields that achieved yields within the 80-100th percentile) averaged 62, 42, and 53 kg (kg of N)(-1) for rice, wheat, and maize systems, respectively. The corresponding grain yield would increase by 1.6-2.3 Mg ha(-1), while the N application rate would be reduced by 56-100 kg of N ha(-1) from average farmer field to highest yield and PFP-N group. In return, the Nr loss intensity (4-11 kg of N (Mg of grain)(-1)) and total N2O emission intensity (0.15-0.29 kg of N (Mg of grain)(-1)) would both be reduced significantly as compared to current agricultural practices. In many circumstances, closing the PFP-N gap in intensive cropping systems is compatible with increased crop productivity and reductions in both Nr losses and total N2O emissions.

Roguing with replacement in perennial crops: conditions for successful disease management.

PubMed

Sisterson, Mark S; Stenger, Drake C

2013-02-01

Replacement of diseased plants with healthy plants is commonly used to manage spread of plant pathogens in perennial cropping systems. This strategy has two potential benefits. First, removing infected plants may slow pathogen spread by eliminating inoculum sources. Second, replacing infected plants with uninfected plants may offset yield losses due to disease. The extent to which these benefits are realized depends on multiple factors. In this study, sensitivity analyses of two spatially explicit simulation models were used to evaluate how assumptions concerning implementation of a plant replacement program and pathogen spread interact to affect disease suppression. In conjunction, effects of assumptions concerning yield loss associated with disease and rates of plant maturity on yields were simultaneously evaluated. The first model was used to evaluate effects of plant replacement on pathogen spread and yield on a single farm, consisting of a perennial crop monoculture. The second model evaluated effects of plant replacement on pathogen spread and yield in a 100 farm crop growing region, with all farms maintaining a monoculture of the same perennial crop. Results indicated that efficient replacement of infected plants combined with a high degree of compliance among farms effectively slowed pathogen spread, resulting in replacement of few plants and high yields. In contrast, inefficient replacement of infected plants or limited compliance among farms failed to slow pathogen spread, resulting in replacement of large numbers of plants (on farms practicing replacement) with little yield benefit. Replacement of infected plants always increased yields relative to simulations without plant replacement provided that infected plants produced no useable yield. However, if infected plants produced useable yields, inefficient removal of infected plants resulted in lower yields relative to simulations without plant replacement for perennial crops with long maturation periods in some cases.

Strengths and Limitations of Operational Use of 1 Km EO Biophysical Products for Regional Prediction of Grain Yelds in Europe (wheat, barley and maize)

NASA Astrophysics Data System (ADS)

Meroni, M.; LEO, O.; Lopez-Lozano, R.; Baruth, B.; Duveiller, G.; Garcia-Condado, S.; Hooker, J.; Seguini, L.

2014-12-01

The site-specific relationship between EO indicators and actual crop yields has been explored in many different studies, describing semi-empirical regression models between spatially aggregated biophysical parameters or vegetation indices and observed yields (from field measurements or official statistics). However, when considering larger extensions -from countries to continents- agro-climatic conditions and crop management may differ substantially among regions, and these differences may greatly influence the relationship between biophysical indicators and the observed yields, which may be also driven by limiting factors other than green biomass formation. The present study aims to better assess the contribution of EO indicators within an operational crop yield forecasting system in Europe and neighbouring countries, by evaluating how these above mentioned geographic differences influence the relationship between biophysical indicators and crop yield. We therefore explore, as a first step, the correspondence between fAPAR time-series (1999-2013) and the inter-annual yield variability of wheat, barley and grain maize, at sub-national level across Europe (270-450 Administrative Units, depending on crop). In a second step, we map the agro-climatic contexts in which EO indicators better explain the observed yield inter-annual variability, identify the influence of some meteorological events on the fAPAR -yield relationship and provide some recommendations for further investigation. The results indicate that in water-limited environments (e.g. Mediterranean and Black Sea areas), fAPAR is highly correlated with yields whereas in northern Europe, crop yield appears much less limited by leaf area expansion along the season, and the relationship between yield and EO products becomes more difficult to interpret.

Sensitivity and requirement of improvements of four soybean crop simulation models for climate change studies in Southern Brazil.

PubMed

Battisti, R; Sentelhas, P C; Boote, K J

2018-05-01

Crop growth models have many uncertainties that affect the yield response to climate change. Based on that, the aim of this study was to evaluate the sensitivity of crop models to systematic changes in climate for simulating soybean attainable yield in Southern Brazil. Four crop models were used to simulate yields: AQUACROP, MONICA, DSSAT, and APSIM, as well as their ensemble. The simulations were performed considering changes of air temperature (0, + 1.5, + 3.0, + 4.5, and + 6.0 °C), [CO 2 ] (380, 480, 580, 680, and 780 ppm), rainfall (- 30, - 15, 0, + 15, and + 30%), and solar radiation (- 15, 0, + 15), applied to daily values. The baseline climate was from 1961 to 2014, totalizing 53 crop seasons. The crop models simulated a reduction of attainable yield with temperature increase, reaching 2000 kg ha -1 for the ensemble at + 6 °C, mainly due to shorter crop cycle. For rainfall, the yield had a higher rate of reduction when it was diminished than when rainfall was increased. The crop models increased yield variability when solar radiation was changed from - 15 to + 15%, whereas [CO 2 ] rise resulted in yield gains, following an asymptotic response, with a mean increase of 31% from 380 to 680 ppm. The models used require further attention to improvements in optimal and maximum cardinal temperature for development rate; runoff, water infiltration, deep drainage, and dynamic of root growth; photosynthesis parameters related to soil water availability; and energy balance of soil-plant system to define leaf temperature under elevated CO 2 .

Production and fuel characteristics of vegetable oil from oilseed crops in the Pacific Northwest

DOE Office of Scientific and Technical Information (OSTI.GOV)

Auld, D.L.; Bettis, B.L.; Peterson, C.L.

1982-01-01

The purpose of this research was to evaluate the potential yield and fuel quality of various oilseed crops adapted to the Pacific Northwest as a source of liquid fuel for diesel engines. The seed yield and oil production of three cultivars of winter rape (Brassica napus L.), two cultivars of safflower (Carthamus tinctorius L.) and two cultivars of sunflower (Helianthus annuus L.) were evaluated in replicated plots at Moscow. Additional trials were conducted at several locations in Idaho, Oregon and Washington. Sunflower, oleic and linoleic safflower, and low and high erucic acid rapeseed were evaluated for fatty acid composition, energymore » content, viscosity and engine performance in short term tests. During 20 minute engine tests power output, fuel economy and thermal efficiency were compared to diesel fuel. Winter rape produced over twice as much farm extractable oil as either safflower or sunflower. The winter rape cultivars, Norde and Jet Neuf had oil yields which averaged 1740 and 1540 L/ha, respectively. Vegetable oils contained 94 to 95% of the KJ/L of diesel fuel, but were 11.1 to 17.6 times more viscous. Viscosity of the vegetable oils was closely related to fatty acid chain length and number of unsaturated bonds (R/sup 2/=.99). During short term engine tests all vegetable oils produced power outputs equivalent to diesel, and had thermal efficiencies 1.8 to 2.8% higher than diesel. Based on these results it appears that species and cultivars of oilseed crops to be utilized as a source of fuel should be selected on the basis of oil yield. 1 figure, 5 tables.« less

Greenhouse gas emissions, soil quality, and crop productivity from a mono-rice cultivation system as influenced by fallow season straw management.

PubMed

Liu, Wei; Hussain, Saddam; Wu, Lishu; Qin, Ziguo; Li, Xiaokun; Lu, Jianwei; Khan, Fahad; Cao, Weidong; Geng, Mingjian

2016-01-01

Straw management during fallow season may influence crop productivity, soil quality, and greenhouse gas (GHG) emissions from rice field. A 3-year field experiment was carried out in central China to examine the influence of different fallow season straw management practices on rice yield, soil properties, and emissions of methane (CH4) and nitrous oxide (N2O) from a mono-rice cultivation system. The treatments comprised an unfertilized control (CK), inorganic fertilization (NPK), rice straw burning in situ (NPK + RSB), rice straw mulching (NPK + RSM), and rice straw strip mulching with green manuring (NPK + RSM + GM). The maximum rice yield, soil organic carbon, soil total nitrogen, and available potassium were observed in NPK + RSM + GM treatment. Compared with NPK, the NPK + RSM + GM recorded 9% higher grain yield averaged across 3 years. However, NPK + RSM and NPK + RSB were statistically similar with NPK regarding grain yield. The NPK + RSM and NPK + RSM + GM recorded significantly higher CH4 emission during rice growing season as well as winter fallow; however, the response of N2O emissions was variable. The NPK + RSM and NPK + RSM + GM were statistically similar for annual cumulative CH4 and N2O emissions. The NPK + RSM + GM recorded 103 and 72% higher straw-induced net economic benefits and soil organic carbon sequestration rate, and reduced net global warming potential by 27% as compared with NPK + RSM. Considering the benefits of soil fertility, higher crop productivity, and environmental safety, the NPK + RSM + GM could be the most feasible and sustainable option for mono-rice cultivation system in central China.

Sweetpotato vine management for confined food production in a space life-support system

NASA Astrophysics Data System (ADS)

Massa, Gioia D.; Mitchell, Cary A.

2012-01-01

Sweetpotato (Ipomea batatas L.) 'Whatley-Loretan' was developed for space life support by researchers at Tuskegee University for its highly productive, nutritious storage roots. This promising candidate space life-support crop has a sprawling habit and aggressive growth rate in favorable environments that demands substantial growing area. Shoot pruning is not a viable option for vine control because removal of the main shoot apex drastically inhibits storage-root initiation and development, and chemical growth retardants typically are not cleared for use with food crops. As part of a large effort by the NASA Specialized Center of Research and Training in Advanced Life Support to reduce equivalent system mass (ESM) for food production in space, the dilemma of vine management for sweetpotato was addressed in effort to conserve growth area without compromising root yield. Root yields from unbranched vines trained spirally around wire frames configured either in the shapes of cones or cylinders were similar to those from vines trained horizontally along the bench, but occupying only a small fraction of the bench area. This finding indicates that sweetpotato is highly adaptable to a variety of vine-training architectures. Planting a second plant in the growth container and training the two vines in opposite directions around frames enhanced root yield and number, but had little effect on average length of each vine or bench area occupied. Once again, root yields were similar for both configurations of wire support frames. The 3-4-month crop-production cycles for sweetpotato in the greenhouse spanned all seasons of multiple years during the course of the study, and although electric lighting was used for photoperiod control and to supplement photosynthetic light during low-light seasons, there still were differences in total light available across seasons. Light variations and other environmental differences among experiments in the greenhouse had more effects on vine length than on root yield. Average vine length correlated positively with total hours of daylight received across seasons, and responses for one plant per container were higher above a threshold duration of solar exposure, suggesting that the vines of two plants per container compete for available light. In addition to the adaptability of sweetpotato to various vine-training architectures and across seasons in terms of maintaining root productivity, the open, interior volumes of the support frames tested in this study will provide future opportunity to enhance sweetpotato root yield in space by adding novel interior lighting, such as from intracanopy arrays of light-emitting diodes. This work was sponsored by NASA grant NAG 5 1286.

Potassium in agriculture--status and perspectives.

PubMed

Zörb, Christian; Senbayram, Mehmet; Peiter, Edgar

2014-05-15

In this review we summarize factors determining the plant availability of soil potassium (K), the role of K in crop yield formation and product quality, and the dependence of crop stress resistance on K nutrition. Average soil reserves of K are generally large, but most of it is not plant-available. Therefore, crops need to be supplied with soluble K fertilizers, the demand of which is expected to increase significantly, particularly in developing regions of the world. Recent investigations have shown that organic exudates of some bacteria and plant roots play a key role in releasing otherwise unavailable K from K-bearing minerals. Thus, breeding for genotypes that have improved mechanisms to gain access to this fixed K will contribute toward more sustainable agriculture, particularly in cropping systems that do not have access to fertilizer K. In K-deficient crops, the supply of sink organs with photosynthates is impaired, and sugars accumulate in source leaves. This not only affects yield formation, but also quality parameters, for example in wheat, potato and grape. As K has beneficial effects on human health, its concentration in the harvest product is a quality parameter in itself. Owing to its fundamental roles in turgor generation, primary metabolism, and long-distance transport, K plays a prominent role in crop resistance to drought, salinity, high light, or cold as well as resistance to pests and pathogens. Despite the abundance of vital roles of K in crop production, an improvement of K uptake and use efficiency has not been a major focus of conventional or transgenic breeding in the past. In addition, current soil analysis methods for K are insufficient for some common soils, posing the risk of imbalanced fertilization. A stronger prioritization of these areas of research is needed to counter declines in soil fertility and to improve food security. Copyright © 2013 Elsevier GmbH. All rights reserved.

Releasing young hardwood crop trees-use of a chain saw costs less than herbicides

Treesearch

Gary W. Miller; Gary W. Miller

1984-01-01

A crown-touching release of 12-year-old black cherry and yellow-poplar crop trees on a good site required removing an average of 14 trees for every crop tree. An average of 80 crop trees per acre was left free-to-grow with an average growing space of 4.7 feet on all sides of the crown. Basal spraying cost $0.80 per crop tree, stem injecting cost $0.61 per crop tree,...

Crop status evaluations and yield predictions

NASA Technical Reports Server (NTRS)

Haun, J. R.

1976-01-01

One phase of the large area crop inventory project is presented. Wheat yield models based on the input of environmental variables potentially obtainable through the use of space remote sensing were developed and demonstrated. By the use of a unique method for visually qualifying daily plant development and subsequent multifactor computer analyses, it was possible to develop practical models for predicting crop development and yield. Development of wheat yield prediction models was based on the discovery that morphological changes in plants are detected and quantified on a daily basis, and that this change during a portion of the season was proportional to yield.

Energy balance in rainfed herbaceous crops in a semiarid environment for a 15-year experiment. 1. Impact of farming systems

NASA Astrophysics Data System (ADS)

Moreno, M. M.; Moreno, C.; Lacasta, C.; Tarquis, A. M.; Meco, R.

2012-04-01

During the last years, agricultural practices have led to increase yields by means of the massive consumption on non-renewable fossil energy. However, the viability of a production system does not depend solely on crop yield, but also on its efficiency in the use of available resources. This work is part of a larger study assessing the effects of three farming systems (conventional, conservation with zero tillage, and organic) and four barley-based crop rotations (barley monoculture and in rotation with vetch, sunflower and fallow) on the energy balance of crop production under the semi-arid conditions over a 15 year period. However, the present work is focused on the farming system effect, so crop rotations and years are averaged. Experiments were conducted at "La Higueruela" Experimental Farm (4°26' W, 40°04' N, altitude 450 m) (Spanish National Research Council, Santa Olalla, Toledo, central Spain). The climate is semi-arid Mediterranean, with an average seasonal rainfall of 480 mm irregularly distributed and a 4-month summer drought period. Conventional farming included the use of moldboard plow for tillage, chemical fertilizers and herbicides. Conservation farming was developed with zero tillage, direct sowing and chemical fertilizers and herbicides. Organic farming included the use of cultivator and no chemical fertilizers or herbicides. The energy balance method used required the identification and quantification of all the inputs and outputs implied, and the conversion to energy values by corresponding coefficients. The parameters considered were (i) energy inputs (EI) (diesel, machines, fertilizers, herbicides, seeds) (ii) energy outputs (EO) (energy in the harvested biomass), (iii) net energy produced (NE) (EI - EO), (iv) the energy output/input ratio (O/I), and (v) energy productivity (EP) (Crop yield/EI). EI was 3.0 and 3.5 times higher in conservation (10.4 GJ ha-1 year-1) and conventional (11.7 GJ ha-1 year-1) than in organic farming (3.41 GJ ha-1 year-1). The difference between conservation and conventional systems was as result of the greater use of machinery and, consequently, of fuel in conventional, though the use of herbicides was slightly lower. In both systems, fertilizer was the most important energy input. EO was lower for organic (17.9 GJ ha-1 year-1) than for either conventional or conservation systems (25.7 and 23.4 GJ ha-1 year-1, respectively), a result of the lower barley grain and vetch hay yields. The highest NE was obtained in organic (14.5 GJ ha-1 year-1), and the lowest in conservation (13.0 GJ ha-1 year-1). In relation to O/I, organic farming were about 2.3 times more energetically efficient (5.36) than either the conventional or conservation systems (about 2.35). EP ranged from 400 kg GJ-1 in organic to 177 kg GJ-1 in conventional. No differences in all the energy variables considered were recorded between the conventional and conservation managements. As conclusions and in terms of energy efficiency, farming systems requiring agrochemicals in semi-arid Mediterranean conditions, whether conventional or conservation, appeared to be little efficient. Chemical fertilizer was the most important energy input in these two systems, but their use did not lead to an equivalent increase in yield because of the irregular distribution in many years. Organic farming would improve the energy efficiency in these environmental conditions, offering a sustainable production with minimal inputs.

Climate change impacts on crop yield: evidence from China.

PubMed

Wei, Taoyuan; Cherry, Todd L; Glomrød, Solveig; Zhang, Tianyi

2014-11-15

When estimating climate change impact on crop yield, a typical assumption is constant elasticity of yield with respect to a climate variable even though the elasticity may be inconstant. After estimating both constant and inconstant elasticities with respect to temperature and precipitation based on provincial panel data in China 1980-2008, our results show that during that period, the temperature change contributes positively to total yield growth by 1.3% and 0.4% for wheat and rice, respectively, but negatively by 12% for maize. The impacts of precipitation change are marginal. We also compare our estimates with other studies and highlight the implications of the inconstant elasticities for crop yield, harvest and food security. We conclude that climate change impact on crop yield would not be an issue in China if positive impacts of other socio-economic factors continue in the future. Copyright © 2014 Elsevier B.V. All rights reserved.

Recent patterns of crop yield growth and stagnation.

PubMed

Ray, Deepak K; Ramankutty, Navin; Mueller, Nathaniel D; West, Paul C; Foley, Jonathan A

2012-01-01

In the coming decades, continued population growth, rising meat and dairy consumption and expanding biofuel use will dramatically increase the pressure on global agriculture. Even as we face these future burdens, there have been scattered reports of yield stagnation in the world's major cereal crops, including maize, rice and wheat. Here we study data from ∼2.5 million census observations across the globe extending over the period 1961-2008. We examined the trends in crop yields for four key global crops: maize, rice, wheat and soybeans. Although yields continue to increase in many areas, we find that across 24-39% of maize-, rice-, wheat- and soybean-growing areas, yields either never improve, stagnate or collapse. This result underscores the challenge of meeting increasing global agricultural demands. New investments in underperforming regions, as well as strategies to continue increasing yields in the high-performing areas, are required.

Improved Satellite-based Crop Yield Mapping by Spatially Explicit Parameterization of Crop Phenology

NASA Astrophysics Data System (ADS)

Jin, Z.; Azzari, G.; Lobell, D. B.

2016-12-01

Field-scale mapping of crop yields with satellite data often relies on the use of crop simulation models. However, these approaches can be hampered by inaccuracies in the simulation of crop phenology. Here we present and test an approach to use dense time series of Landsat 7 and 8 acquisitions data to calibrate various parameters related to crop phenology simulation, such as leaf number and leaf appearance rates. These parameters are then mapped across the Midwestern United States for maize and soybean, and for two different simulation models. We then implement our recently developed Scalable satellite-based Crop Yield Mapper (SCYM) with simulations reflecting the improved phenology parameterizations, and compare to prior estimates based on default phenology routines. Our preliminary results show that the proposed method can effectively alleviate the underestimation of early-season LAI by the default Agricultural Production Systems sIMulator (APSIM), and that spatially explicit parameterization for the phenology model substantially improves the SCYM performance in capturing the spatiotemporal variation in maize and soybean yield. The scheme presented in our study thus preserves the scalability of SCYM, while significantly reducing its uncertainty.

Monitoring Crop Productivity over the U.S. Corn Belt using an Improved Light Use Efficiency Model

NASA Astrophysics Data System (ADS)

Wu, X.; Xiao, X.; Zhang, Y.; Qin, Y.; Doughty, R.

2017-12-01

Large-scale monitoring of crop yield is of great significance for forecasting food production and prices and ensuring food security. Satellite data that provide temporally and spatially continuous information that by themselves or in combination with other data or models, raises possibilities to monitor and understand agricultural productivity regionally. In this study, we first used an improved light use efficiency model-Vegetation Photosynthesis Model (VPM) to simulate the gross primary production (GPP). Model evaluation showed that the simulated GPP (GPPVPM) could well captured the spatio-temporal variation of GPP derived from FLUXNET sites. Then we applied the GPPVPM to further monitor crop productivity for corn and soybean over the U.S. Corn Belt and benchmarked with county-level crop yield statistics. We found VPM-based approach provides pretty good estimates (R2 = 0.88, slope = 1.03). We further showed the impacts of climate extremes on the crop productivity and carbon use efficiency. The study indicates the great potential of VPM in estimating crop yield and in understanding of crop yield responses to climate variability and change.

Precision agriculture in dry land: spatial variability of crop yield and roles of soil surveys, aerial photos, and digital elevation models

NASA Astrophysics Data System (ADS)

Nachabe, Mahmood; Ahuja, Laj; Shaffer, Mary Lou; Ascough, J.; Flynn, Brian; Cipra, J.

1998-12-01

In dryland, yield of crop varies substantially in space, often changing by an order of magnitude within few meters. Precision agriculture aims at exploiting this variability by changing agriculture management practices in space according to site specific conditions. Thus instead of managing a field (typical area 50 to 100 hectares) as a single unit using average conditions, the field is partitioned into small pieces of land known as management units. The size of management units can be in the order of 100 to 1,000 m2 to capture the patterns of variation of yield in the field. Agricultural practices like seeding rate, type of crop, and tillage and fertilizers are applied at the scale of the management unit to suit local agronomic conditions in unit. If successfully practiced, precision agriculture has the potential of increasing income and minimizing environmental impacts by reducing over application of crop production inputs. In the 90s, the implementation of precision agriculture was facilitated tremendously due to the wide availability and use of three technologies: (1) the Global Positioning System (GPS), (2) the Geographic Information System (GIS), and (3) remote sensing. The introduction of the GPS allowed the farmer to determine his coordinate location as equipments are moved in the field. Thus, any piece of equipment can be easily programmed to vary agricultural practices according to coordinate location over the field. The GIS allowed the storage and manipulation of large sets of data and the production of yield maps. Yield maps can be correlated with soil attributes from soil survey, and/or topographical attributes from a Digital Elevation Model (DEM). This helps predicting variation of potential yield over the landscape based on the spatial distribution of soil and topographical attributes. Soil attributes may include soil PH, Organic Matter, porosity, and hydraulic conductivity, whereas topographical attributes involve the estimations of elevation, slope, aspect, curvature, and specific catchment area. Finally remote sensing provided a means of assessing soil and crop conditions over large scales from the air, without excessive sampling on the ground. There are two objectives for this work. The first objective is to analyze the spatial variability of yield across a spectrum of scales to identify the spatial characteristics of yield variation; in essence, we are trying to answer the following questions, at what scale of management unit we should resolve the field level variability and what is the relationship between this resolution and the observed variability form a yield map? The second objective is to identify the soil and topographical attributes that control yield variation over the landscape topography. We already know that, because erosion and deposition are major processes in the formation of a catena, soil variations occur in response to surface and subsurface flow over the landscape. Also landscape positions corresponding to low elevation tend to have high catchment area which usually results in high soil water content in the root zone and thick A horizon. Can topographical attributes explain yield variation observed in the landscape? Will topographical attributes extracted from a DEM compensate for the relatively poor spatial resolution from a soil survey?

Uncertainties in Predicting Rice Yield by Current Crop Models Under a Wide Range of Climatic Conditions

NASA Technical Reports Server (NTRS)

Li, Tao; Hasegawa, Toshihiro; Yin, Xinyou; Zhu, Yan; Boote, Kenneth; Adam, Myriam; Bregaglio, Simone; Buis, Samuel; Confalonieri, Roberto; Fumoto, Tamon;

Photosynthetic Energy Conversion Efficiency: Setting a Baseline for Gauging Future Improvements in Important Food and Biofuel Crops1

PubMed Central

2015-01-01

The conversion efficiency (εc) of absorbed radiation into biomass (MJ of dry matter per MJ of absorbed photosynthetically active radiation) is a component of yield potential that has been estimated at less than half the theoretical maximum. Various strategies have been proposed to improve εc, but a statistical analysis to establish baseline εc levels across different crop functional types is lacking. Data from 164 published εc studies conducted in relatively unstressed growth conditions were used to determine the means, greatest contributors to variation, and genetic trends in εc across important food and biofuel crop species. εc was greatest in biofuel crops (0.049–0.066), followed by C4 food crops (0.046–0.049), C3 nonlegumes (0.036–0.041), and finally C3 legumes (0.028–0.035). Despite confining our analysis to relatively unstressed growth conditions, total incident solar radiation and average growing season temperature most often accounted for the largest portion of εc variability. Genetic improvements in εc, when present, were less than 0.7% per year, revealing the unrealized potential of improving εc as a promising contributing strategy to meet projected future agricultural demand. PMID:25829463

Economic Performance and Sustainability of a Novel Intercropping System on the North China Plain

PubMed Central

Huang, Chengdong; Liu, Quanqing; Heerink, Nico; Stomph, TjeerdJan; Li, Baoshen; Liu, Ruili; Zhang, Hongyan; Wang, Chong; Li, Xiaolin; Zhang, Chaochun; van der Werf, Wopke; Zhang, Fusuo

2015-01-01

Double cropping of wheat and maize is common on the North China Plain, but it provides limited income to rural households due to the small farm sizes in the region. Local farmers in Quzhou County have therefore innovated their production system by integration of watermelon as a companion cash crop into the system. We examine the economic performance and sustainability of this novel intercropping system using crop yield data from 2010 to 2012 and farm household survey data collected in 2012. Our results show that the gross margin of the intercropping system exceeded that of the double cropping system by more than 50% in 2012. Labor use in the intercropping system was more than three times that in double cropping. The lower returns per labor hour in intercropping, however, exceeded the average off-farm wage in the region by a significant margin. Nutrient surpluses and irrigation water use are significant larger under the intercropping system. We conclude that the novel wheat-maize/watermelon intercropping system contributes to rural poverty alleviation and household-level food security, by raising farm incomes and generating more employment, but needs further improvement to enhance its sustainability. PMID:26275297

Economic Performance and Sustainability of a Novel Intercropping System on the North China Plain.

PubMed

Huang, Chengdong; Liu, Quanqing; Heerink, Nico; Stomph, TjeerdJan; Li, Baoshen; Liu, Ruili; Zhang, Hongyan; Wang, Chong; Li, Xiaolin; Zhang, Chaochun; van der Werf, Wopke; Zhang, Fusuo

2015-01-01

Double cropping of wheat and maize is common on the North China Plain, but it provides limited income to rural households due to the small farm sizes in the region. Local farmers in Quzhou County have therefore innovated their production system by integration of watermelon as a companion cash crop into the system. We examine the economic performance and sustainability of this novel intercropping system using crop yield data from 2010 to 2012 and farm household survey data collected in 2012. Our results show that the gross margin of the intercropping system exceeded that of the double cropping system by more than 50% in 2012. Labor use in the intercropping system was more than three times that in double cropping. The lower returns per labor hour in intercropping, however, exceeded the average off-farm wage in the region by a significant margin. Nutrient surpluses and irrigation water use are significant larger under the intercropping system. We conclude that the novel wheat-maize/watermelon intercropping system contributes to rural poverty alleviation and household-level food security, by raising farm incomes and generating more employment, but needs further improvement to enhance its sustainability.

Improving the monitoring of crop productivity using spaceborne solar-induced fluorescence.

PubMed

Guan, Kaiyu; Berry, Joseph A; Zhang, Yongguang; Joiner, Joanna; Guanter, Luis; Badgley, Grayson; Lobell, David B

2016-02-01

Large-scale monitoring of crop growth and yield has important value for forecasting food production and prices and ensuring regional food security. A newly emerging satellite retrieval, solar-induced fluorescence (SIF) of chlorophyll, provides for the first time a direct measurement related to plant photosynthetic activity (i.e. electron transport rate). Here, we provide a framework to link SIF retrievals and crop yield, accounting for stoichiometry, photosynthetic pathways, and respiration losses. We apply this framework to estimate United States crop productivity for 2007-2012, where we use the spaceborne SIF retrievals from the Global Ozone Monitoring Experiment-2 satellite, benchmarked with county-level crop yield statistics, and compare it with various traditional crop monitoring approaches. We find that a SIF-based approach accounting for photosynthetic pathways (i.e. C3 and C4 crops) provides the best measure of crop productivity among these approaches, despite the fact that SIF sensors are not yet optimized for terrestrial applications. We further show that SIF provides the ability to infer the impacts of environmental stresses on autotrophic respiration and carbon-use-efficiency, with a substantial sensitivity of both to high temperatures. These results indicate new opportunities for improved mechanistic understanding of crop yield responses to climate variability and change. © 2015 John Wiley & Sons Ltd.

Improving the Monitoring of Crop Productivity Using Spaceborne Solar-Induced Fluorescence

NASA Technical Reports Server (NTRS)

Guan, Kaiyu; Berry, Joseph A.; Zhang, Yongguang; Joiner, Joanna; Guanter, Luis; Badgley, Grayson; Lobell, David B.

2015-01-01

Large-scale monitoring of crop growth and yield has important value for forecasting food production and prices and ensuring regional food security. A newly emerging satellite retrieval, solar-induced fluorescence (SIF) of chlorophyll, provides for the first time a direct measurement related to plant photosynthetic activity (i.e. electron transport rate). Here, we provide a framework to link SIF retrievals and crop yield, accounting for stoichiometry, photosynthetic pathways, and respiration losses. We apply this framework to estimate United States crop productivity for 2007-2012, where we use the spaceborne SIF retrievals from the Global Ozone Monitoring Experiment-2 satellite, benchmarked with county-level crop yield statistics, and compare it with various traditional crop monitoring approaches. We find that a SIF-based approach accounting for photosynthetic pathways (i.e. C3 and C4 crops) provides the best measure of crop productivity among these approaches, despite the fact that SIF sensors are not yet optimized for terrestrial applications. We further show that SIF provides the ability to infer the impacts of environmental stresses on autotrophic respiration and carbon-use-efficiency, with a substantial sensitivity of both to high temperatures. These results indicate new opportunities for improved mechanistic understanding of crop yield responses to climate variability and change.

Effect of Tillage Practices on Soil Properties and Crop Productivity in Wheat-Mungbean-Rice Cropping System under Subtropical Climatic Conditions

PubMed Central

Islam, Md. Monirul; Hasanuzzaman, Mirza

2014-01-01

This study was conducted to know cropping cycles required to improve OM status in soil and to investigate the effects of medium-term tillage practices on soil properties and crop yields in Grey Terrace soil of Bangladesh under wheat-mungbean-T. aman cropping system. Four different tillage practices, namely, zero tillage (ZT), minimum tillage (MT), conventional tillage (CT), and deep tillage (DT), were studied in a randomized complete block (RCB) design with four replications. Tillage practices showed positive effects on soil properties and crop yields. After four cropping cycles, the highest OM accumulation, the maximum root mass density (0–15 cm soil depth), and the improved physical and chemical properties were recorded in the conservational tillage practices. Bulk and particle densities were decreased due to tillage practices, having the highest reduction of these properties and the highest increase of porosity and field capacity in zero tillage. The highest total N, P, K, and S in their available forms were recorded in zero tillage. All tillage practices showed similar yield after four years of cropping cycles. Therefore, we conclude that zero tillage with 20% residue retention was found to be suitable for soil health and achieving optimum yield under the cropping system in Grey Terrace soil (Aeric Albaquept). PMID:25197702

Quantifying differences in water and carbon cycling between paddy and rainfed rice (Oryza sativa L.) by flux partitioning.

PubMed

Nay-Htoon, Bhone; Xue, Wei; Lindner, Steve; Cuntz, Matthias; Ko, Jonghan; Tenhunen, John; Werner, Christiane; Dubbert, Maren

2018-01-01

Agricultural crops play an important role in the global carbon and water cycle. Global climate change scenarios predict enhanced water scarcity and altered precipitation pattern in many parts of the world. Hence, a mechanistic understanding of water fluxes, productivity and water use efficiency of cultivated crops is of major importance, i.e. to adapt management practices. We compared water and carbon fluxes of paddy and rainfed rice by canopy scale gas exchange measurements, crop growth, daily evapotranspiration, transpiration and carbon flux modeling. Throughout a monsoon rice growing season, soil evaporation in paddy rice contributed strongly to evapotranspiration (96.6% to 43.3% from initial growth to fully developed canopy and amounted to 57.9% of total water losses over the growing seasons. Evaporation of rainfed rice was significantly lower (by 65% on average) particularly before canopy closure. Water use efficiency (WUE) was significantly higher in rainfed rice both from an agronomic (WUEagro, i.e. grain yield per evapotranspiration) and ecosystem (WUEeco, i.e. gross primary production per evapotranspiration) perspective. However, our results also show that higher WUE in rainfed rice comes at the expense of higher respiration losses compared to paddy rice (26% higher on average). Hence, suggestions on water management depend on the regional water availability (i.e. Mediterranean vs. Monsoon climate) and the balance between higher respiratory losses versus a potential reduction in CH4 and other greenhouse gas emissions. Our results suggest that a shift from rainfed/unsaturated soil to waterlogged paddy conditions after closure of the rice canopy might be a good compromise towards a sustainable use of water while preserving grain yield, particularly for water-limited production areas.

Quantifying differences in water and carbon cycling between paddy and rainfed rice (Oryza sativa L.) by flux partitioning

PubMed Central

Nay‐Htoon, Bhone; Xue, Wei; Lindner, Steve; Cuntz, Matthias; Ko, Jonghan; Tenhunen, John; Werner, Christiane

2018-01-01

Agricultural crops play an important role in the global carbon and water cycle. Global climate change scenarios predict enhanced water scarcity and altered precipitation pattern in many parts of the world. Hence, a mechanistic understanding of water fluxes, productivity and water use efficiency of cultivated crops is of major importance, i.e. to adapt management practices. We compared water and carbon fluxes of paddy and rainfed rice by canopy scale gas exchange measurements, crop growth, daily evapotranspiration, transpiration and carbon flux modeling. Throughout a monsoon rice growing season, soil evaporation in paddy rice contributed strongly to evapotranspiration (96.6% to 43.3% from initial growth to fully developed canopy and amounted to 57.9% of total water losses over the growing seasons. Evaporation of rainfed rice was significantly lower (by 65% on average) particularly before canopy closure. Water use efficiency (WUE) was significantly higher in rainfed rice both from an agronomic (WUEagro, i.e. grain yield per evapotranspiration) and ecosystem (WUEeco, i.e. gross primary production per evapotranspiration) perspective. However, our results also show that higher WUE in rainfed rice comes at the expense of higher respiration losses compared to paddy rice (26% higher on average). Hence, suggestions on water management depend on the regional water availability (i.e. Mediterranean vs. Monsoon climate) and the balance between higher respiratory losses versus a potential reduction in CH4 and other greenhouse gas emissions. Our results suggest that a shift from rainfed/unsaturated soil to waterlogged paddy conditions after closure of the rice canopy might be a good compromise towards a sustainable use of water while preserving grain yield, particularly for water-limited production areas. PMID:29624613

Climate analogues suggest limited potential for intensification of production on current croplands under climate change

PubMed Central

Pugh, T.A.M.; Müller, C.; Elliott, J.; Deryng, D.; Folberth, C.; Olin, S.; Schmid, E.; Arneth, A.

2016-01-01

Climate change could pose a major challenge to efforts towards strongly increase food production over the coming decades. However, model simulations of future climate-impacts on crop yields differ substantially in the magnitude and even direction of the projected change. Combining observations of current maximum-attainable yield with climate analogues, we provide a complementary method of assessing the effect of climate change on crop yields. Strong reductions in attainable yields of major cereal crops are found across a large fraction of current cropland by 2050. These areas are vulnerable to climate change and have greatly reduced opportunity for agricultural intensification. However, the total land area, including regions not currently used for crops, climatically suitable for high attainable yields of maize, wheat and rice is similar by 2050 to the present-day. Large shifts in land-use patterns and crop choice will likely be necessary to sustain production growth rates and keep pace with demand. PMID:27646707

Climate Analogues Suggest Limited Potential for Intensification of Production on Current Croplands Under Climate Change

NASA Technical Reports Server (NTRS)

Pugh, T. A. M.; Mueller, C.; Elliott, J.; Deryng, D.; Folberth, C.; Olin, S.; Schmid, E.; Arneth, A.

2016-01-01

Climate change could pose a major challenge to efforts towards strongly increase food production over the coming decades. However, model simulations of future climate-impacts on crop yields differ substantially in the magnitude and even direction of the projected change. Combining observations of current maximum-attainable yield with climate analogues, we provide a complementary method of assessing the effect of climate change on crop yields. Strong reductions in attainable yields of major cereal crops are found across a large fraction of current cropland by 2050. These areas are vulnerable to climate change and have greatly reduced opportunity for agricultural intensification. However, the total land area, including regions not currently used for crops, climatically suitable for high attainable yields of maize, wheat and rice is similar by 2050 to the present-day. Large shifts in land-use patterns and crop choice will likely be necessary to sustain production growth rates and keep pace with demand.

Climate analogues suggest limited potential for intensification of production on current croplands under climate change

NASA Astrophysics Data System (ADS)

Pugh, T. A. M.; Müller, C.; Elliott, J.; Deryng, D.; Folberth, C.; Olin, S.; Schmid, E.; Arneth, A.

2016-09-01

Climate change could pose a major challenge to efforts towards strongly increase food production over the coming decades. However, model simulations of future climate-impacts on crop yields differ substantially in the magnitude and even direction of the projected change. Combining observations of current maximum-attainable yield with climate analogues, we provide a complementary method of assessing the effect of climate change on crop yields. Strong reductions in attainable yields of major cereal crops are found across a large fraction of current cropland by 2050. These areas are vulnerable to climate change and have greatly reduced opportunity for agricultural intensification. However, the total land area, including regions not currently used for crops, climatically suitable for high attainable yields of maize, wheat and rice is similar by 2050 to the present-day. Large shifts in land-use patterns and crop choice will likely be necessary to sustain production growth rates and keep pace with demand.

Crop responses to climatic variation

PubMed Central

Porter, John R; Semenov, Mikhail A

2005-01-01

The yield and quality of food crops is central to the well being of humans and is directly affected by climate and weather. Initial studies of climate change on crops focussed on effects of increased carbon dioxide (CO2) level and/or global mean temperature and/or rainfall and nutrition on crop production. However, crops can respond nonlinearly to changes in their growing conditions, exhibit threshold responses and are subject to combinations of stress factors that affect their growth, development and yield. Thus, climate variability and changes in the frequency of extreme events are important for yield, its stability and quality. In this context, threshold temperatures for crop processes are found not to differ greatly for different crops and are important to define for the major food crops, to assist climate modellers predict the occurrence of crop critical temperatures and their temporal resolution. This paper demonstrates the impacts of climate variability for crop production in a number of crops. Increasing temperature and precipitation variability increases the risks to yield, as shown via computer simulation and experimental studies. The issue of food quality has not been given sufficient importance when assessing the impact of climate change for food and this is addressed. Using simulation models of wheat, the concentration of grain protein is shown to respond to changes in the mean and variability of temperature and precipitation events. The paper concludes with discussion of adaptation possibilities for crops in response to drought and argues that characters that enable better exploration of the soil and slower leaf canopy expansion could lead to crop higher transpiration efficiency. PMID:16433091

Satellite-based mapping of field-scale stress indicators for crop yield forecasting: an application over Mead, NE

NASA Astrophysics Data System (ADS)

Yang, Y.; Anderson, M. C.; Gao, F.; Wardlow, B.; Hain, C.; Otkin, J.; Sun, L.; Dulaney, W.

2017-12-01

In agricultural regions, water is one of the most widely limiting factors of crop performance and production. Evapotranspiration (ET) describes crop water use through transpiration and water lost through direct soil evaporation, which makes it a good indicator of soil moisture availability and vegetation health and thus has been an integral part of many yield estimation efforts. The Evaporative Stress Index (ESI) describes temporal anomalies in a normalized evapotranspiration metric (fRET) as derived from satellite remote sensing and has demonstrated capacity to explain regional yield variability in water limited crop growing regions. However, its performance in some regions where the vegetation cycle is intensively managed appears to be degraded. In this study we generated maps of ET, fRET, and ESI at high spatiotemporal resolution (30-m pixels, daily timesteps) using a multi-sensor data fusion method, integrating information from satellite platforms with good temporal coverage and other platforms that provide field-scale spatial detail. The study was conducted over the period 2010-2014, covering a region around Mead, Nebraska that includes both rainfed and irrigated crops. Correlations between ESI and measurements of corn yield are investigated at both the field and county level to assess the value of ESI as a yield forecasting tool. To examine the role of phenology in ESI-yield correlations, annual input fRET timeseries were aligned by both calendar day and by biophysically relevant dates (e.g. days since planting or emergence). Results demonstrate that mapping of fRET and ESI at 30-m has the advantage of being able to resolve different crop types with varying phenology. The study also suggests that incorporating phenological information significantly improves yield-correlations by accounting for effects of phenology such as variable planting date and emergence date. The yield-ESI relationship in this study well captures the inter-annual variability of yields and thus has potential to be used for yield prediction, or for ingestion into a crop simulation model as a crop-specific moisture stress function.

Water Stress & Biomass Monitoring and SWAP Modeling of Irrigated Crops in Saratov Region of Russia

NASA Astrophysics Data System (ADS)

Zeyliger, Anatoly; Ermolaeva, Olga

2016-04-01

Development of modern irrigation technologies are balanced between the need to maximize production and the need to minimize water use which provides harmonious interaction of irrigated systems with closely-spaced environment. Thus requires an understanding of complex interrelationships between landscape and underground of irrigated and adjacent areas in present and future conditions aiming to minimize development of negative scenarios. In this way in each irrigated areas a combination of specific factors and drivers must be recognized and evaluated. Much can be obtained by improving the efficiency use of water applied for irrigation. Modern RS monitoring technologies offers the opportunity to develop and implement an effective irrigation control program permitting today to increase efficiency of irrigation water use. These technologies provide parameters with both high temporal and adequate spatial needed to monitor agrohydrological parameters of irrigated agricultural crops. Combination of these parameters with meteorological and biophysical parameters can be used to estimate crop water stress defined as ratio between actual (ETa) and potential (ETc) evapotranspiration. Aggregation of actual values of crop water stress with biomass (yield) data predicted by agrohydrological model based on weather forecasting and scenarios of irrigation water application may be used for indication of both rational timing and amount of irrigation water allocation. This type of analysis facilitating an efficient water management can be easily extended to irrigated areas by developing maps of water efficiency application serving as an irrigation advice system for farmers at his fields and as a decision support tool for the authorities on the large perimeter irrigation management. This contribution aims to communicate an illustrative explanation about the practical application of a data combination of agrohydrological modeling and ground & space based monitoring. For this aim some results of analyzing water stress during growing season of 2012 and yielded biomass of crops three types of crops alfalfa, corn and soya irrigated by sprinkling machines at left bank of Volga River at Saratov Region of Russia are presented and analyzed. For that a combination of data received from satellite, local meteorological station and farmers as well as SWAP model was used. Analyze of data sets of monitored water deficit of each crop averaged for irrigation period was done by linear regression with yielded biomass values. Following analyze of effectiveness of irrigation water application was done by SWAP agrohydrological model.

Interactive effects of pests increase seed yield.

PubMed

Gagic, Vesna; Riggi, Laura Ga; Ekbom, Barbara; Malsher, Gerard; Rusch, Adrien; Bommarco, Riccardo

2016-04-01

Loss in seed yield and therefore decrease in plant fitness due to simultaneous attacks by multiple herbivores is not necessarily additive, as demonstrated in evolutionary studies on wild plants. However, it is not clear how this transfers to crop plants that grow in very different conditions compared to wild plants. Nevertheless, loss in crop seed yield caused by any single pest is most often studied in isolation although crop plants are attacked by many pests that can cause substantial yield losses. This is especially important for crops able to compensate and even overcompensate for the damage. We investigated the interactive impacts on crop yield of four insect pests attacking different plant parts at different times during the cropping season. In 15 oilseed rape fields in Sweden, we estimated the damage caused by seed and stem weevils, pollen beetles, and pod midges. Pest pressure varied drastically among fields with very low correlation among pests, allowing us to explore interactive impacts on yield from attacks by multiple species. The plant damage caused by each pest species individually had, as expected, either no, or a negative impact on seed yield and the strongest negative effect was caused by pollen beetles. However, seed yield increased when plant damage caused by both seed and stem weevils was high, presumably due to the joint plant compensatory reaction to insect attack leading to overcompensation. Hence, attacks by several pests can change the impact on yield of individual pest species. Economic thresholds based on single species, on which pest management decisions currently rely, may therefore result in economically suboptimal choices being made and unnecessary excessive use of insecticides.

Fertilizer consumption and energy input for 16 crops in the United States

USGS Publications Warehouse

Amenumey, Sheila E.; Capel, Paul D.

2014-01-01

Fertilizer use by U.S. agriculture has increased over the past few decades. The production and transportation of fertilizers (nitrogen, N; phosphorus, P; potassium, K) are energy intensive. In general, about a third of the total energy input to crop production goes to the production of fertilizers, one-third to mechanization, and one-third to other inputs including labor, transportation, pesticides, and electricity. For some crops, fertilizer is the largest proportion of total energy inputs. Energy required for the production and transportation of fertilizers, as a percentage of total energy input, was determined for 16 crops in the U.S. to be: 19–60% for seven grains, 10–41% for two oilseeds, 25% for potatoes, 12–30% for three vegetables, 2–23% for two fruits, and 3% for dry beans. The harvested-area weighted-average of the fraction of crop fertilizer energy to the total input energy was 28%. The current sources of fertilizers for U.S. agriculture are dependent on imports, availability of natural gas, or limited mineral resources. Given these dependencies plus the high energy costs for fertilizers, an integrated approach for their efficient and sustainable use is needed that will simultaneously maintain or increase crop yields and food quality while decreasing adverse impacts on the environment.

Application of Thermal Infrared Remote Sensing for Quantitative Evaluation of Crop Characteristics

NASA Technical Reports Server (NTRS)

Shaw, J.; Luvall, J.; Rickman, D.; Mask, P.; Wersinger, J.; Sullivan, D.; Arnold, James E. (Technical Monitor)

2002-01-01

Evidence suggests that thermal infrared emittance (TIR) at the field-scale is largely a function of the integrated crop/soil moisture continuum. Because soil moisture dynamics largely determine crop yields in non-irrigated farming (85 % of Alabama farms are non-irrigated), TIR may be an effective method of mapping within field crop yield variability, and possibly, absolute yields. The ability to map yield variability at juvenile growth stages can lead to improved soil fertility and pest management, as well as facilitating the development of economic forecasting. Researchers at GHCC/MSFC/NASA and Auburn University are currently investigating the role of TIR in site-specific agriculture. Site-specific agriculture (SSA), or precision farming, is a method of crop production in which zones and soils within a field are delineated and managed according to their unique properties. The goal of SSA is to improve farm profits and reduce environmental impacts through targeted agrochemical applications. The foundation of SSA depends upon the spatial and temporal characterization of soil and crop properties through the creation of management zones. Management zones can be delineated using: 1) remote sensing (RS) data, 2) conventional soil testing and soil mapping, and 3) yield mapping. Portions of this research have concentrated on using remote sensing data to map yield variability in corn (Zea mays L.) and soybean (Glycine max L.) crops. Remote sensing data have been collected for several fields in the Tennessee Valley region at various crop growth stages during the last four growing seasons. Preliminary results of this study will be presented.

Global assessment of nitrogen losses and trade-offs with yields from major crop cultivations.

PubMed

Liu, Wenfeng; Yang, Hong; Liu, Junguo; Azevedo, Ligia B; Wang, Xiuying; Xu, Zongxue; Abbaspour, Karim C; Schulin, Rainer

2016-12-01

Agricultural application of reactive nitrogen (N) for fertilization is a cause of massive negative environmental problems on a global scale. However, spatially explicit and crop-specific information on global N losses into the environment and knowledge of trade-offs between N losses and crop yields are largely lacking. We use a crop growth model, Python-based Environmental Policy Integrated Climate (PEPIC), to determine global N losses from three major food crops: maize, rice, and wheat. Simulated total N losses into the environment (including water and atmosphere) are 44TgNyr -1 . Two thirds of these, or 29TgNyr -1 , are losses to water alone. Rice accounts for the highest N losses, followed by wheat and maize. The N loss intensity (NLI), defined as N losses per unit of yield, is used to address trade-offs between N losses and crop yields. The NLI presents high variation among different countries, indicating diverse N losses to produce the same amount of yields. Simulations of mitigation scenarios indicate that redistributing global N inputs and improving N management could significantly abate N losses and at the same time even increase yields without any additional total N inputs. Copyright © 2016 Elsevier B.V. All rights reserved.

Using statistical model to simulate the impact of climate change on maize yield with climate and crop uncertainties

NASA Astrophysics Data System (ADS)

Zhang, Yi; Zhao, Yanxia; Wang, Chunyi; Chen, Sining

2017-11-01

Assessment of the impact of climate change on crop productions with considering uncertainties is essential for properly identifying and decision-making agricultural practices that are sustainable. In this study, we employed 24 climate projections consisting of the combinations of eight GCMs and three emission scenarios representing the climate projections uncertainty, and two crop statistical models with 100 sets of parameters in each model representing parameter uncertainty within the crop models. The goal of this study was to evaluate the impact of climate change on maize ( Zea mays L.) yield at three locations (Benxi, Changling, and Hailun) across Northeast China (NEC) in periods 2010-2039 and 2040-2069, taking 1976-2005 as the baseline period. The multi-models ensembles method is an effective way to deal with the uncertainties. The results of ensemble simulations showed that maize yield reductions were less than 5 % in both future periods relative to the baseline. To further understand the contributions of individual sources of uncertainty, such as climate projections and crop model parameters, in ensemble yield simulations, variance decomposition was performed. The results indicated that the uncertainty from climate projections was much larger than that contributed by crop model parameters. Increased ensemble yield variance revealed the increasing uncertainty in the yield simulation in the future periods.

Opposing effects of different soil organic matter fractions on crop yields.

PubMed

Wood, Stephen A; Sokol, Noah; Bell, Colin W; Bradford, Mark A; Naeem, Shahid; Wallenstein, Matthew D; Palm, Cheryl A

2016-10-01

Soil organic matter is critical to sustainable agriculture because it provides nutrients to crops as it decomposes and increases nutrient- and water-holding capacity when built up. Fast- and slow-cycling fractions of soil organic matter can have different impacts on crop production because fast-cycling fractions rapidly release nutrients for short-term plant growth and slow-cycling fractions bind nutrients that mineralize slowly and build up water-holding capacity. We explored the controls on these fractions in a tropical agroecosystem and their relationship to crop yields. We performed physical fractionation of soil organic matter from 48 farms and plots in western Kenya. We found that fast-cycling, particulate organic matter was positively related to crop yields, but did not have a strong effect, while slower-cycling, mineral-associated organic matter was negatively related to yields. Our finding that slower-cycling organic matter was negatively related to yield points to a need to revise the view that stabilization of organic matter positively impacts food security. Our results support a new paradigm that different soil organic matter fractions are controlled by different mechanisms, potentially leading to different relationships with management outcomes, like crop yield. Effectively managing soils for sustainable agriculture requires quantifying the effects of specific organic matter fractions on these outcomes. © 2016 by the Ecological Society of America.

The importance of key floral bioactive compounds to honey bees for the detection and attraction of hybrid vegetable crops and increased seed yield.

PubMed

Mas, Flore; Harper, Aimee; Horner, Rachael; Welsh, Taylor; Jaksons, Peter; Suckling, David M

2018-02-15

Crop breeding programmes generally select for traits for improved yield and human consumption preferences. Yet, they often overlook one fundamental trait essential for insect-pollinated crops: pollinator attraction. This is even more critical for hybrid plants that rely on cross-pollination between the male-fertile line and the male-sterile line to set seeds. This study investigated the role of floral odours for honey bee pollination that could explain the poor seed yield in hybrid crops. The key floral bioactive compounds that honey bees detect were identified for three vegetable hybrid crops. It was found that 30% of the variation in bioactive compound quantities was explained by variety. Differences in quantities of the bioactive compounds triggered different degrees of olfactory response and were also associated with varied appetitive response. Correlating the abundance of each bioactive compound with seed yield, it was found that aldehydes such as nonanal and decanal can have a strong negative influence on seed yield with increasing quantity. Using these methodologies to identify relevant bioactive compounds associated with honey bee pollination, plant breeding programmes should also consider selecting for floral traits attractive to honey bees to improve crop pollination for enhanced seed yield. © 2018 Society of Chemical Industry. © 2018 Society of Chemical Industry.

Contrasting effects of landscape composition on crop yield mediated by specialist herbivores.

PubMed

Perez-Alvarez, Ricardo; Nault, Brian A; Poveda, Katja

2018-04-01

Landscape composition not only affects a variety of arthropod-mediated ecosystem services, but also disservices, such as herbivory by insect pests that may have negative effects on crop yield. Yet, little is known about how different habitats influence the dynamics of multiple herbivore species, and ultimately their collective impact on crop production. Using cabbage as a model system, we examined how landscape composition influenced the incidence of three specialist cruciferous pests (aphids, flea beetles, and leaf-feeding Lepidoptera), lepidopteran parasitoids, and crop yield across a gradient of landscape composition in New York, USA. We expected that landscapes with a higher proportion of cropland and lower habitat diversity would lead to an increase in pest pressure of the specialist herbivores and a reduction in crop yield. However, results indicated that neither greater cropland area nor lower landscape diversity influenced pest pressure or yield. Rather, pest pressure and yield were best explained by the presence of non-crop habitats (i.e., meadows) in the landscape. Specifically, cabbage was infested with fewer Lepidoptera in landscapes with a higher proportion of meadows likely resulting from increased parasitism. Conversely, cabbage was infested with more flea beetles and aphids as the proportion of meadows in the landscape increased, suggesting that these pests benefit from non-crop habitats. Furthermore, path analysis confirmed that these landscape-mediated effects on pest populations can have either positive or negative cascading effects on crop yield. Our findings illustrate how different pest species within the same cropping system show contrasting responses to landscape composition with respect to both the direction and spatial scale of the relationship. Such tradeoffs resulting from the complex interaction between multiple-pests, natural enemies, and landscape composition must be considered, if we are to manage landscapes for pest suppression benefits. © 2018 by the Ecological Society of America.

Characterizing drought stress and trait influence on maize yield under current and future conditions.

PubMed

Harrison, Matthew T; Tardieu, François; Dong, Zhanshan; Messina, Carlos D; Hammer, Graeme L

2014-03-01

Global climate change is predicted to increase temperatures, alter geographical patterns of rainfall and increase the frequency of extreme climatic events. Such changes are likely to alter the timing and magnitude of drought stresses experienced by crops. This study used new developments in the classification of crop water stress to first characterize the typology and frequency of drought-stress patterns experienced by European maize crops and their associated distributions of grain yield, and second determine the influence of the breeding traits anthesis-silking synchrony, maturity and kernel number on yield in different drought-stress scenarios, under current and future climates. Under historical conditions, a low-stress scenario occurred most frequently (ca. 40%), and three other stress types exposing crops to late-season stresses each occurred in ca. 20% of cases. A key revelation shown was that the four patterns will also be the most dominant stress patterns under 2050 conditions. Future frequencies of low drought stress were reduced by ca. 15%, and those of severe water deficit during grain filling increased from 18% to 25%. Despite this, effects of elevated CO2 on crop growth moderated detrimental effects of climate change on yield. Increasing anthesis-silking synchrony had the greatest effect on yield in low drought-stress seasonal patterns, whereas earlier maturity had the greatest effect in crops exposed to severe early-terminal drought stress. Segregating drought-stress patterns into key groups allowed greater insight into the effects of trait perturbation on crop yield under different weather conditions. We demonstrate that for crops exposed to the same drought-stress pattern, trait perturbation under current climates will have a similar impact on yield as that expected in future, even though the frequencies of severe drought stress will increase in future. These results have important ramifications for breeding of maize and have implications for studies examining genetic and physiological crop responses to environmental stresses. © 2013 John Wiley & Sons Ltd.

The impacts of data constraints on the predictive performance of a general process-based crop model (PeakN-crop v1.0)

NASA Astrophysics Data System (ADS)

Caldararu, Silvia; Purves, Drew W.; Smith, Matthew J.

2017-04-01

Improving international food security under a changing climate and increasing human population will be greatly aided by improving our ability to modify, understand and predict crop growth. What we predominantly have at our disposal are either process-based models of crop physiology or statistical analyses of yield datasets, both of which suffer from various sources of error. In this paper, we present a generic process-based crop model (PeakN-crop v1.0) which we parametrise using a Bayesian model-fitting algorithm to three different sources: data-space-based vegetation indices, eddy covariance productivity measurements and regional crop yields. We show that the model parametrised without data, based on prior knowledge of the parameters, can largely capture the observed behaviour but the data-constrained model greatly improves both the model fit and reduces prediction uncertainty. We investigate the extent to which each dataset contributes to the model performance and show that while all data improve on the prior model fit, the satellite-based data and crop yield estimates are particularly important for reducing model error and uncertainty. Despite these improvements, we conclude that there are still significant knowledge gaps, in terms of available data for model parametrisation, but our study can help indicate the necessary data collection to improve our predictions of crop yields and crop responses to environmental changes.

Cover cropping to reduce nitrate loss through subsurface drainage in the northern U.S. corn belt.

PubMed

Strock, J S; Porter, P M; Russelle, M P

2004-01-01

Despite the use of best management practices for nitrogen (N) application rate and timing, significant losses of nitrate nitrogen (NO3(-)-N) in drainage discharge continue to occur from row crop cropping systems. Our objective was to determine whether a autumn-seeded winter rye (Secale cereale L.) cover crop following corn (Zea mays L.) would reduce NO3(-)-N losses through subsurface tile drainage in a corn-soybean [Glycine mar (L.) Merr.] cropping system in the northern Corn Belt (USA) in a moderately well-drained soil. Both phases of the corn-soybean rotation, with and without the winter rye cover crop following corn, were established in 1998 in a Normania clay loam (fine-loamy, mixed, mesic Aquic Haplustoll) soil at Lamberton, MN. Cover cropping did not affect subsequent soybean yield, but reduced drainage discharge, flow-weighted mean nitrate concentration (FWMNC), and NO3(-)-N loss relative to winter fallow, although the magnitude of the effect varied considerably with annual precipitation. Three-year average drainage discharge was lower with a winter rye cover crop than without (p = 0.06). Over three years, subsurface tile-drainage discharge was reduced 11% and NO3(-)-N loss was reduced 13% for a corn-soybean cropping system with a rye cover crop following corn than with no rye cover crop. We estimate that establishment of a winter rye cover crop after corn will be successful in one of four years in southwestern Minnesota. Cover cropping with rye has the potential to be an effective management tool for reducing NO3(-)-N loss from subsurface drainage discharge despite challenges to establishment and spring growth in the north-central USA.

Variation in canopy duration in the perennial biofuel crop Miscanthus reveals complex associations with yield.

PubMed

Robson, Paul R H; Farrar, Kerrie; Gay, Alan P; Jensen, Elaine F; Clifton-Brown, John C; Donnison, Iain S

2013-05-01

Energy crops can provide a sustainable source of power and fuels, and mitigate the negative effects of CO2 emissions associated with fossil fuel use. Miscanthus is a perennial C4 energy crop capable of producing large biomass yields whilst requiring low levels of input. Miscanthus is largely unimproved and therefore there could be significant opportunities to increase yield. Further increases in yield will improve the economics, energy balance, and carbon mitigation of the crop, as well as reducing land-take. One strategy to increase yield in Miscanthus is to maximize the light captured through an extension of canopy duration. In this study, canopy duration was compared among a diverse collection of 244 Miscanthus genotypes. Canopy duration was determined by calculating the number of days between canopy establishment and senescence. Yield was positively correlated with canopy duration. Earlier establishment and later senescence were also both separately correlated with higher yield. However, although genotypes with short canopy durations were low yielding, not all genotypes with long canopy durations were high yielding. Differences of yield between genotypes with long canopy durations were associated with variation in stem and leaf traits. Different methodologies to assess canopy duration traits were investigated, including visual assessment, image analysis, light interception, and different trait thresholds. The highest correlation coefficients were associated with later assessments of traits and the use of quantum sensors for canopy establishment. A model for trait optimization to enable yield improvement in Miscanthus and other bioenergy crops is discussed.

Variation in canopy duration in the perennial biofuel crop Miscanthus reveals complex associations with yield

PubMed Central

Robson, Paul R.H.; Farrar, Kerrie; Gay, Alan P.; Jensen, Elaine F.; Clifton-Brown, John C.; Donnison, Iain S.

2013-01-01

Energy crops can provide a sustainable source of power and fuels, and mitigate the negative effects of CO2 emissions associated with fossil fuel use. Miscanthus is a perennial C4 energy crop capable of producing large biomass yields whilst requiring low levels of input. Miscanthus is largely unimproved and therefore there could be significant opportunities to increase yield. Further increases in yield will improve the economics, energy balance, and carbon mitigation of the crop, as well as reducing land-take. One strategy to increase yield in Miscanthus is to maximize the light captured through an extension of canopy duration. In this study, canopy duration was compared among a diverse collection of 244 Miscanthus genotypes. Canopy duration was determined by calculating the number of days between canopy establishment and senescence. Yield was positively correlated with canopy duration. Earlier establishment and later senescence were also both separately correlated with higher yield. However, although genotypes with short canopy durations were low yielding, not all genotypes with long canopy durations were high yielding. Differences of yield between genotypes with long canopy durations were associated with variation in stem and leaf traits. Different methodologies to assess canopy duration traits were investigated, including visual assessment, image analysis, light interception, and different trait thresholds. The highest correlation coefficients were associated with later assessments of traits and the use of quantum sensors for canopy establishment. A model for trait optimization to enable yield improvement in Miscanthus and other bioenergy crops is discussed. PMID:23599277

Assessment of energy crops alternative to maize for biogas production in the Greater Region.

PubMed

Mayer, Frédéric; Gerin, Patrick A; Noo, Anaïs; Lemaigre, Sébastien; Stilmant, Didier; Schmit, Thomas; Leclech, Nathael; Ruelle, Luc; Gennen, Jerome; von Francken-Welz, Herbert; Foucart, Guy; Flammang, Jos; Weyland, Marc; Delfosse, Philippe

2014-08-01

The biomethane yield of various energy crops, selected among potential alternatives to maize in the Greater Region, was assessed. The biomass yield, the volatile solids (VS) content and the biochemical methane potential (BMP) were measured to calculate the biomethane yield per hectare of all plant species. For all species, the dry matter biomass yield and the VS content were the main factors that influence, respectively, the biomethane yield and the BMP. Both values were predicted with good accuracy by linear regressions using the biomass yield and the VS as independent variable. The perennial crop miscanthus appeared to be the most promising alternative to maize when harvested as green matter in autumn and ensiled. Miscanthus reached a biomethane yield of 5.5 ± 1 × 10(3)m(3)ha(-1) during the second year after the establishment, as compared to 5.3 ± 1 × 10(3)m(3)ha(-1) for maize under similar crop conditions. Copyright © 2014. Published by Elsevier Ltd.

Soil properties, greenhouse gas emissions and crop yield under compost, biochar and co-composted biochar in two tropical agronomic systems.

PubMed

Bass, Adrian M; Bird, Michael I; Kay, Gavin; Muirhead, Brian

2016-04-15

The addition of organic amendments to agricultural soils has the potential to increase crop yields, reduce dependence on inorganic fertilizers and improve soil condition and resilience. We evaluated the effect of biochar (B), compost (C) and co-composted biochar (COMBI) on the soil properties, crop yield and greenhouse gas emissions from a banana and a papaya plantation in tropical Australia in the first harvest cycle. Biochar, compost and COMBI organic amendments improved soil properties, including significant increases in soil water content, CEC, K, Ca, NO3, NH4 and soil carbon content. However, increases in soil nutrient content and improvements in physical properties did not translate to improved fruit yield. Counter to our expectations, banana crop yield (weight per bunch) was reduced by 18%, 12% and 24% by B, C and COMBI additions respectively, and no significant effect was observed on the papaya crop yield. Soil efflux of CO2 was elevated by addition of C and COMBI amendments, likely due to an increase in labile carbon for microbial processing. Our data indicate a reduction in N2O flux in treatments containing biochar. The application of B, C and COMBI amendments had a generally positive effect on soil properties, but this did not translate into a crop productivity increase in this study. The benefits to soil nutrient content, soil carbon storage and N2O emission reduction need to be carefully weighed against potentially deleterious effects on crop yield, at least in the short-term. Copyright © 2016 Elsevier B.V. All rights reserved.

Downscaled climate change impacts on agricultural water resources in Puerto Rico

DOE Office of Scientific and Technical Information (OSTI.GOV)

Harmsen, E.W.; Miller, N.L.; Schlegel, N.J.

2009-04-01

The purpose of this study is to estimate reference evapotranspiration (ET{sub o}), rainfall deficit (rainfall - ET{sub o}) and relative crop yield reduction for a generic crop under climate change conditions for three locations in Puerto Rico: Adjuntas, Mayaguez, and Lajas. Reference evapotranspiration is estimated by the Penman-Monteith method. Rainfall and temperature data were statistically downscaled and evaluated using the DOE/NCAR PCM global circulation model projections for the B1 (low), A2 (mid-high) and A1fi (high) emission scenarios of the Intergovernmental Panel on Climate Change Special Report on Emission Scenarios. Relative crop yield reductions were estimated from a function dependent watermore » stress factor, which is a function of soil moisture content. Average soil moisture content for the three locations was determined by means of a simple water balance approach. Results from the analysis indicate that the rainy season will become wetter and the dry season will become drier. The 20-year mean 1990-2010 September rainfall excess (i.e., rainfall - ET{sub o} > 0) increased for all scenarios and locations from 149.8 to 356.4 mm for 2080-2100. Similarly, the 20-year average February rainfall deficit (i.e., rainfall - ET{sub o} < 0) decreased from a -26.1 mm for 1990-2010 to -72.1 mm for the year 2080-2100. The results suggest that additional water could be saved during the wet months to offset increased irrigation requirements during the dry months. Relative crop yield reduction did not change significantly under the B1 projected emissions scenario, but increased by approximately 20% during the summer months under the A1fi emissions scenario. Components of the annual water balance for the three climate change scenarios are rainfall, evapotranspiration (adjusted for soil moisture), surface runoff, aquifer recharge and change in soil moisture storage. Under the A1fi scenario, for all locations, annual evapotranspiration decreased owing to lower soil moisture, surface runoff decreased, and aquifer recharge increased. Aquifer recharge increased at all three locations because the majority of recharge occurs during the wet season and the wet season became wetter. This is good news from a groundwater production standpoint. Increasing aquifer recharge also suggests that groundwater levels may increase and this may help to minimize saltwater intrusion near the coasts as sea levels increase, provided that groundwater use is not over-subscribed.« less

Closing the yield gap could reduce projected greenhouse gas emissions: a case study of maize production in China.

PubMed

Cui, Zhenling; Yue, Shanchao; Wang, Guiliang; Meng, Qingfeng; Wu, Liang; Yang, Zhiping; Zhang, Qiang; Li, Shiqing; Zhang, Fusuo; Chen, Xinping

2013-08-01

Although the goal of doubling food demand while simultaneously reducing agricultural environmental damage has become widely accepted, the dominant agricultural paradigm still considers high yields and reduced greenhouse gas (GHG) intensity to be in conflict with one another. Here, we achieved an increase in maize yield of 70% in on-farm experiments by closing the yield gap and evaluated the trade-off between grain yield, nitrogen (N) fertilizer use, and GHG emissions. Based on two groups of N application experiments in six locations for 16 on-farm site-years, an integrated soil-crop system (HY) approach achieved 93% of the yield potential and averaged 14.8 Mg ha(-1) maize grain yield at 15.5% moisture. This is 70% higher than current crop (CC) management. More importantly, the optimal N rate for the HY system was 250 kg N ha(-1) , which is only 38% more N fertilizer input than that applied in the CC system. Both the N2 O emission intensity and GHG intensity increased exponentially as the N application rate increased, and the response curve for the CC system was always higher than that for the HY system. Although the N application rate increased by 38%, N2 O emission intensity and the GHG intensity of the HY system were reduced by 12% and 19%, respectively. These on-farm observations indicate that closing the yield gap alongside efficient N management should therefore be prominent among a portfolio of strategies to meet food demand while reducing GHG intensity at the same time. © 2013 John Wiley & Sons Ltd.

Iowa Stream Nitrate, Discharge and Precipitation: 30-Year Perspective.

PubMed

Jones, Christopher S; Schilling, Keith E; Simpson, Ian M; Wolter, Calvin F

2018-05-31

We evaluated Iowa Department of Natural Resources nitrate (NO 3 -N) and US Geological Survey hydrological data from 1987 to 2016 in nine agricultural watersheds to assess how transport of this pollutant has changed in the US state of Iowa. When the first 15 years of the 30-year water-quality record is compared to the second 15 years (1987-2001 and 2002-2016), three different metrics used to quantify NO 3 -N transport all indicate levels of this pollutant are increasing. Yield of NO 3 -N (kg ha -1 ) averaged 18% higher in the second 15 years, while flow-weighted average concentrations (mg L -1 ) were 12% higher. We also introduced the new metric of NO 3 -N yield (g ha -1 ) per mm precipitation to assess differences between years and watersheds, which averaged 21 g NO 3 -N ha -1 per 1 mm of precipitation across all watersheds and was 13% higher during the second half of the record. These increases of NO 3 -N occurred within a backdrop of increasing wetness across Iowa, with precipitation and discharge levels 8 and 16% higher in the last half of the record, indicating how NO 3 -N transport is amplified by increasing precipitation levels. The implications of this are that in future climate scenarios where rainfall is more abundant, detaining water and increasing evapotranspiration within the cropping system will be necessary to control NO 3 -N losses. Land use changes that include use of cover crops, living mulches, and perennial plants should be expanded to improve water quality and affect the water balance within agricultural basins.

The reuse of treated wastewater for agricultural purposes in Nicaragua; Central America.

PubMed

Platzer, M; Cáceres, V; Fong, N

2004-01-01

The first subsurface flow wetland (SSFW) system for about 1,000 PE, was constructed in Nicaragua in 1996 to apply this technology in the form of an integral project, combining the treatment of domestic wastewater with its reuse for crop production in small and medium size communities. The SSFW-effluent meets all standards established in the national regulations for wastewater reuse in agriculture, except for faecal coliforms, existent at an average concentration of 7 x 10(4) MPN/100 ml. A conventional surface irrigation method was used to irrigate different crop species selected to establish their risk of contamination. To judge the potential health risk for consumers and farmers, samples of vegetables and fruits harvested in the dry seasons of the years 1997 to 2002, were analyzed for the presence of pathogenic microorganisms like faecal coliforms, salmonella and shigella. In addition, a yield comparison between crops irrigated with well water using chemical fertilizers, and crops irrigated with the effluent of the SSFW-system was made, to analyze the economical benefits of the wastewater reuse.

Crop damage and livestock depredation by wildlife: a case study from Nanda Devi Biosphere Reserve, India.

PubMed

Rao, K S; Maikhuri, R K; Nautiyal, S; Saxena, K G

2002-11-01

The success of conserving biological resources in any Biosphere Reserve or protected area depends on the extent of support and positive attitudes and perceptions of local people have towards such establishments. Ignoring the dependence of the local people for their subsistence needs on resources of such areas leads to conflicts between protected area managers and the local inhabitants. Crop yield losses and livestock depredation were serious problems observed in most buffer zone villages of Nanda Devi Biosphere Reserve. In the present study 10 villages situated in the buffer zone of Nanada Devi Biosphere Reserve (1612 km2 area) in Chamoli district of Uttaranchal, India were studied during 1996-97 using a questionnaire survey of each household (419 = households; 2253 = total population in 1991; 273 ha = cultivated area). Estimates of crop yield losses were made using paired plots technique in four representative villages for each crop species. The magnitude of crop yield losses varied significantly with the distance of agricultural field from forest boundary. The total crop yield losses were high for wheat and potato in all the villages. The spatial distribution of total crop yield losses in any village indicated that they were highest in the area near to forest and least in the area near to village for all crops. Losses from areas near to forest contributed to more than 50% of total losses for each crop in all villages. However, in Lata, Peng and Tolma villages, the losses are high for kidney bean and chemmi (local variety of kidney bean) which varied between 18.5% to 30% of total losses in those villages. Potato alone represents 43.6% of total crop yield loss due to wildlife in Dronagiri village in monetary terms. Among the crops, the monetary value of yield losses are least for amaranth and highest for kidney bean. The projected total value of crop yield losses due to wildlife damage for buffer zone villages located in Garhwal Himalaya is about Rs. 538,620 (US$ 15,389). Besides food grains, horticultural crops i.e. apple, also suffered maximum damage. Major wildlife agents responsible for crop damage were wild boar, bear, porcupine, monkey, musk deer and partridge (chokor). Monkey and wild boar alone accounted for about 50% to 60% of total crop damage in the study villages. Goat and sheep are the major livestock killed by leopard. The total value of livestock losses at prevailing market rates is about Rs. 1,024,520 (US$ 29,272) in the study villages. Due to existing conservation policies and laxity in implementation of preventive measures, the problems for local inhabitants are increasing. Potential solutions discussed emphasize the need to undertake suitable and appropriate protective measures to minimize the crop losses. Change in cropping and crop composition, particularly cultivation of medicinal plants (high value low volume crops), were also suggested. Besides, fair and quick disbursement of compensation for crop loss and livestock killing need to be adopted. Local people of the buffer zone area already have a negative attitude towards park/reserve establishment due to socio-political changes inducing major economic losses and this attitude may lead to clashes and confrontations if proper ameliorative measures are not taken immediately.

How are arbuscular mycorrhizal associations related to maize growth performance during short-term cover crop rotation?

PubMed

Higo, Masao; Takahashi, Yuichi; Gunji, Kento; Isobe, Katsunori

2018-03-01

Better cover crop management options aiming to maximize the benefits of arbuscular mycorrhizal fungi (AMF) to subsequent crops are largely unknown. We investigated the impact of cover crop management methods on maize growth performance and assemblages of AMF colonizing maize roots in a field trial. The cover crop treatments comprised Italian ryegrass, wheat, brown mustard and fallow in rotation with maize. The diversity of AMF communities among cover crops used for maize management was significantly influenced by the cover crop and time course. Cover crops did not affect grain yield and aboveground biomass of subsequent maize but affected early growth. A structural equation model indicated that the root colonization, AMF diversity and maize phosphorus uptake had direct strong positive effects on yield performance. AMF variables and maize performance were related directly or indirectly to maize grain yield, whereas root colonization had a positive effect on maize performance. AMF may be an essential factor that determines the success of cover crop rotational systems. Encouraging AMF associations can potentially benefit cover cropping systems. Therefore, it is imperative to consider AMF associations and crop phenology when making management decisions. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

Simulated Near-term Climate Change Impacts on Major Crops across Latin America and the Caribbean

NASA Astrophysics Data System (ADS)

Gourdji, S.; Mesa-Diez, J.; Obando-Bonilla, D.; Navarro-Racines, C.; Moreno, P.; Fisher, M.; Prager, S.; Ramirez-Villegas, J.

2016-12-01

Robust estimates of climate change impacts on agricultural production can help to direct investments in adaptation in the coming decades. In this study commissioned by the Inter-American Development Bank, near-term climate change impacts (2020-2049) are simulated relative to a historical baseline period (1971-2000) for five major crops (maize, rice, wheat, soybean and dry bean) across Latin America and the Caribbean (LAC) using the DSSAT crop model. No adaptation or technological change is assumed, thereby providing an analysis of existing climatic stresses on yields in the region and a worst-case scenario in the coming decades. DSSAT is run across irrigated and rain-fed growing areas in the region at a 0.5° spatial resolution for each crop. Crop model inputs for soils, planting dates, crop varieties and fertilizer applications are taken from previously-published datasets, and also optimized for this study. Results show that maize and dry bean are the crops most affected by climate change, followed by wheat, with only minimal changes for rice and soybean. Generally, rain-fed production sees more severe yield declines than irrigated production, although large increases in irrigation water are needed to maintain yields, reducing the yield-irrigation productivity in most areas and potentially exacerbating existing supply limitations in watersheds. This is especially true for rice and soybean, the two crops showing the most neutral yield changes. Rain-fed yields for maize and bean are projected to decline most severely in the sub-tropical Caribbean, Central America and northern South America, where climate models show a consistent drying trend. Crop failures are also projected to increase in these areas, necessitating switches to other crops or investment in adaptation measures. Generally, investment in agricultural adaptation to climate change (such as improved seed and irrigation infrastructure) will be needed throughout the LAC region in the 21st century.

Crop yield monitoring in the Sahel using root zone soil moisture anomalies derived from SMOS soil moisture data assimilation

NASA Astrophysics Data System (ADS)

Gibon, François; Pellarin, Thierry; Alhassane, Agali; Traoré, Seydou; Baron, Christian

2017-04-01

West Africa is greatly vulnerable, especially in terms of food sustainability. Mainly based on rainfed agriculture, the high variability of the rainy season strongly impacts the crop production driven by the soil water availability in the soil. To monitor this water availability, classical methods are based on daily precipitation measurements. However, the raingauge network suffers from the poor network density in Africa (1/10000km2). Alternatively, real-time satellite-derived precipitations can be used, but they are known to suffer from large uncertainties which produce significant error on crop yield estimations. The present study proposes to use root soil moisture rather than precipitation to evaluate crop yield variations. First, a local analysis of the spatiotemporal impact of water deficit on millet crop production in Niger was done, from in-situ soil moisture measurements (AMMA-CATCH/OZCAR (French Critical Zone exploration network)) and in-situ millet yield survey. Crop yield measurements were obtained for 10 villages located in the Niamey region from 2005 to 2012. The mean production (over 8 years) is 690 kg/ha, and ranges from 381 to 872 kg/ha during this period. Various statistical relationships based on soil moisture estimates were tested, and the most promising one (R>0.9) linked the 30-cm soil moisture anomalies from mid-August to mid-September (grain filling period) to the crop yield anomalies. Based on this local study, it was proposed to derive regional statistical relationships using 30-cm soil moisture maps over West Africa. The selected approach was to use a simple hydrological model, the Antecedent Precipitation Index (API), forced by real-time satellite-based precipitation (CMORPH, PERSIANN, TRMM3B42). To reduce uncertainties related to the quality of real-time rainfall satellite products, SMOS soil moisture measurements were assimilated into the API model through a Particular Filter algorithm. Then, obtained soil moisture anomalies were compared to 17 years of crop yield estimates from the FAOSTAT database (1998-2014). Results showed that the 30-cm soil moisture anomalies explained 89% of the crop yield variation in Niger, 72% in Burkina Faso, 82% in Mali and 84% in Senegal.

Benefits of supplementing an industrial waste anaerobic digester with energy crops for increased biogas production

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nges, Ivo Achu, E-mail: Nges.Ivo_Achu@biotek.lu.se; Escobar, Federico; Fu Xinmei

2012-01-15

Highlights: Black-Right-Pointing-Pointer This study demonstrates the feasibility of co-digestion food industrial waste with energy crops. Black-Right-Pointing-Pointer Laboratory batch co-digestion led to improved methane yield and carbon to nitrogen ratio as compared to mono-digestion of industrial waste. Black-Right-Pointing-Pointer Co-digestion was also seen as a means of degrading energy crops with nutrients addition as crops are poor in nutrients. Black-Right-Pointing-Pointer Batch co-digestion methane yields were used to predict co-digestion methane yield in full scale operation. Black-Right-Pointing-Pointer It was concluded that co-digestion led an over all economically viable process and ensured a constant supply of feedstock. - Abstract: Currently, there is increasing competitionmore » for waste as feedstock for the growing number of biogas plants. This has led to fluctuation in feedstock supply and biogas plants being operated below maximum capacity. The feasibility of supplementing a protein/lipid-rich industrial waste (pig manure, slaughterhouse waste, food processing and poultry waste) mesophilic anaerobic digester with carbohydrate-rich energy crops (hemp, maize and triticale) was therefore studied in laboratory scale batch and continuous stirred tank reactors (CSTR) with a view to scale-up to a commercial biogas process. Co-digesting industrial waste and crops led to significant improvement in methane yield per ton of feedstock and carbon-to-nitrogen ratio as compared to digestion of the industrial waste alone. Biogas production from crops in combination with industrial waste also avoids the need for micronutrients normally required in crop digestion. The batch co-digestion methane yields were used to predict co-digestion methane yield in full scale operation. This was done based on the ratio of methane yields observed for laboratory batch and CSTR experiments compared to full scale CSTR digestion of industrial waste. The economy of crop-based biogas production is limited under Swedish conditions; therefore, adding crops to existing industrial waste digestion could be a viable alternative to ensure a constant/reliable supply of feedstock to the anaerobic digester.« less

Increasing influence of heat stress on French maize yields from the 1960s to the 2030s

PubMed Central

Hawkins, Ed; Fricker, Thomas E; Challinor, Andrew J; Ferro, Christopher A T; Kit Ho, Chun; Osborne, Tom M

2013-01-01

Improved crop yield forecasts could enable more effective adaptation to climate variability and change. Here, we explore how to combine historical observations of crop yields and weather with climate model simulations to produce crop yield projections for decision relevant timescales. Firstly, the effects on historical crop yields of improved technology, precipitation and daily maximum temperatures are modelled empirically, accounting for a nonlinear technology trend and interactions between temperature and precipitation, and applied specifically for a case study of maize in France. The relative importance of precipitation variability for maize yields in France has decreased significantly since the 1960s, likely due to increased irrigation. In addition, heat stress is found to be as important for yield as precipitation since around 2000. A significant reduction in maize yield is found for each day with a maximum temperature above 32 °C, in broad agreement with previous estimates. The recent increase in such hot days has likely contributed to the observed yield stagnation. Furthermore, a general method for producing near-term crop yield projections, based on climate model simulations, is developed and utilized. We use projections of future daily maximum temperatures to assess the likely change in yields due to variations in climate. Importantly, we calibrate the climate model projections using observed data to ensure both reliable temperature mean and daily variability characteristics, and demonstrate that these methods work using retrospective predictions. We conclude that, to offset the projected increased daily maximum temperatures over France, improved technology will need to increase base level yields by 12% to be confident about maintaining current levels of yield for the period 2016–2035; the current rate of yield technology increase is not sufficient to meet this target. PMID:23504849

An energy balance approach for mapping crop waterstress and yield impacts over the Czech Republic

USDA-ARS?s Scientific Manuscript database

There is a growing demand for timely, spatially distributed information regarding crop condition and water use to inform agricultural decision making and yield forecasting efforts. Remote sensing of land-surface temperature has proven valuable for mapping evapotranspiration (ET) and crop stress from...

Independent Peer Evaluation of the Large Area Crop Inventory Experiment (LACIE): The LACIE Symposium

NASA Technical Reports Server (NTRS)

1978-01-01

Yield models and crop estimate accuracy are discussed within the Large Area Crop Inventory Experiment. The wheat yield estimates in the United States, Canada, and U.S.S.R. are emphasized. Experimental results design, system implementation, data processing systems, and applications were considered.

Row and forage crop rotation effects on maize mineral nutrition and yield

USDA-ARS?s Scientific Manuscript database

Extended crop rotations provide many attributes in support of sustainable agriculture. Objectives were to investigate rotations that included row crops and forages in terms of their effects on soil characteristics as well as on maize (Zea mays L.) stover biomass, grain yield, and mineral components...

Relationship between drought severity and observed regional yields in the Czech Republic

NASA Astrophysics Data System (ADS)

Hlavinka, Petr; Semerádová, Daniela; Balek, Jan; Možný, Martin; Žalud, Zdeněk; Trnka, Miroslav

2015-04-01

Although the Czech Republic is not generally characterized as a drought prone region within European context, drought occurs and is one of the most important climatic extremes in terms of economic damages. Crop production is highly sensitive to soil water availability and the rainfed agriculture almost dominantly prevails in the Czech Republic. Generally we can observe trends towards drier conditions with more often and more severe drought episodes. Based on this, the impact analyzes are very important. The relationship between drought episodes (with various timing and severity) and observed decrease of yields at district level (NUTS4) during the period from 2000 to 2014 was analyzed within submitted study. The observed yields of spring barley, winter wheat and oilseed winter rape from 14 districts were used (210 seasons are included). All districts are positioned within southeastern part of the Czech Republic and represent various agro-climatic conditions. The regressions between various drought indicators (as independent variables) and yields (dependent variable) were established. For this purpose the several drought indicators in monthly time step were derived as spatial average for arable land (each district separately). The difference between precipitation and reference evapotranspiration (ET0), average soil moisture content available for crops up to 40 cm and 100 cm depth, percent of time with soil moisture below 50 % and below 30 % of available soil moisture up to 100 cm depth were used. For reference evapotranspiration (ET0) and soil water estimates SoilClim model was used. This software is the main module used within Drought monitoring system in the Czech Republic (www.intersucho.cz). Within this study SoilClim was used in resolution 500 x 500 meters within grids of arable land. The soil water holding capacity as well as vegetation development was considered. By this way the yield losses due to various drought intensity was identified and compared. In case of extremely dry years (e.g. 2000, 2012, …) yields declines (often devastating) were mostly explained by water balance. Moreover the differences among regions were analyzed in high detail. Based on achieved results could be concluded that SoilClim software is proper tool for quantification of drought impact within yields. The difference between precipitation and ET0 (from April to June) was identified as reasonably robust indicator but also soil water holding capacity consideration is very important. This study was funded by project "Building up a multidisciplinary scientific team focused on drought" No. CZ.1.07/2.3.00/20.0248, project supported by Czech National Agency of Agricultural Research No. QJ1310123 "Crop modelling as a tool for increasing the production potential and food security of the Czech Republic under Climate Change".

Climate driven crop planting date in the ACME Land Model (ALM): Impacts on productivity and yield

NASA Astrophysics Data System (ADS)

Drewniak, B.

2017-12-01

Climate is one of the key drivers of crop suitability and productivity in a region. The influence of climate and weather on the growing season determine the amount of time crops spend in each growth phase, which in turn impacts productivity and, more importantly, yields. Planting date can have a strong influence on yields with earlier planting generally resulting in higher yields, a sensitivity that is also present in some crop models. Furthermore, planting date is already changing and may continue, especially if longer growing seasons caused by future climate change drive early (or late) planting decisions. Crop models need an accurate method to predict plant date to allow these models to: 1) capture changes in crop management to adapt to climate change, 2) accurately model the timing of crop phenology, and 3) improve crop simulated influences on carbon, nutrient, energy, and water cycles. Previous studies have used climate as a predictor for planting date. Climate as a plant date predictor has more advantages than fixed plant dates. For example, crop expansion and other changes in land use (e.g., due to changing temperature conditions), can be accommodated without additional model inputs. As such, a new methodology to implement a predictive planting date based on climate inputs is added to the Accelerated Climate Model for Energy (ACME) Land Model (ALM). The model considers two main sources of climate data important for planting: precipitation and temperature. This method expands the current temperature threshold planting trigger and improves the estimated plant date in ALM. Furthermore, the precipitation metric for planting, which synchronizes the crop growing season with the wettest months, allows tropical crops to be introduced to the model. This presentation will demonstrate how the improved model enhances the ability of ALM to capture planting date compared with observations. More importantly, the impact of changing the planting date and introducing tropical crops will be explored. Those impacts include discussions on productivity, yield, and influences on carbon and energy fluxes.

Separating out the influence of climatic trend, fluctuations, and extreme events on crop yield: a case study in Hunan Province, China

NASA Astrophysics Data System (ADS)

Wang, Zhu; Shi, Peijun; Zhang, Zhao; Meng, Yongchang; Luan, Yibo; Wang, Jiwei

2017-09-01

Separating out the influence of climatic trend, fluctuations and extreme events on crop yield is of paramount importance to climate change adaptation, resilience, and mitigation. Previous studies lack systematic and explicit assessment of these three fundamental aspects of climate change on crop yield. This research attempts to separate out the impacts on rice yields of climatic trend (linear trend change related to mean value), fluctuations (variability surpassing the "fluctuation threshold" which defined as one standard deviation (1 SD) of the residual between the original data series and the linear trend value for each climatic variable), and extreme events (identified by absolute criterion for each kind of extreme events related to crop yield). The main idea of the research method was to construct climate scenarios combined with crop system simulation model. Comparable climate scenarios were designed to express the impact of each climate change component and, were input to the crop system model (CERES-Rice), which calculated the related simulated yield gap to quantify the percentage impacts of climatic trend, fluctuations, and extreme events. Six Agro-Meteorological Stations (AMS) in Hunan province were selected to study the quantitatively impact of climatic trend, fluctuations and extreme events involving climatic variables (air temperature, precipitation, and sunshine duration) on early rice yield during 1981-2012. The results showed that extreme events were found to have the greatest impact on early rice yield (-2.59 to -15.89%). Followed by climatic fluctuations with a range of -2.60 to -4.46%, and then the climatic trend (4.91-2.12%). Furthermore, the influence of climatic trend on early rice yield presented "trade-offs" among various climate variables and AMS. Climatic trend and extreme events associated with air temperature showed larger effects on early rice yield than other climatic variables, particularly for high-temperature events (-2.11 to -12.99%). Finally, the methodology use to separate out the influences of the climatic trend, fluctuations, and extreme events on crop yield was proved to be feasible and robust. Designing different climate scenarios and feeding them into a crop system model is a potential way to evaluate the quantitative impact of each climate variable.

Effects of input uncertainty on cross-scale crop modeling

NASA Astrophysics Data System (ADS)

Waha, Katharina; Huth, Neil; Carberry, Peter

2014-05-01

The quality of data on climate, soils and agricultural management in the tropics is in general low or data is scarce leading to uncertainty in process-based modeling of cropping systems. Process-based crop models are common tools for simulating crop yields and crop production in climate change impact studies, studies on mitigation and adaptation options or food security studies. Crop modelers are concerned about input data accuracy as this, together with an adequate representation of plant physiology processes and choice of model parameters, are the key factors for a reliable simulation. For example, assuming an error in measurements of air temperature, radiation and precipitation of ± 0.2°C, ± 2 % and ± 3 % respectively, Fodor & Kovacs (2005) estimate that this translates into an uncertainty of 5-7 % in yield and biomass simulations. In our study we seek to answer the following questions: (1) are there important uncertainties in the spatial variability of simulated crop yields on the grid-cell level displayed on maps, (2) are there important uncertainties in the temporal variability of simulated crop yields on the aggregated, national level displayed in time-series, and (3) how does the accuracy of different soil, climate and management information influence the simulated crop yields in two crop models designed for use at different spatial scales? The study will help to determine whether more detailed information improves the simulations and to advise model users on the uncertainty related to input data. We analyse the performance of the point-scale crop model APSIM (Keating et al., 2003) and the global scale crop model LPJmL (Bondeau et al., 2007) with different climate information (monthly and daily) and soil conditions (global soil map and African soil map) under different agricultural management (uniform and variable sowing dates) for the low-input maize-growing areas in Burkina Faso/West Africa. We test the models' response to different levels of input data from very little to very detailed information, and compare the models' abilities to represent the spatial variability and temporal variability in crop yields. We display the uncertainty in crop yield simulations from different input data and crop models in Taylor diagrams which are a graphical summary of the similarity between simulations and observations (Taylor, 2001). The observed spatial variability can be represented well from both models (R=0.6-0.8) but APSIM predicts higher spatial variability than LPJmL due to its sensitivity to soil parameters. Simulations with the same crop model, climate and sowing dates have similar statistics and therefore similar skill to reproduce the observed spatial variability. Soil data is less important for the skill of a crop model to reproduce the observed spatial variability. However, the uncertainty in simulated spatial variability from the two crop models is larger than from input data settings and APSIM is more sensitive to input data then LPJmL. Even with a detailed, point-scale crop model and detailed input data it is difficult to capture the complexity and diversity in maize cropping systems.

Use of vegetation health data for estimation of aus rice yield in bangladesh.

PubMed

Rahman, Atiqur; Roytman, Leonid; Krakauer, Nir Y; Nizamuddin, Mohammad; Goldberg, Mitch

2009-01-01

Rice is a vital staple crop for Bangladesh and surrounding countries, with interannual variation in yields depending on climatic conditions. We compared Bangladesh yield of aus rice, one of the main varieties grown, from official agricultural statistics with Vegetation Health (VH) Indices [Vegetation Condition Index (VCI), Temperature Condition Index (TCI) and Vegetation Health Index (VHI)] computed from Advanced Very High Resolution Radiometer (AVHRR) data covering a period of 15 years (1991-2005). A strong correlation was found between aus rice yield and VCI and VHI during the critical period of aus rice development that occurs during March-April (weeks 8-13 of the year), several months in advance of the rice harvest. Stepwise principal component regression (PCR) was used to construct a model to predict yield as a function of critical-period VHI. The model reduced the yield prediction error variance by 62% compared with a prediction of average yield for each year. Remote sensing is a valuable tool for estimating rice yields well in advance of harvest and at a low cost.