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Sample records for agricultural crop yields

  1. Prediction of Potato Crop Yield Using Precision Agriculture Techniques

    PubMed Central

    Al-Gaadi, Khalid A.; Hassaballa, Abdalhaleem A.; Tola, ElKamil; Kayad, Ahmed G.; Madugundu, Rangaswamy; Alblewi, Bander; Assiri, Fahad

    2016-01-01

    Crop growth and yield monitoring over agricultural fields is an essential procedure for food security and agricultural economic return prediction. The advances in remote sensing have enhanced the process of monitoring the development of agricultural crops and estimating their yields. Therefore, remote sensing and GIS techniques were employed, in this study, to predict potato tuber crop yield on three 30 ha center pivot irrigated fields in an agricultural scheme located in the Eastern Region of Saudi Arabia. Landsat-8 and Sentinel-2 satellite images were acquired during the potato growth stages and two vegetation indices (the normalized difference vegetation index (NDVI) and the soil adjusted vegetation index (SAVI)) were generated from the images. Vegetation index maps were developed and classified into zones based on vegetation health statements, where the stratified random sampling points were accordingly initiated. Potato yield samples were collected 2–3 days prior to the harvest time and were correlated to the adjacent NDVI and SAVI, where yield prediction algorithms were developed and used to generate prediction yield maps. Results of the study revealed that the difference between predicted yield values and actual ones (prediction error) ranged between 7.9 and 13.5% for Landsat-8 images and between 3.8 and 10.2% for Sentinel-2 images. The relationship between actual and predicted yield values produced R2 values ranging between 0.39 and 0.65 for Landsat-8 images and between 0.47 and 0.65 for Sentinel-2 images. Results of this study revealed a considerable variation in field productivity across the three fields, where high-yield areas produced an average yield of above 40 t ha-1; while, the low-yield areas produced, on the average, less than 21 t ha-1. Identifying such great variation in field productivity will assist farmers and decision makers in managing their practices. PMID:27611577

  2. Prediction of Potato Crop Yield Using Precision Agriculture Techniques.

    PubMed

    Al-Gaadi, Khalid A; Hassaballa, Abdalhaleem A; Tola, ElKamil; Kayad, Ahmed G; Madugundu, Rangaswamy; Alblewi, Bander; Assiri, Fahad

    2016-01-01

    Crop growth and yield monitoring over agricultural fields is an essential procedure for food security and agricultural economic return prediction. The advances in remote sensing have enhanced the process of monitoring the development of agricultural crops and estimating their yields. Therefore, remote sensing and GIS techniques were employed, in this study, to predict potato tuber crop yield on three 30 ha center pivot irrigated fields in an agricultural scheme located in the Eastern Region of Saudi Arabia. Landsat-8 and Sentinel-2 satellite images were acquired during the potato growth stages and two vegetation indices (the normalized difference vegetation index (NDVI) and the soil adjusted vegetation index (SAVI)) were generated from the images. Vegetation index maps were developed and classified into zones based on vegetation health statements, where the stratified random sampling points were accordingly initiated. Potato yield samples were collected 2-3 days prior to the harvest time and were correlated to the adjacent NDVI and SAVI, where yield prediction algorithms were developed and used to generate prediction yield maps. Results of the study revealed that the difference between predicted yield values and actual ones (prediction error) ranged between 7.9 and 13.5% for Landsat-8 images and between 3.8 and 10.2% for Sentinel-2 images. The relationship between actual and predicted yield values produced R2 values ranging between 0.39 and 0.65 for Landsat-8 images and between 0.47 and 0.65 for Sentinel-2 images. Results of this study revealed a considerable variation in field productivity across the three fields, where high-yield areas produced an average yield of above 40 t ha-1; while, the low-yield areas produced, on the average, less than 21 t ha-1. Identifying such great variation in field productivity will assist farmers and decision makers in managing their practices.

  3. Agriculture and Bioactives: Achieving Both Crop Yield and Phytochemicals

    PubMed Central

    García-Mier, Lina; Guevara-González, Ramón G.; Mondragón-Olguín, Víctor M.; Verduzco-Cuellar, Beatriz del Rocío; Torres-Pacheco, Irineo

    2013-01-01

    Plants are fundamental elements of the human diet, either as direct sources of nutrients or indirectly as feed for animals. During the past few years, the main goal of agriculture has been to increase yield in order to provide the food that is needed by a growing world population. As important as yield, but commonly forgotten in conventional agriculture, is to keep and, if it is possible, to increase the phytochemical content due to their health implications. Nowadays, it is necessary to go beyond this, reconciling yield and phytochemicals that, at first glance, might seem in conflict. This can be accomplished through reviewing food requirements, plant consumption with health implications, and farming methods. The aim of this work is to show how both yield and phytochemicals converge into a new vision of agricultural management in a framework of integrated agricultural practices. PMID:23429238

  4. Commercial Crop Yields Reveal Strengths and Weaknesses for Organic Agriculture in the United States

    PubMed Central

    Savage, Steven D.; Jabbour, Randa

    2016-01-01

    Land area devoted to organic agriculture has increased steadily over the last 20 years in the United States, and elsewhere around the world. A primary criticism of organic agriculture is lower yield compared to non-organic systems. Previous analyses documenting the yield deficiency in organic production have relied mostly on data generated under experimental conditions, but these studies do not necessarily reflect the full range of innovation or practical limitations that are part of commercial agriculture. The analysis we present here offers a new perspective, based on organic yield data collected from over 10,000 organic farmers representing nearly 800,000 hectares of organic farmland. We used publicly available data from the United States Department of Agriculture to estimate yield differences between organic and conventional production methods for the 2014 production year. Similar to previous work, organic crop yields in our analysis were lower than conventional crop yields for most crops. Averaged across all crops, organic yield averaged 80% of conventional yield. However, several crops had no significant difference in yields between organic and conventional production, and organic yields surpassed conventional yields for some hay crops. The organic to conventional yield ratio varied widely among crops, and in some cases, among locations within a crop. For soybean (Glycine max) and potato (Solanum tuberosum), organic yield was more similar to conventional yield in states where conventional yield was greatest. The opposite trend was observed for barley (Hordeum vulgare), wheat (Triticum aestevum), and hay crops, however, suggesting the geographical yield potential has an inconsistent effect on the organic yield gap. PMID:27552217

  5. Commercial Crop Yields Reveal Strengths and Weaknesses for Organic Agriculture in the United States.

    PubMed

    Kniss, Andrew R; Savage, Steven D; Jabbour, Randa

    2016-01-01

    Land area devoted to organic agriculture has increased steadily over the last 20 years in the United States, and elsewhere around the world. A primary criticism of organic agriculture is lower yield compared to non-organic systems. Previous analyses documenting the yield deficiency in organic production have relied mostly on data generated under experimental conditions, but these studies do not necessarily reflect the full range of innovation or practical limitations that are part of commercial agriculture. The analysis we present here offers a new perspective, based on organic yield data collected from over 10,000 organic farmers representing nearly 800,000 hectares of organic farmland. We used publicly available data from the United States Department of Agriculture to estimate yield differences between organic and conventional production methods for the 2014 production year. Similar to previous work, organic crop yields in our analysis were lower than conventional crop yields for most crops. Averaged across all crops, organic yield averaged 80% of conventional yield. However, several crops had no significant difference in yields between organic and conventional production, and organic yields surpassed conventional yields for some hay crops. The organic to conventional yield ratio varied widely among crops, and in some cases, among locations within a crop. For soybean (Glycine max) and potato (Solanum tuberosum), organic yield was more similar to conventional yield in states where conventional yield was greatest. The opposite trend was observed for barley (Hordeum vulgare), wheat (Triticum aestevum), and hay crops, however, suggesting the geographical yield potential has an inconsistent effect on the organic yield gap.

  6. Airborne and satellite imagery for mapping crop yield variability and other precision agriculture applications

    Technology Transfer Automated Retrieval System (TEKTRAN)

    With increased use of precision agriculture techniques, information concerning within-field yield variability is becoming important for effective crop management. Despite the commercial availability of yield monitors, most of the harvesters are not equipped with them. Moreover, yield monitor data ca...

  7. 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

  8. 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.

  9. Stagnating crop yields: An overlooked risk for the carbon balance of agricultural soils?

    PubMed

    Wiesmeier, Martin; Hübner, Rico; Kögel-Knabner, Ingrid

    2015-12-01

    The carbon (C) balance of agricultural soils may be largely affected by climate change. Increasing temperatures are discussed to cause a loss of soil organic carbon (SOC) due to enhanced decomposition of soil organic matter, which has a high intrinsic temperature sensitivity. On the other hand, several modeling studies assumed that potential SOC losses would be compensated or even outperformed by an increased C input by crop residues into agricultural soils. This assumption was based on a predicted general increase of net primary productivity (NPP) as a result of the CO2 fertilization effect and prolonged growing seasons. However, it is questionable if the crop C input into agricultural soils can be derived from NPP predictions of vegetation models. The C input in European croplands is largely controlled by the agricultural management and was strongly related to the development of crop yields in the last decades. Thus, a glance at past yield development will probably be more instructive for future estimations of the C input than previous modeling approaches based on NPP predictions. An analysis of European yield statistics indicated that yields of wheat, barley and maize are stagnating in Central and Northern Europe since the 1990s. The stagnation of crop yields can probably be related to a fundamental change of the agricultural management and to climate change effects. It is assumed that the soil C input is concurrently stagnating which would necessarily lead to a decrease of agricultural SOC stocks in the long-term given a constant temperature increase. Remarkably, for almost all European countries that are faced with yield stagnation indications for agricultural SOC decreases were already found. Potentially adverse effects of yield stagnation on the C balance of croplands call for an interdisciplinary investigation of its causes and a comprehensive monitoring of SOC stocks in agricultural soils of Europe.

  10. Satellite Estimates of Crop Area and Maize Yield in Zambia's Agricultural Districts

    NASA Astrophysics Data System (ADS)

    Azzari, G.; Lobell, D. B.

    2015-12-01

    Predicting crop yield and area from satellite is a valuable tool to monitor different aspects of productivity dynamics and food security. In Sub-Saharan Africa, where the agricultural landscape is complex and dominated by smallholder systems, such dynamics need to be investigated at the field scale. We leveraged the large data pool and computational power of Google Earth Engine to 1) generate 30 m resolution cover maps of selected provinces of Zambia, 2) estimate crop area, and 3) produce yearly maize yield maps using the recently developed SCYM (Scalable satellite-based Crop Yield Mapper) algorithm. We will present our results and their validation against a ground survey dataset collected yearly by the Zambia Ministry of Agriculture from about 12,500 households.

  11. Agricultural management practices to sustain crop yields and improve soil and environmental qualities.

    PubMed

    Sainju, Upendra M; Whitehead, Wayne F; Singh, Bharat P

    2003-08-20

    In the past several decades, agricultural management practices consisting of intensive tillage and high rate of fertilization to improve crop yields have resulted in the degradation of soil and environmental qualities by increasing erosion and nutrient leaching in the groundwater and releasing greenhouses gases, such as carbon dioxide (CO2) and nitrous oxide (N2O), that cause global warming in the atmosphere by oxidation of soil organic matter. Consequently, management practices that sustain crop yields and improve soil and environmental qualities are needed. This paper reviews the findings of the effects of tillage practices, cover crops, and nitrogen (N) fertilization rates on crop yields, soil organic carbon (C) and N concentrations, and nitrate (NO3)-N leaching from the soil. Studies indicate that conservation tillage, such as no-till or reduced till, can increase soil organic C and N concentrations at 0- to 20-cm depth by as much as 7-17% in 8 years compared with conventional tillage without significantly altering crop yields. Similarly, cover cropping and 80-180 kg N ha(-1) year(-1) fertilization can increase soil organic C and N concentrations by as much as 4-12% compared with no cover cropping or N fertilization by increasing plant biomass and amount of C and N inputs to the soil. Reduced till, cover cropping, and decreased rate of N fertilization can reduce soil N leaching compared with conventional till, no cover cropping, and full rate of N fertilization. Management practices consisting of combinations of conservation tillage, mixture of legume and nonlegume cover crops, and reduced rate of N fertilization have the potentials for sustaining crop yields, increasing soil C and N storage, and reducing soil N leaching, thereby helping to improve soil and water qualities. Economical and social analyses of such practices are needed to find whether they are cost effective and acceptable to the farmers.

  12. Understanding the relative influence of climatic variations and agricultural management practices on crop yields at the US county level

    NASA Astrophysics Data System (ADS)

    Leng, G.; Zhang, X.; Huang, M.; Yang, Q.; Rafique, R.; Asrar, G.; Leung, L. R.

    2015-12-01

    Crop yields are largely determined by climate variations and agricultural management practices, such as irrigation, fertilization and residue management. Understanding the role of these factors in regulating crop yield variations is not only important for improved crop yield production, but also equally valuable for future crop yield prediction and food security assessments. Recently, the Community Land Model (CLM) has been augmented and evaluated for simulating corn, soybean and cereals at coarse aerial resolutions of 2 degrees (2000x2000 km). To better understand the underlying mechanisms controlling yield variations, we implemented and validated the agricultural version of CLM (CLM-crop) at a 0.125 degree resolution over the Conterminous United States (CONUS). We conducted a suite of numerical experiments to untangle the relative influence of climatic variations (temperature, precipitation, and radiation) and agricultural management practices on yield variations for the past 30 years at the US county level. Preliminary results show that the model with default parameter settings captures well the temporal variations in crop yields, as compared with the actual yield reported by the US Department of Agriculture (USDA). However, the magnitude of simulated crop yields is substantially higher, especially in the Mid-western US. We find that improved characterization of fertilizers and irrigation practices is key to model performance. Retrospectively (1979-2012), crop yields are more sensitive to changes in climate factors (such as temperature) than to changes in crop management practices. The results of this study advances understanding of the dominant factors in regulating the crop yield variations at the county level, which is essential for credible prediction of crop yields in a changing climate, under different agricultural management practices.

  13. Drought Effects on Agricultural Yield: Comparison Across Regions and Crop Types

    NASA Astrophysics Data System (ADS)

    Daryanto, S.; Wang, L.; Jacinthe, P. A.

    2014-12-01

    Global agricultural production is dominated by rainfed agriculture, and is therefore prone to disruption from climate extreme weathers. These uncertainties become more problematic when considering the projection of increased drought frequency suggested by several climate models for various world regions. Curiously, few regional analyses of drought impact of food production have been attempted. We collated and analyzed data from the last 25 years to disentangle the effects of drought (i.e. timing, intensity and duration) on agricultural production in different eco-regions and with varying crop types. Our preliminary results suggested greater yield reduction in annual (-21.5%) than perennial plants (-16%), in C4 (-21%) compared to C3 crops (-17%), and when drought occurred during generative (i.e. flowering until maturity; -16.5%) than vegetative stage (-15.5%). Although drought caused similar amounts of yield reduction in both tropical and subtropical regions (i.e. -17%), it carries a greater food security risk in the tropics due to inherently low productivity (i.e. less than half than in the subtropical regions). Consequently, cultivating drought-resistant C3 perennial plants (e.g. sweet potato and cassava) in the tropics could prove a viable adaptive strategy to mitigate the effects of climate variability. In addition, these crops have limited input requirements, are well adapted to nutrient-poor Oxisols and Ultisols of the tropics, and generally outyield cereal crops in the region. Our analysis is ongoing and needs to take into account agronomic traits (e.g. water requirement), as well as the energy and nutritional values (e.g. protein, minerals) of alternative crops. Our results could inform the selection and development of new cultivars for the drought-prone regions of the world.

  14. From rainfed agriculture to stress-avoidance irrigation: II. Sustainability, crop yield, and profitability

    NASA Astrophysics Data System (ADS)

    Vico, Giulia; Porporato, Amilcare

    2011-02-01

    The optimality of irrigation strategies may be sought with respect to a number of criteria, including water requirements, crop yield, and profitability. To explore the suitability of different demand-based irrigation strategies, we link the probabilistic description of irrigation requirements under stochastic hydro-climatic conditions, provided in a companion paper [Vico G, Porporato A. From rainfed agriculture to stress-avoidance irrigation: I. A generalized irrigation scheme with stochastic soil moisture. Adv Water Resour 2011;34(2):263-71], to crop-yield and economic analyses. Water requirements, application efficiency, and investment costs of different irrigation methods, such as surface, sprinkler and drip irrigation systems, are described via a unified conceptual and theoretical approach, which includes rainfed agriculture and stress-avoidance irrigation as extreme cases. This allows us to analyze irrigation strategies with respect to sustainability, productivity, and economic return, using the same framework, and quantify them as a function of climate, crop, and soil parameters. We apply our results to corn ( Zea mays), a food staple and biofuel source, which is currently mainly irrigated through surface systems. As our analysis shows, micro-irrigation maximizes water productivity, but more traditional solutions may be more profitable at least in some contexts.

  15. The global impact of ozone on agricultural crop yields under current and future air quality legislation

    NASA Astrophysics Data System (ADS)

    Van Dingenen, Rita; Dentener, Frank J.; Raes, Frank; Krol, Maarten C.; Emberson, Lisa; Cofala, Janusz

    In this paper we evaluate the global impact of surface ozone on four types of agricultural crop. The study is based on modelled global hourly ozone fields for the year 2000 and 2030, using the global 1°×1° 2-way nested atmospheric chemical transport model (TM5). Projections for the year 2030 are based on the relatively optimistic "current legislation (CLE) scenario", i.e. assuming that currently approved air quality legislation will be fully implemented by the year 2030, without a further development of new abatement policies. For both runs, the relative yield loss due to ozone damage is evaluated based on two different indices (accumulated concentration above a 40 ppbV threshold and seasonal mean daytime ozone concentration respectively) on a global, regional and national scale. The cumulative metric appears to be far less robust than the seasonal mean, while the seasonal mean shows satisfactory agreement with measurements in Europe, the US, China and Southern India and South-East Asia. Present day global relative yield losses are estimated to range between 7% and 12% for wheat, between 6% and 16% for soybean, between 3% and 4% for rice, and between 3% and 5% for maize (range resulting from different metrics used). Taking into account possible biases in our assessment, introduced through the global application of "western" crop exposure-response functions, and through model performance in reproducing ozone-exposure metrics, our estimates may be considered as being conservative. Under the 2030 CLE scenario, the global situation is expected to deteriorate mainly for wheat (additional 2-6% loss globally) and rice (additional 1-2% loss globally). India, for which no mitigation measures have been assumed by 2030, accounts for 50% of these global increase in crop yield loss. On a regional-scale, significant reductions in crop losses by CLE-2030 are only predicted in Europe (soybean) and China (wheat). Translating these assumed yield losses into total global economic

  16. 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

  17. Trading carbon for food: Global comparison of carbon stocks vs. crop yields on agricultural land

    PubMed Central

    West, Paul C.; Gibbs, Holly K.; Monfreda, Chad; Wagner, John; Barford, Carol C.; Carpenter, Stephen R.; Foley, Jonathan A.

    2010-01-01

    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. PMID:21041633

  18. 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.

  19. Micronutrient-Efficient Genotypes for Crop Yield and Nutritional Quality in Sustainable Agriculture: A Review

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Micronutrient deficiency is a limiting factor for crop productivity in many agricultural lands worldwide. Furthermore, many food systems in developing countries can not provide sufficient micronutrient contents to meet the demands of their people, especially low-income families. Several approaches...

  20. Vulnerability of Agriculture to Climate Change as Revealed by Relationships between Simulated Crop Yield and Climate Change Indices

    NASA Astrophysics Data System (ADS)

    King, A. W.; Absar, S. M.; Nair, S.; Preston, B. L.

    2012-12-01

    The vulnerability of agriculture is among the leading concerns surrounding climate change. Agricultural production is influenced by drought and other extremes in weather and climate. In regions of subsistence farming, worst case reductions in yield lead to malnutrition and famine. Reduced surplus contributes to poverty in agrarian economies. In more economically diverse and industrialized regions, variations in agricultural yield can influence the regional economy through market mechanisms. The latter grows in importance as agriculture increasingly services the energy market in addition to markets for food and fiber. Agriculture is historically a highly adaptive enterprise and will respond to future changes in climate with a variety of adaptive mechanisms. Nonetheless, the risk, if not expectation, of increases in climate extremes and hazards exceeding historical experience motivates scientifically based anticipatory assessment of the vulnerability of agriculture to climate change. We investigate the sensitivity component of that vulnerability using EPIC, a well established field-scale model of cropping systems that includes the simulation of economic yield. The core of our analysis is the relationship between simulated yield and various indices of climate change, including the CCI/CLIVAR/JCOM ETCCDI indices, calculated from weather inputs to the model. We complement this core with analysis using the DSSAT cropping system model and exploration of relationships between historical yield statistics and climate indices calculated from weather records. Our analyses are for sites in the Southeast/Gulf Coast region of the United States. We do find "tight" monotonic relationships between annual yield and climate for some indices, especially those associated with available water. More commonly, however, we find an increase in the variability of yield as the index value becomes more extreme. Our findings contribute to understanding the sensitivity of crop yield as part of

  1. Crop yield gaps in Cameroon.

    PubMed

    Yengoh, Genesis T; Ardö, Jonas

    2014-03-01

    Although food crop yields per hectare have generally been increasing in Cameroon since 1961, the food price crisis of 2008 and the ensuing social unrest and fatalities raised concerns about the country's ability to meet the food needs of its population. This study examines the country's potential for increasing crop yields and food production to meet this food security challenge. Fuzzy set theory is used to develop a biophysical spatial suitability model for different crops, which in turn is employed to ascertain whether crop production is carried out in biophysically suited areas. We use linear regression to examine the trend of yield development over the last half century. On the basis of yield data from experimental stations and farmers' fields we assess the yield gap for major food crops. We find that yields have generally been increasing over the last half century and that agricultural policies can have significant effects on them. To a large extent, food crops are cultivated in areas that are biophysically suited for their cultivation, meaning that the yield gap is not a problem of biophysical suitability. Notwithstanding, there are significantly large yield gaps between actual yields on farmers' farms and maximum attainable yields from research stations. We conclude that agronomy and policies are likely to be the reasons for these large yield gaps. A key challenge to be addressed in closing the yield gaps is that of replenishing and properly managing soil nutrients.

  2. Simulated crop yield in response to changes in climate and agricultural practices: results from a simple process based model

    NASA Astrophysics Data System (ADS)

    Caldararu, S.; Smith, M. J.; Purves, D.; Emmott, S.

    2013-12-01

    Global agriculture will, in the future, be faced with two main challenges: climate change and an increase in global food demand driven by an increase in population and changes in consumption habits. To be able to predict both the impacts of changes in climate on crop yields and the changes in agricultural practices necessary to respond to such impacts we currently need to improve our understanding of crop responses to climate and the predictive capability of our models. Ideally, what we would have at our disposal is a modelling tool which, given certain climatic conditions and agricultural practices, can predict the growth pattern and final yield of any of the major crops across the globe. We present a simple, process-based crop growth model based on the assumption that plants allocate above- and below-ground biomass to maintain overall carbon optimality and that, to maintain this optimality, the reproductive stage begins at peak nitrogen uptake. The model includes responses to available light, water, temperature and carbon dioxide concentration as well as nitrogen fertilisation and irrigation. The model is data constrained at two sites, the Yaqui Valley, Mexico for wheat and the Southern Great Plains flux site for maize and soybean, using a robust combination of space-based vegetation data (including data from the MODIS and Landsat TM and ETM+ instruments), as well as ground-based biomass and yield measurements. We show a number of climate response scenarios, including increases in temperature and carbon dioxide concentrations as well as responses to irrigation and fertiliser application.

  3. Digital Mapping of Soil Salinity and Crop Yield across a Coastal Agricultural Landscape Using Repeated Electromagnetic Induction (EMI) Surveys.

    PubMed

    Yao, Rongjiang; Yang, Jingsong; Wu, Danhua; Xie, Wenping; Gao, Peng; Jin, Wenhui

    2016-01-01

    Reliable and real-time information on soil and crop properties is important for the development of management practices in accordance with the requirements of a specific soil and crop within individual field units. This is particularly the case in salt-affected agricultural landscape where managing the spatial variability of soil salinity is essential to minimize salinization and maximize crop output. The primary objectives were to use linear mixed-effects model for soil salinity and crop yield calibration with horizontal and vertical electromagnetic induction (EMI) measurements as ancillary data, to characterize the spatial distribution of soil salinity and crop yield and to verify the accuracy of spatial estimation. Horizontal and vertical EMI (type EM38) measurements at 252 locations were made during each survey, and root zone soil samples and crop samples at 64 sampling sites were collected. This work was periodically conducted on eight dates from June 2012 to May 2013 in a coastal salt-affected mud farmland. Multiple linear regression (MLR) and restricted maximum likelihood (REML) were applied to calibrate root zone soil salinity (ECe) and crop annual output (CAO) using ancillary data, and spatial distribution of soil ECe and CAO was generated using digital soil mapping (DSM) and the precision of spatial estimation was examined using the collected meteorological and groundwater data. Results indicated that a reduced model with EMh as a predictor was satisfactory for root zone ECe calibration, whereas a full model with both EMh and EMv as predictors met the requirement of CAO calibration. The obtained distribution maps of ECe showed consistency with those of EMI measurements at the corresponding time, and the spatial distribution of CAO generated from ancillary data showed agreement with that derived from raw crop data. Statistics of jackknifing procedure confirmed that the spatial estimation of ECe and CAO exhibited reliability and high accuracy. A general

  4. Digital Mapping of Soil Salinity and Crop Yield across a Coastal Agricultural Landscape Using Repeated Electromagnetic Induction (EMI) Surveys

    PubMed Central

    Yao, Rongjiang; Yang, Jingsong; Wu, Danhua; Xie, Wenping; Gao, Peng; Jin, Wenhui

    2016-01-01

    Reliable and real-time information on soil and crop properties is important for the development of management practices in accordance with the requirements of a specific soil and crop within individual field units. This is particularly the case in salt-affected agricultural landscape where managing the spatial variability of soil salinity is essential to minimize salinization and maximize crop output. The primary objectives were to use linear mixed-effects model for soil salinity and crop yield calibration with horizontal and vertical electromagnetic induction (EMI) measurements as ancillary data, to characterize the spatial distribution of soil salinity and crop yield and to verify the accuracy of spatial estimation. Horizontal and vertical EMI (type EM38) measurements at 252 locations were made during each survey, and root zone soil samples and crop samples at 64 sampling sites were collected. This work was periodically conducted on eight dates from June 2012 to May 2013 in a coastal salt-affected mud farmland. Multiple linear regression (MLR) and restricted maximum likelihood (REML) were applied to calibrate root zone soil salinity (ECe) and crop annual output (CAO) using ancillary data, and spatial distribution of soil ECe and CAO was generated using digital soil mapping (DSM) and the precision of spatial estimation was examined using the collected meteorological and groundwater data. Results indicated that a reduced model with EMh as a predictor was satisfactory for root zone ECe calibration, whereas a full model with both EMh and EMv as predictors met the requirement of CAO calibration. The obtained distribution maps of ECe showed consistency with those of EMI measurements at the corresponding time, and the spatial distribution of CAO generated from ancillary data showed agreement with that derived from raw crop data. Statistics of jackknifing procedure confirmed that the spatial estimation of ECe and CAO exhibited reliability and high accuracy. A general

  5. Object-Oriented Agricultural System Modeling: Component-Driven Nutrient Dynamics and Crop Yield Simulations

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Challenges in agro-ecosystem conservation management have created demand for state-of-the-art, integrated, and flexible modeling tools. For example, agricultural system modeling tools are needed which are robust and fast enough to be applied on large watershed scales, but which are also able to sim...

  6. Decomposing global crop yield variability

    NASA Astrophysics Data System (ADS)

    Ben-Ari, Tamara; Makowski, David

    2014-11-01

    Recent food crises have highlighted the need to better understand the between-year variability of agricultural production. Although increasing future production seems necessary, the globalization of commodity markets suggests that the food system would also benefit from enhanced supplies stability through a reduction in the year-to-year variability. Here, we develop an analytical expression decomposing global crop yield interannual variability into three informative components that quantify how evenly are croplands distributed in the world, the proportion of cultivated areas allocated to regions of above or below average variability and the covariation between yields in distinct world regions. This decomposition is used to identify drivers of interannual yield variations for four major crops (i.e., maize, rice, soybean and wheat) over the period 1961-2012. We show that maize production is fairly spread but marked by one prominent region with high levels of crop yield interannual variability (which encompasses the North American corn belt in the USA, and Canada). In contrast, global rice yields have a small variability because, although spatially concentrated, much of the production is located in regions of below-average variability (i.e., South, Eastern and South Eastern Asia). Because of these contrasted land use allocations, an even cultivated land distribution across regions would reduce global maize yield variance, but increase the variance of global yield rice. Intermediate results are obtained for soybean and wheat for which croplands are mainly located in regions with close-to-average variability. At the scale of large world regions, we find that covariances of regional yields have a negligible contribution to global yield variance. The proposed decomposition could be applied at any spatial and time scales, including the yearly time step. By addressing global crop production stability (or lack thereof) our results contribute to the understanding of a key

  7. Linking Drought Information to Crop Yield

    NASA Astrophysics Data System (ADS)

    Madadgar, S.; Farahmand, A.; Li, L.; Aghakouchak, A.

    2015-12-01

    Droughts have detrimental impacts on agricultural yields all over the world every year. This study analyzes the relationship between three drought indicators including Standardized Precipitation Index (SPI); Standardized Soil Moisture Index (SSI), Multivariate Standardized Drought Index (MSDI) and the yields of five largest rain-fed crops in Australia (wheat, broad beans, canola, lupins and barley). Variation of the five chosen crop yields is overall in agreement with the three drought indicators SPI, SSI, and MSDI during the analysis period of 1980-2012. This study develops a bivariate copula model to investigate the statistical dependence of drought and crop yield. Copula functions are used to establish the existing connections between climate variables and crop yields during the Millennium drought in Australia. The proposed model estimates the likelihood of crop yields given the observed or predicted drought indicators SPI, SSI or MSDI. The results are also useful to estimate crop yields associated with different thresholds of precipitation or soil moisture.

  8. Impacts of varying agricultural intensification on crop yield and groundwater resources: comparison of the North China Plain and US High Plains

    NASA Astrophysics Data System (ADS)

    Pei, Hongwei; Scanlon, Bridget R.; Shen, Yanjun; Reedy, Robert C.; Long, Di; Liu, Changming

    2015-04-01

    Agricultural intensification is often considered the primary approach to meet rising food demand. Here we compare impacts of intensive cultivation on crop yield in the North China Plain (NCP) with less intensive cultivation in the US High Plains (USHP) and associated effects on water resources using spatial datasets. Average crop yield during the past decade from intensive double cropping of wheat and corn in the NCP was only 15% higher than the yield from less intensive single cropping of corn in the USHP, although nitrogen fertilizer application and percent of cropland that was irrigated were both ˜2 times greater in the NCP than in the USHP. Irrigation and fertilization in both regions have depleted groundwater storage and resulted in widespread groundwater nitrate contamination. The limited response to intensive management in the NCP is attributed in part to the two month shorter growing season for corn to accommodate winter wheat than that for corn in the USHP. Previous field and modeling studies of crop yield in the NCP highlight over application of N and water resulting in low nitrogen and water use efficiencies and indicate that cultivars, plant densities, soil fertility and other factors had a much greater impact on crop yields over the past few decades. The NCP-USHP comparison along with previous field and modeling studies underscores the need to weigh the yield returns from intensive management relative to the negative impacts on water resources. Future crop management should consider the many factors that contribute to yield along with optimal fertilization and irrigation to further increase crop yields while reducing adverse impacts on water resources.

  9. Light- and water-use efficiency model synergy: a revised look at crop yield estimation for agricultural decision-making

    NASA Astrophysics Data System (ADS)

    Marshall, M.; Tu, K. P.

    2015-12-01

    Large-area crop yield models (LACMs) are commonly employed to address climate-driven changes in crop yield and inform policy makers concerned with climate change adaptation. Production efficiency models (PEMs), a class of LACMs that rely on the conservative response of carbon assimilation to incoming solar radiation absorbed by a crop contingent on environmental conditions, have increasingly been used over large areas with remote sensing spectral information to improve the spatial resolution of crop yield estimates and address important data gaps. Here, we present a new PEM that combines model principles from the remote sensing-based crop yield and evapotranspiration (ET) model literature. One of the major limitations of PEMs is that they are evaluated using data restricted in both space and time. To overcome this obstacle, we first validated the model using 2009-2014 eddy covariance flux tower Gross Primary Production data in a rice field in the Central Valley of California- a critical agro-ecosystem of the United States. This evaluation yielded a Willmot's D and mean absolute error of 0.81 and 5.24 g CO2/d, respectively, using CO2, leaf area, temperature, and moisture constraints from the MOD16 ET model, Priestley-Taylor ET model, and the Global Production Efficiency Model (GLOPEM). A Monte Carlo simulation revealed that the model was most sensitive to the Enhanced Vegetation Index (EVI) input, followed by Photosynthetically Active Radiation, vapor pressure deficit, and air temperature. The model will now be evaluated using 30 x 30m (Landsat resolution) biomass transects developed in 2011 and 2012 from spectroradiometric and other non-destructive in situ metrics for several cotton, maize, and rice fields across the Central Valley. Finally, the model will be driven by Daymet and MODIS data over the entire State of California and compared with county-level crop yield statistics. It is anticipated that the new model will facilitate agro-climatic decision-making in

  10. Rapid Prototyping of NASA's Solar and Meteorological Data For Regional Level Modeling of Agricultural and Bio-fuel Crop Phenology and Yield Potential

    NASA Astrophysics Data System (ADS)

    Hoell, J. M.; Stackhouse, P. W.; Eckman, R. S.

    2006-12-01

    Global demand for food, feedstock and bio-fuel crops is expanding rapidly due to population growth, increasing consumption of these products (especially in developing countries), and more recently skyrocketing use of these crops to produce ethanol as a bio-fuel. As a result, there are growing concerns, both in the US and world wide, about the ability to meet the projected demand for agricultural/bio-fuel crops without expanding production areas into environmentally sensitive regions. Concurrently, there are increasing concerns over the negative impact of global warming on crop yields. Accurate ecophysiological crop models have been developed for many of the food and bio-fuel crops and serve as the back-bone in sophisticated Decision Support Systems (DSS). These DSS's are increasingly being used to address the balance between the need to increase production/efficiency and environmental concerns, as well as the impact of global warming on crop production. Realistic application of these agricultural DSS's requires accurate environmental data on time scales ranging from hours to decades. To date only sparse surface measurements are used that typically do not measure solar irradiance. NASA's Prediction of Worldwide Energy Resource (POWER) project, which has as one of its objectives the development of data products for agricultural applications, currently provides a climatological data base of meteorological parameters and surface solar energy fluxes on a global 1-degree latitude by 1- degree longitude grid. NASA is also developing capabilities to produce near-real time data sets specifically designed for application by agricultural DSS's. In this presentation, we discuss the development of 1-degree global data products which combine the climatological data in the POWER project archive (http://earth-www.larc.nasa.gov/power), near real time (2 to 3 day lag) meteorological data from the Goddard Earth Observing System (GEOS) quick-look products, and global solar energy

  11. 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

  12. Agricultural Yield Trends in Malawi: Utilizing Remote Sensing to Observe Crop Productivity and Sensitivity to Biophysical and Social Drivers

    NASA Astrophysics Data System (ADS)

    Peter, B.

    2015-12-01

    The primary objective of this research is to distinguish primary and secondary trends in the spatiotemporal variability of agricultural productivity in Malawi. The assessment was performed by analyzing the Net Primary Productivity (NPP) product derived from NASA MODIS satellite imagery and by drawing comparisons between individual land areas and the country-wide statistics. The data were categorized by placing each individual land area into one of six categories: low, average, or high productivity, and whether or not they were resilient or sensitive to biophysical and/or social production drivers. In order to mitigate productivity interference from forest and other land cover types, a custom agricultural land use was developed. Five land cover datasets, including FAO, GLC, IFPRI, GlobCover, and MODIS were combined to minimize errors of commission. Model assessment occurred via field work in Malawi. Approximately 200 sites were visited across nearly the entire extent of the country. Cropland and land cover were assessed via visual inspection, true color/near-infrared photography, and on-site interviews with farmers and extension officers to inquire about productivity and limiting factors for yield. Additionally, we present a continental scale application of the model to demonstrate its performance across scales.

  13. Ecoinformatics reveals effects of crop rotational histories on cotton yield.

    PubMed

    Meisner, Matthew H; Rosenheim, Jay A

    2014-01-01

    Crop rotation has been practiced for centuries in an effort to improve agricultural yield. However, the directions, magnitudes, and mechanisms of the yield effects of various crop rotations remain poorly understood in many systems. In order to better understand how crop rotation influences cotton yield, we used hierarchical Bayesian models to analyze a large ecoinformatics database consisting of records of commercial cotton crops grown in California's San Joaquin Valley. We identified several crops that, when grown in a field the year before a cotton crop, were associated with increased or decreased cotton yield. Furthermore, there was a negative association between the effect of the prior year's crop on June densities of the pest Lygus hesperus and the effect of the prior year's crop on cotton yield. This suggested that some crops may enhance L. hesperus densities in the surrounding agricultural landscape, because residual L. hesperus populations from the previous year cannot continuously inhabit a focal field and attack a subsequent cotton crop. In addition, we found that cotton yield declined approximately 2.4% for each additional year in which cotton was grown consecutively in a field prior to the focal cotton crop. Because L. hesperus is quite mobile, the effects of crop rotation on L. hesperus would likely not be revealed by small plot experimentation. These results provide an example of how ecoinformatics datasets, which capture the true spatial scale of commercial agriculture, can be used to enhance agricultural productivity.

  14. Case study of the effects of atmospheric aerosols and regional haze on agriculture: An opportunity to enhance crop yields in China through emission controls?

    PubMed Central

    Chameides, W. L.; Yu, H.; Liu, S. C.; Bergin, M.; Zhou, X.; Mearns, L.; Wang, G.; Kiang, C. S.; Saylor, R. D.; Luo, C.; Huang, Y.; Steiner, A.; Giorgi, F.

    1999-01-01

    The effect of atmospheric aerosols and regional haze from air pollution on the yields of rice and winter wheat grown in China is assessed. The assessment is based on estimates of aerosol optical depths over China, the effect of these optical depths on the solar irradiance reaching the earth’s surface, and the response of rice and winter wheat grown in Nanjing to the change in solar irradiance. Two sets of aerosol optical depths are presented: one based on a coupled, regional climate/air quality model simulation and the other inferred from solar radiation measurements made over a 12-year period at meteorological stations in China. The model-estimated optical depths are significantly smaller than those derived from observations, perhaps because of errors in one or both sets of optical depths or because the data from the meteorological stations has been affected by local pollution. Radiative transfer calculations using the smaller, model-estimated aerosol optical depths indicate that the so-called “direct effect” of regional haze results in an ≈5–30% reduction in the solar irradiance reaching some of China’s most productive agricultural regions. Crop-response model simulations suggest an ≈1:1 relationship between a percentage increase (decrease) in total surface solar irradiance and a percentage increase (decrease) in the yields of rice and wheat. Collectively, these calculations suggest that regional haze in China is currently depressing optimal yields of ≈70% of the crops grown in China by at least 5–30%. Reducing the severity of regional haze in China through air pollution control could potentially result in a significant increase in crop yields and help the nation meet its growing food demands in the coming decades. PMID:10570123

  15. Why we need GMO crops in agriculture

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The fact that in a very short period of 35 years the global population will reach an estimated 9 billion people presents a massive challenge to agriculture: how do we feed all of these people with nutritious food in a sustainable way? At the present time the yields of most of our major crops are sta...

  16. Effects of geoengineering on crop yields

    NASA Astrophysics Data System (ADS)

    Pongratz, J.; Lobell, D. B.; Cao, L.; Caldeira, K.

    2011-12-01

    market shares of agricultural output may change with the different spatial pattern of climate change. More importantly, geoengineering by SRM does not address a range of other detrimental consequences of climate change, such as ocean acidification, which could also affect food security via effects on marine food webs. Finally, SRM poses substantial anticipated and unanticipated risks by interfering with complex, not fully understood systems. Therefore, despite potential positive effects of SRM on crop yields, the most certain way to reduce climate risks to global food security is to reduce emissions of greenhouse gases.

  17. Interacting Agricultural Pests and Their Effect on Crop Yield: Application of a Bayesian Decision Theory Approach to the Joint Management of Bromus tectorum and Cephus cinctus

    PubMed Central

    Keren, Ilai N.; Menalled, Fabian D.; Weaver, David K.; Robison-Cox, James F.

    2015-01-01

    Worldwide, the landscape homogeneity of extensive monocultures that characterizes conventional agriculture has resulted in the development of specialized and interacting multitrophic pest complexes. While integrated pest management emphasizes the need to consider the ecological context where multiple species coexist, management recommendations are often based on single-species tactics. This approach may not provide satisfactory solutions when confronted with the complex interactions occurring between organisms at the same or different trophic levels. Replacement of the single-species management model with more sophisticated, multi-species programs requires an understanding of the direct and indirect interactions occurring between the crop and all categories of pests. We evaluated a modeling framework to make multi-pest management decisions taking into account direct and indirect interactions among species belonging to different trophic levels. We adopted a Bayesian decision theory approach in combination with path analysis to evaluate interactions between Bromus tectorum (downy brome, cheatgrass) and Cephus cinctus (wheat stem sawfly) in wheat (Triticum aestivum) systems. We assessed their joint responses to weed management tactics, seeding rates, and cultivar tolerance to insect stem boring or competition. Our results indicated that C. cinctus oviposition behavior varied as a function of B. tectorum pressure. Crop responses were more readily explained by the joint effects of management tactics on both categories of pests and their interactions than just by the direct impact of any particular management scheme on yield. In accordance, a C. cinctus tolerant variety should be planted at a low seeding rate under high insect pressure. However as B. tectorum levels increase, the C. cinctus tolerant variety should be replaced by a competitive and drought tolerant cultivar at high seeding rates despite C. cinctus infestation. This study exemplifies the necessity of

  18. Climate variation explains a third of global crop yield variability

    NASA Astrophysics Data System (ADS)

    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.

  19. Climate variation explains a third of global crop yield variability.

    PubMed

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

    2015-01-22

    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.

  20. 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

  1. Global crop yield losses from recent warming

    SciTech Connect

    Lobell, D; Field, C

    2006-06-02

    Global yields of the world-s six most widely grown crops--wheat, rice, maize, soybeans, barley, sorghum--have increased since 1961. Year-to-year variations in growing season minimum temperature, maximum temperature, and precipitation explain 30% or more of the variations in yield. Since 1991, climate trends have significantly decreased yield trends in all crops but rice, leading to foregone production since 1981 of about 12 million tons per year of wheat or maize, representing an annual economic loss of $1.2 to $1.7 billion. At the global scale, negative impacts of climate trends on crop yields are already apparent. Annual global temperatures have increased by {approx}0.4 C since 1980, with even larger changes observed in several regions (1). While many studies have considered the impacts of future climate changes on food production (2-5), the effects of these past changes on agriculture remain unclear. It is likely that warming has improved yields in some areas, reduced them in others, and had negligible impacts in still others; the relative balance of these effects at the global scale is unknown. An understanding of this balance would help to anticipate impacts of future climate changes, as well as to more accurately assess recent (and thereby project future) technologically driven yield progress. Separating the contribution of climate from concurrent changes in other factors--such as crop cultivars, management practices, soil quality, and atmospheric carbon dioxide (CO{sub 2}) levels--requires models that describe the response of yields to climate. Studies of future global impacts of climate change have typically relied on a bottom-up approach, whereby field scale, process-based models are applied to hundreds of representative sites and then averaged (e.g., ref 2). Such approaches require input data on soil and management conditions, which are often difficult to obtain. Limitations on data quality or quantity can thus limit the utility of this approach

  2. [Effects of agricultural activities and transgenic crops on agricultural biodiversity].

    PubMed

    Zhang, Xi-Tao; Luo, Hong-Bing; Li, Jun-Sheng; Huang, Hai; Liu, Yong-Bo

    2014-09-01

    Agricultural biodiversity is a key part of the ecosystem biodiversity, but it receives little concern. The monoculture, environmental pollution and habitat fragmentation caused by agricultural activities have threatened agricultural biodiversity over the past 50 years. To optimize agricultural management measures for crop production and environmental protection, we reviewed the effects of agricultural activities, including cultivation patterns, plastic mulching, chemical additions and the cultivation of transgenic crops, on agricultural biodiversity. The results showed that chemical pesticides and fertilizers had the most serious influence and the effects of transgenic crops varied with other factors like the specific transgene inserted in crops. The environmental risk of transgenic crops should be assessed widely through case-by-case methods, particularly its potential impacts on agricultural biodiversity. It is important to consider the protection of agricultural biodiversity before taking certain agricultural practices, which could improve agricultural production and simultaneously reduce the environmental impacts.

  3. 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.

  4. 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.

  5. Crop yield response to climate change varies with cropping intensity.

    PubMed

    Challinor, Andrew J; Parkes, Ben; Ramirez-Villegas, Julian

    2015-04-01

    Projections of the response of crop yield to climate change at different spatial scales are known to vary. However, understanding of the causes of systematic differences across scale is limited. Here, we hypothesize that heterogeneous cropping intensity is one source of scale dependency. Analysis of observed global data and regional crop modelling demonstrate that areas of high vs. low cropping intensity can have systematically different yields, in both observations and simulations. Analysis of global crop data suggests that heterogeneity in cropping intensity is a likely source of scale dependency for a number of crops across the globe. Further crop modelling and a meta-analysis of projected tropical maize yields are used to assess the implications for climate change assessments. The results show that scale dependency is a potential source of systematic bias. We conclude that spatially comprehensive assessments of climate impacts based on yield alone, without accounting for cropping intensity, are prone to systematic overestimation of climate impacts. The findings therefore suggest a need for greater attention to crop suitability and land use change when assessing the impacts of climate change.

  6. Crop Yield Response to Increasing Biochar Rates

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  7. Yield responses of wild C3 and C4 crop progenitors to subambient CO2 : a test for the role of CO2 limitation in the origin of agriculture.

    PubMed

    Cunniff, Jennifer; Jones, Glynis; Charles, Michael; Osborne, Colin P

    2017-01-01

    Limitation of plant productivity by the low partial pressure of atmospheric CO2 (Ca ) experienced during the last glacial period is hypothesized to have been an important constraint on the origins of agriculture. In support of this hypothesis, previous work has shown that glacial Ca limits vegetative growth in the wild progenitors of both C3 and C4 founder crops. Here, we present data showing that glacial Ca also reduces grain yield in both crop types. We grew four wild progenitors of C3 (einkorn wheat and barley) and C4 crops (foxtail and broomcorn millets) at glacial and postglacial Ca , measuring grain yield and the morphological and physiological components contributing to these yield changes. The C3 species showed a significant increase in unthreshed grain yield of ~50% with the glacial to postglacial increase in Ca , which matched the stimulation of photosynthesis, suggesting that increases in photosynthesis are directly translated into yield at subambient levels of Ca . Increased yield was controlled by a higher rate of tillering, leading to a larger number of tillers bearing fertile spikes, and increases in seed number and size. The C4 species showed smaller, but significant, increases in grain yield of 10-15%, arising from larger seed numbers and sizes. Photosynthesis was enhanced by Ca in only one C4 species and the effect diminished during development, suggesting that an indirect mechanism mediated by plant water relations could also be playing a role in the yield increase. Interestingly, the C4 species at glacial Ca showed some evidence that photosynthetic capacity was upregulated to enhance carbon capture. Development under glacial Ca also impacted negatively on the subsequent germination and viability of seeds. These results suggest that the grain production of both C3 and C4 crop progenitors was limited by the atmospheric conditions of the last glacial period, with important implications for the origins of agriculture.

  8. Ants and termites increase crop yield in a dry climate

    PubMed Central

    Evans, Theodore A.; Dawes, Tracy Z.; Ward, Philip R.; Lo, Nathan

    2011-01-01

    Agricultural intensification has increased crop yields, but at high economic and environmental cost. Harnessing ecosystem services of naturally occurring organisms is a cheaper but under-appreciated approach, because the functional roles of organisms are not linked to crop yields, especially outside the northern temperate zone. Ecosystem services in soil come from earthworms in these cooler and wetter latitudes; what may fulfill their functional role in agriculture in warmer and drier habitats, where they are absent, is unproven. Here we show in a field experiment that ants and termites increase wheat yield by 36% from increased soil water infiltration due to their tunnels and improved soil nitrogen. Our results suggest that ants and termites have similar functional roles to earthworms, and that they may provide valuable ecosystem services in dryland agriculture, which may become increasingly important for agricultural sustainability in arid climates. PMID:21448161

  9. 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.

  10. Pollinator shortage and global crop yield

    PubMed Central

    Aizen, Marcelo A; Cunningham, Saul A; Klein, Alexandra M

    2009-01-01

    A pollinator decline caused by environmental degradation might be compromising the production of pollinator-dependent crops. In a recent article, we compared 45 year series (1961–2006) in yield, production and cultivated area of pollinator-dependent and nondependent crop around the world. If pollinator shortage is occurring globally, we expected a lower annual growth rate in yield for pollinator-dependent than nondependent crops, but a higher growth in cultivated area to compensate the lower yield. We have found little evidence for the first “yield” prediction but strong evidence for the second “area” prediction. Here, we present an additional analysis to show that the first and second predictions are both supported for crops that vary in dependency levels from nondependent to moderate dependence (i.e., up to 65% average yield reduction without pollinators). However, those crops for which animal pollination is essential (i.e., 95% average yield reduction without pollinators) showed higher growth in yield and lower expansion in area than expected in a pollination shortage scenario. We propose that pollination management for highly pollinator-dependent crops, such us renting hives or hand pollination, might have compensated for pollinator limitation of yield. PMID:19704865

  11. Random Forests for Global and Regional Crop Yield Predictions

    PubMed Central

    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.

    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. PMID:27257967

  12. 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.

  13. Crop yield evaluation under controlled drainage in Ohio, United States

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Drainage water management (NRCS Practice Code 554) is an important agricultural water management practice for reducing nitrate loading to surface water across the Midwest US. There may also be a positive crop yield benefit which could add incentive for adoption of the practice. Results from a three ...

  14. 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.

  15. Agricultural Residues and Biomass Energy Crops

    SciTech Connect

    2016-06-01

    There are many opportunities to leverage agricultural resources on existing lands without interfering with production of food, feed, fiber, or forest products. In the recently developed advanced biomass feedstock commercialization vision, estimates of potentially available biomass supply from agriculture are built upon the U.S. Department of Agriculture’s (USDA’s) Long-Term Forecast, ensuring that existing product demands are met before biomass crops are planted. Dedicated biomass energy crops and agricultural crop residues are abundant, diverse, and widely distributed across the United States. These potential biomass supplies can play an important role in a national biofuels commercialization strategy.

  16. Spectrally-Based Assessment of Crop Seasonal Performance and Yield

    NASA Astrophysics Data System (ADS)

    Kancheva, Rumiana; Borisova, Denitsa; Georgiev, Georgy

    The rapid advances of space technologies concern almost all scientific areas from aeronautics to medicine, and a wide range of application fields from communications to crop yield predictions. Agricultural monitoring is among the priorities of remote sensing observations for getting timely information on crop development. Monitoring agricultural fields during the growing season plays an important role in crop health assessment and stress detection provided that reliable data is obtained. Successfully spreading is the implementation of hyperspectral data to precision farming associated with plant growth and phenology monitoring, physiological state assessment, and yield prediction. In this paper, we investigated various spectral-biophysical relationships derived from in-situ reflectance measurements. The performance of spectral data for the assessment of agricultural crops condition and yield prediction was examined. The approach comprisesd development of regression models between plant spectral and state-indicative variables such as biomass, vegetation cover fraction, leaf area index, etc., and development of yield forecasting models from single-date (growth stage) and multitemporal (seasonal) reflectance data. Verification of spectral predictions was performed through comparison with estimations from biophysical relationships between crop growth variables. The study was carried out for spring barley and winter wheat. Visible and near-infrared reflectance data was acquired through the whole growing season accompanied by detailed datasets on plant phenology and canopy structural and biochemical attributes. Empirical relationships were derived relating crop agronomic variables and yield to various spectral predictors. The study findings were tested using airborne remote sensing inputs. A good correspondence was found between predicted and actual (ground-truth) estimates

  17. 7 CFR 1412.32 - Direct payment yield for designated oilseed and pulse crops.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... average of the National Agricultural Statistics Service (NASS) harvested acreage yields for the crop using... 7 Agriculture 10 2011-01-01 2011-01-01 false Direct payment yield for designated oilseed and pulse... Establishment of Yields for Direct and Counter-Cyclical Payments § 1412.32 Direct payment yield for...

  18. 7 CFR 1412.32 - Direct payment yield for designated oilseed and pulse crops.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... average of the National Agricultural Statistics Service (NASS) harvested acreage yields for the crop using... 7 Agriculture 10 2014-01-01 2014-01-01 false Direct payment yield for designated oilseed and pulse... Establishment of Yields for Direct and Counter-Cyclical Payments § 1412.32 Direct payment yield for...

  19. 7 CFR 1412.32 - Direct payment yield for designated oilseed and pulse crops.

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ... average of the National Agricultural Statistics Service (NASS) harvested acreage yields for the crop using... 7 Agriculture 10 2012-01-01 2012-01-01 false Direct payment yield for designated oilseed and pulse... Establishment of Yields for Direct and Counter-Cyclical Payments § 1412.32 Direct payment yield for...

  20. 7 CFR 1412.32 - Direct payment yield for designated oilseed and pulse crops.

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ... average of the National Agricultural Statistics Service (NASS) harvested acreage yields for the crop using... 7 Agriculture 10 2013-01-01 2013-01-01 false Direct payment yield for designated oilseed and pulse... Establishment of Yields for Direct and Counter-Cyclical Payments § 1412.32 Direct payment yield for...

  1. 7 CFR 1412.32 - Direct payment yield for designated oilseed and pulse crops.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... average of the National Agricultural Statistics Service (NASS) harvested acreage yields for the crop using... 7 Agriculture 10 2010-01-01 2010-01-01 false Direct payment yield for designated oilseed and pulse... Establishment of Yields for Direct and Counter-Cyclical Payments § 1412.32 Direct payment yield for...

  2. Agricultural impacts: Mapping future crop geographies

    NASA Astrophysics Data System (ADS)

    Travis, William R.

    2016-06-01

    Modelled patterns of climate change impacts on sub-Saharan agriculture provide a detailed picture of the space- and timescales of change. They reveal hotspots where crop cultivation may disappear entirely, but also large areas where current or substitute crops will remain viable through this century.

  3. Cropping frequency and area response to climate variability can exceed yield response

    NASA Astrophysics Data System (ADS)

    Cohn, Avery S.; Vanwey, Leah K.; Spera, Stephanie A.; Mustard, John F.

    2016-06-01

    The sensitivity of agricultural output to climate change has often been estimated by modelling crop yields under climate change scenarios or with statistical analysis of the impacts of year-to-year climatic variability on crop yields. However, the area of cropland and the number of crops harvested per growing season (cropping frequency) both also affect agricultural output and both also show sensitivity to climate variability and change. We model the change in agricultural output associated with the response of crop yield, crop frequency and crop area to year-to-year climate variability in Mato Grosso (MT), Brazil, a key agricultural region. Roughly 70% of the change in agricultural output caused by climate was determined by changes in frequency and/or changes in area. Hot and wet conditions were associated with the largest losses and cool and dry conditions with the largest gains. All frequency and area effects had the same sign as total effects, but this was not always the case for yield effects. A focus on yields alone may therefore bias assessments of the vulnerability of agriculture to climate change. Efforts to reduce climate impacts to agriculture should seek to limit production losses not only from crop yield, but also from changes in cropland area and cropping frequency.

  4. 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

  5. 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.

  6. The edge extraction of agricultural crop leaf

    NASA Astrophysics Data System (ADS)

    Wang, Beilei; Cao, Ying; Xiao, Huiming; Jiang, Huiyan; Liu, Hongjuan

    2009-07-01

    In agricultural engineering, to ensure rational use of pesticide and improvement of crop production, computer image recognition technology is currently applied to help farmers to identify the degree of crop diseases. Considering the importance of feature extraction in this field, in this paper, we first present and discuss several widely used edge operator, including Sobel, Prewitt, Roberts, Canny and LoG. Furthermore, an experiment is conducted to compare performance and accuracy of five operators by applying them to a leaf image taken from agricultural crop for edge detection. The results of experiment show that, in practice, LoG edge operator is relatively a better choice and performs well for edge detection of agricultural crop leaf image.

  7. Crop yields in a geoengineered climate

    NASA Astrophysics Data System (ADS)

    Pongratz, J.; Lobell, D. B.; Cao, L.; Caldeira, K.

    2012-02-01

    Crop models predict that recent and future climate change may have adverse effects on crop yields. Intentional deflection of sunlight away from the Earth could diminish the amount of climate change in a high-CO2 world. However, it has been suggested that this diminution would come at the cost of threatening the food and water supply for billions of people. Here, we carry out high-CO2, geoengineering and control simulations using two climate models to predict the effects on global crop yields. We find that in our models solar-radiation geoengineering in a high-CO2 climate generally causes crop yields to increase, largely because temperature stresses are diminished while the benefits of CO2 fertilization are retained. Nevertheless, possible yield losses on the local scale as well as known and unknown side effects and risks associated with geoengineering indicate that the most certain way to reduce climate risks to global food security is to reduce emissions of greenhouse gases.

  8. 7 CFR 1412.31 - Direct payment yields for covered commodities, except pulse crops.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... 7 Agriculture 10 2014-01-01 2014-01-01 false Direct payment yields for covered commodities, except pulse crops. 1412.31 Section 1412.31 Agriculture Regulations of the Department of Agriculture (Continued) COMMODITY CREDIT CORPORATION, DEPARTMENT OF AGRICULTURE LOANS, PURCHASES, AND OTHER OPERATIONS DIRECT...

  9. 7 CFR 1412.31 - Direct payment yields for covered commodities, except pulse crops.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 7 Agriculture 10 2010-01-01 2010-01-01 false Direct payment yields for covered commodities, except pulse crops. 1412.31 Section 1412.31 Agriculture Regulations of the Department of Agriculture (Continued) COMMODITY CREDIT CORPORATION, DEPARTMENT OF AGRICULTURE LOANS, PURCHASES, AND OTHER OPERATIONS DIRECT...

  10. Will current trends close major crop yield gaps by 2025?

    NASA Astrophysics Data System (ADS)

    Ray, D. K.; Mueller, N. D.; Gerber, J. S.; Johnston, M.; Foley, J. A.

    2012-12-01

    Several studies have projected a need to double global agricultural production by 2050 to meet the demands posed by population growth, increased dairy and meat consumption, and biofuel use. However, recent work shows many regions where there are shortfalls in production compared to the regions with the highest yield. While these "yield gaps" could be closed through more intensive and advanced management, already between 24% and 39% of the global crop growing regions are witnessing yield stagnation. In this presentation we will identify the areas across the globe where yield gaps (as quantified circa the year 2000) are projected to either close or persist given observed rates of yield increases. Major investments in better management are needed in areas where yield gaps are projected to persist.

  11. Soil Moisture as an Estimator for Crop Yield in Germany

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

    Annual crop yield depends on various factors such as soil properties, management decisions, and meteorological conditions. Unfavorable weather conditions, e.g. 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. Predicting crop yields allows to mitigate negative effects of weather extremes which are assumed to occur more often in the future due to climate change. A standard approach in economics is to predict the impact of climate change on agriculture as a function of temperature and precipitation. This approach has been developed further using concepts like growing degree days. Other econometric models use nonlinear functions of heat or vapor pressure deficit. However, none of these approaches uses soil moisture to predict crop yield. We hypothesize that soil moisture is a better indicator to explain stress on plant growth than estimations based on precipitation and temperature. This is the case because the latter variables do not explicitly account for the available water content in the root zone, which is the primary source of water supply for plant growth. In this study, a reduced form panel approach is applied to estimate a multivariate econometric production function for the years 1999 to 2010. Annual crop yield data of various crops on the administrative district level serve as depending variables. The explanatory variable of major interest is the Soil Moisture Index (SMI), which quantifies anomalies in root zone soil moisture. The SMI is computed by the mesoscale Hydrological Model (mHM, www.ufz.de/mhm). The index represents the monthly soil water quantile at a 4 km2 grid resolution covering entire Germany. A reduced model approach is suitable because the SMI is the result of a stochastic weather process and therefore can be considered exogenous. For the ease of interpretation a linear functionality is preferred. Meteorological

  12. Volatile Organic Compound Emissions by Agricultural Crops

    NASA Astrophysics Data System (ADS)

    Ormeno, E.; Farres, S.; Gentner, D.; Park, J.; McKay, M.; Karlik, J.; Goldstein, A.

    2008-12-01

    Biogenic Volatile Organic Compounds (BVOCs) participate in ozone and aerosol formation, and comprise a substantial fraction of reactive VOC emission inventories. In the agriculturally intensive Central Valley of California, emissions from crops may substantially influence regional air quality, but emission potentials have not been extensively studied with advanced instrumentation for many important crops. Because crop emissions may vary according to the species, and California emission inventories are constructed via a bottom-up approach, a better knowledge of the emission rate at the species-specific level is critical for reducing uncertainties in emission inventories and evaluating emission model performance. In the present study we identified and quantified the BVOCs released by dominant agricultural crops in California. A screening study to investigate both volatile and semivolatile BVOC fractions (oxygenated VOCs, isoprene, monoterepenes, sesquiterpenes, etc.) was performed for 25 crop species (at least 3 replicates plants each), including branch enclosures of woody species (e.g. peach, mandarin, grape, pistachio) and whole plant enclosures for herbaceous species (e.g. onion, alfalfa, carrot), through a dynamic cuvette system with detection by PTRMS, in-situ GCMS/FID, and collection on carbon-based adsorbents followed by extraction and GCMS analysis. Emission data obtained in this study will allow inclusion of these crops in BVOC emission inventories and air quality simulations.

  13. The fingerprint of climate trends on European crop yields

    PubMed Central

    Moore, Frances C.; Lobell, David B.

    2015-01-01

    Europe has experienced a stagnation of some crop yields since the early 1990s as well as statistically significant warming during the growing season. Although it has been argued that these two are causally connected, no previous studies have formally attributed long-term yield trends to a changing climate. Here, we present two statistical tests based on the distinctive spatial pattern of climate change impacts and adaptation, and explore their power under a range of parameter values. We show that statistical power for the identification of climate change impacts is high in many settings, but that power for identifying adaptation is almost always low. Applying these tests to European agriculture, we find evidence that long-term temperature and precipitation trends since 1989 have reduced continent-wide wheat and barley yields by 2.5% and 3.8%, respectively, and have slightly increased maize and sugar beet yields. These averages disguise large heterogeneity across the continent, with regions around the Mediterranean experiencing significant adverse impacts on most crops. This result means that climate trends can account for ∼10% of the stagnation in European wheat and barley yields, with likely explanations for the remainder including changes in agriculture and environmental policies. PMID:25691735

  14. The fingerprint of climate trends on European crop yields.

    PubMed

    Moore, Frances C; Lobell, David B

    2015-03-03

    Europe has experienced a stagnation of some crop yields since the early 1990s as well as statistically significant warming during the growing season. Although it has been argued that these two are causally connected, no previous studies have formally attributed long-term yield trends to a changing climate. Here, we present two statistical tests based on the distinctive spatial pattern of climate change impacts and adaptation, and explore their power under a range of parameter values. We show that statistical power for the identification of climate change impacts is high in many settings, but that power for identifying adaptation is almost always low. Applying these tests to European agriculture, we find evidence that long-term temperature and precipitation trends since 1989 have reduced continent-wide wheat and barley yields by 2.5% and 3.8%, respectively, and have slightly increased maize and sugar beet yields. These averages disguise large heterogeneity across the continent, with regions around the Mediterranean experiencing significant adverse impacts on most crops. This result means that climate trends can account for ∼ 10% of the stagnation in European wheat and barley yields, with likely explanations for the remainder including changes in agriculture and environmental policies.

  15. Crop Farm Employee. Agricultural Cooperative Training. Vocational Agriculture. Revised.

    ERIC Educational Resources Information Center

    Boyd, Chester; And Others

    Designed for students enrolled in the Vocational Agricultural Cooperative Part-Time Training Program, this course of study contains 13 units for crop farm employees. Units include (examples of unit topics in parentheses): introduction (opportunities in farming, farming as a science, and farming in the United States), farm records (keeping farm…

  16. Crop status evaluations and yield predictions

    NASA Technical Reports Server (NTRS)

    Haun, J. R.

    1975-01-01

    A model was developed for predicting the day 50 percent of the wheat crop is planted in North Dakota. This model incorporates location as an independent variable. The Julian date when 50 percent of the crop was planted for the nine divisions of North Dakota for seven years was regressed on the 49 variables through the step-down multiple regression procedure. This procedure begins with all of the independent variables and sequentially removes variables that are below a predetermined level of significance after each step. The prediction equation was tested on daily data. The accuracy of the model is considered satisfactory for finding the historic dates on which to initiate yield prediction model. Growth prediction models were also developed for spring wheat.

  17. Yield and Economic Responses of Peanut to Crop Rotation Sequence

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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 ...

  18. A decade of precision agriculture impacts on grain yield and yield variation

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Targeting management practices and inputs with precision agriculture has high potential to meet some of the grand challenges of sustainability in the coming century, including simultaneously improving crop yields and reducing environmental impacts. Although the potential is high, few studies have do...

  19. Yield and Economic Responses of Peanut to Crop Rotation Sequence

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  20. Second Generation Crop Yield Models Review

    NASA Technical Reports Server (NTRS)

    Hodges, T. (Principal Investigator)

    1982-01-01

    Second generation yield models, including crop growth simulation models and plant process models, may be suitable for large area crop yield forecasting in the yield model development project. Subjective and objective criteria for model selection are defined and models which might be selected are reviewed. Models may be selected to provide submodels as input to other models; for further development and testing; or for immediate testing as forecasting tools. A plant process model may range in complexity from several dozen submodels simulating (1) energy, carbohydrates, and minerals; (2) change in biomass of various organs; and (3) initiation and development of plant organs, to a few submodels simulating key physiological processes. The most complex models cannot be used directly in large area forecasting but may provide submodels which can be simplified for inclusion into simpler plant process models. Both published and unpublished models which may be used for development or testing are reviewed. Several other models, currently under development, may become available at a later date.

  1. Assessing the impact of long-term cultivation on runoff, pollutant load, and crop yields

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Over the past century, agriculture had detrimental impacts on soil and water quality revealed by increased surface runoff and non-point source pollution. In this study, we estimated the impact of long-term agriculture on surface runoff, sediment yield, atrazine load, and crop yields. Soil samples we...

  2. Agricultural sectoral demand and crop productivity response across the world

    NASA Astrophysics Data System (ADS)

    Johnston, M.; Ray, D. K.; Cassidy, E. S.; Foley, J. A.

    2013-12-01

    With an increasing and increasingly affluent population, humans will need to roughly double agricultural production by 2050. Continued yield growth forms the foundation of all future strategies aiming to increase agricultural production while slowing or eliminating cropland expansion. However, a recent analysis by one of our co-authors has shown that yield trends in many important maize, wheat and rice growing regions have begun stagnating or declining from the highs seen during the green revolution (Ray et al. 2013). Additional research by our group has shown that nearly 50% of new agricultural production since the 1960s has gone not to direct human consumption, but instead to animal feed and other industrial uses. Our analysis for GLP looks at the convergence of these two trends by examining time series utilization data for 16 of the biggest crops to determine how demand from different sectors has shaped our land-use and intensification strategies around the world. Before rushing headlong into the next agricultural doubling, it would be prudent to first consult our recent agricultural history to better understand what was driving past changes in production. Using newly developed time series dataset - a fusion of cropland maps with historic agricultural census data gathered from around the world - we can examine yield and harvested area trends over the last half century for 16 top crops. We combine this data with utilization rates from the FAO Food Balance Sheet to see how demand from different sectors - food, feed, and other - has influenced long-term growth trends from the green revolution forward. We will show how intensification trends over time and across regions have grown or contracted depending on what is driving the change in production capacity. Ray DK, Mueller ND, West PC, Foley JA (2013) Yield Trends Are Insufficient to Double Global Crop Production by 2050. PLoS ONE 8(6): e66428. doi:10.1371/journal.pone.0066428

  3. Impact of derived global weather data on simulated crop yields.

    PubMed

    van Wart, Justin; Grassini, Patricio; Cassman, Kenneth G

    2013-12-01

    Crop simulation models can be used to estimate impact of current and future climates on crop yields and food security, but require long-term historical daily weather data to obtain robust simulations. In many regions where crops are grown, daily weather data are not available. Alternatively, gridded weather databases (GWD) with complete terrestrial coverage are available, typically derived from: (i) global circulation computer models; (ii) interpolated weather station data; or (iii) remotely sensed surface data from satellites. The present study's objective is to evaluate capacity of GWDs to simulate crop yield potential (Yp) or water-limited yield potential (Yw), which can serve as benchmarks to assess impact of climate change scenarios on crop productivity and land use change. Three GWDs (CRU, NCEP/DOE, and NASA POWER data) were evaluated for their ability to simulate Yp and Yw of rice in China, USA maize, and wheat in Germany. Simulations of Yp and Yw based on recorded daily data from well-maintained weather stations were taken as the control weather data (CWD). Agreement between simulations of Yp or Yw based on CWD and those based on GWD was poor with the latter having strong bias and large root mean square errors (RMSEs) that were 26-72% of absolute mean yield across locations and years. In contrast, simulated Yp or Yw using observed daily weather data from stations in the NOAA database combined with solar radiation from the NASA-POWER database were in much better agreement with Yp and Yw simulated with CWD (i.e. little bias and an RMSE of 12-19% of the absolute mean). We conclude that results from studies that rely on GWD to simulate agricultural productivity in current and future climates are highly uncertain. An alternative approach would impose a climate scenario on location-specific observed daily weather databases combined with an appropriate upscaling method.

  4. 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.

  5. Separability of agricultural crops with airborne scatterometry

    NASA Technical Reports Server (NTRS)

    Mehta, N. C.

    1983-01-01

    Backscattering measurements were acquired with airborne scatterometers over a site in Cass County, North Dakota on four days in the 1981 crop growing season. Data were acquired at three frequencies (L-, C- and Ku-bands), two polarizations (like and cross) and ten incidence angles (5 degrees to 50 degrees in 5 degree steps). Crop separability is studied in an hierarchical fashion. A two-class separability measure is defined, which compares within-class to between-class variability, to determine crop separability. The scatterometer channels with the best potential for crop separability are determined, based on this separability measure. Higher frequencies are more useful for discriminating small grains, while lower frequencies tend to separate non-small grains better. Some crops are more separable when row direction is taken into account. The effect of pixel purity is to increase the separability between all crops while not changing the order of useful scatterometer channels. Crude estimates of separability errors are calculated based on these analyses. These results are useful in selecting the parameters of active microwave systems in agricultural remote sensing.

  6. Earth Observation Based Canadian Crop Yield Forecasting -- Impact of Spatial Modeling Scale

    NASA Astrophysics Data System (ADS)

    Zhang, Y.; Daneshfar, B.; Chipanshi, A.; Champagne, C.; Davidson, A. M.

    2015-12-01

    Earth Observation (EO) based yield modelling has long been in development as an alternative method to the traditional survey based methods in forecasting the regional and global crop yield. However, it is only in last decade or so, with availability of high quality regional EO data in near real time (NRT), EO-based crop yield forecasting has become practical enough to be applied towards operational crop yield reporting. The Canadian Crop Yield Forecaster (CCYF) is one of such modelling tool that designed to provide regional and national crop yield outlooks during and shortly after the growing season. The CCYF integrates climate, remote sensing and other earth observation information (e.g., historical yields, soil and crop maps) using a physical based soil moisture budget model and a statistical based yield forecasting model. One of the major challenges for CCYF and many other EO-based crop yield forecasting systems is to determine a proper spatial modelling scale that could be easily aggregated to various required yield reporting units, yet still retain the statistical sensitivity of crop yield to variations in climate, soil and remote sensing vegetation indices. In this study, we have compared yield modelling using CCYF at three different administrative scales, i.e. township, Census Agricultural Regions (CARs) and province for four crops (spring wheat, canola, corn and soybeans) in the agricultural regions of Manitoba, Canada. Due to the shorter available historical yield records at the township scale, different modelling scheme is applied for township scale modelling compared to the other two larger scales. The modelling at provincial scale did not capture the yield variability, while the modelling at CAR level provided reasonable results for some CARs while failed for others. The modelling at township scale captured most of the yield variability, yet its performance and implementation is restricted by the availability of the yield data at this scale.

  7. Quantifying the US Crop Yield in Response to Extreme Climatic Events from 1948 to 2013

    NASA Astrophysics Data System (ADS)

    Jin, Z.; Zhuang, Q.

    2014-12-01

    The increasingly frequent and severe extreme climatic events (ECEs) under climate changes will negatively affect crop productivity and threat the global food security. Reliable forecast of crop yields response to those ECEs is a prerequisite for developing strategies on agricultural risk management. However, the progress of quantifying such responses with ecosystem models has been slow. In this study, we first review existing algorithms of yields response to ECEs among major crops (i.e., Corn, Wheat and Soybean) for the United States from a set of process-based crop models. These algorithms are aggregated into four categories of ECEs: drought, heavy precipitation, extreme heat, and frost. Species-specific ECEs thresholds as tipping point of crop yield response curve are examined. Four constraint scalar functions derived for each category of ECEs are then added to an agricultural ecosystem model, CLM-AG, respectively. The revised model is driven by NCEP/NCAR reanalysis data from 1948 to 2013 to estimate the US major crop yields, and then evaluated with county-level yield statistics from the National Agricultural Statistics Service (NASS). We also include MODIS NPP product as a reference for the period 2001-2013. Our study will help to identify gaps in capturing yield response to ECEs with contemporary crop models, and provide a guide on developing the new generation of crop models to account for the effects of more future extreme climate events.

  8. An energy balance approach for mapping crop waterstress and yield impacts over the Czech Republic

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  9. The Fingerprint of Climate Trends on European Crop Yields

    NASA Astrophysics Data System (ADS)

    Moore, F.; Lobell, D. B.

    2014-12-01

    Europe has experienced a stagnation of some crop yields since the early-1990s as well as statistically-significant warming during the growing-season. While it has been argued that these two are causally connected, no previous studies have formally attributed long-term European yield trends to a changing climate. Here we present two statistical tests based on the distinctive spatial pattern of climate change impacts and adaptation, and explore their power under a range of parameter values. We show that statistical power for the identification of climate change impacts is high in many settings, but that power for identifying adaptation is almost always low. Applying these test to European agriculture, we find evidence that long-term temperature and precipitation trends have reduced continent-wide wheat, maize, and barley yields by 2.7%, 1.1%, and 3.9% respectively, and have increased sugarbeet yields by 1.0%. This can account for approximately 10% of the yield stagnation in Europe, with changes in agricultural and environmental policies likely explaining the remainder.

  10. Impacts of the Future Changes in Extreme Events on the Regional Crop Yield in Turkey

    NASA Astrophysics Data System (ADS)

    An, Nazan; Turp, M. Tufan; Ozturk, Tugba; Kurnaz, M. Levent

    2016-04-01

    The changes in extreme events caused by climate change have the greatest impact on agricultural sector specifically crop yield. Therefore, it requires a clear understanding of how extreme events affect the crop yield and how it causes high economic losses. In this research, we cover the relationship between extreme events and the crop yield in Turkey for the period of 2020 - 2045 with respect to 1980 - 2005. We focus on the role of those extreme event causing natural disasters on the regional crop yield. This research comprises 2 parts. In the first part, the projection is performed according to the business as usual scenario of IPCC, RCP8.5, via the RegCM4.4 in order to obtain extreme event indices required for the crop assessment. In the second part, the crop yield and the extreme event indices are combined by applying the econometric analysis in order to see the relationship between natural disasters and crop yield. The risks for crop yield caused by the extreme events are estimated and interpreted. This study aims to assess the effect of frequency of expected extreme events on the crop yield at the cropland of Turkey. This research has been supported by Boǧaziçi University Research Fund Grant Number 10421.

  11. Weather-based forecasts of California crop yields

    SciTech Connect

    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 the 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.

  12. 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.

  13. Double-crop sunflowers for agricultural diesel fuel

    SciTech Connect

    Glenn, T.L.; Keener, H.M.; Henry, J.E.; Triplett, G.B. Jr.

    1982-01-01

    Agronomic and engineering information on double-crop sunflower production, processing and utilization is presented. This and other available information is used to assess feasibility and future directions in the use of sunflower oil for agricultural diesel fuel in the US Eastern Corn Belt area. Double-cropping yields varied considerably due to precipitation extremes, plus different soil characteristics and management practices. Average expeller oil yields of 0.344 kg of oil per kg of moisture free seed were achieved with a feed rate of 125 kg per hour for a range in seed and processing conditions. Results from feasibility analyses suggest that sunflower oil can be grown in Ohio and processed in a community cooperative plant with a favorable energy ratio and marginal profitability. 3 figures, 4 tables.

  14. Statistical estimates to emulate yields from global gridded crop models

    NASA Astrophysics Data System (ADS)

    Blanc, Elodie

    2016-04-01

    This study provides a statistical emulator 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 weather variables for over a century at the grid cell level. This dataset is then used to estimate, for each crop and gridded crop model, the statistical relationship between yields and temperature, precipitation and carbon dioxide. This study considers a new functional form to better capture the non-linear response of yields to weather, especially for extreme temperature and precipitation events. In- and out-of-sample validations show that the statistical models are able to closely replicate crop yields projected by the crop models and perform well out-of-sample. 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 will be useful for climate change impact assessments and to account for uncertainty in crop modeling.

  15. 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.

  16. The Impact of Climate and Its Variability on Crop Yield and Irrigation

    NASA Astrophysics Data System (ADS)

    Li, X.; Troy, T.

    2014-12-01

    As the global population grows and the climate changes, having a secure food supply is increasingly important especially under water stressed-conditions. Although irrigation is a positive climate adaptation mechanism for agriculture, it has a potentially negative effect on water resources. It is therefore important to understand how crop yields due to irrigation are affected by climate variability and how irrigation may buffer against climate, allowing for more resilient agricultural systems. Efforts to solve these barely exposed questions can benefit from comprehending the influence of climate variability on crop yield and irrigation water use in the past. To do this, we use historical climate data,irrigation water use data and rainfed and irrigated crop yields over the US to analyze the relationship among climate, irrigation and delta crop yields, gained by subtracting rainfed yield from irrigated yield since 1970. We find that the increase in delta crop yield due to irrigation is larger for certain climate conditions, such that there are optimal climate conditions where irrigation provides a benefit and other conditions where irrigation proves to have marginal benefits when temperature increased to certain degrees. We find that crop water requirements are linked to potential evapotranspiration, yet actual irrigation water use is largely decoupled from the climate conditions but related with other causes. This has important implications for agricultural and water resource system planning, as it implies there are optimal climate zones where irrigation is productive and that changes in water use, both temporally and spatially, could lead to increased water availability without negative impacts on crop yields. Furthermore, based on the exposed relationship between crop yield gained by irrigation and climate variability, those models predicting the global harvest will be redress to estimate crop production in the future more accurately.

  17. 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

  18. 4% Yield Increase (HH4), All Energy Crops scenario of the 2016 Billion Ton Report

    SciTech Connect

    Davis, Maggie R.; Hellwinkel, Chad; Eaton, Laurence; Langholtz, Matthew H; Turhollow, Anthony; Brandt, Craig; Myers, Aaron

    2016-07-13

    Scientific reason for data generation: to serve as an alternate high-yield scenario for the BT16 volume 1 agricultural scenarios to compare these projections of potential biomass supplies against a reference case (agricultural baseline 10.11578/1337885). The simulation runs from 2015 through 2040; a starting year of 2014 is used but not reported. Date the data set was last modified: 02/02/2016. How each parameter was produced (methods), format, and relationship to other data in the data set: This exogenous price simulations (also referred to as “specified-price” simulations) introduces a farmgate price, and POLYSYS solves for biomass supplies that may be brought to market in response to these prices. In specified-price scenarios, a specified farmgate price is offered constantly in all counties over all years of the simulation. This simulation begins in 2015 with an offered farmgate price for primary crop residues only between 2015 and 2018 and long-term contracts for dedicated crops beginning in 2019. Expected mature energy crop yield grows at a compounding rate of 4% beginning in 2016. The yield growth assumptions are fixed after crops are planted such that yield gains do not apply. Instruments used: Policy Analysis System –POLYSYS (version POLYS2015_V10_alt_JAN22B), an agricultural policy modeling system of U.S. agriculture (crops and livestock), supplied by the University of Tennessee Institute of Agriculture, Agricultural Policy Analysis Center.

  19. WEBGIS based CropWatch online agriculture monitoring system

    NASA Astrophysics Data System (ADS)

    Zhang, X.; Wu, B.; Zeng, H.; Zhang, M.; Yan, N.

    2015-12-01

    CropWatch, which was developed by the Institute of Remote Sensing and Digital Earth (RADI), Chinese Academy of Sciences (CAS), has achieved breakthrough results in the integration of methods, independence of the assessments and support to emergency response by periodically releasing global agricultural information. Taking advantages of the multi-source remote sensing data and the openness of the data sharing policies, CropWatch group reported their monitoring results by publishing four bulletins one year. In order to better analysis and generate the bulletin and provide an alternative way to access agricultural monitoring indicators and results in CropWatch, The CropWatch online system based on the WEBGIS techniques has been developed. Figure 1 shows the CropWatch online system structure and the system UI in Clustering mode. Data visualization is sorted into three different modes: Vector mode, Raster mode and Clustering mode. Vector mode provides the statistic value for all the indicators over each monitoring units which allows users to compare current situation with historical values (average, maximum, etc.). Users can compare the profiles of each indicator over the current growing season with the historical data in a chart by selecting the region of interest (ROI). Raster mode provides pixel based anomaly of CropWatch indicators globally. In this mode, users are able to zoom in to the regions where the notable anomaly was identified from statistic values in vector mode. Data from remote sensing image series at high temporal and low spatial resolution provide key information in agriculture monitoring. Clustering mode provides integrated information on different classes in maps, the corresponding profiles for each class and the percentage of area of each class to the total area of all classes. The time series data is categorized into limited types by the ISODATA algorithm. For each clustering type, pixels on the map, profiles, and percentage legend are all linked

  20. 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

  1. 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

  2. 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

  3. Cost Methodology for Biomass Feedstocks: Herbaceous Crops and Agricultural Residues

    SciTech Connect

    Turhollow Jr, Anthony F; Webb, Erin; Sokhansanj, Shahabaddine

    2009-12-01

    This report describes a set of procedures and assumptions used to estimate production and logistics costs of bioenergy feedstocks from herbaceous crops and agricultural residues. The engineering-economic analysis discussed here is based on methodologies developed by the American Society of Agricultural and Biological Engineers (ASABE) and the American Agricultural Economics Association (AAEA). An engineering-economic analysis approach was chosen due to lack of historical cost data for bioenergy feedstocks. Instead, costs are calculated using assumptions for equipment performance, input prices, and yield data derived from equipment manufacturers, research literature, and/or standards. Cost estimates account for fixed and variable costs. Several examples of this costing methodology used to estimate feedstock logistics costs are included at the end of this report.

  4. 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.

  5. 7 CFR 201.18 - Other agricultural seeds (crop seeds).

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 7 Agriculture 3 2010-01-01 2010-01-01 false Other agricultural seeds (crop seeds). 201.18 Section... SERVICE (Standards, Inspections, Marketing Practices), DEPARTMENT OF AGRICULTURE (CONTINUED) FEDERAL SEED ACT FEDERAL SEED ACT REGULATIONS Labeling Agricultural Seeds § 201.18 Other agricultural seeds...

  6. An overview of crop growing condition monitoring in China agriculture remote sensing monitoring system

    NASA Astrophysics Data System (ADS)

    Huang, Qing; Zhou, Qing-bo; Zhang, Li

    2009-07-01

    China is a large agricultural country. To understand the agricultural production condition timely and accurately is related to government decision-making, agricultural production management and the general public concern. China Agriculture Remote Sensing Monitoring System (CHARMS) can monitor crop acreage changes, crop growing condition, agriculture disaster (drought, floods, frost damage, pest etc.) and predict crop yield etc. quickly and timely. The basic principles, methods and regular operation of crop growing condition monitoring in CHARMS are introduced in detail in the paper. CHARMS can monitor crop growing condition of wheat, corn, cotton, soybean and paddy rice with MODIS data. An improved NDVI difference model was used in crop growing condition monitoring in CHARMS. Firstly, MODIS data of every day were received and processed, and the max NDVI values of every fifteen days of main crop were generated, then, in order to assessment a certain crop growing condition in certain period (every fifteen days, mostly), the system compare the remote sensing index data (NDVI) of a certain period with the data of the period in the history (last five year, mostly), the difference between NDVI can indicate the spatial difference of crop growing condition at a certain period. Moreover, Meteorological data of temperature, precipitation and sunshine etc. as well as the field investigation data of 200 network counties were used to modify the models parameters. Last, crop growing condition was assessment at four different scales of counties, provinces, main producing areas and nation and spatial distribution maps of crop growing condition were also created.

  7. Ruminant Grazing of Cover Crops: Effects on Soil Properties and Agricultural Production

    ERIC Educational Resources Information Center

    Poffenbarger, Hanna

    2010-01-01

    Integrating livestock into a cropping system by allowing ruminant animals to graze cover crops may yield economic and environmental benefits. The effects of grazing on soil physical properties, soil organic matter, nitrogen cycling and agricultural production are presented in this literature review. The review found that grazing cover crops…

  8. Modifying agricultural crops for improved nutrition.

    PubMed

    McGloughlin, Martina Newell

    2010-11-30

    The first generation of biotechnology products commercialized were crops focusing largely on input agronomic traits whose value was often opaque to consumers. The coming generations of crop plants can be grouped into four broad areas each presenting what, on the surface, may appear as unique challenges and opportunities. The present and future focus is on continuing improvement of agronomic traits such as yield and abiotic stress resistance in addition to the biotic stress tolerance of the present generation; crop plants as biomass feedstocks for biofuels and "bio-synthetics"; value-added output traits such as improved nutrition and food functionality; and plants as production factories for therapeutics and industrial products. From a consumer perspective, the focus on value-added traits, especially improved nutrition, is undoubtedly one of the areas of greatest interest. From a basic nutrition perspective, there is a clear dichotomy in demonstrated need between different regions and socioeconomic groups, the starkest being inappropriate consumption in the developed world and under-nourishment in Less Developed Countries (LDCs). Dramatic increases in the occurrence of obesity and related ailments in affluent regions are in sharp contrast to chronic malnutrition in many LDCs. Both problems require a modified food supply, and the tools of biotechnology have a part to play. Developing plants with improved traits involves overcoming a variety of technical, regulatory and indeed perception hurdles inherent in perceived and real challenges of complex traits modifications. Continuing improvements in molecular and genomic technologies are contributing to the acceleration of product development to produce plants with the appropriate quality traits for the different regions and needs. Crops with improved traits in the pipeline, the evolving technologies and the opportunities and challenges that lie ahead are covered.

  9. Comparing the yields of organic and conventional agriculture.

    PubMed

    Seufert, Verena; Ramankutty, Navin; Foley, Jonathan A

    2012-05-10

    Numerous reports have emphasized the need for major changes in the global food system: agriculture must meet the twin challenge of feeding a growing population, with rising demand for meat and high-calorie diets, while simultaneously minimizing its global environmental impacts. Organic farming—a system aimed at producing food with minimal harm to ecosystems, animals or humans—is often proposed as a solution. However, critics argue that organic agriculture may have lower yields and would therefore need more land to produce the same amount of food as conventional farms, resulting in more widespread deforestation and biodiversity loss, and thus undermining the environmental benefits of organic practices. Here we use a comprehensive meta-analysis to examine the relative yield performance of organic and conventional farming systems globally. Our analysis of available data shows that, overall, organic yields are typically lower than conventional yields. But these yield differences are highly contextual, depending on system and site characteristics, and range from 5% lower organic yields (rain-fed legumes and perennials on weak-acidic to weak-alkaline soils), 13% lower yields (when best organic practices are used), to 34% lower yields (when the conventional and organic systems are most comparable). Under certain conditions—that is, with good management practices, particular crop types and growing conditions—organic systems can thus nearly match conventional yields, whereas under others it at present cannot. To establish organic agriculture as an important tool in sustainable food production, the factors limiting organic yields need to be more fully understood, alongside assessments of the many social, environmental and economic benefits of organic farming systems.

  10. Influence of seasonal weather and climate variability on crop yields in Scotland

    NASA Astrophysics Data System (ADS)

    Brown, Iain

    2013-07-01

    The climatic sensitivity of four important agriculture crops (wheat, barley, oats, potatoes) in a northern temperate bioclimatic region is investigated using national-level yield data for 1963-2005. The climate variables include monthly and annual meteorological data, derived bioclimatic metrics, and the North Atlantic Oscillation index. Statistical analysis shows that significant relationships between yield and climate vary depending on the crop type and month but highlight the influence of precipitation (negative correlation) and sunshine duration (positive correlation) rather than temperature. Soil moisture deficit is shown to be a particular useful indicator of yield with drier summers providing the best yields for Scotland as a whole. It is also tentatively inferred that the sensitivity of these crops, particularly wheat and barley, to soil moisture deficits has increased in recent years. This suggests that improved crop yields are optimised for dry sunny years despite the continued prevalence of considerable inter-annual variability in seasonal weather.

  11. Influence of seasonal weather and climate variability on crop yields in Scotland.

    PubMed

    Brown, Iain

    2013-07-01

    The climatic sensitivity of four important agriculture crops (wheat, barley, oats, potatoes) in a northern temperate bioclimatic region is investigated using national-level yield data for 1963-2005. The climate variables include monthly and annual meteorological data, derived bioclimatic metrics, and the North Atlantic Oscillation index. Statistical analysis shows that significant relationships between yield and climate vary depending on the crop type and month but highlight the influence of precipitation (negative correlation) and sunshine duration (positive correlation) rather than temperature. Soil moisture deficit is shown to be a particular useful indicator of yield with drier summers providing the best yields for Scotland as a whole. It is also tentatively inferred that the sensitivity of these crops, particularly wheat and barley, to soil moisture deficits has increased in recent years. This suggests that improved crop yields are optimised for dry sunny years despite the continued prevalence of considerable inter-annual variability in seasonal weather.

  12. Estimation of corn and soybeans yield using remote sensing and crop yield data in the United States

    NASA Astrophysics Data System (ADS)

    Kim, Nari; Lee, Yang-Won

    2014-10-01

    The crop yield estimation is essential for the food security and the economic development of any nation. Particularly, the United States is the world largest grain exporter, and the total amount of corn exported from the U.S. accounted for 49.2% of the world corn trade in 2010 and 2011. Thus, accurate estimation of crop yield in U.S. is very significant for not only the U.S. crop producers but also decision makers of food importing countries. Estimating the crop yield using remote sensing data plays an important role in the Agricultural Sector, and it is actively discussed and studied in many countries. This is because remote sensing can observe the large areas repetitively. Consequently, the use of various techniques based on remote sensing data is steadily increasing to accurately estimate for crop yield. Therefore, the objective of this study is to estimate the accurate yield of corn and soybeans using climate dataset of PRISM climate group and Terra/MODIS products in the United States. We construct the crop yield estimation model for the decade (2001-2010) and perform predictions and validation for 2011 and 2012.

  13. Climate impacts on agriculture: Implications for crop production

    SciTech Connect

    Hatfield, Jerry L.; Boote, Kenneth J.; Kimball, B. A.; Ziska, Lewis A.; Izaurralde, Roberto C.; Ort, Don; Thomson, Allison M.; Wolfe, David W.

    2011-04-19

    Changes in temperature, CO2, and precipitation under the scenarios of climate change for the next 30 years present a challenge to crop production. This review focuses on the impact of temperature, CO2, and ozone on agronomic crops and the implications for crop production. Understanding these implications for agricultural crops is critical for developing cropping systems resilient to stresses induced by climate change. There is variation among crops in their response to CO2, temperature, and precipitation changes and, with the regional differences in predicted climate, a situation is created in which the responses will be further complicated. For example, the temperature effects on soybean could potentially cause yield reductions of 2.4% in the South but an increase of 1.7% in the Midwest. The frequency of years when temperatures exceed thresholds for damage during critical growth stages is likely to increase for some crops and regions. The increase in CO2 contributes significantly to enhanced plant growth and improved water use efficiency; however, there may be a downscaling of these positive impacts due to higher temperatures plants will experience during their growth cycle. A challenge is to understand the interactions of the changing climatic parameters because of the interactions among temperature, CO2, and precipitation on plant growth and development and also on the biotic stresses of weeds, insects, and diseases. Agronomists will have to consider the variations in temperature and precipitation as part of the production system if they are to ensure the food security required by an ever increasing population.

  14. An Assessment of the Quality of Crop Yield Predictions under Different Degrees of Water Limitation in European Crop Producing Countries

    NASA Astrophysics Data System (ADS)

    Vogel, E.

    2015-12-01

    The Fifth IPCC Assessment Report on climate change shows that the frequency and/or intensity of different types of weather extreme events is likely to increase in a number of regions across the globe. The agricultural sector, which plays a crucial role for the livelihood of a large fraction of the world's population, is particularly vulnerable to extreme events due to its dependency on climate conditions.Process-based crop models play an important role for translating climate and weather information into agricultural forecasts, both at decadal time scales as part of climate impact assessments and shorter time scales, for examples for seasonal yield predictions as part of early warning systems for harvest failures. A variety of crop models exist, with different degrees of complexity, spatial and temporal resolutions, incorporated chemical, physical and biological processes and mathematical formulations of these processes. Furthermore, crop models differ with regard to the agro-climatic zones and crop types for which they were calibrated and validated. For these reasons, crop models can vary significantly with respect to their suitability for yield forecasts under different climate conditions, geographical regions and crop types.In this study, we assess the quality of crop yield predictions of the vegetation model LPJmL for four major crops (maize, rice, wheat, soy) under a range of water limitation conditions in Europe, using a high-resolution regional climate data set (0.1 ° x 0.1 °) covering the period 1989-2008. The aim of the study is to examine the degree of uncertainty of yield predictions for different agro-climatic zones and to identify the factors that influence the goodness-of-fit of model predictions. By this, we hope to provide input into further model improvements and to provide guidance for decision-makers on the suitability of yield predictions for different climatic regions within the European continent.

  15. Redefining agricultural yields: from tonnes to people nourished per hectare

    NASA Astrophysics Data System (ADS)

    Cassidy, Emily S.; West, Paul C.; Gerber, James S.; Foley, Jonathan A.

    2013-09-01

    Worldwide demand for crops is increasing rapidly due to global population growth, increased biofuel production, and changing dietary preferences. Meeting these growing demands will be a substantial challenge that will tax the capability of our food system and prompt calls to dramatically boost global crop production. However, to increase food availability, we may also consider how the world’s crops are allocated to different uses and whether it is possible to feed more people with current levels of crop production. Of particular interest are the uses of crops as animal feed and as biofuel feedstocks. Currently, 36% of the calories produced by the world’s crops are being used for animal feed, and only 12% of those feed calories ultimately contribute to the human diet (as meat and other animal products). Additionally, human-edible calories used for biofuel production increased fourfold between the years 2000 and 2010, from 1% to 4%, representing a net reduction of available food globally. In this study, we re-examine agricultural productivity, going from using the standard definition of yield (in tonnes per hectare, or similar units) to using the number of people actually fed per hectare of cropland. We find that, given the current mix of crop uses, growing food exclusively for direct human consumption could, in principle, increase available food calories by as much as 70%, which could feed an additional 4 billion people (more than the projected 2-3 billion people arriving through population growth). Even small shifts in our allocation of crops to animal feed and biofuels could significantly increase global food availability, and could be an instrumental tool in meeting the challenges of ensuring global food security.

  16. Global crop yield reductions due to surface ozone exposure: 1. Year 2000 crop production losses and economic damage

    NASA Astrophysics Data System (ADS)

    Avnery, Shiri; Mauzerall, Denise L.; Liu, Junfeng; Horowitz, Larry W.

    2011-04-01

    Exposure to elevated concentrations of surface ozone (O 3) causes substantial reductions in the agricultural yields of many crops. As emissions of O 3 precursors rise in many parts of the world over the next few decades, yield reductions from O 3 exposure appear likely to increase the challenges of feeding a global population projected to grow from 6 to 9 billion between 2000 and 2050. This study estimates year 2000 global yield reductions of three key staple crops (soybean, maize, and wheat) due to surface ozone exposure using hourly O 3 concentrations simulated by the Model for Ozone and Related Chemical Tracers version 2.4 (MOZART-2). We calculate crop losses according to two metrics of ozone exposure - seasonal daytime (08:00-19:59) mean O 3 (M12) and accumulated O 3 above a threshold of 40 ppbv (AOT40) - and predict crop yield losses using crop-specific O 3 concentration:response functions established by field studies. Our results indicate that year 2000 O 3-induced global yield reductions ranged, depending on the metric used, from 8.5-14% for soybean, 3.9-15% for wheat, and 2.2-5.5% for maize. Global crop production losses totaled 79-121 million metric tons, worth $11-18 billion annually (USD 2000). Our calculated yield reductions agree well with previous estimates, providing further evidence that yields of major crops across the globe are already being substantially reduced by exposure to surface ozone - a risk that will grow unless O 3-precursor emissions are curbed in the future or crop cultivars are developed and utilized that are resistant to O 3.

  17. 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

  18. 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.

  19. Yield Trends Are Insufficient to Double Global Crop Production by 2050.

    PubMed

    Ray, Deepak K; Mueller, Nathaniel D; West, Paul C; Foley, Jonathan A

    2013-01-01

    Several studies have shown that global crop production needs to double by 2050 to meet the projected demands from rising population, diet shifts, and increasing biofuels consumption. Boosting crop yields to meet these rising demands, rather than clearing more land for agriculture has been highlighted as a preferred solution to meet this goal. However, we first need to understand how crop yields are changing globally, and whether we are on track to double production by 2050. Using ∼2.5 million agricultural statistics, collected for ∼13,500 political units across the world, we track four key global crops-maize, rice, wheat, and soybean-that currently produce nearly two-thirds of global agricultural calories. We find that yields in these top four crops are increasing at 1.6%, 1.0%, 0.9%, and 1.3% per year, non-compounding rates, respectively, which is less than the 2.4% per year rate required to double global production by 2050. At these rates global production in these crops would increase by ∼67%, ∼42%, ∼38%, and ∼55%, respectively, which is far below what is needed to meet projected demands in 2050. We present detailed maps to identify where rates must be increased to boost crop production and meet rising demands.

  20. 3% Yield Increase (HH3), All Energy Crops scenario of the 2016 Billion Ton Report

    SciTech Connect

    Davis, Maggie R.; Hellwinkel, Chad; Eaton, Laurence; Langholtz, Matthew H.; Turhollow, Anthony; Brandt, Craig; Myers, Aaron

    2016-07-13

    Scientific reason for data generation: to serve as an alternate high-yield scenario for the BT16 volume 1 agricultural scenarios to compare these projections of potential biomass supplies against a reference case (agricultural baseline 10.11578/1337885). The simulation runs from 2015 through 2040; a starting year of 2014 is used but not reported. Date the data set was last modified: 02/02/2016 How each parameter was produced (methods), format, and relationship to other data in the data set: This exogenous price simulations (also referred to as “specified-price” simulations) introduces a farmgate price, and POLYSYS solves for biomass supplies that may be brought to market in response to these prices. In specified-price scenarios, a specified farmgate price is offered constantly in all counties over all years of the simulation. This simulation begins in 2015 with an offered farmgate price for primary crop residues only between 2015 and 2018 and long-term contracts for dedicated crops beginning in 2019. Expected mature energy crop yield grows at a compounding rate of 3% beginning in 2016. The yield growth assumptions are fixed after crops are planted such that yield gains do not apply to crops already planted, but new plantings do take advantage of the gains in expected yield growth. Instruments used: Policy Analysis System –POLYSYS (version POLYS2015_V10_alt_JAN22B), an agricultural policy modeling system of U.S. agriculture (crops and livestock), supplied by the University of Tennessee Institute of Agriculture, Agricultural Policy Analysis Center.

  1. 2% Yield Increase (HH2), All Energy Crops scenario of the 2016 Billion Ton Report

    DOE Data Explorer

    Davis, Maggie R. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)] (ORCID:0000000181319328); Hellwinkel, Chad [University of Tennessee] (ORCID:0000000173085058); Eaton, Laurence [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)] (ORCID:0000000312709626); Langholtz, Matthew H [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)] (ORCID:0000000281537154); Turhollow, Anthony [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)] (ORCID:0000000228159350); Brandt, Craig [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)] (ORCID:0000000214707379); Myers, Aaron [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)] (ORCID:0000000320373827)

    2016-07-13

    Scientific reason for data generation: to serve as an alternate high-yield scenario for the BT16 volume 1 agricultural scenarios to compare these projections of potential biomass supplies against a reference case (agricultural baseline 10.11578/1337885). The simulation runs from 2015 through 2040; a starting year of 2014 is used but not reported. Date the data set was last modified: 02/02/2016 How each parameter was produced (methods), format, and relationship to other data in the data set: This exogenous price simulations (also referred to as “specified-price” simulations) introduces a farmgate price, and POLYSYS solves for biomass supplies that may be brought to market in response to these prices. In specified-price scenarios, a specified farmgate price is offered constantly in all counties over all years of the simulation. This simulation begins in 2015 with an offered farmgate price for primary crop residues only between 2015 and 2018 and long-term contracts for dedicated crops beginning in 2019. Expected mature energy crop yield grows at a compounding rate of 2% beginning in 2016. The yield growth assumptions are fixed after crops are planted such that yield gains do not apply to crops already planted, but new plantings do take advantage of the gains in expected yield growth. Instruments used: Policy Analysis System –POLYSYS (version POLYS2015_V10_alt_JAN22B), an agricultural policy modeling system of U.S. agriculture (crops and livestock), supplied by the University of Tennessee Institute of Agriculture, Agricultural Policy Analysis Center.

  2. 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.

  3. Projecting crop yield in northern high latitude area.

    PubMed

    Matsumura, Kanichiro

    2014-01-01

    Changing climatic conditions on seasonal and longer time scales influence agricultural production. Improvement of soil and fertilizer is a strong factor in agricultural production, but agricultural production is influenced by climate conditions even in highly developed countries. It is valuable if fewer predictors make it possible to conduct future projections. Monthly temperature and precipitation, wintertime 500hPa geopotential height, and the previous year's yield are used as predictors to forecast spring wheat yield in advance. Canadian small agricultural divisions (SAD) are used for analysis. Each SAD is composed of a collection of Canadian Agricultural Regions (CAR) of similar weather and growing conditions. Spring wheat yields in each CAR are forecast from the following variables: (a) the previous year's yield, (b) earlier stages of the growing season's climate conditions and, (c) the previous year's wintertime northern hemisphere 500hPa geopotential height field. Arctic outflow events in the Okanagan Valley in Canada are associated with episodes of extremely low temperatures during wintertime. Principal component analysis (PCA) is applied for wintertime northern hemisphere 500hPa geopotential height anomalies. The spatial PCA mode1 is defined as Arctic Oscillation and it influences prevailing westerlies. The prevailing westerlies meanders and influences climatic conditions. The spatial similarity between wintertime top 5 Arctic outflow event year's composites of 500hPa geopotential height anomalies and mode 3's spatial pattern is found. Mode 3's spatial pattern looks like the Pacific/North American (PNA) pattern which describes the variation of atmospheric circulation pattern over the Pacific Ocean and North America. Climate conditions from April to June, May to July, mode 3's time coefficients, and previous year's yield are used for forecasting spring wheat yield in each SAD. Cross-validation procedure which generates eight sets of models for the eight

  4. Transgenic Crops: Implications for Biodiversity and Sustainable Agriculture

    ERIC Educational Resources Information Center

    Garcia, Maria Alice; Altieri, Miguel A.

    2005-01-01

    The potential for genetically modified (GM) crops to threaten biodiversity conservation and sustainable agriculture is substantial. Megadiverse countries and centers of origin and/or diversity of crop species are particularly vulnerable regions. The future of sustainable agriculture may be irreversibly jeopardized by contamination of in situ…

  5. Agricultural Development Workers Training Manual. Volume III. Crops.

    ERIC Educational Resources Information Center

    Leonard, David; And Others

    This training manual, the third volume in a four-volume series of curriculum guides for use in training Peace Corps agricultural development workers, deals with crops. The first chapter provides suggested guidelines for setting up and carrying out the crops component of the agricultural development worker training series. Included in the second…

  6. Scheduling for deficit irrigation, Crop Yield Predictor

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Irrigators in many countries with dwindling water supplies face the prospect that they will not be able to fully irrigate their crops. In these cases, they still need to schedule their water applications to make the best economic use of available water. Major scheduling questions for deficit irrigat...

  7. Soil total carbon and crop yield affected by crop rotation and cultural practice

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  8. Crop rotations with annual and perennial forages under no-till soil management: soil attributes, soybean mineral nutrition, and yield

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Extensive use of sustainable and intensive agricultural systems would result in profitable farms producing greater yields while maintaining or enhancing natural resources. Development of sustainable crop and soil management systems depends on understanding complex relationships between soil managem...

  9. Crop yield network and its response to changes in climate system

    NASA Astrophysics Data System (ADS)

    Yokozawa, M.

    2013-12-01

    Crop failure (reduction in crop yield) due to extreme weather and climate change could lead to unstable food supply, reflecting the recent globalization in world agricultural production. Specifically, in several major production countries producing large amount of main cereal crops, wheat, maize, soybean and rice, abrupt crop failures in wide area are significantly serious for world food supply system. We examined the simultaneous changes in crop yield in USA, China and Brazil, in terms of the changes in climate system such as El Nino, La nina and so on. In this study, we defined a crop yield networks, which represent the correlation between yearly changes in crop yields and climate resources during the crop growing season in two regions. The climate resources during the crop growing season represents here the average temperature and the accumulated precipitation during the crop growing season of a target crop. As climate data, we used a reanalysis climate data JRA-25 (Japan Meteorological Agency). The yearly changes in crop yields are based on a gridded crop productivity database with a resolution of 1.125 degree in latitude/longitude (Iizumi et al. 2013). It is constructed from the agriculture statistics issued by local administrative bureau in each country, which covers the period during 1982 to 2006 (25 years). For the regions being lack of data, the data was interpolated referring to NPP values estimated by satellite data. Crop yield network is constructed as follows: (1) let DY(i,y) be negative difference in crop yield of year y from the trend yield at grid i; (2) define the correlation of the differences Cij(y) = DY(i, y) DY(j, y); (3) if Cij(y) > Q, then grids i and j are mutually linked for a threshold value Q. Links between grids make a crop yield network. It is here noted that only negative differences are taken into account because we focused on the lean year cases (i.e. yields of both grids were lower than those in the long-term trend). The arrays of

  10. Linkages among climate change, crop yields and Mexico-US cross-border migration.

    PubMed

    Feng, Shuaizhang; Krueger, Alan B; Oppenheimer, Michael

    2010-08-10

    Climate change is expected to cause mass human migration, including immigration across international borders. This study quantitatively examines the linkages among variations in climate, agricultural yields, and people's migration responses by using an instrumental variables approach. Our method allows us to identify the relationship between crop yields and migration without explicitly controlling for all other confounding factors. Using state-level data from Mexico, we find a significant effect of climate-driven changes in crop yields on the rate of emigration to the United States. The estimated semielasticity of emigration with respect to crop yields is approximately -0.2, i.e., a 10% reduction in crop yields would lead an additional 2% of the population to emigrate. We then use the estimated semielasticity to explore the potential magnitude of future emigration. Depending on the warming scenarios used and adaptation levels assumed, with other factors held constant, by approximately the year 2080, climate change is estimated to induce 1.4 to 6.7 million adult Mexicans (or 2% to 10% of the current population aged 15-65 y) to emigrate as a result of declines in agricultural productivity alone. Although the results cannot be mechanically extrapolated to other areas and time periods, our findings are significant from a global perspective given that many regions, especially developing countries, are expected to experience significant declines in agricultural yields as a result of projected warming.

  11. Linkages among climate change, crop yields and Mexico–US cross-border migration

    PubMed Central

    Feng, Shuaizhang; Krueger, Alan B.; Oppenheimer, Michael

    2010-01-01

    Climate change is expected to cause mass human migration, including immigration across international borders. This study quantitatively examines the linkages among variations in climate, agricultural yields, and people's migration responses by using an instrumental variables approach. Our method allows us to identify the relationship between crop yields and migration without explicitly controlling for all other confounding factors. Using state-level data from Mexico, we find a significant effect of climate-driven changes in crop yields on the rate of emigration to the United States. The estimated semielasticity of emigration with respect to crop yields is approximately −0.2, i.e., a 10% reduction in crop yields would lead an additional 2% of the population to emigrate. We then use the estimated semielasticity to explore the potential magnitude of future emigration. Depending on the warming scenarios used and adaptation levels assumed, with other factors held constant, by approximately the year 2080, climate change is estimated to induce 1.4 to 6.7 million adult Mexicans (or 2% to 10% of the current population aged 15–65 y) to emigrate as a result of declines in agricultural productivity alone. Although the results cannot be mechanically extrapolated to other areas and time periods, our findings are significant from a global perspective given that many regions, especially developing countries, are expected to experience significant declines in agricultural yields as a result of projected warming. PMID:20660749

  12. Priorities for worldwide remote sensing of agricultural crops

    NASA Technical Reports Server (NTRS)

    Bowker, D. E.

    1985-01-01

    The world's crops are ranked according to total harvested area, and comparisons are made among major world regions of differences in crops produced. The eight leading world crops are wheat, rice, corn, barley, millet, soybeans, sorghum, and cotton. Regionally, millet and sorghum are most important in Africa, wheat is the most extensively grown crop in north-central America, Europe, USSR, and Oceania; corn is the dominant crop in South America; and rice is the most extensively grown crop in Asia. Agriculture in the USA is considered in more detail to show the national economic impact of variations in value per hectare among crops. On the world scene, the cereals are the most important crops, but locally, such crops as tobacco can play a dominant role.

  13. Developing robust crop plants for sustaining growth and yield under adverse climatic changes

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Agricultural production and quality are expected to suffer from adverse changes in climatic conditions, including global warming, and this will affect worldwide human and animal food security. Global warming has been shown to negatively impact crop yield and therefore will affect sustainability of a...

  14. 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.

  15. 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.

  16. Impacts of Future Climate Change on California Perennial Crop Yields: Model Projections with Climate and Crop Uncertainties

    SciTech Connect

    Lobell, D; Field, C; Cahill, K; Bonfils, C

    2006-01-10

    Most research on the agricultural impacts of climate change has focused on the major annual crops, yet perennial cropping systems are less adaptable and thus potentially more susceptible to damage. Improved assessments of yield responses to future climate are needed to prioritize adaptation strategies in the many regions where perennial crops are economically and culturally important. These impact assessments, in turn, must rely on climate and crop models that contain often poorly defined uncertainties. We evaluated the impact of climate change on six major perennial crops in California: wine grapes, almonds, table grapes, oranges, walnuts, and avocados. Outputs from multiple climate models were used to evaluate climate uncertainty, while multiple statistical crop models, derived by resampling historical databases, were used to address crop response uncertainties. We find that, despite these uncertainties, climate change in California is very likely to put downward pressure on yields of almonds, walnuts, avocados, and table grapes by 2050. Without CO{sub 2} fertilization or adaptation measures, projected losses range from 0 to >40% depending on the crop and the trajectory of climate change. Climate change uncertainty generally had a larger impact on projections than crop model uncertainty, although the latter was substantial for several crops. Opportunities for expansion into cooler regions are identified, but this adaptation would require substantial investments and may be limited by non-climatic constraints. Given the long time scales for growth and production of orchards and vineyards ({approx}30 years), climate change should be an important factor in selecting perennial varieties and deciding whether and where perennials should be planted.

  17. Estimating agricultural yield gap in Africa using MODIS NDVI dataset

    NASA Astrophysics Data System (ADS)

    Luan, Y.; Zhu, W.; Luo, X.; Liu, J.; Cui, X.

    2013-12-01

    Global agriculture has undergone a period of rapid intensification characterized as 'Green Revolution', except for Africa, which is the region most affected by unreliable food access and undernourishment. Increasing crop production will be one of the most challenges and most effectual way to mitigate food insecurity there, as Africa's agricultural yield is on a much lower level comparing to global average. In this study we characterize cropland vegetation phenology in Africa based on MODIS NDVI time series between 2000 and 2012. Cumulated NDVI is a proxy for net primary productivity and used as an indicator for evaluating the potential yield gap in Africa. It is achieved via translating the gap between optimum attainable productivity level in each classification of cropping systems and actual productivity level by the relationship of cumulated NDVI and cereal-equivalent production. The results show most of cropland area in Africa have decreasing trend in cumulated NDVI, distributing in the Nile Delta, Eastern Africa and central of semi-arid to arid savanna area, except significant positive cumulated NDVI trends are mainly found between Senegal and Benin. Using cumulated NDVI and statistics of cereal equivalent production, we find remarkable potential yield gap at the Horn of East Africa (especially in Somalia), Northern Africa (Morocco, Algeria and Tunisia). Meanwhile, countries locating at the savanna area near Sahel desert and South Africa also show significant potential, though they already have a relatively high level of productivity. Our results can help provide policy recommendation for local government or NGO to tackle food security problems by identifying zones with high potential of yield improvement.

  18. 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.

  19. 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; Deryng, Delphine; Folberth, Christian; Izaurralde, Robert C.; Jones, Curtis D.; Khabarov, Nikolay; Lawrence, Peter J.; Liu, Wenfeng; Pugh, Thomas A. M.; Reddy, Ashwan; Sakurai, Gen; Schmid, Erwin; Wang, Xuhui; Wu, Xiuchen; de Wit, Allard

    2016-01-01

    The aggregation of simulated gridded crop yields to national or regional scale requires information on temporal and spatial patterns of crop-specific harvested areas. This analysis estimates the uncertainty of simulated gridded yield time series related to the aggregation with four different harvested area data sets. We compare aggregated yield time series from the Global Gridded Crop Model Inter-comparison project for four crop types from 14 models at global, national, and regional scale to determine aggregation-driven differences in mean yields and temporal patterns as measures of uncertainty. The quantity and spatial patterns of harvested areas differ for individual crops among the four datasets applied for the aggregation. Also simulated spatial yield patterns differ among the 14 models. These differences in harvested areas and simulated yield patterns lead to differences in aggregated productivity estimates, both in mean yield and in the temporal dynamics. Among the four investigated crops, wheat yield (17% relative difference) is most affected by the uncertainty introduced by the aggregation at the global scale. The correlation of temporal patterns of global aggregated yield time series can be as low as for soybean (r = 0.28).For the majority of countries, mean relative differences of nationally aggregated yields account for10% or less. The spatial and temporal difference can be substantial higher for individual countries. Of the top-10 crop producers, aggregated national multi-annual mean relative difference of yields can be up to 67% (maize, South Africa), 43% (wheat, Pakistan), 51% (rice, Japan), and 427% (soybean, Bolivia).Correlations of differently aggregated yield time series can be as low as r = 0.56 (maize, India), r = 0.05*Corresponding (wheat, Russia), r = 0.13 (rice, Vietnam), and r = -0.01 (soybean, Uruguay). The aggregation to sub-national scale in comparison to country scale shows that spatial uncertainties can cancel out in countries with

  20. Topsoil Depth Effects on Crop Yields as Affected by Weather

    NASA Astrophysics Data System (ADS)

    Lee, Scott; Cruse, Richard

    2015-04-01

    Topsoil (A-horizon) depth is positively correlated with crop productivity; crop roots and available nutrients are concentrated in this layer; topsoil is critical for nutrient retention and water holding capacity. Its loss or reduction can be considered an irreversible impact of soil erosion. Climatic factors such as precipitation and temperature extremes that impose production stress further complicate the relationship between soil erosion and crop productivity. The primary research objective was to determine the effects of soil erosion on corn and soybean yields of loess and till-derived soils in the rain-fed farming region of Iowa. Data collection took place from 2007 to 2012 at seven farm sites located in different major soil regions. Collection consisted of 40 to 50 randomly selected georeferenced soil probe locations across varying erosion classes in well drained landscape positions. Soil probes were done to a minimum depth of 100 cm and soil organic carbon samples were obtained in the top 10 cm. Crop yields were determined utilizing georeferenced harvest maps from yield monitoring devices and cross referenced with georeferenced field data points. Data analysis targeted relationships between crop yields versus soil organic carbon contents (SOC) and crop yields versus topsoil depths (TSD). The variation of yield and growing season rainfall across multiple years were also evaluated to provide an indication of soil resiliency associated with topsoil depth and soil organic carbon levels across varying climatic conditions. Results varied between sites but generally indicated a greater yield potential at thicker TSD's and higher SOC concentrations; an annual variation in yield response as a function of precipitation amount during the growing season; largest yield responses to both TSD and SOC occurred in the driest study year (2012); and little to no significant yield responses to TSD occurred during the wettest study year (2010). These results were not

  1. Crop growth stress and yield reduction as detected from spectral data

    NASA Astrophysics Data System (ADS)

    Kancheva, Rumiana

    A significant amount of research is being performed to develop efficient methods for monitoring of vegetation dynamics at different scales and from different data sources. To provide distinguishable markers for agricultural crop assessment is a core task in vegetation remote sensing. This task is relevant to precision farming in order to track crop development and evaluate crop growth conditions in terms of detecting unfavorable or stress situations as well as to make yield predictions. In this paper we present some results from experiments that have been conducted over different species grown under different conditions: nutrient supply (fertilization types and rates), heavy metal pollution, soil properties. The effect of these conditions on crop growth and productivity has been studied and related to plant spectral features in a statistical manner. Crops have been characterized by key bioparameters during plant development (biomass, leaf area index, canopy cover) and by crop yield at the end of the growing season. Multispectral and multitemporal vegetation indices from ground based and airborne data have been used to quantitatively distinguish between crop state and in yield prediction models. The main pillars of the algorithm are: - development of inverse crop radiative models for estimation of crop state variables from radiometric data; - development of yield prediction models based on crop state variables with consideration of plant phenology; - current yield prediction models from crop radiometric data; - yield forecast updates from time series radiometric data; - yield prediction verification from plant biophysical models. This approach is quite suitable for implementation at local scales using airborne multispectral data with a temporal resolution in accordance with the proper for the case time-lag (crop type, ontogenesis, etc.). It has been developed for winter wheat and spring barley through ground-based experiments and has been tested and validated using

  2. Impact of climate change on crop yield and role of model for achieving food security.

    PubMed

    Kumar, Manoj

    2016-08-01

    In recent times, several studies around the globe indicate that climatic changes are likely to impact the food production and poses serious challenge to food security. In the face of climate change, agricultural systems need to adapt measures for not only increasing food supply catering to the growing population worldwide with changing dietary patterns but also to negate the negative environmental impacts on the earth. Crop simulation models are the primary tools available to assess the potential consequences of climate change on crop production and informative adaptive strategies in agriculture risk management. In consideration with the important issue, this is an attempt to provide a review on the relationship between climate change impacts and crop production. It also emphasizes the role of crop simulation models in achieving food security. Significant progress has been made in understanding the potential consequences of environment-related temperature and precipitation effect on agricultural production during the last half century. Increased CO2 fertilization has enhanced the potential impacts of climate change, but its feasibility is still in doubt and debates among researchers. To assess the potential consequences of climate change on agriculture, different crop simulation models have been developed, to provide informative strategies to avoid risks and understand the physical and biological processes. Furthermore, they can help in crop improvement programmes by identifying appropriate future crop management practises and recognizing the traits having the greatest impact on yield. Nonetheless, climate change assessment through model is subjected to a range of uncertainties. The prediction uncertainty can be reduced by using multimodel, incorporating crop modelling with plant physiology, biochemistry and gene-based modelling. For devloping new model, there is a need to generate and compile high-quality field data for model testing. Therefore, assessment of

  3. 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.

  4. Linear unmixing of multidate hyperspectral imagery for crop yield estimation

    Technology Transfer Automated Retrieval System (TEKTRAN)

    In this paper, we have evaluated an unsupervised unmixing approach, vertex component analysis (VCA), for the application of crop yield estimation. The results show that abundance maps of the vegetation extracted by the approach are strongly correlated to the yield data (the correlation coefficients ...

  5. Surprising yields with no-till cropping systems

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Producers using no-till systems have found that crop yields often exceed their expectation based on nutrient and water supply. For example, corn yields 7% higher in a no-till system in central South Dakota than in a tilled system in eastern South Dakota. This is surprising because rainfall is 5 in...

  6. Surprising yields with no-till cropping systems

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Producers using no-till practices have observed that crop yields can greatly exceed expectations based on nutrient and water supply. For example, Ralph Holzwarth, who farms near Gettysburg, SD, has averaged 150 bu/ac of corn on his farm for the past 6 years. We were surprised with this yield, as c...

  7. Fuel production potential of several agricultural crops

    SciTech Connect

    Mays, D.A.; Buchanan, W.; Bradford, B.N.

    1984-11-01

    Data collected on starch and sugar crops indicate that sweet potato and sweet sorghum have the best potential for alcohol production in the TVA area. Of the oil crops evaluated in this series of experiments only sunflower and okara appear to offer potential in the Tennessee Valley for oil production for fuel or other uses. 21 tabs.

  8. Estimation of flood losses to agricultural crops using remote sensing

    NASA Astrophysics Data System (ADS)

    Tapia-Silva, Felipe-Omar; Itzerott, Sibylle; Foerster, Saskia; Kuhlmann, Bernd; Kreibich, Heidi

    2011-01-01

    The estimation of flood damage is an important component of risk-oriented flood design, risk mapping, financial appraisals and comparative risk analyses. However, research on flood loss modelling, especially in the agricultural sector, has not yet gained much attention. Agricultural losses strongly depend on the crops affected, which need to be predicted accurately. Therefore, three different methods to predict flood-affected crops using remote sensing and ancillary data were developed, applied and validated. These methods are: (a) a hierarchical classification based on standard curves of spectral response using satellite images, (b) disaggregation of crop statistics using a Monte Carlo simulation and probabilities of crops to be cultivated on specific soils and (c) analysis of crop rotation with data mining Net Bayesian Classifiers (NBC) using soil data and crop data derived from a multi-year satellite image analysis. A flood loss estimation model for crops was applied and validated in flood detention areas (polders) at the Havel River (Untere Havelniederung) in Germany. The polders were used for temporary storage of flood water during the extreme flood event in August 2002. The flood loss to crops during the extreme flood event in August 2002 was estimated based on the results of the three crop prediction methods. The loss estimates were then compared with official loss data for validation purposes. The analysis of crop rotation with NBC obtained the best result, with 66% of crops correctly classified. The accuracy of the other methods reached 34% with identification using Normalized Difference Vegetation Index (NDVI) standard curves and 19% using disaggregation of crop statistics. The results were confirmed by evaluating the loss estimation procedure, in which the damage model using affected crops estimated by NBC showed the smallest overall deviation (1%) when compared to the official losses. Remote sensing offers various possibilities for the improvement of

  9. Development of a global, gridded, and time-series crop yield dataset for four major cereal and legume crops

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

    Global, gridded crop yield data are essential to study impacts of climate variability and change on food production, atmosphere-soil-managed ecosystem carbon and nitrogen cycle at a global scale. However so far available data are limited to country, time-series data from the Food and Agriculture Organization (FAO) and global, gridded data in the circa 2000 from Monfreda et al. (2008). This necessitates an effort to develop a global, gridded, and time-series dataset. To that end we developed a 25-yr long (1982-2006) dataset with 1.125 x 1.125 grid size for maize, soybean, rice, and wheat by merging county statistics, FAO country statistics, and yield proxy from satellite products. Yield statistics were collected from agricultural agencies in 19 countries: those correspond to 58-95% of the global production in the 2000. The proportion for rice and wheat (58%) is less than those for maize (72%) and soybean (95%). Also net primary production (NPP) for that period was estimated crop by crop from the normalized differential vegetation index bi-monthly time series at 8-km resolution from the Global Inventory Modeling and Mapping Studies group, using the method of Los et al. (2000). When estimating yield from NPP, for each crop, we used the following six procedures: (1) for a given grid where an intended crop grows (evaluated from harvested area from Monfreda et al. (2008)), accumulate NPP time series for the whole growth period from Sacks et al. (2010), considering the temporal distribution of planting/harvesting date through an ensemble calculation of 100 different planting/harvesting date; (2) average over accumulated NPPs that locate within a given country and compute the ratio of a grid NPP against a country mean (this represents the spatial variation of yield); (3) multiply this ratio and country FAO yield year by year; (4) calculate correction coefficient that is a ratio between estimated grid yield in the 2000 and that from Monfreda et al. (2000); (5) repeat (1

  10. 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.

  11. Investigate the Capabilities of Remotely Sensed Crop Indicators for Agricultural Drought Monitoring in Kansas

    NASA Astrophysics Data System (ADS)

    Zhang, J.; Becker-Reshef, I.; Justice, C. O.

    2013-12-01

    Although agricultural production has been rising in the past years, drought remains the primary cause of crop failure, leading to food price instability and threatening food security. The recent 'Global Food Crisis' in 2008, 2011 and 2012 has put drought and its impact on crop production at the forefront, highlighting the need for effective agricultural drought monitoring. Satellite observations have proven a practical, cost-effective and dynamic tool for drought monitoring. However, most satellite based methods are not specially developed for agriculture and their performances for agricultural drought monitoring still need further development. Wheat is the most widely grown crop in the world, and the recent droughts highlight the importance of drought monitoring in major wheat producing areas. As the largest wheat producing state in the US, Kansas plays an important role in both global and domestic wheat markets. Thus, the objective of this study is to investigate the capabilities of remotely sensed crop indicators for effective agricultural drought monitoring in Kansas wheat-grown regions using MODIS data and crop yield statistics. First, crop indicators such as NDVI, anomaly and cumulative metrics were calculated. Second, the varying impacts of agricultural drought at different stages were explored by examining the relationship between the derived indicators and yields. Also, the starting date of effective agricultural drought early detection and the key agricultural drought alert period were identified. Finally, the thresholds of these indicators for agricultural drought early warning were derived and the implications of these indicators for agricultural drought monitoring were discussed. The preliminary results indicate that drought shows significant impacts from the mid-growing-season (after Mid-April); NDVI anomaly shows effective drought early detection from Late-April, and Late-April to Early-June can be used as the key alert period for agricultural

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

    NASA Astrophysics Data System (ADS)

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

    2017-01-01

    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.

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

    PubMed Central

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

    2017-01-01

    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. PMID:28079051

  14. Industrial oilseeds bolster "hub" crop yields when used in rotation

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Lack of agroecosystem diversity across the U.S. agricultural landscape is linked to several environmental issues associated with air, water, and soil quality and biodiversity. Several new industrial oilseed crops with commercial potential, offer farmers new economic opportunities and a portfolio of ...

  15. Base-Case 1% Yield Increase (BC1), All Energy Crops scenario of the 2016 Billion Ton Report

    SciTech Connect

    Davis, Maggie R.; Hellwinkel, Chad; Eaton, Laurence; Langholtz, Matthew H.; Turhollow, Anthony; Brandt, Craig; Myers, Aaron

    2016-07-13

    Scientific reason for data generation: to serve as the base-case scenario for the BT16 volume 1 agricultural scenarios to compare these projections of potential biomass supplies against a reference case (agricultural baseline 10.11578/1337885). The simulation runs from 2015 through 2040; a starting year of 2014 is used but not reported. How each parameter was produced (methods), format, and relationship to other data in the data set: This exogenous price simulations (also referred to as “specified-price” simulations) introduces a farmgate price, and POLYSYS solves for biomass supplies that may be brought to market in response to these prices. In specified-price scenarios, a specified farmgate price is offered constantly in all counties over all years of the simulation. This simulation begins in 2015 with an offered farmgate price for primary crop residues only between 2015 and 2018 and long-term contracts for dedicated crops beginning in 2019. Expected mature energy crop yield grows at a compounding rate of 1% beginning in 2016. The yield growth assumptions are fixed after crops are planted such that yield gains do not apply to crops already planted, but new plantings do take advantage of the gains in expected yield growth. Instruments used: Policy Analysis System –POLYSYS (version POLYS2015_V10_alt_JAN22B), an agricultural policy modeling system of U.S. agriculture (crops and livestock), supplied by the University of Tennessee Institute of Agriculture, Agricultural Policy Analysis Center.

  16. Response of different crop growth and yield to enhanced UV-B radiation under field conditions

    NASA Astrophysics Data System (ADS)

    Zheng, Youfei; Gao, Wei; Slusser, James R.; Grant, Richard H.; Wang, Chuanhai

    2004-10-01

    Enhanced UV-B radiation due to stratospheric ozone depletion may have impacts on the productivity of agricultural crops. Which crop will be more sensitive to increased UV-B has received little attention. This paper presents a comparative study of the effects of supplemental UV-B on plant height, leaf area, biomass and yield among soybean, cotton, corn and wheat which were cultivated in fields in Nanjing, China. The experimental results showed that the four crops response to enhanced UV-B irradiation was shortened plant height, decreased leaf area and reduced biomass and yield of crops. Using the same criteria, the response of soybean and cotton to elevated UV-B is bigger than that of wheat and corn. RI (response index) is an integrated index which is the accumulation of relative change in plant height, leaf area, biomass and yield, reflecting general impact of increased UV-B on crops. The results suggested that the RI for the four crops was minus, demonstrating a negative impact of enhanced UV-B on the crops. According to the RI, the soybean and cotton belong to the sensitive plants category, wheat is a moderately sensitive plant and corn is a tolerant plant.

  17. Alternative scenarios of bioenergy crop production in an agricultural landscape and implications for bird communities.

    PubMed

    Blank, Peter J; Williams, Carol L; Sample, David W; Meehan, Timothy D; Turner, Monica G

    2016-01-01

    Increased demand and government mandates for bioenergy crops in the United States could require a large allocation of agricultural land to bioenergy feedstock production and substantially alter current landscape patterns. Incorporating bioenergy landscape design into land-use decision making could help maximize benefits and minimize trade-offs among alternative land uses. We developed spatially explicit landscape scenarios of increased bioenergy crop production in an 80-km radius agricultural landscape centered on a potential biomass-processing energy facility and evaluated the consequences of each scenario for bird communities. Our scenarios included conversion of existing annual row crops to perennial bioenergy grasslands and conversion of existing grasslands to annual bioenergy row crops. The scenarios explored combinations of four biomass crop types (three potential grassland crops along a gradient of plant diversity and one annual row crop [corn]), three land conversion percentages to bioenergy crops (10%, 20%, or 30% of row crops or grasslands), and three spatial configurations of biomass crop fields (random, clustered near similar field types, or centered on the processing plant), yielding 36 scenarios. For each scenario, we predicted the impact on four bird community metrics: species richness, total bird density, species of greatest conservation need (SGCN) density, and SGCN hotspots (SGCN birds/ha ≥ 2). Bird community metrics consistently increased with conversion of row crops to bioenergy grasslands and consistently decreased with conversion of grasslands to bioenergy row crops. Spatial arrangement of bioenergy fields had strong effects on the bird community and in some cases was more influential than the amount converted to bioenergy crops. Clustering grasslands had a stronger positive influence on the bird community than locating grasslands near the central plant or at random. Expansion of bioenergy grasslands onto marginal agricultural lands will

  18. Development of Crop Yield Estimation Method by Applying Seasonal Climate Prediction in Asia-Pacific Region

    NASA Astrophysics Data System (ADS)

    Shin, Y.; Lee, E.

    2015-12-01

    Under the influence of recent climate change, abnormal weather condition such as floods and droughts has issued frequently all over the world. The occurrence of abnormal weather in major crop production areas leads to soaring world grain prices because it influence the reduction of crop yield. Development of crop yield estimation method is important means to accommodate the global food crisis caused by abnormal weather. However, due to problems with the reliability of the seasonal climate prediction, application research on agricultural productivity has not been much progress yet. In this study, it is an object to develop long-term crop yield estimation method in major crop production countries worldwide using multi seasonal climate prediction data collected by APEC Climate Center. There are 6-month lead seasonal predictions produced by six state-of-the-art global coupled ocean-atmosphere models(MSC_CANCM3, MSC_CANCM4, NASA, NCEP, PNU, POAMA). First of all, we produce a customized climate data through temporal and spatial downscaling methods for use as a climatic input data to the global scale crop model. Next, we evaluate the uncertainty of climate prediction by applying multi seasonal climate prediction in the crop model. Because rice is the most important staple food crop in the Asia-Pacific region, we assess the reliability of the rice yields using seasonal climate prediction for main rice production countries. RMSE(Root Mean Squire Error) and TCC(Temporal Correlation Coefficient) analysis is performed in Asia-Pacific countries, major 14 rice production countries, to evaluate the reliability of the rice yield according to the climate prediction models. We compare the rice yield data obtained from FAOSTAT and estimated using the seasonal climate prediction data in Asia-Pacific countries. In addition, we show that the reliability of seasonal climate prediction according to the climate models in Asia-Pacific countries where rice cultivation is being carried out.

  19. 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.

  20. Food for Thought: Crop Yields in the Columbia River Basin in an Altered Future

    NASA Astrophysics Data System (ADS)

    Rajagopalan, K.; Chinnayakanahalli, K.; Nelson, R.; Stockle, C.; Kruger, C.; Brady, M.; Adam, J. C.

    2013-12-01

    Growth of global population and food consumption in the next several decades is expected to result in a food security challenge. Strategies to address this challenge, such as enhancing agricultural productivity and resiliency, need to be considered within the context of a full range of plausible consequences so as to identify investments that create win-win-win scenarios for the environment, economy, and society. Regional earth systems models can provide the necessary scale-appropriate framework to inform the decision making context for adaptation strategies, especially in the context of global change. In an altered future, changes to climate, technology and socioeconomics affect regional agriculture both directly and indirectly. These effects are not independent and an integrated process-based model may better capture unanticipated non-linear and non-monotonic responses and feedbacks over time . BioEarth is a research initiative designed to explore the coupling of multiple stand-alone earth systems models to generate usable information for agricultural and natural resource decision making at the regional scale at decadal time-steps. This project focuses on the U.S. Pacific Northwest (PNW) region and is a framework that integrates atmospheric, terrestrial, aquatic, and economic models. We apply component models of BioEarth to the Columbia River basin in the PNW to study the direct and indirect impacts of climate change on regional irrigated and dryland crop yields for a variety of annual and perennial crops. Results indicate that the net effect of climate change on crop yields is dependent on the crop type. There is a negative effect of temperature on yields for most crops. Dryland winter wheat is a notable exception. With warming, although the available growing season increases, faster thermal accumulation results in a shorter time to maturity. Precipitation changes in the region have a positive impact on dryland agriculture. Carbon dioxide (CO2) fertilization has

  1. Tentative critical levels of tropospheric ozone for agricultural crops in Japan

    NASA Astrophysics Data System (ADS)

    Yonekura, T.

    2010-12-01

    Ground level ozone concentrations have increased year by year in Japan. High ozone concentrations have been known to affect growth and yield of agricultural crops. In the US and Europe, much effort has been directed to establish regulatory policies such as secondary air quality standard and critical levels to protect vegetation against ozone. On the contrary, in Japan, there is a few data of agricultural crops sensitivity to ozone. Furthermore, there is no information about the ozone risk of agricultural crop loss by based on ozone index (e.g. AOT40, SUM06, W126)-crop response relationship, yet. The objects of our research are: (1) to screen sensitivity of ozone on 10 crops cultivated in urban area in Japan. (2) to establish critical levels of ozone for protecting agricultural crops based on ozone index-crop response relationship. The 10 Japanese agricultural crops such as Japanese rice, Hanegi (Welsh onion), Shungiku (Crown daisy), Saradana (Lettus), Hatsukadaikon (Radish), Kokabu (Small Turnip), Santosai (Chinese cabbage), Tasai (Spinach mustard), Komatsuna (Japanese mustard spinach) and Chingensai (Bok Choy), were fumigated to three levels of ozone (clean air (< 5 ppbv), ambient level of ozone, 1.5 times ambient ozone) in open-top chambers during 30 to 120 days. Those experiments were repeated five times during two growing season. Throughout the experimental period, the growth or yield were measured, and the relationship between growth (or yield) and ozone index was examined. As a result, the influences of ozone on growth or yield were different among 10 crops. Relatively good correlations of coefficients of determination (r2) for linear regressions to growth or yield were obtained with “8h means” and “AOT40” rather than “SUM00”, “SUM06” and “W126”. Critical level for 10 crops in terms of an AOT40 were 1.1 to 2.1 ppm h per month. The ozone sensitive crop in our study was sound to be 1.0 ppm h per month in AOT40.

  2. Effect of Climate-Induced Change in Crop Yields on Emigration: The Case of Mexico

    NASA Astrophysics Data System (ADS)

    Oppenheimer, M.; Krueger, A. B.; Feng, S.

    2009-05-01

    Researchers have suggested several channels through which future global warming could trigger mass migration across country borders. This paper examines one of them by focusing on the effect of climate- induced crop failures on out-migration. Using data from Mexico, we identify and estimate elasticity of emigration with respect to changes in crop yield, which sheds light on the possible magnitudes of migrant flows for other areas of the world under different climate change scenarios. We choose Mexico as the study object as it is by far the largest migrant-sending country, with an estimated number of emigrants living in the United States to be well over 10 million. In addition, over 20% of Mexico population directly relies on the agricultural sector, which is heavily dependent on climate. For example, the prolonged drought from 1996 to 1998 in northern Mexico resulted in mass crop failures and the death of livestock. Historically, farmers have been using emigration as an adaptation strategy to cope with crop yield reductions. We first examine the relationship between corn yields and climate variables for the period of 1980-2000, using state-level data. We find significant positive effects of annual precipitation and annual average temperature, but a negative effect of summer temperature on corn yields. The effects of both annual and summer temperatures are also nonlinear. Our analyses of other crops such as wheat yield very similar results. Using Mexico Census micro data, we calculate the number of emigrants from each state for the periods of 1990-1995 and 1995-2000. We then regress changes in the number of emigrants on changes in crop yields, instrumented by changes in temperatures and precipitation. Our preferred specification gives an elasticity of -4, which suggests that a 25% reduction in crop yields would double the number of emigrants. The null hypothesis of no effect is rejected at the 5% significance level.

  3. Remote sensing of agricultural crops and soils

    NASA Technical Reports Server (NTRS)

    Bauer, M. E. (Principal Investigator)

    1983-01-01

    Research in the correlative and noncorrelative approaches to image registration and the spectral estimation of corn canopy phytomass and water content is reported. Scene radiation research results discussed include: corn and soybean LANDSAT MSS classification performance as a function of scene characteristics; estimating crop development stages from MSS data; the interception of photosynthetically active radiation in corn and soybean canopies; costs of measuring leaf area index of corn; LANDSAT spectral inputs to crop models including the use of the greenness index to assess crop stress and the evaluation of MSS data for estimating corn and soybean development stages; field research experiment design data acquisition and preprocessing; and Sun-view angles studies of corn and soybean canopies in support of vegetation canopy reflection modeling.

  4. Germany wide seasonal flood risk analysis for agricultural crops

    NASA Astrophysics Data System (ADS)

    Klaus, Stefan; Kreibich, Heidi; Kuhlmann, Bernd; Merz, Bruno; Schröter, Kai

    2016-04-01

    In recent years, large-scale flood risk analysis and mapping has gained attention. Regional to national risk assessments are needed, for example, for national risk policy developments, for large-scale disaster management planning and in the (re-)insurance industry. Despite increasing requests for comprehensive risk assessments some sectors have not received much scientific attention, one of these is the agricultural sector. In contrast to other sectors, agricultural crop losses depend strongly on the season. Also flood probability shows seasonal variation. Thus, the temporal superposition of high flood susceptibility of crops and high flood probability plays an important role for agricultural flood risk. To investigate this interrelation and provide a large-scale overview of agricultural flood risk in Germany, an agricultural crop loss model is used for crop susceptibility analyses and Germany wide seasonal flood-frequency analyses are undertaken to derive seasonal flood patterns. As a result, a Germany wide map of agricultural flood risk is shown as well as the crop type most at risk in a specific region. The risk maps may provide guidance for federal state-wide coordinated designation of retention areas.

  5. 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.

  6. Examining the roles that changing harvested areas, closing yield-gaps, and increasing yield ceilings have had on crop production

    NASA Astrophysics Data System (ADS)

    Johnston, M.; Ray, D. K.; Mueller, N. D.; Foley, J. A.

    2011-12-01

    -weighted result of area and yield contributions for each country, at each time-step. As part of our research we will generate historic figures and tabular data for every country-crop combination. Phase 3: In the final phase of our research, we attempt to demonstrate how different yield performers (for example, those growing crops at the yield floor vs. the yield ceiling) have utilized different area/yield strategies to increase agricultural production. To group individual pixels into performance quintiles, we utilize binning strategies from previous spatial yield-gap assessments. The results from this step will illustrate how the yield ceiling has improved over time vis-à-vis improvements in the yield floor. As we look forward to a more sustainable and productive agricultural future, we hope the results of this global analysis of our agricultural past can be utilized to identify both optimal and adverse strategies for agricultural growth.

  7. 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

  8. 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.

  9. Impacts of biofuel cultivation on mortality and crop yields

    NASA Astrophysics Data System (ADS)

    Ashworth, K.; Wild, O.; Hewitt, C. N.

    2013-05-01

    Ground-level ozone is a priority air pollutant, causing ~ 22,000 excess deaths per year in Europe, significant reductions in crop yields and loss of biodiversity. It is produced in the troposphere through photochemical reactions involving oxides of nitrogen (NOx) and volatile organic compounds (VOCs). The biosphere is the main source of VOCs, with an estimated 1,150TgCyr-1 (~ 90% of total VOC emissions) released from vegetation globally. Isoprene (2-methyl-1,3-butadiene) is the most significant biogenic VOC in terms of mass (around 500TgCyr-1) and chemical reactivity and plays an important role in the mediation of ground-level ozone concentrations. Concerns about climate change and energy security are driving an aggressive expansion of bioenergy crop production and many of these plant species emit more isoprene than the traditional crops they are replacing. Here we quantify the increases in isoprene emission rates caused by cultivation of 72Mha of biofuel crops in Europe. We then estimate the resultant changes in ground-level ozone concentrations and the impacts on human mortality and crop yields that these could cause. Our study highlights the need to consider more than simple carbon budgets when considering the cultivation of biofuel feedstock crops for greenhouse-gas mitigation.

  10. Agricultural land application of pulp and paper mill sludges in the Donnacona area, Quebec: Chemical evaluation and crop response

    SciTech Connect

    Veillette, A.X.; Tanguay, M.G.

    1997-12-31

    Primary paper mill sludges from a thermomechanical pulp (TMP) mill were land applied at the rate of 20 metric ton per hectare (t/ha) for agricultural purposes in the Donnacona area, Quebec, in May 1994 and May 1995. Eleven agricultural sites featuring various crops were tested over two seasons to measure the impact of TMP primary paper mill sludges on soil, plant tissue and crop yield. Cereal and potato crops showed a significant increase in yield. TMP Primary sludges were also applied at the rate of 225 t/ha for land reclamation purposes of one site at the end of 1994. Soils were tested every second month. Chemical crop analyses were also performed. The first year crop response was satisfactory. Combined (primary and secondary) TMP sludges were added at the rate of 200 t/ha in the beginning of 1996. Soil, vadose zone water and crop analysis are being investigated. Impressive crop responses were obtained in the 1996 season.

  11. Topography Mediates the Influence of Cover Crops on Soil Nitrate Levels in Row Crop Agricultural Systems

    PubMed Central

    Ladoni, Moslem; Kravchenko, Alexandra N.; Robertson, G. Phillip

    2015-01-01

    Supplying adequate amounts of soil N for plant growth during the growing season and across large agricultural fields is a challenge for conservational agricultural systems with cover crops. Knowledge about cover crop effects on N comes mostly from small, flat research plots and performance of cover crops across topographically diverse agricultural land is poorly understood. Our objective was to assess effects of both leguminous (red clover) and non-leguminous (winter rye) cover crops on potentially mineralizable N (PMN) and NO3--N levels across a topographically diverse landscape. We studied conventional, low-input, and organic managements in corn-soybean-wheat rotation. The rotations of low-input and organic managements included rye and red clover cover crops. The managements were implemented in twenty large undulating fields in Southwest Michigan starting from 2006. The data collection and analysis were conducted during three growing seasons of 2011, 2012 and 2013. Observational micro-plots with and without cover crops were laid within each field on three contrasting topographical positions of depression, slope and summit. Soil samples were collected 4–5 times during each growing season and analyzed for NO3--N and PMN. The results showed that all three managements were similar in their temporal and spatial distributions of NO3—N. Red clover cover crop increased NO3--N by 35% on depression, 20% on slope and 32% on summit positions. Rye cover crop had a significant 15% negative effect on NO3--N in topographical depressions but not in slope and summit positions. The magnitude of the cover crop effects on soil mineral nitrogen across topographically diverse fields was associated with the amount of cover crop growth and residue production. The results emphasize the potential environmental and economic benefits that can be generated by implementing site-specific topography-driven cover crop management in row-crop agricultural systems. PMID:26600462

  12. Topography Mediates the Influence of Cover Crops on Soil Nitrate Levels in Row Crop Agricultural Systems.

    PubMed

    Ladoni, Moslem; Kravchenko, Alexandra N; Robertson, G Phillip

    2015-01-01

    Supplying adequate amounts of soil N for plant growth during the growing season and across large agricultural fields is a challenge for conservational agricultural systems with cover crops. Knowledge about cover crop effects on N comes mostly from small, flat research plots and performance of cover crops across topographically diverse agricultural land is poorly understood. Our objective was to assess effects of both leguminous (red clover) and non-leguminous (winter rye) cover crops on potentially mineralizable N (PMN) and [Formula: see text] levels across a topographically diverse landscape. We studied conventional, low-input, and organic managements in corn-soybean-wheat rotation. The rotations of low-input and organic managements included rye and red clover cover crops. The managements were implemented in twenty large undulating fields in Southwest Michigan starting from 2006. The data collection and analysis were conducted during three growing seasons of 2011, 2012 and 2013. Observational micro-plots with and without cover crops were laid within each field on three contrasting topographical positions of depression, slope and summit. Soil samples were collected 4-5 times during each growing season and analyzed for [Formula: see text] and PMN. The results showed that all three managements were similar in their temporal and spatial distributions of NO3-N. Red clover cover crop increased [Formula: see text] by 35% on depression, 20% on slope and 32% on summit positions. Rye cover crop had a significant 15% negative effect on [Formula: see text] in topographical depressions but not in slope and summit positions. The magnitude of the cover crop effects on soil mineral nitrogen across topographically diverse fields was associated with the amount of cover crop growth and residue production. The results emphasize the potential environmental and economic benefits that can be generated by implementing site-specific topography-driven cover crop management in row-crop

  13. From the ground up: The role of climate versus management on global crop yield patterns

    NASA Astrophysics Data System (ADS)

    Licker, R.; Johnston, M.; Foley, J. A.; Ramankutty, N.

    2008-12-01

    Agricultural lands are one of the most expansive land cover types on Earth, extending across approximately 12 percent of the planet's land surface. The management of these lands has changed dramatically since the Green Revolution of the 1960s. Nitrogen fertilizer inputs are almost 7 times greater, and irrigated lands have nearly doubled. Yet, the number of undernourished people is still increasing, and may continue to as the world's population is expected to grow by 2.5 billion people over the next three decades. In addition, there is a shift toward diets heavy in grain-fed meats taking place, as well as an increase in the demand of grains for fuel. While an altered distribution of crops may help remedy some of our food shortages, humanity will need to produce more if it is to meet its demands for crops. Obtaining more crops could entail both an expansion of agricultural lands as well as a change in the way many lands are currently managed - scenarios that would have implications for ecosystem goods and services at large given agriculture's already prominent place on the planet's landscape. Here, we explore society's ability to increase yields on existing croplands by way of altered management. We begin by quantifying the current influence that management practices such as chemical fertilizer use and irrigation have on global crop yield patterns relative to biophysical factors such as climate. In particular, we test the traditional assumption that more intensively managed lands have higher yields. We utilize new global, gridded maps of cropland cover and yields, as well as new maps showing climatically determined crop yield potentials. With this, we hope to contribute to a discussion of how we might, as a civilization, continue to shape our planet's land cover in pursuit of food, feed, and fuel.

  14. Temporal changes in climatic variables and their impact on crop yields in southwestern China

    NASA Astrophysics Data System (ADS)

    Liu, Hong-Bin; Gou, Yu; Wang, Hong-Ye; Li, Hong-Mei; Wu, Wei

    2014-08-01

    Knowledge of variability in climatic variables changes and its impact on crop yields is important for farmers and policy makers, especially in southwestern China where rainfed agriculture is dominant. In the current study, six climatic parameters (mean temperature, rainfall, relative humidity, sunshine hours, temperature difference, and rainy days) and aggregated yields of three main crops (rice: Oryza sativa L., oilseed rape: Brassica napus L., and tobacco: Nicotiana tabacum L.) during 1985-2010 were collected and analyzed for Chongqing—a large agricultural municipality of China. Climatic variables changes were detected by Mann-Kendall test. Increased mean temperature and temperature difference and decreased relative humidity were found in annual and oilseed rape growth time series ( P < 0.05). Increased sunshine hours were observed during the oilseed rape growth period ( P < 0.05). Rainy days decreased slightly in annual and oilseed rape growth time series ( P < 0.10). Correlation analysis showed that yields of all three crops could benefit from changes in climatic variables in this region. Yield of rice increased with rainfall ( P < 0.10). Yield of oilseed rape increased with mean temperature and temperature difference but decreased with relative humidity ( P < 0.01). Tobacco yield increased with mean temperature ( P < 0.05). Path analysis provided additional information about the importance and contribution paths of climatic variables to crop yields. Temperature difference and sunshine hours had higher direct and indirect effects via other climatic variables on yields of rice and tobacco. Mean temperature, relative humidity, rainy days, and temperature difference had higher direct and indirect effects via others on yield of oilseed rape.

  15. Temporal changes in climatic variables and their impact on crop yields in southwestern China.

    PubMed

    Liu, Hong-Bin; Gou, Yu; Wang, Hong-Ye; Li, Hong-Mei; Wu, Wei

    2014-08-01

    Knowledge of variability in climatic variables changes and its impact on crop yields is important for farmers and policy makers, especially in southwestern China where rainfed agriculture is dominant. In the current study, six climatic parameters (mean temperature, rainfall, relative humidity, sunshine hours, temperature difference, and rainy days) and aggregated yields of three main crops (rice: Oryza sativa L., oilseed rape: Brassica napus L., and tobacco: Nicotiana tabacum L.) during 1985-2010 were collected and analyzed for Chongqing-a large agricultural municipality of China. Climatic variables changes were detected by Mann-Kendall test. Increased mean temperature and temperature difference and decreased relative humidity were found in annual and oilseed rape growth time series (P<0.05). Increased sunshine hours were observed during the oilseed rape growth period (P<0.05). Rainy days decreased slightly in annual and oilseed rape growth time series (P<0.10). Correlation analysis showed that yields of all three crops could benefit from changes in climatic variables in this region. Yield of rice increased with rainfall (P<0.10). Yield of oilseed rape increased with mean temperature and temperature difference but decreased with relative humidity (P<0.01). Tobacco yield increased with mean temperature (P<0.05). Path analysis provided additional information about the importance and contribution paths of climatic variables to crop yields. Temperature difference and sunshine hours had higher direct and indirect effects via other climatic variables on yields of rice and tobacco. Mean temperature, relative humidity, rainy days, and temperature difference had higher direct and indirect effects via others on yield of oilseed rape.

  16. Wild chimpanzees show group differences in selection of agricultural crops

    PubMed Central

    McLennan, Matthew R.; Hockings, Kimberley J.

    2014-01-01

    The ability of wild animals to respond flexibly to anthropogenic environmental changes, including agriculture, is critical to survival in human-impacted habitats. Understanding use of human foods by wildlife can shed light on the acquisition of novel feeding habits and how animals respond to human-driven land-use changes. Little attention has focused on within-species variation in use of human foods or its causes. We examined crop-feeding in two groups of wild chimpanzees – a specialist frugivore – with differing histories of exposure to agriculture. Both groups exploited a variety of crops, with more accessible crops consumed most frequently. However, crop selection by chimpanzees with long-term exposure to agriculture was more omnivorous (i.e., less fruit-biased) compared to those with more recent exposure, which ignored most non-fruit crops. Our results suggest chimpanzees show increased foraging adaptations to cultivated landscapes over time; however, local feeding traditions may also contribute to group differences in crop-feeding in this species. Understanding the dynamic responses of wildlife to agriculture can help predict current and future adaptability of species to fast-changing anthropogenic landscapes. PMID:25090940

  17. 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

  18. 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

  19. Proximity to crops and residential to agricultural herbicides in Iowa

    USGS Publications Warehouse

    Ward, M.H.; Lubin, J.; Giglierano, J.; Colt, J.S.; Wolter, C.; Bekiroglu, N.; Camann, D.; Hartge, P.; Nuckols, J.R.

    2006-01-01

    Rural residents can be exposed to agricultural pesticides through the proximity of their homes to crop fields. Previously, we developed a method to create historical crop maps using a geographic information system. The aim of the present study was to determine whether crop maps are useful for predicting levels of crop herbicides in carpet dust samples from residences. From homes of participants in a case-control study of non-Hodgkin lymphoma in Iowa (1998-2000), we collected vacuum cleaner dust and measured 14 herbicides with high use on corn and soybeans in Iowa. Of 112 homes, 58% of residences had crops within 500 m of their home, an intermediate distance for primary drift from aerial and ground applications. Detection rates for herbicides ranged from 0% for metribuzin and cyanazine to 95% for 2,4-dichlorophenoxyacetic acid. Six herbicides used almost exclusively in agriculture were detected in 28% of homes. Detections and concentrations were highest in homes with an active farmer. Increasing acreage of corn and soybean fields within 750 m of homes was associated with significantly elevated odds of detecting agricultural herbicides compared with homes with no crops within 750 m (adjusted odds ratio per 10 acres = 1.06; 95% confidence interval, 1.02-1.11). Herbicide concentrations also increased significantly with increasing acreage within 750 m. We evaluated the distance of crop fields from the home at < 100, 101-250, 251-500, and 501-750 m. Including the crop buffer distance parameters in the model did not significantly improve the fit compared with a model with total acres within 750 m. Our results indicate that crop maps may be a useful method for estimating levels of herbicides in homes from nearby crop fields.

  20. Using the CLM Crop Model to assess the impacts of changes in Climate, Atmospheric CO2, Irrigation, Fertilizer and Geographic Distribution on Historical and Future Crop Yields

    NASA Astrophysics Data System (ADS)

    Lawrence, P.

    2015-12-01

    Since the start of the green revolution global crop yields have increased linearly for most major cereal crops, so that present day global values are around twice those of the 1960s. The increase in crop yields have allowed for large increases in global agricultural production without correspondingly large increases in cropping area. Future projections under the Shared Socio-economic Pathways (SSP) framework and other assessments result in increases of global crop production of greater than 100% by the year 2050. In order to meet this increased agricultural demand within the available arable land, future production gains need to be understood in terms of the yield changes due to changes in climate, atmospheric CO2, and adaptive management such as irrigation and fertilizer application. In addition to the changes in crop yield, future agricultural demand will need to be met through increasing cropping areas into what are currently marginal lands at the cost of existing forests and other natural ecosystems. In this study we assess the utility of the crop model within the Community Land Model (CLM Crop) to provide both historical and future guidance on changes in crop yields under a range of global idealized crop modeling experiments. The idealized experiments follow the experimental design of the AgMIP Global Gridded Crop Model Intercomparison (GGCMI) in which CLM Crop is a participating model. The idealized experiments consist of global crop simulations for Cotton, Maize, Rice, Soy, Sugarcane, and Wheat under various climate, atmospheric CO2 levels, irrigation prescription, and nitrogen fertilizer application. The time periods simulated for the experiments are for the Historical period (1901 - 2005), and for the two Representative Concentration Pathways of RCP 4.5 and RCP 8.5 (2006 - 2100). Each crop is simulated on all land grid cells globally for each time period with atmospheric forcing that is a combination of: 1. transient climate and CO2; 2. transient climate

  1. Characterization of yield reduction in Ethiopia using a GIS-based crop water balance model

    USGS Publications Warehouse

    Senay, G.B.; Verdin, J.

    2003-01-01

    In many parts of sub-Saharan Africa, subsistence agriculture is characterized by significant fluctuations in yield and production due to variations in moisture availability to staple crops. Widespread drought can lead to crop failures, with associated deterioration in food security. Ground data collection networks are sparse, so methods using geospatial rainfall estimates derived from satellite and gauge observations, where available, have been developed to calculate seasonal crop water balances. Using conventional crop production data for 4 years in Ethiopia (1996-1999), it was found that water-limited and water-unlimited growing regions can be distinguished. Furthermore, maize growing conditions are also indicative of conditions for sorghum. However, another major staple, teff, was found to behave sufficiently differently from maize to warrant studies of its own.

  2. Application of a CROPWAT Model to Analyze Crop Yields in Nicaragua

    NASA Astrophysics Data System (ADS)

    Doria, R.; Byrne, J. M.

    2013-12-01

    ABSTRACT Changes in climate are likely to influence crop yields due to varying evapotranspiration and precipitation over agricultural regions. In Nicaragua, agriculture is extensive, with new areas of land brought into production as the population increases. Nicaraguan staple food items (maize and beans) are produced mostly by small scale farmers with less than 10 hectares, but they are critical for income generation and food security for rural communities. Given that the majority of these farmers are dependent on rain for crop irrigation, and that maize and beans are sensitive to variations in temperature and rainfall patterns, the present study was undertaken to assess the impact of climate change on these crop yields. Climate data were generated per municipio representing the three major climatic zones of the country: the wet Pacific lowland, the cooler Central highland, and the Caribbean lowland. Historical normal climate data from 1970-2000 (baseline period) were used as input to CROPWAT model to analyze the potential and actual evapotranspiration (ETo and ETa, respectively) that affects crop yields. Further, generated local climatic data of future years (2030-2099) under various scenarios were inputted to the CROPWAT to determine changes in ETo and ETa from the baseline period. Spatial variability maps of both ETo and ETa as well as crop yields were created. Results indicated significant variation in seasonal rainfall depth during the baseline period and predicted decreasing trend in the future years that eventually affects yields. These maps enable us to generate appropriate adaptation measures and best management practices for small scale farmers under future climate change scenarios. KEY WORDS: Climate change, evapotranspiration, CROPWAT, yield, Nicaragua

  3. More uneven distributions overturn benefits of higher precipitation for crop yields

    NASA Astrophysics Data System (ADS)

    Fishman, Ram

    2016-02-01

    Climate change is expected to lead to more uneven temporal distributions of precipitation, but the impacts on human systems are little studied. Most existing, statistically based agricultural climate change impact projections only account for changes in total precipitation, ignoring its intra-seasonal distribution, and conclude that in places that will become wetter, agriculture will benefit. Here, an analysis of daily rainfall and crop yield data from across India (1970-2003), where a fifth of global cereal supply is produced, shows that decreases in the number of rainy days have robust negative impacts that are large enough to overturn the benefits of increased total precipitation for the yields of most major crops. As an illustration, the net, mid 21st century projection for rice production shifts from +2% to -11% when changes in distribution are also accounted for, independently of additional negative impacts of rising temperatures.

  4. Development and testing of crop monitoring methods to improve global agricultural monitoring in support of GEOGLAM

    NASA Astrophysics Data System (ADS)

    Gilliams, S. J. B.; Bydekerke, L.

    2014-12-01

    The SIGMA project (Stimulating Innovation for Global Monitoring of Agriculture) is funded through the EC FPY7 Research programme with the particular aim to contribute to the GEOGLAM Research Agenda. It is a partnership of globally distributed expert organizations, focusses on developing innovative techniques and datasets in support of agricultural monitoring and its impact on the environment in support of GEOGLAM. SIGMA has 3 generic objectives which are: (i) develop and test methods to characterize cropland and assess its changes at various scales; (ii) develop and test methods to assess changes in agricultural production levels; and; (iii) study environmental impacts of agriculture. Firstly, multi-scale remote sensing data sets, in combination with field and other ancillary data, are used to generate an improved (global) agro-ecological zoning map and crop mask. Secondly, a combination of agro-meteorological models, satellite-based information and long-term time series are be explored to better assess crop yield gaps and shifts in cultivation. The third research topic entails the development of best practices for assessing the impact of crop land and cropping system change on the environment. In support of the GEO JECAM (Joint Experiment for Crop Assessment and Monitoring) initiative, case studies in Ukraine, Russia, Europe, Africa, Latin America and China are carried out in order to explore possible methodological synergies and particularities according to different cropping systems. This presentation will report on the progress made with respect to the three topics above.

  5. Technical Guidelines and References: Crops Training Component. From: Agricultural Development Workers Training Manual. Volume III: Crops.

    ERIC Educational Resources Information Center

    Peace Corps, Washington, DC. Information Collection and Exchange Div.

    This reference manual for training Peace Corps agricultural development workers deals with crops. The document begins with common units of area, length, weight, volume, and conversions between them. A practice problem is worked and other conversion problems are given. The second section is intended to show agricultural field workers how to survey…

  6. Bats and birds increase crop yield in tropical agroforestry landscapes.

    PubMed

    Maas, Bea; Clough, Yann; Tscharntke, Teja

    2013-12-01

    Human welfare is significantly linked to ecosystem services such as the suppression of pest insects by birds and bats. However, effects of biocontrol services on tropical cash crop yield are still largely unknown. For the first time, we manipulated the access of birds and bats in an exclosure experiment (day, night and full exclosures compared to open controls in Indonesian cacao agroforestry) and quantified the arthropod communities, the fruit development and the final yield over a long time period (15 months). We found that bat and bird exclusion increased insect herbivore abundance, despite the concurrent release of mesopredators such as ants and spiders, and negatively affected fruit development, with final crop yield decreasing by 31% across local (shade cover) and landscape (distance to primary forest) gradients. Our results highlight the tremendous economic impact of common insectivorous birds and bats, which need to become an essential part of sustainable landscape management.

  7. Correlation between biogas yield and chemical composition of energy crops.

    PubMed

    Dandikas, V; Heuwinkel, H; Lichti, F; Drewes, J E; Koch, K

    2014-12-01

    The scope of this study was to investigate the influence of the chemical composition of energy crops on biogas and methane yield. In total, 41 different plants were analyzed in batch test and their chemical composition was determined. For acid detergent lignin (ADL) content below 10% of total solids, a significant negative correlation for biogas and methane yields (r≈-0.90) was observed. Based on a simple regression analysis, more than 80% of the sample variation can be explained through ADL. Based on a principal component analysis and multiple regression analysis, ADL and hemicellulose are suggested as suitable model variables for biogas yield potential predictions across plant species.

  8. Evaluation of crop yield simulations in the SE USA using the NARCCAP regional climate models

    NASA Astrophysics Data System (ADS)

    Cocke, S.; Shin, D. W.; Baigorria, G. A.; Romero, C. C.

    2015-12-01

    We integrate climate projections, crop modeling systems and economic assessment to develop a tool for studying and assessing agricultural production in the southeast United States. This integrated framework will enable us to assess the potential impact of future climate variability and trend on the production of economically-valuable crops in the southeast United States where weather/climate has major effects on agricultural yields. Optimally weighted multi-model ensemble (MME) approaches are used in order to improve the projection of future regional crop yield. This research will enhance the current knowledge of linking climate and process models, with an economic evaluation, as a demonstration of an approach that can be applied for other settings, problems, etc. The current maize/peanut/cotton yields and the future yield projections over the southeast US were obtained using (a) observed COOP data (1971-2010), (b) a reanalysis (NCEP R2), and (c) the NARCCAP (CMIP3) ensemble data for irrigated and non-irrigated conditions with 7 to 8 different planting dates (potential adaptation options). We found that the future yield amounts over the southeast US are generally decreased in the NARCCAP runs.

  9. Control of Vertebrate Pests of Agricultural Crops.

    ERIC Educational Resources Information Center

    Wingard, Robert G.; Studholme, Clinton R.

    This agriculture extension service publication of Pennsylvania State University discusses the damage from and control of vertebrate pests. Specific discussions describe the habits, habitat, and various control measures for blackbirds and crows, deer, meadow and pine mice, European starlings, and woodchucks. Where confusion with non-harmful species…

  10. An integrated model for assessing both crop productivity and agricultural water resources at a large scale

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

    Agricultural production utilizes regional resources (e.g. river water and ground water) as well as local resources (e.g. temperature, rainfall, solar energy). Future climate changes and increasing demand due to population increases and economic developments would intensively affect the availability of water resources for agricultural production. While many studies assessed the impacts of climate change on agriculture, there are few studies that dynamically account for changes in water resources and crop production. This study proposes an integrated model for assessing both crop productivity and agricultural water resources at a large scale. Also, the irrigation management to subseasonal variability in weather and crop response varies for each region and each crop. To deal with such variations, we used the Markov Chain Monte Carlo technique to quantify regional-specific parameters associated with crop growth and irrigation water estimations. We coupled a large-scale crop model (Sakurai et al. 2012), with a global water resources model, H08 (Hanasaki et al. 2008). The integrated model was consisting of five sub-models for the following processes: land surface, crop growth, river routing, reservoir operation, and anthropogenic water withdrawal. The land surface sub-model was based on a watershed hydrology model, SWAT (Neitsch et al. 2009). Surface and subsurface runoffs simulated by the land surface sub-model were input to the river routing sub-model of the H08 model. A part of regional water resources available for agriculture, simulated by the H08 model, was input as irrigation water to the land surface sub-model. The timing and amount of irrigation water was simulated at a daily step. The integrated model reproduced the observed streamflow in an individual watershed. Additionally, the model accurately reproduced the trends and interannual variations of crop yields. To demonstrate the usefulness of the integrated model, we compared two types of impact assessment of

  11. Boosting Crop Yields with Plant Steroids[W

    PubMed Central

    Vriet, Cécile; Russinova, Eugenia; Reuzeau, Christophe

    2012-01-01

    Plant sterols and steroid hormones, the brassinosteroids (BRs), are compounds that exert a wide range of biological activities. They are essential for plant growth, reproduction, and responses to various abiotic and biotic stresses. Given the importance of sterols and BRs in these processes, engineering their biosynthetic and signaling pathways offers exciting potentials for enhancing crop yield. In this review, we focus on how alterations in components of sterol and BR metabolism and signaling or application of exogenous steroids and steroid inhibitors affect traits of agronomic importance. We also discuss areas for future research and identify the fine-tuning modulation of endogenous BR content as a promising strategy for crop improvement. PMID:22438020

  12. Crop yield forecast for France based on the CNDVI technique

    NASA Astrophysics Data System (ADS)

    Vignolles, Cecile; Genovese, Giampiero; Negre, Thierry

    2002-01-01

    The objective of the research presented here is to obtain crop yield forecasts basing on the information of NOAA- AVHRR/NDVI and CORINE land cover data. The methodology described in Genovese et al. (2001) consists of extracting yield indicators from CNDVI (CORINE-NDVI) time series at a regional scale. In Genovese et al. (2001), a preliminary study on Spain for a four year span (1995-1998) has shown that indicators extracted from the CNDVI profiles can be more closely related to crop yield performances than indicators based on simple NDVI profiles. To prove the validity of this approach, a more complete experiment was realised on France for the same period. Linear regressions were calculated using regional CNDVI-based indicators versus regional wheat yield data (EUROSTAT NEW CRONOS database). A French national wheat yield forecast was then derived by aggregation of regional results. The goodness of the results confirms the advantages of such approach. The combination of a CNDVI-based indicator with the linear trend observed on yields between 1975 and 1997 led to very good regression criteria (coefficient of determination higher than 86%) and allowed a satisfying prediction of wheat yields.

  13. Designing bioenergy crop buffers to mitigate nitrous oxide emissions and water quality impacts from agriculture

    NASA Astrophysics Data System (ADS)

    Gopalakrishnan, G.; Negri, C. M.

    2010-12-01

    There is a strong societal need to evaluate and understand the environmental aspects of bioenergy production, especially due to the significant increases in production mandated by many countries, including the United States. Bioenergy is a land-based renewable resource and increases in production are likely to result in large-scale conversion of land from current uses to bioenergy crop production; potentially causing increases in the prices of food, land and agricultural commodities as well as disruption of ecosystems. Current research on the environmental sustainability of bioenergy has largely focused on the potential of bioenergy crops to sequester carbon and mitigate greenhouse gas (GHG) emissions and possible impacts on water quality and quantity. A key assumption in these studies is that bioenergy crops will be grown in a manner similar to current agricultural crops such as corn and hence would affect the environment similarly. This study presents a systems approach where the agricultural, energy and environmental sectors are considered as components of a single system, and bioenergy crops are used to design multi-functional agricultural landscapes that meet society’s requirements for food, energy and environmental protection. We evaluate the production of bioenergy crop buffers on marginal land and using degraded water and discuss the potential for growing cellulosic bioenergy crops such as miscanthus and switchgrass in optimized systems such that (1) marginal land is brought into productive use; (2) impaired water is used to boost yields (3); clean freshwater is left for other uses that require higher water quality; and (4) feedstock diversification is achieved that helps ecological sustainability, biodiversity, and economic opportunities for farmers. The process-based biogeochemical model DNDC was used to simulate crop yield, nitrous oxide production and nitrate concentrations in groundwater when bioenergy crops were grown in buffer strips adjacent to

  14. Impacts of future climate change on potential yields of major crops in China

    NASA Astrophysics Data System (ADS)

    Yin, Y.; Tang, Q.; Liu, X.

    2014-05-01

    Climate change may affect crop development and yield, and consequently cast a shadow of doubt over China's food self-sufficiency efforts. In this study we used the model projections of a couple of global gridded crop models (GGCMs) to assess the effects of future climate change on the potential yields of the major crops (i.e. wheat, rice, maize and soybean) over China. The GGCMs were forced with the bias-corrected climate data from 5 global climate models (GCMs) under the Representative Concentration Pathways (RCP) 8.5 which were made available by the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP). The results show that the potential yields of rice may increase over a large portion of China. Climate change may benefit food productions over the high-altitude and cold regions where are outside current main agricultural area. However, the potential yield of maize, soybean and wheat may decrease in a large portion of the current main crop planting areas such as North China Plain. Development of new agronomic management strategy may be useful for coping with climate change in the areas with high risk of yield reduction.

  15. Impact of historical droughts on crop yields in Sub-Saharan Africa

    NASA Astrophysics Data System (ADS)

    Kamali, Bahareh; Yang, Hong; abbaspour, karim

    2014-05-01

    Sub-Saharan Africa (SSA) has been faced with frequent drought events in the past. Future climate change scenarios have suggested increasing drought frequency and severity. The devastating impacts of drought on rainfed farming and food production pose many challenges in SSA countries both today and in the future. Therefore, a comprehensive investigation of droughts and assessment of their impacts on crop yield and production are critically important to support SSA to formulate effective adaptive measures to improve food security. The current study assesses the historical meteorological and agricultural droughts and quantifies their impacts on two major crop yields namely maize and cassava in SSA. The GIS-based crop model (GEPIC) is used for the simulation of the historical yields. Drought severities are categorized into levels of mild, moderate and severe. The impacts of each category on maize and cassava yields are examined and drought hotspots are highlighted. The knowledge learnt from the historical data helps enhance the projection of the impacts of future weather conditions on crop yield in the region and facilitate the societal preparedness to drought impact.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  17. Effect of nutrient management planning on crop yield, nitrate leaching and sediment loading in Thomas Brook watershed.

    PubMed

    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 [Formula: see text] 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., [Formula: see text] 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 [Formula: see text] 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 [Formula: see text] leaching while balancing impacts on crop yields within the watershed.

  18. Modeling temporal and spatial variability of crop yield

    NASA Astrophysics Data System (ADS)

    Bonetti, S.; Manoli, G.; Scudiero, E.; Morari, F.; Putti, M.; Teatini, P.

    2014-12-01

    In a world of increasing food insecurity the development of modeling tools capable of supporting on-farm decision making processes is highly needed to formulate sustainable irrigation practices in order to preserve water resources while maintaining adequate crop yield. The design of these practices starts from the accurate modeling of soil-plant-atmosphere interaction. We present an innovative 3D Soil-Plant model that couples 3D hydrological soil dynamics with a mechanistic description of plant transpiration and photosynthesis, including a crop growth module. Because of its intrinsically three dimensional nature, the model is able to capture spatial and temporal patterns of crop yield over large scales and under various climate and environmental factors. The model is applied to a 25 ha corn field in the Venice coastland, Italy, that has been continuously monitored over the years 2010 and 2012 in terms of both hydrological dynamics and yield mapping. The model results satisfactorily reproduce the large variability observed in maize yield (from 2 to 15 ton/ha). This variability is shown to be connected to the spatial heterogeneities of the farmland, which is characterized by several sandy paleo-channels crossing organic-rich silty soils. Salt contamination of soils and groundwater in a large portion of the area strongly affects the crop yield, especially outside the paleo-channels, where measured salt concentrations are lower than the surroundings. The developed model includes a simplified description of the effects of salt concentration in soil water on transpiration. The results seem to capture accurately the effects of salt concentration and the variability of the climatic conditions occurred during the three years of measurements. This innovative modeling framework paves the way to future large scale simulations of farmland dynamics.

  19. 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

  20. Reductions in India's crop yield due to ozone

    NASA Astrophysics Data System (ADS)

    Ghude, Sachin D.; Jena, Chinmay; Chate, D. M.; Beig, G.; Pfister, G. G.; Kumar, Rajesh; Ramanathan, V.

    2014-08-01

    This bottom-up modeling study, supported by emission inventories and crop production, simulates ozone on local to regional scales. It quantifies, for the first time, potential impact of ozone on district-wise cotton, soybeans, rice, and wheat crops in India for the first decade of the 21st century. Wheat is the most impacted crop with losses of 3.5 ± 0.8 million tons (Mt), followed by rice at 2.1 ± 0.8 Mt, with the losses concentrated in central and north India. On the national scale, this loss is about 9.2% of the cereals required every year (61.2 Mt) under the provision of the recently implemented National Food Security Bill (in 2013) by the Government of India. The nationally aggregated yield loss is sufficient to feed about 94 million people living below poverty line in India.

  1. Rapid Intensification of Agriculture in Brazil: Dynamics and Implications of Double Cropping

    NASA Astrophysics Data System (ADS)

    Spera, S. A.; Mustard, J. F.; Rudorff, B.; VanWey, L.; Risso, J.; Adami, M.

    2012-12-01

    Global food production and yield have increased substantially over the past 50 years to keep up with the demands of the world's growing population. At the forefront of some recent developments is Brazil, where Mato Grosso State has contributed to this increase in yield and production by both extensifying (converting forest to pasture or row crops) and intensifying (converting pasture to row crops or one-crop/growing year to two-crops/growing year) large areas of land. Our research reported here is focused on characterizing the land-cover and -use dynamics in this rapidly evolving region. We have developed a new algorithm to quantify both the conversion of land to mechanized agriculture and the character of those crop rotations. We use the systematic MODIS enhanced vegetation index (EVI) product (MODIS13Q1) aggregated from daily observations to a 16-day cloud free measurement. Each pixel's resulting 2000-2011 EVI time series is analyzed with a decision tree-like algorithm created in ENVI+IDL to determine not only the area of agricultural land for each of the past decade's growing seasons, but also the specific crop dynamic of that agricultural land: a soy or cotton single-cropping rotation or a soy/corn or soy/cotton double-cropping rotation. The algorithm is based on analysis of growing season EVI patterns of forest, pasture/cerrado, and annual crops. We define specific thresholds for the magnitude of EVI over the growing season to distinguish between natural vegetation, pasture, and cropland, and then use growing season length and crop calendars to separate specific crop types. Because the intra-annual EVI phenology of forest and pasture/cerrado is relatively constant but cropland shows a large dynamic range, the algorithm uses the standard deviation of a growing season's EVI time series to separate between forest and pasture/cerrado and agricultural land. For pixels identified as agricultural land, the algorithm then uses crop-specific growing season lengths and

  2. Were Fertile Crescent crop progenitors higher yielding than other wild species that were never domesticated?

    PubMed

    Preece, Catherine; Livarda, Alexandra; Wallace, Michael; Martin, Gemma; Charles, Michael; Christin, Pascal-Antoine; Jones, Glynis; Rees, Mark; Osborne, Colin P

    2015-08-01

    During the origin of agriculture in the Fertile Crescent, the broad spectrum of wild plant species exploited by hunter-gatherers narrowed dramatically. The mechanisms responsible for this specialization and the associated domestication of plants are intensely debated. We investigated why some species were domesticated rather than others, and which traits they shared. We tested whether the progenitors of cereal and pulse crops, grown individually, produced a higher yield and less chaff than other wild grasses and legumes, thereby maximizing the return per seed planted and minimizing processing time. We compared harvest traits of species originating from the Fertile Crescent, including those for which there is archaeological evidence of deliberate collection. Unexpectedly, wild crop progenitors in both families had neither higher grain yield nor, in grasses, less chaff, although they did have larger seeds. Moreover, small-seeded grasses actually returned a higher yield relative to the mass of seeds sown. However, cereal progenitors had threefold fewer seeds per plant, representing a major difference in how seeds are packaged on plants. These data suggest that there was no intrinsic yield advantage to adopting large-seeded progenitor species as crops. Explaining why Neolithic agriculture was founded on these species, therefore, remains an important unresolved challenge.

  3. Sequencing Crop Genomes: A Gateway to Improve Tropical Agriculture

    PubMed Central

    Thottathil, Gincy Paily; Jayasekaran, Kandakumar; Othman, Ahmad Sofiman

    2016-01-01

    Agricultural development in the tropics lags behind development in the temperate latitudes due to the lack of advanced technology, and various biotic and abiotic factors. To cope with the increasing demand for food and other plant-based products, improved crop varieties have to be developed. To breed improved varieties, a better understanding of crop genetics is necessary. With the advent of next-generation DNA sequencing technologies, many important crop genomes have been sequenced. Primary importance has been given to food crops, including cereals, tuber crops, vegetables, and fruits. The DNA sequence information is extremely valuable for identifying key genes controlling important agronomic traits and for identifying genetic variability among the cultivars. However, massive DNA re-sequencing and gene expression studies have to be performed to substantially improve our understanding of crop genetics. Application of the knowledge obtained from the genomes, transcriptomes, expression studies, and epigenetic studies would enable the development of improved varieties and may lead to a second green revolution. The applications of next generation DNA sequencing technologies in crop improvement, its limitations, future prospects, and the features of important crop genome projects are reviewed herein. PMID:27019684

  4. Growth-stage dependent crop yield response to ozone exposure.

    PubMed

    Younglove, T; McCool, P M; Musselman, R C; Kahl, M E

    1994-01-01

    Data from four crop yield-loss field trials were examined to determine if analysis using an imposed phenological weighting function based on seasonal growth stage would provide a more accurate indication of impact of ozone exposure. Alfalfa (Medicago sativa L. cv. Moapa 69), dry bean (Phaseolus vulgaris L. cv. California Dark Red kidney), fresh market and processing tomato (Lycopersicon esculentum Mill. cv. 6718 VF and VF-145-B7879, respectively) were grown at 9-11 ambient field plots within southern California comprising an ambient gradient of ozone. The growing season for each crop was artificially divided into 'quarters' composed of equal numbers of whole days and roughly corresponding to specific growth stages. Ozone exposure was calculated for each of these 'quarters' and regressed against final crop yield using 163 different exposure statistics. Weighting functions were developed using reciprocal residual mean square (1/RMS) or percentage of the best 100 exposure statistics of the 163 tested (TOP100) for each of the quarters. The third quarter of the alfalfa season was clearly most responsive to ozone as measured by both of the weighting functions. Third quarter ozone was also weighted highest by both weighting functions for dry bean. Fresh market and processing tomato were each influenced the greatest by second quartero zone as demonstrated by both weighting functions. The occurrence of ozone during physiologically important events (flowering and initial fruit set in second quarter for tomato; pod development in third quarter for dry bean) appeared to influence the yield of these crops the greatest. Growth-stage-dependent phenological weighting of pollutant exposure may result in more effective predictions of levels of ozone exposure resulting in yield reductions.

  5. Bayesian Inference of Baseline Fertility and Treatment Effects via a Crop Yield-Fertility Model

    PubMed Central

    Chen, Hungyen; Yamagishi, Junko; Kishino, Hirohisa

    2014-01-01

    To effectively manage soil fertility, knowledge is needed of how a crop uses nutrients from fertilizer applied to the soil. Soil quality is a combination of biological, chemical and physical properties and is hard to assess directly because of collective and multiple functional effects. In this paper, we focus on the application of these concepts to agriculture. We define the baseline fertility of soil as the level of fertility that a crop can acquire for growth from the soil. With this strict definition, we propose a new crop yield-fertility model that enables quantification of the process of improving baseline fertility and the effects of treatments solely from the time series of crop yields. The model was modified from Michaelis-Menten kinetics and measured the additional effects of the treatments given the baseline fertility. Using more than 30 years of experimental data, we used the Bayesian framework to estimate the improvements in baseline fertility and the effects of fertilizer and farmyard manure (FYM) on maize (Zea mays), barley (Hordeum vulgare), and soybean (Glycine max) yields. Fertilizer contributed the most to the barley yield and FYM contributed the most to the soybean yield among the three crops. The baseline fertility of the subsurface soil was very low for maize and barley prior to fertilization. In contrast, the baseline fertility in this soil approximated half-saturated fertility for the soybean crop. The long-term soil fertility was increased by adding FYM, but the effect of FYM addition was reduced by the addition of fertilizer. Our results provide evidence that long-term soil fertility under continuous farming was maintained, or increased, by the application of natural nutrients compared with the application of synthetic fertilizer. PMID:25405353

  6. Bayesian inference of baseline fertility and treatment effects via a crop yield-fertility model.

    PubMed

    Chen, Hungyen; Yamagishi, Junko; Kishino, Hirohisa

    2014-01-01

    To effectively manage soil fertility, knowledge is needed of how a crop uses nutrients from fertilizer applied to the soil. Soil quality is a combination of biological, chemical and physical properties and is hard to assess directly because of collective and multiple functional effects. In this paper, we focus on the application of these concepts to agriculture. We define the baseline fertility of soil as the level of fertility that a crop can acquire for growth from the soil. With this strict definition, we propose a new crop yield-fertility model that enables quantification of the process of improving baseline fertility and the effects of treatments solely from the time series of crop yields. The model was modified from Michaelis-Menten kinetics and measured the additional effects of the treatments given the baseline fertility. Using more than 30 years of experimental data, we used the Bayesian framework to estimate the improvements in baseline fertility and the effects of fertilizer and farmyard manure (FYM) on maize (Zea mays), barley (Hordeum vulgare), and soybean (Glycine max) yields. Fertilizer contributed the most to the barley yield and FYM contributed the most to the soybean yield among the three crops. The baseline fertility of the subsurface soil was very low for maize and barley prior to fertilization. In contrast, the baseline fertility in this soil approximated half-saturated fertility for the soybean crop. The long-term soil fertility was increased by adding FYM, but the effect of FYM addition was reduced by the addition of fertilizer. Our results provide evidence that long-term soil fertility under continuous farming was maintained, or increased, by the application of natural nutrients compared with the application of synthetic fertilizer.

  7. Effect of crop residue harvest on long-term crop yield, soil erosion, and carbon balance: tradeoffs for a sustainable bioenergy feedstock

    SciTech Connect

    Gregg, Jay S.; Izaurralde, Roberto C.

    2010-08-26

    Agricultural residues are a potential feedstock for bioenergy production, if residue harvest can be done sustainably. The relationship between crop residue harvest, soil erosion, crop yield and carbon balance was modeled with the Erosion Productivity Impact Calculator/ Environment Policy Integrated Climate (EPIC) using a factorial design. Four crop rotations (winter wheat [Triticum aestivum (L.)] – sunflower [Helianthus annuus]; spring wheat [Triticum aestivum (L.)] – canola [Brassica napus]; corn [Zea mays L.] – soybean [Glycine max (L.) Merr.]; and cotton [Gossypium hirsutum] – peanut [Arachis hypogaea]) were simulated at four US locations each, under different topographies (0-10% slope), and management practices [crop residue removal rates (0-75%), conservation practices (no till, contour cropping, strip cropping, terracing)].

  8. Sustainable Management in Crop Monocultures: The Impact of Retaining Forest on Oil Palm Yield

    PubMed Central

    Edwards, Felicity A.; Edwards, David P.; Sloan, Sean; Hamer, Keith C.

    2014-01-01

    Tropical agriculture is expanding rapidly at the expense of forest, driving a global extinction crisis. How to create agricultural landscapes that minimise the clearance of forest and maximise sustainability is thus a key issue. One possibility is protecting natural forest within or adjacent to crop monocultures to harness important ecosystem services provided by biodiversity spill-over that may facilitate production. Yet this contrasts with the conflicting potential that the retention of forest exports dis-services, such as agricultural pests. We focus on oil palm and obtained yields from 499 plantation parcels spanning a total of ≈23,000 ha of oil palm plantation in Sabah, Malaysian Borneo. We investigate the relationship between the extent and proximity of both contiguous and fragmented dipterocarp forest cover and oil palm yield, controlling for variation in oil palm age and for environmental heterogeneity by incorporating proximity to non-native forestry plantations, other oil palm plantations, and large rivers, elevation and soil type in our models. The extent of forest cover and proximity to dipterocarp forest were not significant predictors of oil palm yield. Similarly, proximity to large rivers and other oil palm plantations, as well as soil type had no significant effect. Instead, lower elevation and closer proximity to forestry plantations had significant positive impacts on oil palm yield. These findings suggest that if dipterocarp forests are exporting ecosystem service benefits or ecosystem dis-services, that the net effect on yield is neutral. There is thus no evidence to support arguments that forest should be retained within or adjacent to oil palm monocultures for the provision of ecosystem services that benefit yield. We urge for more nuanced assessments of the impacts of forest and biodiversity on yields in crop monocultures to better understand their role in sustainable agriculture. PMID:24638038

  9. Sustainable management in crop monocultures: the impact of retaining forest on oil palm yield.

    PubMed

    Edwards, Felicity A; Edwards, David P; Sloan, Sean; Hamer, Keith C

    2014-01-01

    Tropical agriculture is expanding rapidly at the expense of forest, driving a global extinction crisis. How to create agricultural landscapes that minimise the clearance of forest and maximise sustainability is thus a key issue. One possibility is protecting natural forest within or adjacent to crop monocultures to harness important ecosystem services provided by biodiversity spill-over that may facilitate production. Yet this contrasts with the conflicting potential that the retention of forest exports dis-services, such as agricultural pests. We focus on oil palm and obtained yields from 499 plantation parcels spanning a total of ≈23,000 ha of oil palm plantation in Sabah, Malaysian Borneo. We investigate the relationship between the extent and proximity of both contiguous and fragmented dipterocarp forest cover and oil palm yield, controlling for variation in oil palm age and for environmental heterogeneity by incorporating proximity to non-native forestry plantations, other oil palm plantations, and large rivers, elevation and soil type in our models. The extent of forest cover and proximity to dipterocarp forest were not significant predictors of oil palm yield. Similarly, proximity to large rivers and other oil palm plantations, as well as soil type had no significant effect. Instead, lower elevation and closer proximity to forestry plantations had significant positive impacts on oil palm yield. These findings suggest that if dipterocarp forests are exporting ecosystem service benefits or ecosystem dis-services, that the net effect on yield is neutral. There is thus no evidence to support arguments that forest should be retained within or adjacent to oil palm monocultures for the provision of ecosystem services that benefit yield. We urge for more nuanced assessments of the impacts of forest and biodiversity on yields in crop monocultures to better understand their role in sustainable agriculture.

  10. Land Resources for Crop Production. Agricultural Economic Report Number 572.

    ERIC Educational Resources Information Center

    Hexem, Roger; Krupa, Kenneth S.

    About 35 million acres not being cultivated have high potential for crop use and 117 million more have medium potential, according to the 1982 National Resources Inventory (NRI) conducted by the U.S. Department of Agriculture. USDA committees evaluated the economic potential for converting land based on physical characteristics of the soil; size…

  11. Modeling Agricultural Crop Production in China using AVHRR-based Vegetation Health Indices

    NASA Astrophysics Data System (ADS)

    Yang, B.; Kogan, F.; Guo, W.; Zhiyuan, P.; Xianfeng, J.

    Weather related crop losses have always been a concern for farmers On a wider scale it has always influenced decision of Governments traders and other policy makers for the purpose of balanced food supplies trade and distribution of aid to the nations in need Therefore national policy and decision makers are giving increasing importance to early assessment of crop losses in response to weather fluctuations This presentation emphasizes utility of AVHRR-based Vegetation health index VHI for early warning of drought-related losses of agricultural production in China The VHI is a three-channel index characterizing greenness vigor and temperature of land surface which can be used as proxy for estimation of how healthy and potentially productive could be vegetation China is the largest in the world producer of grain including wheat and rice and cotton In the major agricultural areas China s crop production is very dependent on weather The VHI being a proxy indicator of weather impact on vegetation showed some correlation with productivity of agricultural crops during the critical period of their development The periods of the strongest correlation were investigated and used to build regression models where crop yield deviation from technological trend was accepted as a dependent and VHI as independent variables The models were developed for several major crops including wheat corn and soybeans

  12. PERUN system and its application for assessing the crop yield potential of the Czech Republic

    NASA Astrophysics Data System (ADS)

    Dubrovsky, M.; Zalud, Z.; Eitzinger, J.; Trnka, M.; Semeradova, D.

    2003-04-01

    The main purpose of the first version of the computer system PERUN, which has been developed in 2001-2002 (presented in EGS 2002), is the probabilistic seasonal crop yield forecasting for a given site. The system is based on the crop growth model WOFOST (version 7, slightly modified) and the six-variate version of the stochastic weather generator Met&Roll. The system is now being enhanced to allow assessment of the crop yield potential of a larger area. As this assessment requires a great amount of meteorological, pedological and crop data to be gathered, but these data are not yet all available to the authors, the presentation will rather focus on the methodological aspects and the results of the sensitivity analysis. The presentation will consist of the following points: (i) Overview of the PERUN system. The results of the validation experiments (spring barley and winter wheat at selected Czech locations) will be presented, too. (ii) Methodology used for a spatial assessment. The assessment is based on integrating model crop yields simulated at multiple sub-regions with region-specific climatic and pedological conditions. The input daily weather series are produced by the stochastic generator. The multi-year crop model simulation is performed for each sub-region to assess the mean and variability of the model yields. (iii) Sensitivity of the regional crop production potential to uncertainties in selected input characteristics: crop cultivar, soil type, hydrological characteristics (e.g. amount of available water at the beginning of the simulation), and climatic conditions (e.g temperature, precipitation). In assessing sensitivity to climate, the climatic characteristics will be varied within the range of values typical for the territory of the Czech Republic. The crops applied in the analysis are spring barley and winter wheat. Acknowledgement: The system PERUN has been developed within the frame of project QC1316 sponsored by the Czech National Agency for

  13. The Importance of Juvenile Root Traits for Crop Yields

    NASA Astrophysics Data System (ADS)

    White, Philip; Adu, Michael; Broadley, Martin; Brown, Lawrie; Dupuy, Lionel; George, Timothy; Graham, Neil; Hammond, John; Hayden, Rory; Neugebauer, Konrad; Nightingale, Mark; Ramsay, Gavin; Thomas, Catherine; Thompson, Jacqueline; Wishart, Jane; Wright, Gladys

    2014-05-01

    Genetic variation in root system architecture (RSA) is an under-exploited breeding resource. This is partly a consequence of difficulties in the rapid and accurate assessment of subterranean root systems. However, although the characterisation of root systems of large plants in the field are both time-consuming and labour-intensive, high-throughput (HTP) screens of root systems of juvenile plants can be performed in the field, glasshouse or laboratory. It is hypothesised that improving the root systems of juvenile plants can accelerate access to water and essential mineral elements, leading to rapid crop establishment and, consequently, greater yields. This presentation will illustrate how aspects of the juvenile root systems of potato (Solanum tuberosum L.) and oilseed rape (OSR; Brassica napus L.) correlate with crop yields and examine the reasons for such correlations. It will first describe the significant positive relationships between early root system development, phosphorus acquisition, canopy establishment and eventual yield among potato genotypes. It will report the development of a glasshouse assay for root system architecture (RSA) of juvenile potato plants, the correlations between root system architectures measured in the glasshouse and field, and the relationships between aspects of the juvenile root system and crop yields under drought conditions. It will then describe the development of HTP systems for assaying RSA of OSR seedlings, the identification of genetic loci affecting RSA in OSR, the development of mathematical models describing resource acquisition by OSR, and the correlations between root traits recorded in the HTP systems and yields of OSR in the field.

  14. Intercontinental trans-boundary contributions to ozone-induced crop yield losses in the Northern Hemisphere

    NASA Astrophysics Data System (ADS)

    Hollaway, M. J.; Arnold, S. R.; Challinor, A. J.; Emberson, L. D.

    2011-08-01

    Enhanced surface ozone concentrations are known to be harmful to vegetation, reducing crop growth and yields. Tropospheric ozone concentrations have increased steadily since pre-industrial times, driven by in-situ production from anthropogenic emissions of nitrogen oxides (NOx), CO and volatile organic compounds. Transport of ozone and its precursors between continents has been shown to contribute to surface ozone air quality exceedences in many regions of the Northern Hemisphere. Using a global atmospheric chemistry model, we have quantified for the first time, intercontinental contributions to crop ozone exposure and yield reduction in the Northern Hemisphere. We apply three metrics (AOT40/M7/M12) to assess the impacts of NOx emissions from each of the Northern Hemispheres three major industrialised regions (North (N) America, South East (SE) Asia and Europe) on global and regional exposure of 6 major agricultural crop types to harmful ozone concentrations, and the resultant yield losses during the 2000 growing season. Using these metrics, model calculations show that for wheat, rice, cotton and potato, 100 % reductions in SE Asian anthropogenic NOx emissions tend to produce the greatest global reduction in crop yield losses (48.8 to 94.7 %) with the same cuts to N American emissions resulting in the greatest global impact on crop yield reductions for maize and soybean (57.5 to 81.7 %). N American NOx emissions produce the largest transboundary impact, resulting in European yield loss reductions of between 12.4 % and 55.6 %, when a 100 % cut is applied to NOx emissions from the N American region. European NOx emissions tend to produce a smaller transboundary impact, due to inefficiency of transport from the European domain. The threshold nature of the AOT40 ozone-exposure metric, results in a strong dependence of the diagnosed impact from trans-boundary emissions on local ozone concentration. In addition, we find that in parts of the United States, biomass

  15. Hyperspectral mapping of crop and soils for precision agriculture

    NASA Astrophysics Data System (ADS)

    Whiting, Michael L.; Ustin, Susan L.; Zarco-Tejada, Pablo; Palacios-Orueta, Alicia; Vanderbilt, Vern C.

    2006-08-01

    Precision agriculture requires high spectral and spatial resolution imagery for advanced analyses of crop and soil conditions to increase environmental protection and producers' sustainability. GIS models that anticipate crop responses to nutrients, water, and pesticides require high spatial detail to generate application prescription maps. While the added precision of geo-spatial interpolation to field scouting generates improved zone maps and are an improvement over field-wide applications, it is limited in detail due to expense, and lacks the high precision required for pixel level applications. Multi-spectral imagery gives the spatial detail required, but broad band indexes are not sensitive to many variables in the crop and soil environment. Hyperspectral imagery provides both the spatial detail of airborne imagery and spectral resolution for spectroscopic and narrow band analysis techniques developed over recent decades in the laboratory that will advance precise determination of water and bio-physical properties of crops and soils. For several years, we have conducted remote sensing investigations to improve cotton production through field spectrometer measurements, and plant and soil samples in commercial fields and crop trials. We have developed spectral analyses techniques for plant and soil conditions through determination of crop water status, effectiveness of pre-harvest defoliant applications, and soil characterizations. We present the most promising of these spectroscopic absorption and narrow band index techniques, and their application to airborne hyperspectral imagery in mapping the variability in crops and soils.

  16. Long-term global trends in crop yield and production reveal no current pollination shortage but increasing pollinator dependency.

    PubMed

    Aizen, Marcelo A; Garibaldi, Lucas A; Cunningham, Saul A; Klein, Alexandra M

    2008-10-28

    There is evidence that pollinators are declining as a result of local and global environmental degradation [1-4]. Because a sizable proportion of the human diet depends directly or indirectly on animal pollination [5], the issue of how decreases in pollinator stocks could affect global crop production is of paramount importance [6-8]. Using the extensive FAO data set [9], we compared 45 year series (1961-2006) in yield, and total production and cultivated area of pollinator-dependent and nondependent crops [5]. We investigated temporal trends separately for the developed and developing world because differences in agricultural intensification, and socioeconomic and environmental conditions might affect yield and pollinators [10-13]. Since 1961, crop yield (Mt/ha) has increased consistently at average annual growth rates of approximately 1.5%. Temporal trends were similar between pollinator-dependent and nondependent crops in both the developed and developing world, thus not supporting the view that pollinator shortages are affecting crop yield at the global scale. We further report, however, that agriculture has become more pollinator dependent because of a disproportionate increase in the area cultivated with pollinator-dependent crops. If the trend toward favoring cultivation of pollinator-dependent crops continues, the need for the service provided by declining pollinators will greatly increase in the near future.

  17. Seventeenth century organic agriculture in China: I. Cropping systems in Jiaxing Region

    SciTech Connect

    Dazhong, W.; Pimentel, D.

    1986-03-01

    The cropping systems of seventeenth century traditional organic agriculture in the Jiaxing Region of eastern China required about 2000 hr of labor per hectare for rice production. Rice and related grain crops were produced employing only human power. The input was about 200 times that for most mechanized grain production today. The charcoal or fossil energy input to produce simple hand tools accounted for only 1-2% total energy in the crop systems. Organic wastes including manures, pond sediments, and green manure crops supplied most of the nutrients. Rice yields, ranging as high as 6700-8400 kg/ha, were similar to some of the highest yields today. The energy output/input ratio ranged from 9 for compost-fertilized rice to 12 for green manure-fertilized rice production. These ratios were 2-10 times higher than most mechanized rice production systems of today. Knowledge of the crop and soil system enabled the early Chinese farms to maintain high crop yields and sustain highly productive soils.

  18. Dryland soil chemical properties and crop yields affected by long-term tillage and cropping sequence.

    PubMed

    Sainju, Upendra M; Allen, Brett L; Caesar-TonThat, Thecan; Lenssen, Andrew W

    2015-01-01

    Information on the effect of long-term management on soil nutrients and chemical properties is scanty. We examined the 30-year effect of tillage frequency and cropping sequence combination on dryland soil Olsen-P, K, Ca, Mg, Na, SO4-S, and Zn concentrations, pH, electrical conductivity (EC), and cation exchange capacity (CEC) at the 0-120 cm depth and annualized crop yield in the northern Great Plains, USA. Treatments were no-till continuous spring wheat (Triticum aestivum L.) (NTCW), spring till continuous spring wheat (STCW), fall and spring till continuous spring wheat (FSTCW), fall and spring till spring wheat-barley (Hordeum vulgare L., 1984-1999) followed by spring wheat-pea (Pisum sativum L., 2000-2013) (FSTW-B/P), and spring till spring wheat-fallow (STW-F, traditional system). At 0-7.5 cm, P, K, Zn, Na, and CEC were 23-60% were greater, but pH, buffer pH, and Ca were 6-31% lower in NTCW, STCW, and FSTW-B/P than STW-F. At 7.5-15 cm, K was 23-52% greater, but pH, buffer pH, and Mg were 3-21% lower in NTCW, STCW, FSTCW, FSTW-B/P than STW-F. At 60-120 cm, soil chemical properties varied with treatments. Annualized crop yield was 23-30% lower in STW-F than the other treatments. Continuous N fertilization probably reduced soil pH, Ca, and Mg, but greater crop residue returned to the soil increased P, K, Na, Zn, and CEC in NTCW and STCW compared to STW-F. Reduced tillage with continuous cropping may be adopted for maintaining long-term soil fertility and crop yields compared with the traditional system.

  19. The Joint Experiment for Crop Assessment and Monitoring (JECAM) Initiative: Developing methods and best practices for global agricultural monitoring

    NASA Astrophysics Data System (ADS)

    Champagne, C.; Jarvis, I.; Defourny, P.; Davidson, A.

    2014-12-01

    Agricultural systems differ significantly throughout the world, making a 'one size fits all' approach to remote sensing and monitoring of agricultural landscapes problematic. The Joint Experiment for Crop Assessment and Monitoring (JECAM) was established in 2009 to bring together the global scientific community to work towards a set of best practices and recommendations for using earth observation data to map, monitor and report on agricultural productivity globally across an array of diverse agricultural systems. These methods form the research and development component of the Group on Earth Observation Global Agricultural Monitoring (GEOGLAM) initiative to harmonize global monitoring efforts and increase market transparency. The JECAM initiative brings together researchers from a large number of globally distributed, well monitored agricultural test sites that cover a range of crop types, cropping systems and climate regimes. Each test site works independently as well as together across multiple sites to test methods, sensors and field data collection techniques to derive key agricultural parameters, including crop type, crop condition, crop yield and soil moisture. The outcome of this project will be a set of best practices that cover the range of remote sensing monitoring and reporting needs, including satellite data acquisition, pre-processing techniques, information retrieval and ground data validation. These outcomes provide the research and development foundation for GEOGLAM and will help to inform the development of the GEOGLAM "system of systems" for global agricultural monitoring. The outcomes of the 2014 JECAM science meeting will be discussed as well as examples of methods being developed by JECAM scientists.

  20. 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

  1. Yield gap mapping as a support tool for risk management in agriculture

    NASA Astrophysics Data System (ADS)

    Lahlou, Ouiam; Imani, Yasmina; Slimani, Imane; Van Wart, Justin; Yang, Haishun

    2016-04-01

    The increasing frequency and magnitude of droughts in Morocco and the mounting losses from extended droughts in the agricultural sector emphasized the need to develop reliable and timely tools to manage drought and to mitigate resulting catastrophic damage. In 2011, Morocco launched a cereals multi-risk insurance with drought as the most threatening and the most frequent hazard in the country. However, and in order to assess the gap and to implement the more suitable compensation, it is essential to quantify the potential yield in each area. In collaboration with the University of Nebraska-Lincoln, a study is carried out in Morocco and aims to determine the yield potentials and the yield gaps in the different agro-climatic zones of the country. It fits into the large project: Global Yield Gap and Water Productivity Atlas: http://www.yieldgap.org/. The yield gap (Yg) is the magnitude and difference between crop yield potential (Yp) or water limited yield potential (Yw) and actual yields, reached by farmers. World Food Studies (WOFOST), which is a Crop simulation mechanistic model, has been used for this purpose. Prior to simulations, reliable information about actual yields, weather data, crop management data and soil data have been collected in 7 Moroccan buffer zones considered, each, within a circle of 100 km around a weather station point, homogenously spread across the country and where cereals are widely grown. The model calibration was also carried out using WOFOST default varieties data. The map-based results represent a robust tool, not only for drought insurance organization, but for agricultural and agricultural risk management. Moreover, accurate and geospatially granular estimates of Yg and Yw will allow to focus on regions with largest unexploited yield gaps and greatest potential to close them, and consequently to improve food security in the country.

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

    SciTech Connect

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

    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). 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.

  3. Airborne Hyperspectral Imagery for the Detection of Agricultural Crop Stress

    NASA Technical Reports Server (NTRS)

    Cassady, Philip E.; Perry, Eileen M.; Gardner, Margaret E.; Roberts, Dar A.

    2001-01-01

    Multispectral digital imagery from aircraft or satellite is presently being used to derive basic assessments of crop health for growers and others involved in the agricultural industry. Research indicates that narrow band stress indices derived from hyperspectral imagery should have improved sensitivity to provide more specific information on the type and cause of crop stress, Under funding from the NASA Earth Observation Commercial Applications Program (EOCAP) we are identifying and evaluating scientific and commercial applications of hyperspectral imagery for the remote characterization of agricultural crop stress. During the summer of 1999 a field experiment was conducted with varying nitrogen treatments on a production corn-field in eastern Nebraska. The AVIRIS (Airborne Visible-Infrared Imaging Spectrometer) hyperspectral imager was flown at two critical dates during crop development, at two different altitudes, providing images with approximately 18m pixels and 3m pixels. Simultaneous supporting soil and crop characterization included spectral reflectance measurements above the canopy, biomass characterization, soil sampling, and aerial photography. In this paper we describe the experiment and results, and examine the following three issues relative to the utility of hyperspectral imagery for scientific study and commercial crop stress products: (1) Accuracy of reflectance derived stress indices relative to conventional measures of stress. We compare reflectance-derived indices (both field radiometer and AVIRIS) with applied nitrogen and with leaf level measurement of nitrogen availability and chlorophyll concentrations over the experimental plots (4 replications of 5 different nitrogen levels); (2) Ability of the hyperspectral sensors to detect sub-pixel areas under crop stress. We applied the stress indices to both the 3m and 18m AVIRIS imagery for the entire production corn field using several sub-pixel areas within the field to compare the relative

  4. Coupling crop growth and hydrologic models to predict crop yield with spatial analysis technologies

    NASA Astrophysics Data System (ADS)

    Jia, Yangwen; Shen, Suhui; Niu, Cunwen; Qiu, Yaqin; Wang, Hao; Liu, Yu

    2011-01-01

    This paper analyzes climate change impact on crop yield of winter wheat, a main crop in the water-stressed Haihe River Basin in North China. An integrated analysis was carried out by coupling the World Food Studies (WOFOST) crop growth model and the distributed hydrological model describing the water and energy transfer processes in large river basins (WEP-L). Various spatial analysis technologies, including remote sensing and geographical information system, were woven together to support model calibration and validation. The WOFOST model was calibrated and validated using the winter wheat data collected in two successive years. Effort was then extended to calibrate and validate the WEP-L distributed hydrologic model for the whole basin. Such an effort was collectively supported by using the remote sensing evapotranspiration and biomass data, the in situ river flow data, and the wheat yield statistical data. With this integration, the wheat yield from 2010 to 2030 can be predicted under the given climate change impact corresponding to Intergovernmental Panel on Climate Change A1B, A2, and B1 scenarios. Given the prescribed climate change scenarios, at the basin-scale, the winter wheat yield may increase in terms of the annual average; however, the long-term trend is geared toward a decreasing yield with significant fluctuations. The colder hilly areas with current lower yield may significantly increase due to possible future temperature rise while the warmer plain areas with current higher yield may slightly increase or decrease. Despite the data collected thus far, it is evident that further studies are needed to reduce the uncertainties of these predictions of climate change effect on winter wheat grain yield.

  5. Cover crop effect on subsequent wheat yield and water use efficiency in the central great plains

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Crop production systems in the water-limited environment of the semi-arid central Great Plains may not have potential to profitably use cover crops because of lowered subsequent wheat (Triticum asestivum L.) yields following the cover crop. Cover crop mixtures have reportedly shown less yield-reduci...

  6. Cover crops can affect subsequent wheat yield in the central great plains

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Crop production systems in the water-limited environment of the semi-arid central Great Plains may not have potential to profitably use cover crops because of lowered subsequent wheat (Triticum asestivum L.) yields following the cover crop. Cover crop mixtures have reportedly shown less yield-reduci...

  7. Determination of caloric values of agricultural crops and crop waste by Adiabatic Bomb Calorimetry

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Calorific values of agricultural crops and their waste were measured by adiabatic bomb calorimetry. Sustainable farming techniques require that all potential sources of revenue be utilized. A wide variety of biomass is beginning to be used as alternative fuels all over the world. The energy potentia...

  8. Determination of potential management zones from soil electrical conductivity, yield and crop data.

    PubMed

    Li, Yan; Shi, Zhou; Wu, Ci-fang; Li, Hong-yi; Li, Feng

    2008-01-01

    One approach to apply precision agriculture to optimize crop production and environmental quality is identifying management zones. In this paper, the variables of soil electrical conductivity (EC) data, cotton yield data and normalized difference vegetation index (NDVI) data in an about 15 ha field in a coastal saline land were selected as data resources, and their spatial variabilities were firstly analyzed and spatial distribution maps constructed with geostatistics technique. Then fuzzy c-means clustering algorithm was used to define management zones, fuzzy performance index (FPI) and normalized classification entropy (NCE) were used to determine the optimal cluster numbers. Finally one-way variance analysis was performed on 224 georeferenced soil and yield sampling points to assess how well the defined management zones reflected the soil properties and productivity level. The results reveal that the optimal number of management zones for the present study area was 3 and the defined management zones provided a better description of soil properties and yield variation. Statistical analyses indicate significant differences between the chemical properties of soil samples and crop yield in each management zone, and management zone 3 presented the highest nutrient level and potential crop productivity, whereas management zone 1 the lowest. Based on these findings, we conclude that fuzzy c-means clustering approach can be used to delineate management zones by using the given three variables in the coastal saline soils, and the defined management zones form an objective basis for targeting soil samples for nutrient analysis and development of site-specific application strategies.

  9. Responses of corn physiology and yield to six agricultural practices over three years in middle Tennessee

    PubMed Central

    Yu, Chih-Li; Hui, Dafeng; Deng, Qi; Wang, Junming; Reddy, K. Chandra; Dennis, Sam

    2016-01-01

    Different agricultural practices may have substantial impacts on crop physiology and yield. However, it is still not entirely clear how multiple agricultural practices such as tillage, biochar and different nutrient applications could influence corn physiology and yield. We conducted a three-year field experiment to study the responses of corn physiology, yield, and soil respiration to six different agricultural practices. The six treatments included conventional tillage (CT) or no tillage (NT), in combination with nitrogen type (URAN or chicken litter) and application method, biochar, or denitrification inhibitor. A randomized complete block design was applied with six replications. Leaf photosynthetic rate, transpiration, plant height, leaf area index (LAI), biomass, and yield were measured. Results showed that different agricultural practices had significant effects on plant leaf photosynthesis, transpiration, soil respiration, height, and yield, but not on LAI and biomass. The average corn yield in the NT-URAN was 10.03 ton/ha, 28.9% more than in the CT-URAN. Compared to the NT-URAN, the NT-biochar had lower soil respiration and similar yield. All variables measured showed remarkable variations among the three years. Our results indicated that no tillage treatment substantially increased corn yield, probably due to the preservation of soil moisture during drought periods. PMID:27272142

  10. Responses of corn physiology and yield to six agricultural practices over three years in middle Tennessee.

    PubMed

    Yu, Chih-Li; Hui, Dafeng; Deng, Qi; Wang, Junming; Reddy, K Chandra; Dennis, Sam

    2016-06-07

    Different agricultural practices may have substantial impacts on crop physiology and yield. However, it is still not entirely clear how multiple agricultural practices such as tillage, biochar and different nutrient applications could influence corn physiology and yield. We conducted a three-year field experiment to study the responses of corn physiology, yield, and soil respiration to six different agricultural practices. The six treatments included conventional tillage (CT) or no tillage (NT), in combination with nitrogen type (URAN or chicken litter) and application method, biochar, or denitrification inhibitor. A randomized complete block design was applied with six replications. Leaf photosynthetic rate, transpiration, plant height, leaf area index (LAI), biomass, and yield were measured. Results showed that different agricultural practices had significant effects on plant leaf photosynthesis, transpiration, soil respiration, height, and yield, but not on LAI and biomass. The average corn yield in the NT-URAN was 10.03 ton/ha, 28.9% more than in the CT-URAN. Compared to the NT-URAN, the NT-biochar had lower soil respiration and similar yield. All variables measured showed remarkable variations among the three years. Our results indicated that no tillage treatment substantially increased corn yield, probably due to the preservation of soil moisture during drought periods.

  11. Long-range climate impacts on crop yield and the implications of enacting global carbon mitigation policies

    EPA Science Inventory

    Research on climate impacts and agriculture over the past two decades has applied simulation models at a range of scales and future climate scenarios, finding that crop growth and yield responds to changing climate conditions, and that the impacts are regional and highly depende...

  12. Field-scale experiments reveal persistent yield gaps in low-input and organic cropping systems.

    PubMed

    Kravchenko, Alexandra N; Snapp, Sieglinde S; Robertson, G Philip

    2017-01-31

    Knowledge of production-system performance is largely based on observations at the experimental plot scale. Although yield gaps between plot-scale and field-scale research are widely acknowledged, their extent and persistence have not been experimentally examined in a systematic manner. At a site in southwest Michigan, we conducted a 6-y experiment to test the accuracy with which plot-scale crop-yield results can inform field-scale conclusions. We compared conventional versus alternative, that is, reduced-input and biologically based-organic, management practices for a corn-soybean-wheat rotation in a randomized complete block-design experiment, using 27 commercial-size agricultural fields. Nearby plot-scale experiments (0.02-ha to 1.0-ha plots) provided a comparison of plot versus field performance. We found that plot-scale yields well matched field-scale yields for conventional management but not for alternative systems. For all three crops, at the plot scale, reduced-input and conventional managements produced similar yields; at the field scale, reduced-input yields were lower than conventional. For soybeans at the plot scale, biological and conventional managements produced similar yields; at the field scale, biological yielded less than conventional. For corn, biological management produced lower yields than conventional in both plot- and field-scale experiments. Wheat yields appeared to be less affected by the experimental scale than corn and soybean. Conventional management was more resilient to field-scale challenges than alternative practices, which were more dependent on timely management interventions; in particular, mechanical weed control. Results underscore the need for much wider adoption of field-scale experimentation when assessing new technologies and production-system performance, especially as related to closing yield gaps in organic farming and in low-resourced systems typical of much of the developing world.

  13. Field-scale experiments reveal persistent yield gaps in low-input and organic cropping systems

    PubMed Central

    Kravchenko, Alexandra N.; Snapp, Sieglinde S.; Robertson, G. Philip

    2017-01-01

    Knowledge of production-system performance is largely based on observations at the experimental plot scale. Although yield gaps between plot-scale and field-scale research are widely acknowledged, their extent and persistence have not been experimentally examined in a systematic manner. At a site in southwest Michigan, we conducted a 6-y experiment to test the accuracy with which plot-scale crop-yield results can inform field-scale conclusions. We compared conventional versus alternative, that is, reduced-input and biologically based–organic, management practices for a corn–soybean–wheat rotation in a randomized complete block-design experiment, using 27 commercial-size agricultural fields. Nearby plot-scale experiments (0.02-ha to 1.0-ha plots) provided a comparison of plot versus field performance. We found that plot-scale yields well matched field-scale yields for conventional management but not for alternative systems. For all three crops, at the plot scale, reduced-input and conventional managements produced similar yields; at the field scale, reduced-input yields were lower than conventional. For soybeans at the plot scale, biological and conventional managements produced similar yields; at the field scale, biological yielded less than conventional. For corn, biological management produced lower yields than conventional in both plot- and field-scale experiments. Wheat yields appeared to be less affected by the experimental scale than corn and soybean. Conventional management was more resilient to field-scale challenges than alternative practices, which were more dependent on timely management interventions; in particular, mechanical weed control. Results underscore the need for much wider adoption of field-scale experimentation when assessing new technologies and production-system performance, especially as related to closing yield gaps in organic farming and in low-resourced systems typical of much of the developing world. PMID:28096409

  14. Statistical rice yield modeling using blended MODIS-Landsat based crop phenology metrics in Taiwan

    NASA Astrophysics Data System (ADS)

    Chen, C. R.; Chen, C. F.; Nguyen, S. T.; Lau, K. V.

    2015-12-01

    Taiwan is a populated island with a majority of residents settled in the western plains where soils are suitable for rice cultivation. Rice is not only the most important commodity, but also plays a critical role for agricultural and food marketing. Information of rice production is thus important for policymakers to devise timely plans for ensuring sustainably socioeconomic development. Because rice fields in Taiwan are generally small and yet crop monitoring requires information of crop phenology associating with the spatiotemporal resolution of satellite data, this study used Landsat-MODIS fusion data for rice yield modeling in Taiwan. We processed the data for the first crop (Feb-Mar to Jun-Jul) and the second (Aug-Sep to Nov-Dec) in 2014 through five main steps: (1) data pre-processing to account for geometric and radiometric errors of Landsat data, (2) Landsat-MODIS data fusion using using the spatial-temporal adaptive reflectance fusion model, (3) construction of the smooth time-series enhanced vegetation index 2 (EVI2), (4) rice yield modeling using EVI2-based crop phenology metrics, and (5) error verification. The fusion results by a comparison bewteen EVI2 derived from the fusion image and that from the reference Landsat image indicated close agreement between the two datasets (R2 > 0.8). We analysed smooth EVI2 curves to extract phenology metrics or phenological variables for establishment of rice yield models. The results indicated that the established yield models significantly explained more than 70% variability in the data (p-value < 0.001). The comparison results between the estimated yields and the government's yield statistics for the first and second crops indicated a close significant relationship between the two datasets (R2 > 0.8), in both cases. The root mean square error (RMSE) and mean absolute error (MAE) used to measure the model accuracy revealed the consistency between the estimated yields and the government's yield statistics. This

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

    NASA Astrophysics Data System (ADS)

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

    2016-11-01

    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. SPEIG90 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

  16. 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. SPEIG90 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

  17. Could Crop Height Affect the Wind Resource at Agriculturally Productive Wind Farm Sites?

    NASA Astrophysics Data System (ADS)

    Vanderwende, Brian; Lundquist, Julie K.

    2016-03-01

    The collocation of cropland and wind turbines in the US Midwest region introduces complex meteorological interactions that could influence both agriculture and wind-power production. Crop management practices may affect the wind resource through alterations of land-surface properties. We use the weather research and forecasting (WRF) model to estimate the impact of crop height variations on the wind resource in the presence of a large turbine array. A hypothetical wind farm consisting of 121 1.8-MW turbines is represented using the WRF model wind-farm parametrization. We represent the impact of selecting soybeans rather than maize by altering the aerodynamic roughness length in a region approximately 65 times larger than that occupied by the turbine array. Roughness lengths of 0.1 and 0.25 m represent the mature soy crop and a mature maize crop, respectively. In all but the most stable atmospheric conditions, statistically significant hub-height wind-speed increases and rotor-layer wind-shear reductions result from switching from maize to soybeans. Based on simulations for the entire month of August 2013, wind-farm energy output increases by 14 %, which would yield a significant monetary gain. Further investigation is required to determine the optimal size, shape, and crop height of the roughness modification to maximize the economic benefit and minimize the cost of such crop-management practices. These considerations must be balanced by other influences on crop choice such as soil requirements and commodity prices.

  18. Could crop height affect the wind resource at agriculturally productive wind farm sites?

    SciTech Connect

    Vanderwende, Brian; Lundquist, Julie K.

    2015-11-07

    The collocation of cropland and wind turbines in the US Midwest region introduces complex meteorological interactions that could influence both agriculture and wind-power production. Crop management practices may affect the wind resource through alterations of land-surface properties. We use the weather research and forecasting (WRF) model to estimate the impact of crop height variations on the wind resource in the presence of a large turbine array. A hypothetical wind farm consisting of 121 1.8-MW turbines is represented using the WRF model wind-farm parametrization. We represent the impact of selecting soybeans rather than maize by altering the aerodynamic roughness length in a region approximately 65 times larger than that occupied by the turbine array. Roughness lengths of 0.1 and 0.25 m represent the mature soy crop and a mature maize crop, respectively. In all but the most stable atmospheric conditions, statistically significant hub-height wind-speed increases and rotor-layer wind-shear reductions result from switching from maize to soybeans. Based on simulations for the entire month of August 2013, wind-farm energy output increases by 14 %, which would yield a significant monetary gain. Further investigation is required to determine the optimal size, shape, and crop height of the roughness modification to maximize the economic benefit and minimize the cost of such crop-management practices. As a result, these considerations must be balanced by other influences on crop choice such as soil requirements and commodity prices.

  19. Research issues in determining the effects of changing climate variability on crop yields

    SciTech Connect

    Mearns, L.O.

    1995-12-31

    The authors discusses three aspects of research necessary for investigating possible effects of changes in climatic variability on crop yields. Additional information on changed variability effects is needed to further elucidate uncertainties in the knowledge of possible impacts of climate change on agriculture. First, sensitivity analyses of crop responses to shifting change in variability must be performed. Second, investigations of how climatic variability may change under perturbed climate conditions should be undertaken. If one has some confidence in estimates of how variability may change, then a third research task is the formation of climate change scenarios that incorporate changes in climatic variability and their application to crop-climate models to determine crop responses. In this chapter, these research tasks are discussed regarding one climate variable, precipitation. The authors summarize two research projects that have been undertaken to investigate the sensitivity of the CERES-wheat (Triticum aestivum L.) crop model to changes in climatic variability, on daily to annual time scales, for sites in the central Great Plains. He also provides an example of determining possible changes in daily variability of precipitation through analysis of results from two regional climate model experiments, and then go on to describe an example of forming a climate change scenario that incorporates changes in daily precipitation variability estimated from the regional model runs. 27 refs., 9 figs., 1 tab.

  20. Modeling the impact of conservation agriculture on crop production and soil properties in Mediterranean climate

    NASA Astrophysics Data System (ADS)

    Moussadek, Rachid; Mrabet, Rachid; Dahan, Rachid; Laghrour, Malika; Lembiad, Ibtissam; ElMourid, Mohamed

    2015-04-01

    In Morocco, rainfed agriculture is practiced in the majority of agricultural land. However, the intensive land use coupled to the irregular rainfall constitutes a serious threat that affect country's food security. Conservation agriculture (CA) represents a promising alternative to produce more and sustainably. In fact, the direct seeding showed high yield in arid regions of Morocco but its extending to other more humid agro-ecological zones (rainfall > 350mm) remains scarce. In order to promote CA in Morocco, differents trials have been installed in central plateau of Morocco, to compare CA to conventional tillage (CT). The yields of the main practiced crops (wheat, lentil and checkpea) under CA and CT were analyzed and compared in the 3 soils types (Vertisol, Cambisol and Calcisol). Also, we studied the effect of CA on soil organic matter (SOM) and soil losses (SL) in the 3 different sites. The APSIM model was used to model the long term impact of CA compared to CT. The results obtained in this research have shown favorable effects of CA on crop production, SOM and soil erosion. Key words: Conservation agriculture, yield, soil properties, modeling, APSIM, Morocco.

  1. Agricultural management change effects on river nutrient yields in a catchment of Central Greece

    NASA Astrophysics Data System (ADS)

    Panagopoulos, Y.

    2009-04-01

    Modelling efforts are strongly recommended nowadays by European legislation for investigating non-structural mitigation measures against water pollution on catchment scale. Agricultural diffuse pollution is considered to be the main responsible human activity for the Eutrophication of inland waters with nitrogen (N) and phosphorus (P). The physically-based water quality model SWAT is implemented in an agricultural medium-size agricultural catchment of Central Greece with the purpose to simulate the baseline situation and subsequently to predict the effects that realistic non-structural interventions, applied on the agricultural land, have on water quality and crop yields. SWAT was successfully calibrated according to measured flows and water quality data and subsequently scenarios were developed by changing chemical fertilizer application rates and timing on corn, cotton and wheat cultivations. All scenarios resulted in a decrease of nutrient emissions to surface waters but with a simultaneous small decrease in crop yields. The model predicted explicitly the consequences of non-structural mitigation measures against water pollution sustaining that the understanding of land management changes in relation to its driving factors provides essential information for sustainable management of the agricultural sector in an agricultural country like Greece.

  2. A Study of Estimating Winter Wheat Yields by Using Satellite Data Assimilation with Crop Growth Model

    NASA Astrophysics Data System (ADS)

    Kuwata, K.

    2013-12-01

    Accurate information of crop yield is important for production planning in agriculture. Crop growth model is a effective tool to comprehend crop growth situation. Accordingly, we use the MOSIS data for two types of utilization to provide necessary information for DSSAT. The objective of this study is developing a method of estimating winter wheat yield without adequate information of the field. The first use is estimation of solar radiation, which is required as input data into DSSAT. Since MODIS is observing the earth everyday, solar radiation can be estimated in a region where a climate observation system is not developed. The second use is data assimilation that provides appropriate parameter of cultivation management to DSSAT. MODIS LAI and Dry Matter Production (DMP) estimated from MODIS GPP are assimilated into DSSAT. Before developing data assimilation, we have accomplished sensitivity analysis of DSSAT. As the result of the analysis, we found that planting date and amount of applied fertilizer have correlated strongly with LAI and Dry Matter (DM) for specific growth period. Based on the result, we estimated winter wheat yield by assimilating MODIS LAI and DMP observed during the specific period. In contrast, previous study estimated crop yield by assimilating satellite data observed for the whole growth period. Three different assimilation schemes were tested to verify the accuracy of our method. Our results showed that the estimated winter wheat yield agreed very well with the Japanese agricultural experiment station data. Among different assimilating scenarios, the best result was obtained when MODIS LAI and DMP observed for specific growth period; the Root Square Mean Error (RMSE) was 406.52 kg ha2. The distribution map of full year incident PAR in Asia. Estimated Winter Wheat Yield in Japan In the case 1, detail information gathered by experiment reports.In the case 2, all management parameters are determined by reference to cultivation manuals.In the

  3. Agronomic conditions and crop evolution in ancient Near East agriculture.

    PubMed

    Araus, José L; Ferrio, Juan P; Voltas, Jordi; Aguilera, Mònica; Buxó, Ramón

    2014-05-23

    The appearance of agriculture in the Fertile Crescent propelled the development of Western civilization. Here we investigate the evolution of agronomic conditions in this region by reconstructing cereal kernel weight and using stable carbon and nitrogen isotope signatures of kernels and charcoal from a set of 11 Upper Mesopotamia archaeological sites, with chronologies spanning from the onset of agriculture to the turn of the era. We show that water availability for crops, inferred from carbon isotope discrimination (Δ(13)C), was two- to fourfold higher in the past than at present, with a maximum between 10,000 and 8,000 cal BP. Nitrogen isotope composition (δ(15)N) decreased over time, which suggests cultivation occurring under gradually less-fertile soil conditions. Domesticated cereals showed a progressive increase in kernel weight over several millennia following domestication. Our results provide a first comprehensive view of agricultural evolution in the Near East inferred directly from archaeobotanical remains.

  4. Agronomic conditions and crop evolution in ancient Near East agriculture

    PubMed Central

    Aguilera, Mònica; Buxó, Ramón

    2014-01-01

    The appearance of agriculture in the Fertile Crescent has propelled the development of Western civilization. Here we investigate the evolution of agronomic conditions in this region by reconstructing cereal kernel weight and using stable carbon and nitrogen isotope signatures of kernels and charcoal from a set of 11 Upper Mesopotamia archaeological sites, with chronologies spanning from the onset of agriculture to the turn of the era. We show that water availability for crops, inferred from carbon isotope discrimination (Δ13C), was two- to fourfold higher in the past than at present, with a maximum between 10,000 and 8,000 cal BP. Nitrogen isotope composition (δ15N) decreased over time, which suggests cultivation occurring under gradually less fertile soil conditions. Domesticated cereals showed a progressive increase in kernel weight over several millennia following domestication. Our results provide a first comprehensive view of agricultural evolution in the Near East inferred directly from archaeobotanical remains. PMID:24853475

  5. Dependency of global primary bioenergy crop potentials in 2050 on food systems, yields, biodiversity conservation and political stability.

    PubMed

    Erb, Karl-Heinz; Haberl, Helmut; Plutzar, Christoph

    2012-08-01

    The future bioenergy crop potential depends on (1) changes in the food system (food demand, agricultural technology), (2) political stability and investment security, (3) biodiversity conservation, (4) avoidance of long carbon payback times from deforestation, and (5) energy crop yields. Using a biophysical biomass-balance model, we analyze how these factors affect global primary bioenergy potentials in 2050. The model calculates biomass supply and demand balances for eleven world regions, eleven food categories, seven food crop types and two livestock categories, integrating agricultural forecasts and scenarios with a consistent global land use and NPP database. The TREND scenario results in a global primary bioenergy potential of 77 EJ/yr, alternative assumptions on food-system changes result in a range of 26-141 EJ/yr. Exclusion of areas for biodiversity conservation and inaccessible land in failed states reduces the bioenergy potential by up to 45%. Optimistic assumptions on future energy crop yields increase the potential by up to 48%, while pessimistic assumptions lower the potential by 26%. We conclude that the design of sustainable bioenergy crop production policies needs to resolve difficult trade-offs such as food vs. energy supply, renewable energy vs. biodiversity conservation or yield growth vs. reduction of environmental problems of intensive agriculture.

  6. Dependency of global primary bioenergy crop potentials in 2050 on food systems, yields, biodiversity conservation and political stability

    PubMed Central

    Erb, Karl-Heinz; Haberl, Helmut; Plutzar, Christoph

    2012-01-01

    The future bioenergy crop potential depends on (1) changes in the food system (food demand, agricultural technology), (2) political stability and investment security, (3) biodiversity conservation, (4) avoidance of long carbon payback times from deforestation, and (5) energy crop yields. Using a biophysical biomass-balance model, we analyze how these factors affect global primary bioenergy potentials in 2050. The model calculates biomass supply and demand balances for eleven world regions, eleven food categories, seven food crop types and two livestock categories, integrating agricultural forecasts and scenarios with a consistent global land use and NPP database. The TREND scenario results in a global primary bioenergy potential of 77 EJ/yr, alternative assumptions on food-system changes result in a range of 26–141 EJ/yr. Exclusion of areas for biodiversity conservation and inaccessible land in failed states reduces the bioenergy potential by up to 45%. Optimistic assumptions on future energy crop yields increase the potential by up to 48%, while pessimistic assumptions lower the potential by 26%. We conclude that the design of sustainable bioenergy crop production policies needs to resolve difficult trade-offs such as food vs. energy supply, renewable energy vs. biodiversity conservation or yield growth vs. reduction of environmental problems of intensive agriculture. PMID:23576836

  7. SWAT Ungauged: Hydrological Budget and Crop Yield Predictions in the Upper Mississippi River Basin

    SciTech Connect

    R. Srinivasan,; X. Zhang,; J. Arnold,

    2010-01-01

    Physically based, distributed hydrologic models are increasingly used in assessments of water resources, best management practices, and climate and land use changes. Model performance evaluation in ungauged basins is an important research topic. In this study, we propose a framework for developing Soil and Water Assessment Tool (SWAT) input data, including hydrography, terrain, land use, soil, tile, weather, and management practices, for the Upper Mississippi River basin (UMRB). We also present a performance evaluation of SWAT hydrologic budget and crop yield simulations in the UMRB without calibration. The uncalibrated SWAT model ably predicts annual streamflow at 11 USGS gauges and crop yield at a four-digit hydrologic unit code (HUC) scale. For monthly streamflow simulation, the performance of SWAT is marginally poor compared with that of annual flow, which may be due to incomplete information about reservoirs and dams within the UMRB. Further validation shows that SWAT can predict base flow contribution ratio reasonably well. Compared with three calibrated SWAT models developed in previous studies of the entire UMRB, the uncalibrated SWAT model presented here can provide similar results. Overall, the SWAT model can provide satisfactory predictions on hydrologic budget and crop yield in the UMRB without calibration. The results emphasize the importance and prospects of using accurate spatial input data for the physically based SWAT model. This study also examines biofuel-biomass production by simulating all agricultural lands with switchgrass, producing satisfactory results in estimating biomass availability for biofuel production.

  8. Dryland Crop Yields and Soil Organic Matter as Influenced by Long-Term Tillage and Cropping Sequence

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Novel management practices are needed to improve the declining dryland crop yields and soil organic matter using 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 of spring ...

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  10. Evaluation of preservation methods for improving biogas production and enzymatic conversion yields of annual crops

    PubMed Central

    2011-01-01

    Background The use of energy crops and agricultural residues is expected to increase to fulfil the legislative demands of bio-based components in transport fuels. Ensiling methods, adapted from the feed sector, are suitable storage methods to preserve fresh crops throughout the year for, for example, biogas production. Various preservation methods, namely ensiling with and without acid addition for whole crop maize, fibre hemp and faba bean were investigated. For the drier fibre hemp, alkaline urea treatment was studied as well. These treatments were also explored as mild pretreatment methods to improve the disassembly and hydrolysis of these lignocellulosic substrates. Results The investigated storage treatments increased the availability of the substrates for biogas production from hemp and in most cases from whole maize but not from faba bean. Ensiling of hemp, without or with addition of formic acid, increased methane production by more than 50% compared to fresh hemp. Ensiling resulted in substantially increased methane yields also from maize, and the use of formic acid in ensiling of maize further enhanced methane yields by 16%, as compared with fresh maize. Ensiled faba bean, in contrast, yielded somewhat less methane than the fresh material. Acidic additives preserved and even increased the amount of the valuable water-soluble carbohydrates during storage, which affected most significantly the enzymatic hydrolysis yield of maize. However, preservation without additives decreased the enzymatic hydrolysis yield especially in maize, due to its high content of soluble sugars that were already converted to acids during storage. Urea-based preservation significantly increased the enzymatic hydrolysability of hemp. Hemp, preserved with urea, produced the highest carbohydrate increase of 46% in enzymatic hydrolysis as compared to the fresh material. Alkaline pretreatment conditions of hemp improved also the methane yields. Conclusions The results of the present

  11. A multi-model analysis of change in potential yield of major crops in China under climate change

    NASA Astrophysics Data System (ADS)

    Yin, Y.; Tang, Q.; Liu, X.

    2015-02-01

    Climate change may affect crop growth and yield, which consequently casts a shadow of doubt over China's food self-sufficiency efforts. In this study, we used the projections derived from four global gridded crop models (GGCropMs) to assess the effects of future climate change on the yields of the major crops (i.e., maize, rice, soybean and wheat) in China. The GGCropMs were forced with the bias-corrected climate data from five global climate models (GCMs) under Representative Concentration Pathway (RCP) 8.5, which were made available through the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP). The results show that the potential yields of the crops would decrease in the 21st century without carbon dioxide (CO2) fertilization effect. With the CO2 effect, the potential yields of rice and soybean would increase, while the potential yields of maize and wheat would decrease. The uncertainty in yields resulting from the GGCropMs is larger than the uncertainty derived from GCMs in the greater part of China. Climate change may benefit rice and soybean yields in high-altitude and cold regions which are not in the current main agricultural area. However, the potential yields of maize, soybean and wheat may decrease in the major food production area. Development of new agronomic management strategies may be useful for coping with climate change in the areas with a high risk of yield reduction.

  12. Carbon payback times for crop-based biofuel expansion in the tropics: the effects of changing yield and technology

    NASA Astrophysics Data System (ADS)

    Gibbs, Holly K.; Johnston, Matt; Foley, Jonathan A.; Holloway, Tracey; Monfreda, Chad; Ramankutty, Navin; Zaks, David

    2008-07-01

    Biofuels from land-rich tropical countries may help displace foreign petroleum imports for many industrialized nations, providing a possible solution to the twin challenges of energy security and climate change. But concern is mounting that crop-based biofuels will increase net greenhouse gas emissions if feedstocks are produced by expanding agricultural lands. Here we quantify the 'carbon payback time' for a range of biofuel crop expansion pathways in the tropics. We use a new, geographically detailed database of crop locations and yields, along with updated vegetation and soil biomass estimates, to provide carbon payback estimates that are more regionally specific than those in previous studies. Using this cropland database, we also estimate carbon payback times under different scenarios of future crop yields, biofuel technologies, and petroleum sources. Under current conditions, the expansion of biofuels into productive tropical ecosystems will always lead to net carbon emissions for decades to centuries, while expanding into degraded or already cultivated land will provide almost immediate carbon savings. Future crop yield improvements and technology advances, coupled with unconventional petroleum supplies, will increase biofuel carbon offsets, but clearing carbon-rich land still requires several decades or more for carbon payback. No foreseeable changes in agricultural or energy technology will be able to achieve meaningful carbon benefits if crop-based biofuels are produced at the expense of tropical forests.

  13. Effects of potato-cotton cropping systems and nematicides on plant-parasitic nematodes and crop yields.

    PubMed

    Crow, W T; Weingartner, D P; Dickson, D W

    2000-09-01

    Belonolaimus longicaudatus has been reported as damaging both potato (Solanum tuberosum) and cotton (Gossypium hirsutum). These crops are not normally grown in cropping systems together in areas where the soil is infested with B. longicaudatus. During the 1990s cotton was grown in a potato production region that was a suitable habitat for B. longicaudatus. It was not known how integrating the production of these two crops by rotation or double-cropping would affect the population densities of B. longicaudatus, other plant-parasitic nematodes common in the region, or crop yields. A 3-year field study evaluated the viability of both crops in monocropping, rotation, and double-cropping systems. Viability was evaluated using effects on population densities of plant-parasitic nematodes and yields. Rotation of cotton with potato was found to decrease population densities of B. longicaudatus and Meloidogyne incognita in comparison with continuous potato. Population densities of B. longicaudatus following double-cropping were greater than following continuous cotton. Yields of both potato and cotton in rotation were equivalent to either crop in monocropping. Yields of both crops were lower following double-cropping when nematicides were not used.

  14. Soil carbon and nitrogen fractions and crop yields affected by residue placement and crop types.

    PubMed

    Wang, Jun; Sainju, Upendra M

    2014-01-01

    Soil labile C and N fractions can change rapidly in response to management practices compared to non-labile fractions. High variability in soil properties in the field, however, results in nonresponse to management practices on these parameters. We evaluated the effects of residue placement (surface application [or simulated no-tillage] and incorporation into the soil [or simulated conventional tillage]) and crop types (spring wheat [Triticum aestivum L.], pea [Pisum sativum L.], and fallow) on crop yields and soil C and N fractions at the 0-20 cm depth within a crop growing season in the greenhouse and the field. Soil C and N fractions were soil organic C (SOC), total N (STN), particulate organic C and N (POC and PON), microbial biomass C and N (MBC and MBN), potential C and N mineralization (PCM and PNM), NH4-N, and NO3-N concentrations. Yields of both wheat and pea varied with residue placement in the greenhouse as well as in the field. In the greenhouse, SOC, PCM, STN, MBN, and NH4-N concentrations were greater in surface placement than incorporation of residue and greater under wheat than pea or fallow. In the field, MBN and NH4-N concentrations were greater in no-tillage than conventional tillage, but the trend reversed for NO3-N. The PNM was greater under pea or fallow than wheat in the greenhouse and the field. Average SOC, POC, MBC, PON, PNM, MBN, and NO3-N concentrations across treatments were higher, but STN, PCM and NH4-N concentrations were lower in the greenhouse than the field. The coefficient of variation for soil parameters ranged from 2.6 to 15.9% in the greenhouse and 8.0 to 36.7% in the field. Although crop yields varied, most soil C and N fractions were greater in surface placement than incorporation of residue and greater under wheat than pea or fallow in the greenhouse than the field within a crop growing season. Short-term management effect on soil C and N fractions were readily obtained with reduced variability under controlled soil and

  15. The value of seasonal forecasting and crop mix adaptation to climate variability for agriculture under climate change

    NASA Astrophysics Data System (ADS)

    Choi, H. S.; Schneider, U.; Schmid, E.; Held, H.

    2012-04-01

    Changes to climate variability and frequency of extreme weather events are expected to impose damages to the agricultural sector. Seasonal forecasting and long range prediction skills have received attention as an option to adapt to climate change because seasonal climate and yield predictions could improve farmers' management decisions. The value of seasonal forecasting skill is assessed with a crop mix adaptation option in Spain where drought conditions are prevalent. Yield impacts of climate are simulated for six crops (wheat, barely, cotton, potato, corn and rice) with the EPIC (Environmental Policy Integrated Climate) model. Daily weather data over the period 1961 to 1990 are used and are generated by the regional climate model REMO as reference period for climate projection. Climate information and its consequent yield variability information are given to the stochastic agricultural sector model to calculate the value of climate information in the agricultural market. Expected consumers' market surplus and producers' revenue is compared with and without employing climate forecast information. We find that seasonal forecasting benefits not only consumers but also producers if the latter adopt a strategic crop mix. This mix differs from historical crop mixes by having higher shares of crops which fare relatively well under climate change. The corresponding value of information is highly sensitive to farmers' crop mix choices.

  16. Improving Biomass Yields: High Biomass, Low Input Dedicated Energy Crops to Enable a Full Scale Bioenergy Industry

    SciTech Connect

    2010-01-01

    Broad Funding Opportunity Announcement Project: Ceres is developing bigger and better grasses for use in biofuels. The bigger the grass yield, the more biomass, and more biomass means more biofuel per acre. Using biotechnology, Ceres is developing grasses that will grow bigger with less fertilizer than current grass varieties. Hardier, higher-yielding grass also requires less land to grow and can be planted in areas where other crops can’t grow instead of in prime agricultural land. Ceres is conducting multi-year trials in Arizona, Texas, Tennessee, and Georgia which have already resulted in grass yields with as much as 50% more biomass than yields from current grass varieties.

  17. Carbon consequences and agricultural implications of growing biofuel crops on marginal agricultural lands in China.

    PubMed

    Qin, Zhangcai; Zhuang, Qianlai; Zhu, Xudong; Cai, Ximing; Zhang, Xiao

    2011-12-15

    Using marginal agricultural lands to grow energy crops for biofuel feedstocks is a promising option to meet the biofuel needs in populous China without causing further food shortages or environmental problems. Here we quantify the effects of growing switchgrass and Miscanthus on Chinese marginal agricultural lands on biomass production and carbon emissions with a global-scale biogeochemical model. We find that the national net primary production (NPP) of these two biofuel crops are 622 and 1546 g C m(-2) yr(-1), respectively, whereas the NPP of food crops is about 600 g C m(-2) yr(-1) in China. The net carbon sink over the 47 Mha of marginal agricultural lands across China is 2.1 Tg C yr(-1) for switchgrass and 5.0 Tg C yr(-1) for Miscanthus. Soil organic carbon is estimated to be 10 kg C m(-2) in both biofuel ecosystems, which is equal to the soil carbon levels of grasslands in China. In order to reach the goal of 12.5 billion liters of bioethanol in 2020 using crop biomass as biofuel feedstocks, 7.9-8.0 Mha corn grain, 4.3-6.1 Mha switchgrass, or 1.4-2.0 Mha Miscanthus will be needed. Miscanthus has tremendous potential to meet future biofuel needs, and to benefit CO(2) mitigation in China.

  18. A review of the use of engineered nanomaterials to suppress plant disease and enhance crop yield

    NASA Astrophysics Data System (ADS)

    Servin, Alia; Elmer, Wade; Mukherjee, Arnab; De la Torre-Roche, Roberto; Hamdi, Helmi; White, Jason C.; Bindraban, Prem; Dimkpa, Christian

    2015-02-01

    Nanotechnology has the potential to play a critical role in global food production, food security, and food safety. The applications of nanotechnology in agriculture include fertilizers to increase plant growth and yield, pesticides for pest and disease management, and sensors for monitoring soil quality and plant health. Over the past decade, a number of patents and products incorporating nanomaterials into agricultural practices (e.g., nanopesticides, nanofertilizers, and nanosensors) have been developed. The collective goal of all of these approaches is to enhance the efficiency and sustainability of agricultural practices by requiring less input and generating less waste than conventional products and approaches. This review evaluates the current literature on the use of nanoscale nutrients (metals, metal oxides, carbon) to suppress crop disease and subsequently enhance growth and yield. Notably, this enhanced yield may not only be directly linked to the reduced presence of pathogenic organisms, but also to the potential nutritional value of the nanoparticles themselves, especially for the essential micronutrients necessary for host defense. We also posit that these positive effects are likely a result of the greater availability of the nutrients in the "nano" form. Last, we offer comments on the current regulatory perspective for such applications.

  19. Ecoinformatics Can Reveal Yield Gaps Associated with Crop-Pest Interactions: A Proof-of-Concept

    PubMed Central

    Rosenheim, Jay A.; Meisner, Matthew H.

    2013-01-01

    Farmers and private consultants execute a vast, decentralized data collection effort with each cropping cycle, as they gather pest density data to make real-time pest management decisions. Here we present a proof of concept for an ecoinformatics approach to pest management research, which attempts to harness these data to answer questions about pest-crop interactions. The impact of herbivory by Lygus hesperus on cotton is explored as a case study. Consultant-derived data satisfied a ‘positive control’ test for data quality by clearly resolving the expected negative relationship between L. hesperus density and retention of flower buds. The enhanced statistical power afforded by the large ecoinformatics dataset revealed an early-season window of crop sensitivity, during which L. hesperus densities as low as 1-2 per sample were associated with yield loss. In contrast, during the mid-season insecticide use by farmers was often unnecessary, as cotton compensated fully for moderate L. hesperus densities. Because the dataset emerged from the commercial production setting, it also revealed the limited degree to which farmers were willing to delay crop harvest to provide opportunities for compensatory fruiting. Observational approaches to pest management research have strengths and weaknesses that complement those of traditional, experimental approaches; combining these methods can contribute to enhanced agricultural productivity. PMID:24260408

  20. Ecoinformatics can reveal yield gaps associated with crop-pest interactions: a proof-of-concept.

    PubMed

    Rosenheim, Jay A; Meisner, Matthew H

    2013-01-01

    Farmers and private consultants execute a vast, decentralized data collection effort with each cropping cycle, as they gather pest density data to make real-time pest management decisions. Here we present a proof of concept for an ecoinformatics approach to pest management research, which attempts to harness these data to answer questions about pest-crop interactions. The impact of herbivory by Lygus hesperus on cotton is explored as a case study. Consultant-derived data satisfied a 'positive control' test for data quality by clearly resolving the expected negative relationship between L. hesperus density and retention of flower buds. The enhanced statistical power afforded by the large ecoinformatics dataset revealed an early-season window of crop sensitivity, during which L. hesperus densities as low as 1-2 per sample were associated with yield loss. In contrast, during the mid-season insecticide use by farmers was often unnecessary, as cotton compensated fully for moderate L. hesperus densities. Because the dataset emerged from the commercial production setting, it also revealed the limited degree to which farmers were willing to delay crop harvest to provide opportunities for compensatory fruiting. Observational approaches to pest management research have strengths and weaknesses that complement those of traditional, experimental approaches; combining these methods can contribute to enhanced agricultural productivity.

  1. Late Foliar Diseases in Wheat Crops Decrease Nitrogen Yield Through N Uptake Rather than Through Variations in N Remobilization

    PubMed Central

    Bancal, Marie-Odile; Roche, Romain; Bancal, Pierre

    2008-01-01

    Background and Aims French wheat grains may be of little value on world markets because they have low and highly variable grain protein concentrations (GPC). This nitrogen-yield to yield ratio depends on crop nitrogen (N) fertilization as well as on crop capacity to use N, which is known to vary with climate and disease severity. Here an examination is made of the respective roles that N remobilization and post-anthesis N uptake play in N yield variations; in particular, when wheat crops (Triticum aestivum) are affected by leaf rust (Puccinia triticina) and Septoria tritici blotch (teleomorph Mycosphaerella graminicola). Methods Data from a 4-year field experiment was used to analyse N yield variations in wheat crops grown either with a third or no late N fertilization. Natural aerial epidemics ensured a range of disease severity, and fungicide ensured disease-free control plots. The data set of Gooding et al. (2005, Journal of Agricultural Science 143: 503–518) was incorporated in order to enlarge the range of conditions. Key Results Post-anthesis N uptake accounted for a third of N yield whilst N remobilization accounted for two-thirds in all crops whether affected by diseases or not. However, variations in N yield were highly correlated with post-anthesis N uptake, more than with N remobilization, in diseased and also healthy crops. Furthermore, N remobilization did not significantly correlate with N yield in healthy crops. These findings matched data from studies using various wheat genotypes under various management and climatic conditions. Leaf area duration (LAD) accurately predicted N remobilization whether or not crops were diseased; in diseased crops, LAD also accurately predicted N uptake. Conclusions Under the experimental conditions, N yield variations were closely associated with post-anthesis N uptake in diseased but also in healthy crops. Understanding the respective roles of N uptake and N remobilization in the case of diseased and healthy crops

  2. Advances in regional crop yield estimation over the United States using satellite remote sensing data

    NASA Astrophysics Data System (ADS)

    Johnson, D. M.; Dorn, M. F.; Crawford, C.

    2015-12-01

    Since the dawn of earth observation imagery, particularly from systems like Landsat and the Advanced Very High Resolution Radiometer, there has been an overarching desire to regionally estimate crop production remotely. Research efforts integrating space-based imagery into yield models to achieve this need have indeed paralleled these systems through the years, yet development of a truly useful crop production monitoring system has been arguably mediocre in coming. As a result, relatively few organizations have yet to operationalize the concept, and this is most acute in regions of the globe where there are not even alternative sources of crop production data being collected. However, the National Agricultural Statistics Service (NASS) has continued to push for this type of data source as a means to complement its long-standing, traditional crop production survey efforts which are financially costly to the government and create undue respondent burden on farmers. Corn and soybeans, the two largest field crops in the United States, have been the focus of satellite-based production monitoring by NASS for the past decade. Data from the Moderate Resolution Imaging Spectroradiometer (MODIS) has been seen as the most pragmatic input source for modeling yields primarily based on its daily revisit capabilities and reasonable ground sample resolution. The research methods presented here will be broad but provides a summary of what is useful and adoptable with satellite imagery in terms of crop yield estimation. Corn and soybeans will be of particular focus but other major staple crops like wheat and rice will also be presented. NASS will demonstrate that while MODIS provides a slew of vegetation related products, the traditional normalized difference vegetation index (NDVI) is still ideal. Results using land surface temperature products, also generated from MODIS, will also be shown. Beyond the MODIS data itself, NASS research has also focused efforts on understanding a

  3. Food security in the 21st century: Global yield projections and agricultural expansion

    NASA Astrophysics Data System (ADS)

    Davis, K. F.; Rulli, M.; D'Odorico, P.

    2013-12-01

    Global demands on agricultural lands are ever increasing as a result of population growth, changes in diet and increasing biofuel use. By mid-century, the demands for food and fiber are expected to roughly double with the population reaching 9.5 billion. However, earth's finite resource base places a ceiling on the amount of agricultural production that is possible. Several strategies have been widely discussed to meet these rapid increases and to extend the ceiling yet higher, including reducing waste, modifying diets, improving yield and productivity and expanding agriculture and aquaculture. One of the most promising of these is closing the yield gap of currently under-performing agricultural land that has the potential to be much more productive. With high inputs (e.g. irrigation, fertilizers), this strategy has real potential to increase food security, particularly in the developing world where population is expected to sharply increase and where a high potential for yield gap closure exists. Thus it is important to consider whether improvements in global yield can adequately meet global dietary demand during the 21st century. Constructing yield projections to the end of the century, we examine whether global crop production for 154 countries and 16 major food crops under selected agricultural and dietary scenarios can keep pace with estimates of population growth to 2100. By calculating the global production of calories, we are then able to examine how many people can be supported under future scenarios and how closing yield gaps can increase this potential. Our findings agree with previous studies that closing the yield gap alone cannot provide sufficient production by mid-century and that a heavy global dependence on trade will persist throughout the century. Using high-resolution global land suitability maps under a suite of climate models, we find that scenarios incorporating a combination of yield gap closure and agricultural expansion provide the most

  4. GM crops in Ethiopia: a realistic way to increase agricultural performance?

    PubMed

    Azadi, Hossein; Talsma, Nanda; Ho, Peter; Zarafshani, Kiumars

    2011-01-01

    Much has been published on the application of genetically modified (GM) crops in Africa, but agricultural performance has hardly been addressed. This paper discusses the main consequences of GM crops on agricultural performance in Ethiopia. Three main criteria of performance - productivity, equitability and sustainability - are evaluated in the context of the Ethiopian agricultural sector. We conclude that the application of GM crops can improve the agricultural productivity and sustainability, whereas equitability cannot be stimulated and might even exacerbate the gap between socioeconomic classes. Before introducing GM crops to Ethiopian agriculture, regulatory issues should be addressed, public research should be fostered, and more ex ante values and socioeconomic studies should be included.

  5. Analysis of Climate Change Impact on U.S. Crop Yields with Reanalysis Data

    NASA Astrophysics Data System (ADS)

    Kuwata, K.

    2014-12-01

    Increasing the world population, food security in the sense of supplying enough food has become more important. Cereals are considerable matter in food security issues, and production of cereals are heavily threatened by climate change. In 2012, terrible drought which might happen once in a hundred years, caused massive damage to the soybean and corn harvest. This event had impact on the agriculture industry in U.S., and led drastic increase of commodity price. To ensuring food security, influence of climate risk to food production should be comprehended quantitatively. We used ERA-Interim which includes temperature, dew-point, pressure, precipitation, solar radiation and wind speed product, to analyze the world condition of climate changes, and calculated warmth index and dew-point depression. Kira (1977) developed warmth index which has close relationship between distribution of plants living. Dew-point depression represents the wetness of atmosphere. Also, we analyzed crop yields statistics from USDA to clarify what kind of climate condition affect crop yields. Figure 1 shows variance distribution of warmth index. It can be said that area where contains high value of variance, is subject to extreme climatic changes. Figure 2 is a distribution map indicating whether warmth index was higher or lower than average value. In 2012, it was very hot in the wide range of the Russia and North America. Figure 3 shows correlation between yield index and ERA-Interim climate data at each month. Crop yields have been in trend of increasing because technology enhancements such as improving of breeds and cultivation have been occurred. Therefore, we calculated simple moving average as normal value and calculated yield index by dividing the normal value and annual yields (left Figure 3). If yield index was under 100, it was harvest failure in that year. In contrast, if yield index was higher than 100, it was good harvest in that year. In this result, temperature, warmth index and

  6. Attenuation of urban agricultural production potential and crop water footprint due to shading from buildings and trees

    NASA Astrophysics Data System (ADS)

    Johnson, Mark S.; Lathuillière, Michael J.; Tooke, Thoreau R.; Coops, Nicholas C.

    2015-06-01

    Urban agriculture requires local water to replace ‘hydrologic externalities’ associated with food produced outside of the local area, with an accompanying shift of the water footprint (WF) for agricultural production from rural to urban areas. Water requirements of urban agriculture have been difficult to estimate due to the heterogeneity of shading from trees and buildings within urban areas. We developed CityCrop, a plant growth and evapotranspiration (ET) model that couples a 3D model of tree canopies and buildings derived from LiDAR with a ray-casting approach to estimate spatially-explicit solar inputs in combination with local climate data. Evaluating CityCrop over a 1 km2 mixed use, residential neighborhood of Vancouver Canada, we estimated median light attenuation to result in 12% reductions in both reference ET (ETo) and crop ET (ETc). However, median crop yields were reduced by only 3.5% relative to potential yield modeled without any light attenuation, while the median crop WF was 9% less than the WF for areas unimpeded by shading. Over the 75 day cropping cycle, median crop water requirements as ETc were 17% less than that required for a well-watered grass (as ETo). If all lawns in our modeled area were replaced with crops, we estimate that about 37% of the resident population could obtain the vegetable portion of their diet from within the local area over a 150 day growing season. However doing so would result in augmented water demand if watering restrictions apply to lawns only. The CityCrop model can therefore be useful to evaluate trade-offs related to urban agriculture and to inform municipal water policy development.

  7. ORECCL - Summary of a national database on energy crop landbase, yields, and costs

    SciTech Connect

    Graham, R.L.; Allison, L.J.; Becker, D.A.

    1997-07-01

    The Biofuels Feedstock Development Program at Oak Ridge National Laboratory has developed a county-level database on energy crops-the Oak Ridge Energy Crop County-Level database (RECCL). This database encompasses all U.S. counties and provides easy access to energy crop information specific to a state or county. The database contains predictions of energy crop yields and farmgate prices along with county-level data on the acreage of land suitable for energy crop production. This paper describes the database and presents state-level summary statistics on land suitable for energy crop production and average predicted yields and farmgate prices.

  8. 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

    2016-09-01

    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.

  9. Enhancing crop yield with the use of N-based fertilizers co-applied with plant hormones or growth regulators.

    PubMed

    Zaman, Mohammad; Kurepin, Leonid V; Catto, Warwick; Pharis, Richard P

    2015-07-01

    Crop yield, vegetative or reproductive, depends on access to an adequate supply of essential mineral nutrients. At the same time, a crop plant's growth and development, and thus yield, also depend on in situ production of plant hormones. Thus optimizing mineral nutrition and providing supplemental hormones are two mechanisms for gaining appreciable yield increases. Optimizing the mineral nutrient supply is a common and accepted agricultural practice, but the co-application of nitrogen-based fertilizers with plant hormones or plant growth regulators is relatively uncommon. Our review discusses possible uses of plant hormones (gibberellins, auxins, cytokinins, abscisic acid and ethylene) and specific growth regulators (glycine betaine and polyamines) to enhance and optimize crop yield when co-applied with nitrogen-based fertilizers. We conclude that use of growth-active gibberellins, together with a nitrogen-based fertilizer, can result in appreciable and significant additive increases in shoot dry biomass of crops, including forage crops growing under low-temperature conditions. There may also be a potential for use of an auxin or cytokinin, together with a nitrogen-based fertilizer, for obtaining additive increases in dry shoot biomass and/or reproductive yield. Further research, though, is needed to determine the potential of co-application of nitrogen-based fertilizers with abscisic acid, ethylene and other growth regulators.

  10. Crop yield changes induced by emissions of individual climate-altering pollutants

    NASA Astrophysics Data System (ADS)

    Shindell, Drew T.

    2016-08-01

    Climate change damages agriculture, causing deteriorating food security and increased malnutrition. Many studies have examined the role of distinct physical processes, but impacts have not been previously attributed to individual pollutants. Using a simple model incorporating process-level results from detailed models, here I show that although carbon dioxide (CO2) is the largest driver of climate change, other drivers appear to dominate agricultural yield changes. I calculate that anthropogenic emissions to date have decreased global agricultural yields by 9.5 ± 3.0%, with roughly 93% stemming from non-CO2 emissions, including methane (-5.2 ± 1.7%) and halocarbons (-1.4 ± 0.4%). The differing impacts stem from atmospheric composition responses: CO2 fertilizes crops, offsetting much of the loss induced by warming; halocarbons do not fertilize; methane leads to minimal fertilization but increases surface ozone which augments warming-induced losses. By the end of the century, strong CO2 mitigation improves agricultural yields by ˜3 ± 5%. In contrast, strong methane and hydrofluorocarbon mitigation improve yields by ˜16 ± 5% and ˜5 ± 4%, respectively. These are the first quantitative analyses to include climate, CO2 and ozone simultaneously, and hence, additional studies would be valuable. Nonetheless, as policy makers have leverage over pollutant emissions rather than isolated processes, the perspective presented here may be more useful for decision making than that in the prior work upon which this study builds. The results suggest that policies should target a broad portfolio of pollutant emissions in order to optimize mitigation of societal damages.

  11. Fly ash application in nutrient poor agriculture soils: impact on methanotrophs population dynamics and paddy yields.

    PubMed

    Singh, Jay Shankar; Pandey, Vimal Chandra

    2013-03-01

    There are reports that the application of fly ash, compost and press mud or a combination thereof, improves plant growth, soil microbial communities etc. Also, fly ash in combination with farmyard manure or other organic amendments improves soil physico-chemical characteristics, rice yield and microbial processes in paddy fields. However, the knowledge about the impact of fly ash inputs alone or in combination with other organic amendments on soil methanotrophs number in paddy soils is almost lacking. We hypothesized that fly ash application at lower doses in paddy agriculture soil could be a potential amendment to elevate the paddy yields and methanotrophs number. Here we demonstrate the impact of fly ash and press mud inputs on number of methanotrophs, antioxidants, antioxidative enzymatic activities and paddy yields at agriculture farm. The impact of amendments was significant for methanotrophs number, heavy metal concentration, antioxidant contents, antioxidant enzymatic activities and paddy yields. A negative correlation was existed between higher doses of fly ash-treatments and methanotrophs number (R(2)=0.833). The content of antioxidants and enzymatic activities in leaves of higher doses fly ash-treated rice plants increased in response to stresses due to heavy metal toxicity, which was negatively correlated with rice grain yield (R(2)=0.944) and paddy straw yield (R(2)=0.934). A positive correlation was noted between heavy metals concentrations and different antioxidant and enzymatic activities across different fly ash treated plots.The data of this study indicate that heavy metal toxicity of fly ash may cause oxidative stress in the paddy crop and the antioxidants and related enzymes could play a defensive role against phytotoxic damages. We concluded that fly ash at lower doses with press mud seems to offer the potential amendments to improving soil methanotrophs population and paddy crop yields for the nutrient poor agriculture soils.

  12. Evaluation of crop yield loss of floods based on water turbidity index with multi-temporal HJ-CCD images

    NASA Astrophysics Data System (ADS)

    Gu, Xiaohe; Xu, Peng; Wang, Lei; Wang, Xiuhui

    2015-12-01

    Paddy is one of the most important food crops in China. Due to the intensive planting in the surrounding of rivers and lakes, paddy is vulnerable to flooding stress. The research on predicting crop yield loss derived from flooding stress will help the adjustment of crop planting structure and the claims of agricultural insurance. The paper aimed to develop a method of estimating yield loss of paddy derived from flooding by multi-temporal HJ CCD images. At first, the water pixels after flooding were extracted, from which the water line (WL) of turbid water pixels was generated. Secondly, the water turbidity index (WTI) and perpendicular vegetation index (PVI) was defined and calculated. By analyzing the relation among WTI, PVI and paddy yield, the model of evaluating yield loss of flooding was developed. Based on this model, the spatial distribution of paddy yield loss derived from flooding was mapped in the study area. Results showed that the water turbidity index (WTI) could be used to monitor the sediment content of flood, which was closely related to the plant physiology and per unit area yield of paddy. The PVI was the good indicator of paddy yield with significant correlation (0.965). So the PVI could be used to estimate the per unit area yield before harvesting. The PVI and WTI had good linear relation, which could provide an effective, practical and feasible method for monitoring yield loss of waterlogged paddy.

  13. Economic Analysis of Energy Crop Production in the U.S. - Location, Quantities, Price, and Impacts on Traditional Agricultural Crops

    SciTech Connect

    Walsh, M.E.; De La Torre Ugarte, D.; Slinsky, S.; Graham, R.L.; Shapouri, H.; Ray, D.

    1998-10-04

    POLYSYS is used to estimate US locations where, for any given energy crop price, energy crop production can be economically competitive with conventional crops. POLYSYS is a multi-crop, multi-sector agricultural model developed and maintained by the University of Tennessee and used by the USDA-Economic Research Service. It includes 305 agricultural statistical districts (ASD) which can be aggregated to provide state, regional, and national information. POLYSYS is being modified to include switchgrass, hybrid poplar, and willow on all land suitable for their production. This paper summarizes the preliminary national level results of the POLYSYS analysis for selected energy crop prices for the year 2007 and presents the corresponding maps (for the same prices) of energy crop production locations by ASD. Summarized results include: (1) estimates of energy crop hectares (acres) and quantities (dry Mg, dry tons), (2) identification of traditional crops allocated to energy crop production and calculation of changes in their prices and hectares (acres) of production, and (3) changes in total net farm returns for traditional agricultural crops. The information is useful for identifying areas of the US where large quantities of lowest cost energy crops can most likely be produced.

  14. Development of an unmanned agricultural robotics system for measuring crop conditions for precision aerial application

    Technology Transfer Automated Retrieval System (TEKTRAN)

    An Unmanned Agricultural Robotics System (UARS) is acquired, rebuilt with desired hardware, and operated in both classrooms and field. The UARS includes crop height sensor, crop canopy analyzer, normalized difference vegetative index (NDVI) sensor, multispectral camera, and hyperspectral radiometer...

  15. Energy from biological processes. Volume III. Appendixes, Part B: Agriculture, unconventional crops, and select biomass wastes

    SciTech Connect

    Not Available

    1980-09-01

    This volume contains the following working papers written for OTA to assist in preparation of the report, Energy from Biological Processes: The Potential of Producing Energy From Agriculture; Cropland Availability for Biomass Production; Energy From Agriculture: Unconventional Crops; Energy From Aquaculture Biomass Systems: Fresh and Brackish Water Aquatic Plants; Energy From Agriculture: Animal Wastes; and Energy From Agriculture: Agricultural Processing Wastes.

  16. Assessment of the availability of agricultural crop residues in the European Union: potential and limitations for bioenergy use.

    PubMed

    Scarlat, Nicolae; Martinov, Milan; Dallemand, Jean-François

    2010-10-01

    This paper provides a resource-based assessment of the available agricultural crop residues for bioenergy production in the European Union, at the level of the 27 Member States. The assessment provides the amount of the residues produced, collected, their present uses and the residues left available for bioenergy. This study considers the crop production and yields and multi-annual yield variation for each crop. The calculation was based on specific residues to product ratios, which were determined, depending on the crop type and crop yield. Sustainable removal rates were considered in order to protect soil fertility. The results show large spatial and temporal variations of available crop residues within EU27. The average amount of crop residues available for bioenergy in EU27 was estimated at 1530 PJ/year, with a variation between 1090 and 1900 PJ/year. The average value represents about 3.2% in final energy consumption in the EU27 while the variation 2.3-4%. This variation, which is even larger at the level of Member States, may result in shortages in biomass supply in some years, when crop residues are available in a lower amount than the average.

  17. The Potato Systems Planner: Integrating Cropping System Impacts on Crop Yield and Quality, Soil Biology, Nutrient Cycling, Diseases, and Economics

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Finding and developing profitable cropping systems is a high priority for the potato industry. Consequently, an interdisciplinary team of ARS scientists from the New England Plant, Soil, & Water Laboratory evaluated 14 different rotations for their impacts on crop yield and quality, nutrient availa...

  18. A study on agricultural drought vulnerability at disaggregated level in a highly irrigated and intensely cropped state of India.

    PubMed

    Murthy, C S; Yadav, Manoj; Mohammed Ahamed, J; Laxman, B; Prawasi, R; Sesha Sai, M V R; Hooda, R S

    2015-03-01

    Drought is an important global hazard, challenging the sustainable agriculture and food security of nations. Measuring agricultural drought vulnerability is a prerequisite for targeting interventions to improve and sustain the agricultural performance of both irrigated and rain-fed agriculture. In this study, crop-generic agricultural drought vulnerability status is empirically measured through a composite index approach. The study area is Haryana state, India, a prime agriculture state of the country, characterised with low rainfall, high irrigation support and stable cropping pattern. By analysing the multiyear rainfall and crop condition data of kharif crop season (June-October) derived from satellite data and soil water holding capacity and groundwater quality, nine contributing indicators were generated for 120 blocks (sub-district administrative units). Composite indices for exposure, sensitivity and adaptive capacity components were generated after assigning variance-based weightages to the respective input indicators. Agricultural Drought Vulnerability Index (ADVI) was developed through a linear combination of the three component indices. ADVI-based vulnerability categorisation revealed that 51 blocks are with vulnerable to very highly vulnerable status. These blocks are located in the southern and western parts of the state, where groundwater quality is saline and water holding capacity of soils is less. The ADVI map has effectively captured the spatial pattern of agricultural drought vulnerability in the state. Districts with large number of vulnerable blocks showed considerably larger variability of de-trended crop yields. Correlation analysis reveals that crop condition variability, groundwater quality and soil factors are closely associated with ADVI. The vulnerability index is useful to prioritise the blocks for implementation of long-term drought management plans. There is scope for improving the methodology by adding/fine-tuning the indicators and

  19. Modeling Long-Term Corn Yield Response to Nitrogen Rate and Crop Rotation

    PubMed Central

    Puntel, Laila A.; Sawyer, John E.; Barker, Daniel W.; Dietzel, Ranae; Poffenbarger, Hanna; Castellano, Michael J.; Moore, Kenneth J.; Thorburn, Peter; Archontoulis, Sotirios V.

    2016-01-01

    Improved prediction of optimal N fertilizer rates for corn (Zea mays L.) can reduce N losses and increase profits. We tested the ability of the Agricultural Production Systems sIMulator (APSIM) to simulate corn and soybean (Glycine max L.) yields, the economic optimum N rate (EONR) using a 16-year field-experiment dataset from central Iowa, USA that included two crop sequences (continuous corn and soybean-corn) and five N fertilizer rates (0, 67, 134, 201, and 268 kg N ha-1) applied to corn. Our objectives were to: (a) quantify model prediction accuracy before and after calibration, and report calibration steps; (b) compare crop model-based techniques in estimating optimal N rate for corn; and (c) utilize the calibrated model to explain factors causing year to year variability in yield and optimal N. Results indicated that the model simulated well long-term crop yields response to N (relative root mean square error, RRMSE of 19.6% before and 12.3% after calibration), which provided strong evidence that important soil and crop processes were accounted for in the model. The prediction of EONR was more complex and had greater uncertainty than the prediction of crop yield (RRMSE of 44.5% before and 36.6% after calibration). For long-term site mean EONR predictions, both calibrated and uncalibrated versions can be used as the 16-year mean differences in EONR’s were within the historical N rate error range (40–50 kg N ha-1). However, for accurate year-by-year simulation of EONR the calibrated version should be used. Model analysis revealed that higher EONR values in years with above normal spring precipitation were caused by an exponential increase in N loss (denitrification and leaching) with precipitation. We concluded that long-term experimental data were valuable in testing and refining APSIM predictions. The model can be used as a tool to assist N management guidelines in the US Midwest and we identified five avenues on how the model can add value toward

  20. Modeling Long-Term Corn Yield Response to Nitrogen Rate and Crop Rotation.

    PubMed

    Puntel, Laila A; Sawyer, John E; Barker, Daniel W; Dietzel, Ranae; Poffenbarger, Hanna; Castellano, Michael J; Moore, Kenneth J; Thorburn, Peter; Archontoulis, Sotirios V

    2016-01-01

    Improved prediction of optimal N fertilizer rates for corn (Zea mays L.) can reduce N losses and increase profits. We tested the ability of the Agricultural Production Systems sIMulator (APSIM) to simulate corn and soybean (Glycine max L.) yields, the economic optimum N rate (EONR) using a 16-year field-experiment dataset from central Iowa, USA that included two crop sequences (continuous corn and soybean-corn) and five N fertilizer rates (0, 67, 134, 201, and 268 kg N ha(-1)) applied to corn. Our objectives were to: (a) quantify model prediction accuracy before and after calibration, and report calibration steps; (b) compare crop model-based techniques in estimating optimal N rate for corn; and (c) utilize the calibrated model to explain factors causing year to year variability in yield and optimal N. Results indicated that the model simulated well long-term crop yields response to N (relative root mean square error, RRMSE of 19.6% before and 12.3% after calibration), which provided strong evidence that important soil and crop processes were accounted for in the model. The prediction of EONR was more complex and had greater uncertainty than the prediction of crop yield (RRMSE of 44.5% before and 36.6% after calibration). For long-term site mean EONR predictions, both calibrated and uncalibrated versions can be used as the 16-year mean differences in EONR's were within the historical N rate error range (40-50 kg N ha(-1)). However, for accurate year-by-year simulation of EONR the calibrated version should be used. Model analysis revealed that higher EONR values in years with above normal spring precipitation were caused by an exponential increase in N loss (denitrification and leaching) with precipitation. We concluded that long-term experimental data were valuable in testing and refining APSIM predictions. The model can be used as a tool to assist N management guidelines in the US Midwest and we identified five avenues on how the model can add value toward

  1. Fly ash-amended compost as a manure for agricultural crops

    SciTech Connect

    Menon, M.P.; Sajwan, K.S.; Ghuman, G.S.; James, J.; Chandra, K. )

    1993-11-01

    Homemade organic compost prepared from lawn grass clippings was amended with fine fly ash collected from a coal-fired power plant (SRS 484.D. Savannah River Site, Aiken, SC) to investigate its usefulness as a manure in enhancing nutrient uptake and increasing dry matter yield in selected agricultural crops. Three treatments were compared: five crops (mustard, collard, string beans, bell pepper, and eggplant) were each grown on three kinds of soil: soil alone, soil amended with composted grass clippings, and soil amended with the mixed compost of grass clippings and 20% fly ash. The fly ash-amended compost was found to be effective in enhancing the dry matter yield of collard greens and mustard greens by 378% and 348%, respectively, but string beans, bell pepper, and eggplant did not show any significant increase in dry matter yield. Analysis of the above-ground biomass of these last three plants showed they assimilated high levels of boron, which is phytotoxic; and this may be the reason for their poor growth. Soils treated with fly ash-amended compost often gave higher concentrations than the control for K, Ca, Mg, S, Zn, and B in the Brassica crops. 18 refs., 2 figs., 5 tabs.

  2. Environmental effects of growing short-rotation woody crops on former agricultural lands

    SciTech Connect

    Tolbert, V.R.; Thornton, F.C.; Joslin, J.D.

    1997-10-01

    Field-scale studies in the Southeast have been addressing the environmental effects of converting agricultural lands to biomass crop production since 1994. Erosion, surface water quality and quantity and subsurface movement of water and nutrients from woody crops, switchgrass and agricultural crops are being compared. Nutrient cycling, soil physical changes and crop productivity are also being monitored at the three sites. Maximum sediment losses occurred in the spring and fall. Losses were greater from sweetgum planted without a cover crop than with a cover crop. Nutrient losses of N and P in runoff and subsurface water occurred primarily after spring fertilizer application.

  3. Could crop height affect the wind resource at agriculturally productive wind farm sites?

    DOE PAGES

    Vanderwende, Brian; Lundquist, Julie K.

    2015-11-07

    The collocation of cropland and wind turbines in the US Midwest region introduces complex meteorological interactions that could influence both agriculture and wind-power production. Crop management practices may affect the wind resource through alterations of land-surface properties. We use the weather research and forecasting (WRF) model to estimate the impact of crop height variations on the wind resource in the presence of a large turbine array. A hypothetical wind farm consisting of 121 1.8-MW turbines is represented using the WRF model wind-farm parametrization. We represent the impact of selecting soybeans rather than maize by altering the aerodynamic roughness length inmore » a region approximately 65 times larger than that occupied by the turbine array. Roughness lengths of 0.1 and 0.25 m represent the mature soy crop and a mature maize crop, respectively. In all but the most stable atmospheric conditions, statistically significant hub-height wind-speed increases and rotor-layer wind-shear reductions result from switching from maize to soybeans. Based on simulations for the entire month of August 2013, wind-farm energy output increases by 14 %, which would yield a significant monetary gain. Further investigation is required to determine the optimal size, shape, and crop height of the roughness modification to maximize the economic benefit and minimize the cost of such crop-management practices. As a result, these considerations must be balanced by other influences on crop choice such as soil requirements and commodity prices.« less

  4. Global bioenergy potentials from agricultural land in 2050: Sensitivity to climate change, diets and yields

    PubMed Central

    Haberl, Helmut; Erb, Karl-Heinz; Krausmann, Fridolin; Bondeau, Alberte; Lauk, Christian; Müller, Christoph; Plutzar, Christoph; Steinberger, Julia K.

    2011-01-01

    There is a growing recognition that the interrelations between agriculture, food, bioenergy, and climate change have to be better understood in order to derive more realistic estimates of future bioenergy potentials. This article estimates global bioenergy potentials in the year 2050, following a “food first” approach. It presents integrated food, livestock, agriculture, and bioenergy scenarios for the year 2050 based on a consistent representation of FAO projections of future agricultural development in a global biomass balance model. The model discerns 11 regions, 10 crop aggregates, 2 livestock aggregates, and 10 food aggregates. It incorporates detailed accounts of land use, global net primary production (NPP) and its human appropriation as well as socioeconomic biomass flow balances for the year 2000 that are modified according to a set of scenario assumptions to derive the biomass potential for 2050. We calculate the amount of biomass required to feed humans and livestock, considering losses between biomass supply and provision of final products. Based on this biomass balance as well as on global land-use data, we evaluate the potential to grow bioenergy crops and estimate the residue potentials from cropland (forestry is outside the scope of this study). We assess the sensitivity of the biomass potential to assumptions on diets, agricultural yields, cropland expansion and climate change. We use the dynamic global vegetation model LPJmL to evaluate possible impacts of changes in temperature, precipitation, and elevated CO2 on agricultural yields. We find that the gross (primary) bioenergy potential ranges from 64 to 161 EJ y−1, depending on climate impact, yields and diet, while the dependency on cropland expansion is weak. We conclude that food requirements for a growing world population, in particular feed required for livestock, strongly influence bioenergy potentials, and that integrated approaches are needed to optimize food and bioenergy supply

  5. Global bioenergy potentials from agricultural land in 2050: Sensitivity to climate change, diets and yields.

    PubMed

    Haberl, Helmut; Erb, Karl-Heinz; Krausmann, Fridolin; Bondeau, Alberte; Lauk, Christian; Müller, Christoph; Plutzar, Christoph; Steinberger, Julia K

    2011-12-01

    There is a growing recognition that the interrelations between agriculture, food, bioenergy, and climate change have to be better understood in order to derive more realistic estimates of future bioenergy potentials. This article estimates global bioenergy potentials in the year 2050, following a "food first" approach. It presents integrated food, livestock, agriculture, and bioenergy scenarios for the year 2050 based on a consistent representation of FAO projections of future agricultural development in a global biomass balance model. The model discerns 11 regions, 10 crop aggregates, 2 livestock aggregates, and 10 food aggregates. It incorporates detailed accounts of land use, global net primary production (NPP) and its human appropriation as well as socioeconomic biomass flow balances for the year 2000 that are modified according to a set of scenario assumptions to derive the biomass potential for 2050. We calculate the amount of biomass required to feed humans and livestock, considering losses between biomass supply and provision of final products. Based on this biomass balance as well as on global land-use data, we evaluate the potential to grow bioenergy crops and estimate the residue potentials from cropland (forestry is outside the scope of this study). We assess the sensitivity of the biomass potential to assumptions on diets, agricultural yields, cropland expansion and climate change. We use the dynamic global vegetation model LPJmL to evaluate possible impacts of changes in temperature, precipitation, and elevated CO(2) on agricultural yields. We find that the gross (primary) bioenergy potential ranges from 64 to 161 EJ y(-1), depending on climate impact, yields and diet, while the dependency on cropland expansion is weak. We conclude that food requirements for a growing world population, in particular feed required for livestock, strongly influence bioenergy potentials, and that integrated approaches are needed to optimize food and bioenergy supply.

  6. Mapping Human-Dominated Landscapes: the Distribution and Yield of Major Crops of the World

    NASA Astrophysics Data System (ADS)

    Monfreda, C.; Ramankutty, N.; Foley, J. A.

    2005-12-01

    Croplands cover 18 million km2, an area the size of South America, and provide ecosystem goods and services essential to human well-being. Most global land-cover classifications group the diversity of croplands into a single or very few categories, thereby excluding critical information to answer key questions ranging from biodiversity conservation to food security to biogeochemical cycling. Information on land-use practices is even more limited. The relative lack of information about agricultural landscapes results partly from difficulties in using satellite data to identify individual crop types and land-use practices at a global scale. We address limitations common to remote-sensing classifications by distributing national, state, and county level statistics across a recently updated global dataset of cropland cover at 5 minute resolution. The resulting datasets depict the fractional harvested area and yield of twenty distinct crop types: maize, wheat, rice, sorghum, millet, barley, oats, soybeans, sunflower, rapeseed/canola, pulses, groundnuts/peanuts, oil palm, cassava, potatoes, sugar cane, sugar beets, tobacco, coffee, and cotton. These datasets represent the state of agriculture circa the year 2000 and will be made available for applications in ecological analysis, modeling, visualization, and education.

  7. Increasing Crop Yields in Water Stressed Countries by Combining Operations of Freshwater Reservoir and Wastewater Reclamation Plant

    NASA Astrophysics Data System (ADS)

    Bhushan, R.; Ng, T. L.

    2015-12-01

    Freshwater resources around the world are increasing in scarcity due to population growth, industrialization and climate change. This is a serious concern for water stressed countries, including those in Asia and North Africa where future food production is expected to be negatively affected by this. To address this problem, we investigate the potential of combining freshwater reservoir and wastewater reclamation operations. Reservoir water is the cheaper source of irrigation, but is often limited and climate sensitive. Treated wastewater is a more reliable alternative for irrigation, but often requires extensive further treatment which can be expensive. We propose combining the operations of a reservoir and a wastewater reclamation plant (WWRP) to augment the supply from the reservoir with reclaimed water for increasing crop yields in water stressed regions. The joint system of reservoir and WWRP is modeled as a multi-objective optimization problem with the double objective of maximizing the crop yield and minimizing total cost, subject to constraints on reservoir storage, spill and release, and capacity of the WWRP. We use the crop growth model Aquacrop, supported by The Food and Agriculture Organization of the United Nations (FAO), to model crop growth in response to water use. Aquacrop considers the effects of water deficit on crop growth stages, and from there estimates crop yield. We generate results comparing total crop yield under irrigation with water from just the reservoir (which is limited and often interrupted), and yield with water from the joint system (which has the potential of higher supply and greater reliability). We will present results for locations in India and Africa to evaluate the potential of the joint operations for improving food security in those areas for different budgets.

  8. 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

  9. Mass-flowering crops dilute pollinator abundance in agricultural landscapes across Europe.

    PubMed

    Holzschuh, Andrea; Dainese, Matteo; González-Varo, Juan P; Mudri-Stojnić, Sonja; Riedinger, Verena; Rundlöf, Maj; Scheper, Jeroen; Wickens, Jennifer B; Wickens, Victoria J; Bommarco, Riccardo; Kleijn, David; Potts, Simon G; Roberts, Stuart P M; Smith, Henrik G; Vilà, Montserrat; Vujić, Ante; Steffan-Dewenter, Ingolf

    2016-10-01

    Mass-flowering crops (MFCs) are increasingly cultivated and might influence pollinator communities in MFC fields and nearby semi-natural habitats (SNHs). Across six European regions and 2 years, we assessed how landscape-scale cover of MFCs affected pollinator densities in 408 MFC fields and adjacent SNHs. In MFC fields, densities of bumblebees, solitary bees, managed honeybees and hoverflies were negatively related to the cover of MFCs in the landscape. In SNHs, densities of bumblebees declined with increasing cover of MFCs but densities of honeybees increased. The densities of all pollinators were generally unrelated to the cover of SNHs in the landscape. Although MFC fields apparently attracted pollinators from SNHs, in landscapes with large areas of MFCs they became diluted. The resulting lower densities might negatively affect yields of pollinator-dependent crops and the reproductive success of wild plants. An expansion of MFCs needs to be accompanied by pollinator-supporting practices in agricultural landscapes.

  10. Remotely sensed vegetation indices for seasonal crop yields predictions in the Czech Republic

    NASA Astrophysics Data System (ADS)

    Hlavinka, Petr; Semerádová, Daniela; Balek, Jan; Bohovic, Roman; Žalud, Zdeněk; Trnka, Miroslav

    2015-04-01

    Remotely sensed vegetation indices by satellites are valuable tool for vegetation conditions assessment also in the case of field crops. This study is based on the use of NDVI (Normalized Difference Vegetation Index) and EVI (Enhanced Vegetation Index) derived from MODIS (Moderate Resolution Imaging Spectroradiometer) aboard Terra satellite. Data available from the year 2000 were analyzed and tested for seasonal yields predictions within selected districts of the Czech Republic (Central Europe). Namely the yields of spring barley, winter wheat and oilseed winter rape during the period from 2000 to 2014 were assessed. Observed yields from 14 districts (NUTS 4) were collected and thus 210 seasons were included. Selected districts differ considerably in their soil fertility and terrain configuration and represent transect across various agroclimatic conditions (from warm and dry to relative cool and wet regions). Two approaches were tested: 1) using of composite remotely sensed data (available in 16 day time step) provided by the USGS (https://lpdaac.usgs.gov/); 2) using daily remotely sensed data in combination with originally developed smoothing method. The yields were successfully predicted based on established regression models (remotely sensed data used as independent parameter). Besides others the impact of severe drought episodes within vegetation were identified and yield reductions at district level predicted (even before harvest). As a result the periods with the best relationship between remotely sensed data and yields were identified. The impact of drought conditions as well as normal or above normal yields of field crops could be predicted by proposed method within study region up to 30 days prior to the harvest. It could be concluded that remotely sensed vegetation conditions assessment should be important part of early warning systems focused on drought. Such information should be widely available for various users (decision makers, farmers, etc.) in

  11. Reusable Software and Open Data Incorporate Ecological Understanding To Optimize Agriculture and Improveme Crops.

    NASA Astrophysics Data System (ADS)

    LeBauer, D.

    2015-12-01

    Humans need a secure and sustainable food supply, and science can help. We have an opportunity to transform agriculture by combining knowledge of organisms and ecosystems to engineer ecosystems that sustainably produce food, fuel, and other services. The challenge is that the information we have. Measurements, theories, and laws found in publications, notebooks, measurements, software, and human brains are difficult to combine. We homogenize, encode, and automate the synthesis of data and mechanistic understanding in a way that links understanding at different scales and across domains. This allows extrapolation, prediction, and assessment. Reusable components allow automated construction of new knowledge that can be used to assess, predict, and optimize agro-ecosystems. Developing reusable software and open-access databases is hard, and examples will illustrate how we use the Predictive Ecosystem Analyzer (PEcAn, pecanproject.org), the Biofuel Ecophysiological Traits and Yields database (BETYdb, betydb.org), and ecophysiological crop models to predict crop yield, decide which crops to plant, and which traits can be selected for the next generation of data driven crop improvement. A next step is to automate the use of sensors mounted on robots, drones, and tractors to assess plants in the field. The TERRA Reference Phenotyping Platform (TERRA-Ref, terraref.github.io) will provide an open access database and computing platform on which researchers can use and develop tools that use sensor data to assess and manage agricultural and other terrestrial ecosystems. TERRA-Ref will adopt existing standards and develop modular software components and common interfaces, in collaboration with researchers from iPlant, NEON, AgMIP, USDA, rOpenSci, ARPA-E, many scientists and industry partners. Our goal is to advance science by enabling efficient use, reuse, exchange, and creation of knowledge.

  12. An integrated landscape designed for commodity and bioenergy crops for a tile-drained agricultural watershed

    SciTech Connect

    Ssegane, Herbert; Negri, M. Cristina

    2016-09-16

    Here, locating bioenergy crops on strategically selected subfield areas of marginal interest for commodity agriculture can increase environmental sustainability. Location and choice of bioenergy crops should improve environmental benefits with minimal disruption of current food production systems. We identified subfield soils of a tile-drained agricultural watershed as marginal if they had areas of low crop productivity index (CPI), were susceptible to nitrate-nitrogen (NO3–N) leaching, or were susceptible to at least two other forms of environmental degradation (marginal areas). In the test watershed (Indian Creek watershed, IL) with annual precipitation of 852 mm, 3% of soils were CPI areas and 22% were marginal areas. The Soil and Water Assessment Tool was used to forecast the impact of growing switchgrass (Panicum virgatum L.), willow (Salix spp.), and big bluestem (Andropogon gerardi Vitman) in these subfield areas on annual grain yields, NO3–N and sediment exports, and water yield. Simulated conversion of CPI areas from current land use to bioenergy crops had no significant (p ≤ 0.05) impact on grain production and reduced NO3–N and sediment exports by 5.0 to 6.0% and 3.0%, respectively. Conversion of marginal areas from current land use to switchgrass forecasted the production of 34,000 t of biomass and reductions in NO3–N (26.0%) and sediment (33.0%) exports. Alternatively, conversion of marginal areas from current land use to willow forecasted similar reductions as switchgrass for sediment but significantly (p ≤ 0.01) lower reductions in annual NO3–N export (18.0 vs. 26.0%).

  13. An integrated landscape designed for commodity and bioenergy crops for a tile-drained agricultural watershed

    DOE PAGES

    Ssegane, Herbert; Negri, M. Cristina

    2016-09-16

    Here, locating bioenergy crops on strategically selected subfield areas of marginal interest for commodity agriculture can increase environmental sustainability. Location and choice of bioenergy crops should improve environmental benefits with minimal disruption of current food production systems. We identified subfield soils of a tile-drained agricultural watershed as marginal if they had areas of low crop productivity index (CPI), were susceptible to nitrate-nitrogen (NO3–N) leaching, or were susceptible to at least two other forms of environmental degradation (marginal areas). In the test watershed (Indian Creek watershed, IL) with annual precipitation of 852 mm, 3% of soils were CPI areas and 22%more » were marginal areas. The Soil and Water Assessment Tool was used to forecast the impact of growing switchgrass (Panicum virgatum L.), willow (Salix spp.), and big bluestem (Andropogon gerardi Vitman) in these subfield areas on annual grain yields, NO3–N and sediment exports, and water yield. Simulated conversion of CPI areas from current land use to bioenergy crops had no significant (p ≤ 0.05) impact on grain production and reduced NO3–N and sediment exports by 5.0 to 6.0% and 3.0%, respectively. Conversion of marginal areas from current land use to switchgrass forecasted the production of 34,000 t of biomass and reductions in NO3–N (26.0%) and sediment (33.0%) exports. Alternatively, conversion of marginal areas from current land use to willow forecasted similar reductions as switchgrass for sediment but significantly (p ≤ 0.01) lower reductions in annual NO3–N export (18.0 vs. 26.0%).« less

  14. An Integrated Landscape Designed for Commodity and Bioenergy Crops for a Tile-Drained Agricultural Watershed.

    PubMed

    Ssegane, Herbert; Negri, M Cristina

    2016-09-01

    Locating bioenergy crops on strategically selected subfield areas of marginal interest for commodity agriculture can increase environmental sustainability. Location and choice of bioenergy crops should improve environmental benefits with minimal disruption of current food production systems. We identified subfield soils of a tile-drained agricultural watershed as marginal if they had areas of low crop productivity index (CPI), were susceptible to nitrate-nitrogen (NO-N) leaching, or were susceptible to at least two other forms of environmental degradation (marginal areas). In the test watershed (Indian Creek watershed, IL) with annual precipitation of 852 mm, 3% of soils were CPI areas and 22% were marginal areas. The Soil and Water Assessment Tool was used to forecast the impact of growing switchgrass ( L.), willow ( spp.), and big bluestem ( Vitman) in these subfield areas on annual grain yields, NO-N and sediment exports, and water yield. Simulated conversion of CPI areas from current land use to bioenergy crops had no significant ( 0.05) impact on grain production and reduced NO-N and sediment exports by 5.0 to 6.0% and 3.0%, respectively. Conversion of marginal areas from current land use to switchgrass forecasted the production of 34,000 t of biomass and reductions in NO-N (26.0%) and sediment (33.0%) exports. Alternatively, conversion of marginal areas from current land use to willow forecasted similar reductions as switchgrass for sediment but significantly ( 0.01) lower reductions in annual NO-N export (18.0 vs. 26.0%).

  15. Hybridization of powdery mildew strains gives rise to pathogens on novel agricultural crop species.

    PubMed

    Menardo, Fabrizio; Praz, Coraline R; Wyder, Stefan; Ben-David, Roi; Bourras, Salim; Matsumae, Hiromi; McNally, Kaitlin E; Parlange, Francis; Riba, Andrea; Roffler, Stefan; Schaefer, Luisa K; Shimizu, Kentaro K; Valenti, Luca; Zbinden, Helen; Wicker, Thomas; Keller, Beat

    2016-02-01

    Throughout the history of agriculture, many new crop species (polyploids or artificial hybrids) have been introduced to diversify products or to increase yield. However, little is known about how these new crops influence the evolution of new pathogens and diseases. Triticale is an artificial hybrid of wheat and rye, and it was resistant to the fungal pathogen powdery mildew (Blumeria graminis) until 2001 (refs. 1,2,3). We sequenced and compared the genomes of 46 powdery mildew isolates covering several formae speciales. We found that B. graminis f. sp. triticale, which grows on triticale and wheat, is a hybrid between wheat powdery mildew (B. graminis f. sp. tritici) and mildew specialized on rye (B. graminis f. sp. secalis). Our data show that the hybrid of the two mildews specialized on two different hosts can infect the hybrid plant species originating from those two hosts. We conclude that hybridization between mildews specialized on different species is a mechanism of adaptation to new crops introduced by agriculture.

  16. 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.

  17. Soil and rainfall factors influencing yields of a dryland cropping system in Colorado

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The semi-arid Great Plains of the United States experience a large variation in crop yields due to variability in rainfall, soil, and other factors. We analyzed crop yields (24-year period) from a no-till rotation of wheat(Triticum aestivum)-corn (Zea mays L.) or sorghum[Sorghum bicolor (L.) Moench]...

  18. Soil nitrate and forage yields of corn grown with clover or grass companion crops and manure

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Few studies have compared the agronomic performance of cover crop and living mulch systems for no-till silage corn (Zea mays L.). In a four-year Wisconsin study, we compared soil nitrate levels, dry matter yields (DMY) and crude protein yields (CPY) from five such corn-companion crop systems amended...

  19. Corn and soybean grain yields in a long-term tillage and cropping systems study

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Reports on the long-term effects of tillage and cropping systems on corn and soybean yields are limited. Yields have been measured in a long-term experiment (30+ years) with three cropping systems [continuous corn (CC), continuous soybean (CSB), and soybean-corn (SB-C)] in six primary tillage system...

  20. Agricultural drought risk monitoring and yield loss forecast with remote sensing data

    NASA Astrophysics Data System (ADS)

    Nagy, Attila; Tamás, János; Fehér, János

    2015-04-01

    The World Meteorological Organization (WMO) and Global Water Partnership (GWP) have launched a joint Integrated Drought Management Programme (IDMP) to improve monitoring and prevention of droughts. In the frame of this project this study focuses on identification of agricultural drought characteristics and elaborates a monitoring method (with application of remote sensing data), which could result in appropriate early warning of droughts before irreversible yield loss and/or quality degradation occur. The spatial decision supporting system to be developed will help the farmers in reducing drought risk of the different regions by plant specific calibrated drought indexes. The study area was the Tisza River Basin, which is located in Central Europe within the Carpathian Basin. For the investigations normalized difference vegetation index (NDVI) was used calculated from 16 day moving average chlorophyll intensity and biomass quantity data. The results offer concrete identification of remote sensing and GIS data tools for agricultural drought monitoring and forecast, which eventually provides information on physical implementation of drought risk levels. In the first step, we statistically normalized the crop yield maps and the MODIS satellite data. Then the drought-induced crop yield loss values were classified. The crop yield loss data were validated against the regional meteorological drought index values (SPI), the water management and soil physical data. The objective of this method was to determine the congruency of data derived from spectral data and from field measurements. As a result, five drought risk levels were developed to identify the effect of drought on yields: Watch, Early Warning, Warning, Alert and Catastrophe. In the frame of this innovation such a data link and integration, missing from decision process of IDMP, are established, which can facilitate the rapid spatial and temporal monitoring of meteorological, agricultural drought phenomena and its

  1. Farming the planet: 2. Geographic distribution of crop areas, yields, physiological types, and net primary production in the year 2000

    NASA Astrophysics Data System (ADS)

    Monfreda, Chad; Ramankutty, Navin; Foley, Jonathan A.

    2008-03-01

    Croplands cover ~15 million km2 of the planet and provide the bulk of the food and fiber essential to human well-being. Most global land cover data sets from satellites group croplands into just a few categories, thereby excluding information that is critical for answering key questions ranging from biodiversity conservation to food security to biogeochemical cycling. Information about agricultural land use practices like crop selection, yield, and fertilizer use is even more limited. Here we present land use data sets created by combining national, state, and county level census statistics with a recently updated global data set of croplands on a 5 min by 5 min (~10 km by 10 km) latitude-longitude grid. The resulting land use data sets depict circa the year 2000 the area (harvested) and yield of 175 distinct crops of the world. We aggregate these individual crop maps to produce novel maps of 11 major crop groups, crop net primary production, and four physiologically based crop types: annuals/perennials, herbaceous/shrubs/trees, C3/C4, and leguminous/nonleguminous.

  2. Assessments of Maize Yield Potential in the Korean Peninsula Using Multiple Crop Models

    NASA Astrophysics Data System (ADS)

    Kim, S. H.; Myoung, B.; Lim, C. H.; Lee, S. G.; Lee, W. K.; Kafatos, M.

    2015-12-01

    The Korean Peninsular has unique agricultural environments due to the differences in the political and socio-economical systems between the Republic of Korea (SK, hereafter) and the Democratic Peoples' Republic of Korea (NK, hereafter). NK has been suffering from the lack of food supplies caused by natural disasters, land degradation and failed political system. The neighboring developed country SK has a better agricultural system but very low food self-sufficiency rate (around 1% of maize). Maize is an important crop in both countries since it is staple food for NK and SK is No. 2 maize importing country in the world after Japan. Therefore evaluating maize yield potential (Yp) in the two distinct regions is essential to assess food security under climate change and variability. In this study, we have utilized multiple process-based crop models capable of regional-scale assessments to evaluate maize Yp over the Korean Peninsula - the GIS version of EPIC model (GEPIC) and APSIM model that can be expanded to regional scales (APSIM regions). First we evaluated model performance and skill for 20 years from 1991 to 2010 using reanalysis data (Local Data Assimilation and Prediction System (LDAPS); 1.5km resolution) and observed data. Each model's performances were compared over different regions within the Korean Peninsula of different regional climate characteristics. To quantify the major influence of individual climate variables, we also conducted a sensitivity test using 20 years of climatology. Lastly, a multi-model ensemble analysis was performed to reduce crop model uncertainties. The results will provide valuable information for estimating the climate change or variability impacts on Yp over the Korean Peninsula.

  3. Agricultural Issues of Significance to Iowa Crop Producers and Their Educational Implications

    ERIC Educational Resources Information Center

    Licht, Melea A. R.; Martin, Robert A.

    2007-01-01

    The purpose of this study was to determine the agricultural information preferences of crop producers in Iowa and the implications for agricultural extension education. The objective was to identify agricultural information issues producers perceive as significant to their businesses. The results will help agricultural extension educators and…

  4. Assessing Sediment Yield for Selected Watersheds in the Laurentian Great Lakes Basin Under Future Agricultural Scenarios

    NASA Astrophysics Data System (ADS)

    Shao, Yang; Lunetta, Ross S.; Macpherson, Alexander J.; Luo, Junyan; Chen, Guo

    2013-01-01

    In the Laurentian Great Lakes Basin (GLB), corn acreage has been expanding since 2005 in response to high demand for corn as an ethanol feedstock. This study integrated remote sensing-derived products and the Soil and Water Assessment Tool (SWAT) within a geographic information system (GIS) modeling environment to assess the impacts of cropland change on sediment yield within four selected watersheds in the GLB. The SWAT models were calibrated during a 6 year period (2000-2005), and predicted stream flows were validated. The R 2 values were 0.76, 0.80, 0.72, and 0.81 for the St. Joseph River, the St. Mary River, the Peshtigo River, and the Cattaraugus Creek watersheds, respectively. The corresponding E (Nash and Sutcliffe model efficiency coefficient) values ranged from 0.24 to 0.79. The average annual sediment yields (tons/ha/year) ranged from 0.12 to 4.44 for the baseline (2000 to 2008) condition. Sediment yields were predicted to increase for possible future cropland change scenarios. The first scenario was to convert all "other" agricultural row crop types (i.e., sorghum) to corn fields and switch the current/baseline crop rotation into continuous corn. The average annual sediment yields increased 7-42 % for different watersheds. The second scenario was to further expand the corn planting to hay/pasture fields. The average annual sediment yields increased 33-127 % compared with baseline conditions.

  5. Assessing sediment yield for selected watersheds in the Laurentian Great Lakes Basin under future agricultural scenarios.

    PubMed

    Shao, Yang; Lunetta, Ross S; Macpherson, Alexander J; Luo, Junyan; Chen, Guo

    2013-01-01

    In the Laurentian Great Lakes Basin (GLB), corn acreage has been expanding since 2005 in response to high demand for corn as an ethanol feedstock. This study integrated remote sensing-derived products and the Soil and Water Assessment Tool (SWAT) within a geographic information system (GIS) modeling environment to assess the impacts of cropland change on sediment yield within four selected watersheds in the GLB. The SWAT models were calibrated during a 6 year period (2000-2005), and predicted stream flows were validated. The R(2) values were 0.76, 0.80, 0.72, and 0.81 for the St. Joseph River, the St. Mary River, the Peshtigo River, and the Cattaraugus Creek watersheds, respectively. The corresponding E (Nash and Sutcliffe model efficiency coefficient) values ranged from 0.24 to 0.79. The average annual sediment yields (tons/ha/year) ranged from 0.12 to 4.44 for the baseline (2000 to 2008) condition. Sediment yields were predicted to increase for possible future cropland change scenarios. The first scenario was to convert all "other" agricultural row crop types (i.e., sorghum) to corn fields and switch the current/baseline crop rotation into continuous corn. The average annual sediment yields increased 7-42 % for different watersheds. The second scenario was to further expand the corn planting to hay/pasture fields. The average annual sediment yields increased 33-127 % compared with baseline conditions.

  6. Rice Yield Estimation Through Assimilating Satellite Data Into a Crop Simumlation Model

    NASA Astrophysics Data System (ADS)

    Son, N. T.; Chen, C. F.; Chen, C. R.; Chang, L. Y.; Chiang, S. H.

    2016-06-01

    Rice is globally the most important food crop, feeding approximately half of the world's population, especially in Asia where around half of the world's poorest people live. Thus, advanced spatiotemporal information of rice crop yield during crop growing season is critically important for crop management and national food policy making. The main objective of this study was to develop an approach to integrate remotely sensed data into a crop simulation model (DSSAT) for rice yield estimation in Taiwan. The data assimilation was processed to integrate biophysical parameters into DSSAT model for rice yield estimation using the particle swarm optimization (PSO) algorithm. The cost function was constructed based on the differences between the simulated leaf area index (LAI) and MODIS LAI, and the optimization process starts from an initial parameterization and accordingly adjusts parameters (e.g., planting date, planting population, and fertilizer amount) in the crop simulation model. The fitness value obtained from the cost function determined whether the optimization algorithm had reached the optimum input parameters using a user-defined tolerance. The results of yield estimation compared with the government's yield statistics indicated the root mean square error (RMSE) of 11.7% and mean absolute error of 9.7%, respectively. This study demonstrated the applicability of satellite data assimilation into a crop simulation model for rice yield estimation, and the approach was thus proposed for crop yield monitoring purposes in the study region.

  7. The Economic Impacts of Bioenergy Crop Production on U.S. Agriculture

    SciTech Connect

    Dr. Daniel De La Torre Ugarte

    2000-07-01

    The oil embargoes of the 1970s raised concerns about energy security. Large scale production of bioenergy crops could have significant impacts on the US agricultural sector in terms of quantities, prices and production location of traditional crops as well as farm income. USDA, UT and ORNL modified an agricultural sector model to include switchgrass, hybrid poplar, and willow.

  8. Incorporating climate change trends to near future variability of crop yields in Iberia Peninsula

    NASA Astrophysics Data System (ADS)

    Capa-Morocho, Mirian; Baethgen, Walter E.; Fernandes, Kátia; Rodríguez-Fonseca, Belén; Ruiz-Ramos, Margarita

    2016-04-01

    In this study, we analyze the effects of near future climate variability on cropping systems in Iberian Peninsula (IP). For this purpose, we generated climate sequences that simulate realistic variability on annual to decadal time scales. The sequences incorporate nonlinear climate change trends, using statistical methods and and an ensemble of global climate models from the Coupled Model Intercomparison Project (CMIP5). Then, the climate sequences are temporal downscaled into daily weather data and used as inputs to crop models. As case study, we evaluate the impacts of plausible future climate scenarios on rain-fed wheat yield two agricultural locations in IP. We adapted the method by Greene et al., (2012 and 2015) for informing climate projections for the coming decades with a combination of seasonal to interannual and anthropogenically forced climate change information for accounting the Near-term Climate Change. Long-term data containing solar radiation, maximum and minimum temperature and rainfall are needed to apply this method. The climate variability observed was decomposed into long-range trend, decadal and interannual variability to understand the relative importance of each time scale. The interannual variability was modeled based on the observational records. The results of this study may have important implications on public and private sectors to analyze the probabilistic projections of impacts and agronomic adaptations of near future climate variability in Iberian Peninsula. This study has been funded by MACSUR project from FACCE-JPI. References Greene, A.M., Goddard, L., Gonzalez, P.L., Ines, A.V. and Chryssanthacopoulos, J., 2015.A climate generator for agricultural planning in southeastern South America.Agricultural and Forest Meteorology, 203: 217-228. Greene, A.M., Hellmuth, M. and Lumsden, T., 2012. Stochastic decadal climate simulations for the Berg and Breede water management areas, western Cape province, South Africa. Water Resources

  9. Climate Change Impacts on Water and Crop Yields in the Glacial Dominated Beas River Basin in India

    NASA Astrophysics Data System (ADS)

    Holman, I.; Remesan, R.; Ojha, C. S. P. S.; Adeloye, A. J.

    2014-12-01

    Himalayan valleys are confronting severe climate change related issues (floods in summer, flash flood and landslides, water scarcity in higher altitudes) because of fluctuating monsoon precipitation and increasing seasonal temperatures. In this study, the Soil and Water Assessment Tool (SWAT) model is applied to the River Beas basin, using daily Tropical Rainfall Measuring Mission (TRMM) precipitation and NCEP Climate Forecast System Reanalysis (CFSR) meteorological data to simulate the river regime and crop yields. The Beas is regionally significant as it holds two giant dams, one which annually diverts 4700 Mm3 of water to a nearby basin. We have applied Sequential Uncertainty Fitting Ver. 2 (SUFI-2) to quantify the parameter uncertainty of the stream flow modelling. The model evaluation statistics for Daily River flows at the Jwalamukhi and Pong gauges show good agreement with measured flows (Nash Sutcliffe efficiency of 0.70 and PBIAS of 7.54 %). We then applied the models within a scenario-neutral framework to develop hydrological and crop yield Impact Response Surfaces (IRS) for future changes in annual temperature and precipitation for the region from AR5. Future Q10 and Q90 daily flows indicate amplified 'flash flood' situations and increased low flows, respectively, with increasing temperatures due to increased snowmelt from retreating glaciers. Under existing crop and irrigation management practices, the IRS show decreasing and increasing crop yields for summer (monsoon) and winter (post monsoon) crops, respectively, with rising temperature. Climate change scenario studies shows that, the sensitivity of winter (post monsoon) crop yields to precipitation increases with increasing temperature. The paper will consider the implications of the research for future agricultural water resource management and the potential of adaptation to offset yield losses

  10. The potential of agricultural practices to increase C storage in cropped soils: an assessment for France

    NASA Astrophysics Data System (ADS)

    Chenu, Claire; Angers, Denis; Métay, Aurélie; Colnenne, Caroline; Klumpp, Katja; Bamière, Laure; Pardon, Lenaic; Pellerin, Sylvain

    2014-05-01

    Though large progress has been achieved in the last decades, net GHG emissions from the agricultural sector are still more poorly quantified than in other sectors. In this study, we examined i) technical mitigation options likely to store carbon in agricultural soils, ii) their potential of additional C storage per unit surface area and iii) applicable areas in mainland France. We considered only agricultural practices being technically feasible by farmers and involving no major change in either production systems or production levels. Moreover, only currently available techniques with validated efficiencies and presenting no major negative environmental impacts were taken into account. Four measures were expected to store additional C in agricultural soils: - Reducing tillage: either a switch to continuous direct seeding, direct seeding with occasional tillage once every five years, or continuous superficial (<15 cm) tillage. - Introducing cover crops in cropping systems: sown between two cash crops on arable farms, in orchards and vineyards (permanent or temporary cover cropping) . - Expanding agroforestry systems; planting of tree lines in cultivated fields and grasslands, and hedges around the field edges. - Increasing the life time of temporary sown grasslands: increase of life time to 5 years. The recent literature was reviewed in order to determine long term (>20yrs) C storage rates (MgC ha-1 y-1,) of cropping systems with and without the proposed practice. Then we analysed the conditions for potential application, in terms of feasibility, acceptance, limitation of yield losses and of other GHG emissions. According to the literature, additional C storage rates were 0.15 (0-0.3) MgC ha-1 y-1 for continuous direct seeding, 0.10 (0-0.2) MgC ha-1 y-1for occasional tillage one year in five, and 0.0 MgC ha-1 y-1 for superficial tillage. Cover crops were estimated to store 0.24 (0.13-0.37) MgC ha-1 y-1 between cash crops and 0.49 (0.23-0.72) MgC ha-1 y-1 when

  11. 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.

  12. Estimated Yield of Some Alternative Crops Under Varying Irrigation in Northeast Colorado

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Much of the irrigated acres in northeastern Colorado are devoted to corn grain production. Diversifying irrigated agricultural production in this region could result in water savings if alternative crops were grown that have lower water requirements than corn. Making such crop choice decisions initi...

  13. Integrating sheep grazing into cereal-based crop rotations: spring wheat yields and weed communities

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Crop diversification and integration of livestock into cropping systems may improve the economic and environmental sustainability of agricultural systems. However, few studies have examined the integration of these practices in the semiarid areas of the Northern Great Plains (NGP). A 3-yr experiment...

  14. Simulation of winter wheat yield and its uncertainty band; A comparison of two crop growth models

    NASA Astrophysics Data System (ADS)

    Javad Khordadi Varamini, Mohammad; Nassiri Mahallati, Mehdi; Alizadeh, Amin

    2016-04-01

    In this study, we used the WOFOST and AquaCrop crop growth simulation models to examine crop yield responses to a set of plausible scenarios of climate change in Mashhad region, located in Ghareghom basin, northeast of Iran up to 2040. We selected winter wheat as an indicator crop. Also six AOGCMs including GFCM21, HADCM3, INCM3, IPCM4, MPEH5 and NCCCSM under A2 and B1 emission scenarios are used. LARS-WG statistical method for downscaling is utilized. In the present research, using 7-year observed crop data, the crop models were calibrated and then validated. Evaluation of WOFOST and AquaCrop models confirmed the models are able for simulating the yield of wheat grown in the study area. The results showed that average potential yield of wheat ranged from 3.43 to 8.42 and 2.76 to 6.49 ton.ha-1, in AquaCrop and WOFOST models, respectively. Finally, the uncertainty band due to the six AOGCMs for estimating crop yield is drawn and investigated. These bands show possible changes for the yield in the future period to the past one. It can be concluded the positive effects of climate warming and elevated CO2 concentrations on the production in the studied region.

  15. Responses of tree-ring growth and crop yield to drought indices in the Shanxi province, North China.

    PubMed

    Sun, Junyan; Liu, Yu

    2014-09-01

    In this paper, we analyze the relationships among the tree-ring chronology, meteorological drought (precipitation), agricultural drought (Palmer Drought Severity Index PDSI), hydrological drought (runoff), and agricultural data in the Shanxi province of North China. Correlation analyses indicate that the tree-ring chronology is significantly correlated with all of the drought indices during the main growing season from March to July. Sign test analyses further indicate that the tree-ring chronology shows variation similar to that of the drought indices in both high and low frequencies. Comparisons of the years with narrow tree rings to the severe droughts reflected in all three indices from 1957 to 2008 reveal that the radial growth of the trees in the study region can accurately record the severe drought for which all three indices were in agreement (1972, 1999, 2000, and 2001). Comparisons with the dryness/wetness index indicate that tree-ring growth can properly record the severe droughts in the history. Correlation analyses among agricultural data, tree-ring chronology, and drought indices indicate that the per-unit yield of summer crops is relatively well correlated with the agricultural drought, as indicated by the PDSI. The PDSI is the climatic factor that significantly influences both tree growth and per-unit yield of summer crops in the study region. These results indicate that the PDSI and tree-ring chronology have the potential to be used to monitor and predict the yield of summer crops. Tree-ring chronology is an important tool for drought research and for wider applications in agricultural and hydrological research.

  16. The impact of large-scale circulation patterns on summer crop yields in IP

    NASA Astrophysics Data System (ADS)

    Capa Morocho, Mirian; Rodríguez Fonseca, Belén; Ruiz Ramos, Margarita

    2014-05-01

    Large-scale circulations patterns (ENSO, NAO) have been shown to have a significant impact on seasonal weather, and therefore on crop yield over many parts of the world(Garnett and Khandekar, 1992; Aasa et al., 2004; Rozas and Garcia-Gonzalez, 2012). In this study, we analyze the influence of large-scale circulation patterns and regional climate on the principal components of maize yield variability in Iberian Peninsula (IP) using reanalysis datasets. Additionally, we investigate the modulation of these relationships by multidecadal patterns. This study is performed analyzing long time series of maize yield, only climate dependent, computed with the crop model CERES-maize (Jones and Kiniry, 1986) included in Decision Support System for Agrotechnology Transfer (DSSAT v.4.5). To simulate yields, reanalysis daily data of radiation, maximum and minimum temperature and precipitation were used. The reanalysis climate data were obtained from National Center for Environmental Prediction (20th Century and NCEP) and European Centre for Medium-Range Weather Forecasts (ECMWF) data server (ERA 40 and ERA Interim). Simulations were run at five locations: Lugo (northwestern), Lerida (NE), Madrid (central), Albacete (southeastern) and Córdoba (S IP) (Gabaldón et al., 2013). From these time series standardized anomalies were calculated. Afterwards, time series were time filtered to focus on the interannual-to-multiannual variability, splitting up in two components: low frequency (LF) and high frequency (HF) time scales. The principal components of HF yield anomalies in IP were compared with a set of documented patterns. These relationships were compared with multidecadal patterns, as Atlanctic Multidecadal Oscillations (AMO) and Interdecadal Pacific Oscillations (IPO). The results of this study have important implications in crop forecasting. In this way, it may have a positive impact on both public (agricultural planning) and private (decision support to farmers, insurance

  17. Catchments Under Change: Assessing Impacts and Feedbacks from New Biomass Crops in the Agricultural Midwestern USA

    NASA Astrophysics Data System (ADS)

    Yaeger, Mary; Housh, Mashor; Ng, Tze Ling; Cai, Ximing; Sivapalan, Murugesu

    2013-04-01

    In order to meet the challenges of future change, it is essential to understand the environmental response to current conditions and historical changes. The central Midwestern US is an example of anthropogenic change and environmental feedbacks, having been transformed from a natural grassland system to an artificially-drained agricultural system. Environmental feedbacks from reduced soil residence times coupled with increasing crop fertilization have manifested as a hypoxic zone in the Gulf of Mexico. In an effort to address these feedbacks while meeting new crop demands, large-scale planting of high-yielding perennial biomass crops has been proposed. This could be detrimental to both human and environmental streamflow users because these plants require more water than do current crops. The lowest natural flows in this shallow groundwater-dependent region coincide with the peak of the growing season, thus compounding the problem. Therefore, for large-scale biomass crop production to be sustainable, these tradeoffs between water quality and water quantity must be fully understood. To better understand the catchment response to current conditions, we have analyzed streamflow data in a central Illinois agricultural watershed. To deal with future changes, we have developed an integrated systems model which provides, among other outputs, the land usage that maximizes the benefit to the human system. This land use is then implemented in a separate hydrologic model to determine the impact to the environmental system. Interactively running the two models, taking into account the catchment response to human actions as well as possible anthropogenic responses to the environment, allows us to examine the feedbacks between the two systems. This lets us plot the trajectory of the state of the system, which we hypothesize will show emergent internal properties of the coupled system. Initial tests of this modeling framework show promise that this may indeed be the case. External

  18. Biochemical production of bioenergy from agricultural crops and residue in Iran.

    PubMed

    Karimi Alavijeh, Masih; Yaghmaei, Soheila

    2016-06-01

    The present study assessed the potential for biochemical conversion of energy stored in agricultural waste and residue in Iran. The current status of agricultural residue as a source of bioenergy globally and in Iran was investigated. The total number of publications in this field from 2000 to 2014 was about 4294. Iran ranked 21st with approximately 54 published studies. A total of 87 projects have been devised globally to produce second-generation biofuel through biochemical pathways. There are currently no second-generation biorefineries in Iran and agricultural residue has no significant application. The present study determined the amount and types of sustainable agricultural residue and oil-rich crops and their provincial distribution. Wheat, barley, rice, corn, potatoes, alfalfa, sugarcane, sugar beets, apples, grapes, dates, cotton, soybeans, rapeseed, sesame seeds, olives, sunflowers, safflowers, almonds, walnuts and hazelnuts have the greatest potential as agronomic and horticultural crops to produce bioenergy in Iran. A total of 11.33million tonnes (Mt) of agricultural biomass could be collected for production of bioethanol (3.84gigaliters (Gl)), biobutanol (1.07Gl), biogas (3.15billion cubic meters (BCM)), and biohydrogen (0.90BCM). Additionally, about 0.35Gl of biodiesel could be obtained using only 35% of total Iranian oilseed. The potential production capacity of conventional biofuel blends in Iran, environmental and socio-economic impacts including well-to-wheel greenhouse gas (GHG) emissions, and the social cost of carbon dioxide reduction are discussed. The cost of emissions could decrease up to 55.83% by utilizing E85 instead of gasoline. The possible application of gaseous biofuel in Iran to produce valuable chemicals and provide required energy for crop cultivation is also studied. The energy recovered from biogas produced by wheat residue could provide energy input for 115.62 and 393.12 thousand hectares of irrigated and rain-fed wheat

  19. Effect of coal fly ash-amended organic compost as a manure for agricultural crops

    SciTech Connect

    Ghuman, G.S.; Menon, M.P.; James, J.; Chandra, K.; Sajwan, K. )

    1991-04-01

    Coal-fired electric power plants generate large quantities of fly ash as a byproduct. In continuation of previous studies on the utilization of fly ash as an amendment to organic compost for use as a manure for agricultural crops, the authors have now determined the effects of this manure on the yield and uptake of selected elements by several plants including collard green, corn, mustard green, bell pepper, egg plant, and climbing beans. An amended compost containing 30-40% fly ash with a compost:soil ratio of 1:3 was found to be most effective to enhance the yield and nutrient uptake of most of the plants. At 20% fly ash level, no increase in yield of any of the above crops was observed. The uptake of K, Mg, Mn, and P was increased in most plants. Boron which is known to be detrimental to the growth of plants above certain level was also found to be increased in plants nourished with the manure.

  20. CropWatch agroclimatic indicators (CWAIs) for weather impact assessment on global agriculture.

    PubMed

    Gommes, René; Wu, Bingfang; Zhang, Ning; Feng, Xueliang; Zeng, Hongwei; Li, Zhongyuan; Chen, Bo

    2017-02-01

    CropWatch agroclimatic indicators (CWAIs) are a monitoring tool developed by the CropWatch global crop monitoring system in the Chinese Academy of Sciences (CAS; www.cropwatch.com.cn , Wu et al Int J Digital Earth 7(2):113-137, 2014, Wu et al Remote Sens 7:3907-3933, 2015). Contrary to most other environmental and agroclimatic indicators, they are "agronomic value-added", i.e. they are spatial values averaged over agricultural areas only and they include a weighting that enhances the contribution of the areas with the largest production potential. CWAIs can be computed for any time interval (starting from dekads) and yield one synthetic value per variable over a specific area and time interval, for instance a national annual value. Therefore, they are very compatible with socio-economic and other variables that are usually reported at regular time intervals over administrative units, such as national environmental or agricultural statistics. Two of the CWAIs are satellite-based (RAIN and Photosynthetically Active radiation, PAR) while the third is ground based (TEMP, air temperature); capitals are used when specifically referring to CWAIs rather than the climate variables in general. The paper first provides an overview of some common agroclimatic indicators, describing their procedural, systemic and normative features in subsequent sections, following the terminology of Binder et al Environ Impact Assess Rev 30:71-81 (2010). The discussion focuses on the systemic and normative aspects: the CWAIs are assessed in terms of their coherent description of the agroclimatic crop environment, at different spatial scales (systemic). The final section shows that the CWAIs retain key statistical properties of the underlying climate variables and that they can be compared to a reference value and used as monitoring and early warning variables (normative).

  1. CropWatch agroclimatic indicators (CWAIs) for weather impact assessment on global agriculture

    NASA Astrophysics Data System (ADS)

    Gommes, René; Wu, Bingfang; Zhang, Ning; Feng, Xueliang; Zeng, Hongwei; Li, Zhongyuan; Chen, Bo

    2016-07-01

    CropWatch agroclimatic indicators (CWAIs) are a monitoring tool developed by the CropWatch global crop monitoring system in the Chinese Academy of Sciences (CAS; www.cropwatch.com.cn, Wu et al Int J Digital Earth 7(2):113-137, 2014, Wu et al Remote Sens 7:3907-3933, 2015). Contrary to most other environmental and agroclimatic indicators, they are "agronomic value-added", i.e. they are spatial values averaged over agricultural areas only and they include a weighting that enhances the contribution of the areas with the largest production potential. CWAIs can be computed for any time interval (starting from dekads) and yield one synthetic value per variable over a specific area and time interval, for instance a national annual value. Therefore, they are very compatible with socio-economic and other variables that are usually reported at regular time intervals over administrative units, such as national environmental or agricultural statistics. Two of the CWAIs are satellite-based (RAIN and Photosynthetically Active radiation, PAR) while the third is ground based (TEMP, air temperature); capitals are used when specifically referring to CWAIs rather than the climate variables in general. The paper first provides an overview of some common agroclimatic indicators, describing their procedural, systemic and normative features in subsequent sections, following the terminology of Binder et al Environ Impact Assess Rev 30:71-81 (2010). The discussion focuses on the systemic and normative aspects: the CWAIs are assessed in terms of their coherent description of the agroclimatic crop environment, at different spatial scales (systemic). The final section shows that the CWAIs retain key statistical properties of the underlying climate variables and that they can be compared to a reference value and used as monitoring and early warning variables (normative).

  2. CropWatch agroclimatic indicators (CWAIs) for weather impact assessment on global agriculture

    NASA Astrophysics Data System (ADS)

    Gommes, René; Wu, Bingfang; Zhang, Ning; Feng, Xueliang; Zeng, Hongwei; Li, Zhongyuan; Chen, Bo

    2017-02-01

    CropWatch agroclimatic indicators (CWAIs) are a monitoring tool developed by the CropWatch global crop monitoring system in the Chinese Academy of Sciences (CAS; http://www.cropwatch.com.cn, Wu et al Int J Digital Earth 7(2):113-137, 2014, Wu et al Remote Sens 7:3907-3933, 2015). Contrary to most other environmental and agroclimatic indicators, they are "agronomic value-added", i.e. they are spatial values averaged over agricultural areas only and they include a weighting that enhances the contribution of the areas with the largest production potential. CWAIs can be computed for any time interval (starting from dekads) and yield one synthetic value per variable over a specific area and time interval, for instance a national annual value. Therefore, they are very compatible with socio-economic and other variables that are usually reported at regular time intervals over administrative units, such as national environmental or agricultural statistics. Two of the CWAIs are satellite-based (RAIN and Photosynthetically Active radiation, PAR) while the third is ground based (TEMP, air temperature); capitals are used when specifically referring to CWAIs rather than the climate variables in general. The paper first provides an overview of some common agroclimatic indicators, describing their procedural, systemic and normative features in subsequent sections, following the terminology of Binder et al Environ Impact Assess Rev 30:71-81 (2010). The discussion focuses on the systemic and normative aspects: the CWAIs are assessed in terms of their coherent description of the agroclimatic crop environment, at different spatial scales (systemic). The final section shows that the CWAIs retain key statistical properties of the underlying climate variables and that they can be compared to a reference value and used as monitoring and early warning variables (normative).

  3. The enemy as ally: herbivore-induced increase in crop yield.

    PubMed

    Poveda, Katja; Jímenez, Maria Isabel Gómez; Kessler, André

    2010-10-01

    There is increasing global concern over the risk of food shortage and instability, and a concomitant demand for an increase in food production. However, the continuing expansion of agricultural areas threatens natural habitats as well as human and ecosystem health. One option for increasing food production is to maximize yields from existing farmland. Here we demonstrate that larval feeding by the Guatemalan potato moth (Tecia solanivora), considered one of the most economically important potato pests in Latin America, leads to a dramatic increase in potato tuber production. Field-grown potato plants (Solanum tuberosum) in the Colombian Andes attacked by low numbers of potato moth larvae produce a 2.5-fold higher marketable potato yield than undamaged plants. Greenhouse experiments demonstrate that this effect is induced by larval regurgitant, rather than by mechanical tissue damage. Our results indicate that compounds from the foregut of T. solanivora are necessary and sufficient to induce an increased yield in potato. Our study suggests that using (1) herbivore-derived chemical cues and (2) induced compensatory plant responses to herbivory can provide viable new tools to increase per area crop productivity.

  4. Synergistic interactions of ecosystem services: florivorous pest control boosts crop yield increase through insect pollination

    PubMed Central

    Albrecht, Matthias

    2016-01-01

    Insect pollination and pest control are pivotal functions sustaining global food production. However, they have mostly been studied in isolation and how they interactively shape crop yield remains largely unexplored. Using controlled field experiments, we found strong synergistic effects of insect pollination and simulated pest control on yield quantity and quality. Their joint effect increased yield by 23%, with synergistic effects contributing 10%, while their single contributions were 7% and 6%, respectively. The potential economic benefit for a farmer from the synergistic effects (12%) was 1.8 times greater than their individual contributions (7% each). We show that the principal underlying mechanism was a pronounced pest-induced reduction in flower lifetime, resulting in a strong reduction in the number of pollinator visits a flower receives during its lifetime. Our findings highlight the importance of non-additive interactions among ecosystem services (ES) when valuating, mapping or predicting them and reveal fundamental implications for ecosystem management and policy aimed at maximizing ES for sustainable agriculture. PMID:26865304

  5. Effects of Conservation Agriculture on Soil Physical Properties and Yield of Lentil in Northern Syria

    NASA Astrophysics Data System (ADS)

    Wahbi, Ammar; Miwak, Hisham; Singh, Raphy

    2014-05-01

    Conservation agriculture (CA) aims to achieve sustainable and profitable agriculture and subsequently improve livelihoods of farmers based on three main components, i.e. minimum or no tillage, retention of crop residues and use of crop rotation. However, to promote CA in semi-arid areas where precipitation is erratic, low, and falls over short periods in winter, its effects on soil and crop yield have to be investigated. The present study was conducted at the main research station of the International Center for Agricultural Research in the Dry Areas (ICARDA), Syria, during the agricultural season of 2010-2011, in the frame of a long term trial (2003-2011), where two treatments; i.e. conservation versus conventional agriculture (replicated twice), and six varieties of lentil (early, medium and late maturity genotypes; 2 each), selected from 100 varieties, were used. Soil samples were taken (before planting and after harvesting), to determine soil bulk density, particle density and total porosity. Aggregate stability was also determined using dry and wet sieving methods for the 0-15 cm soil depth, and the effective diameter of the aggregate was calculated for both treatments of conservation agriculture (CA) and conventional tillage (CT). Soil moisture was monitored in the top soil layer (0-15 cm) using Time Domain Reflectometry (TDR) on a weekly or two weekly-intervals. Soil moisture release curve was done for disturbed, 2 mm dry sieved soil at 0-15, 15-30, 30-45 and 45-60 cm depth using pressure plate chamber. Dry plant production (oven dry at 70°C) was estimated at the harvesting stage, and then threshed to estimate grain yield. CA showed higher (p = 0.001) soil moisture values than CT. The difference in volumetric soil moisture content between CA and CT during the studied period ranged from 20 to 30 %. Volumetric water content was higher for, CA compared with CT, at a given soil water potential especially at the lower pressure; this observation was consistent

  6. Technical Note: Scheduling for deficit irrigation-crop yield predictor

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Irrigators in many countries with dwindling water supplies face the prospect that they will not be able to fully irrigate their crops. In these cases, they still need to schedule their water applications to make the best economic use of available water. Major scheduling questions for deficit irrigat...

  7. The path of carbon in photosynthesis: improved crop yields with methanol.

    PubMed Central

    Nonomura, A M; Benson, A A

    1992-01-01

    Foliar sprays of aqueous 10-50% methanol increased growth and development of C3 crop plants in arid environments. The effects of low levels (< 1 ml per plant) of methanol were observed for weeks after the brief time necessary for its rapid metabolism. Within several hours, foliar treatment with methanol resulted in increased turgidity. Plants treated with nutrient-supplemented methanol showed up to 100% increases in yields when maintained under direct sunlight in desert agriculture. In the shade and when winter crops were treated with methanol, plants showed no improvement of growth. When repeatedly treated with nutrient-supplemented methanol, shaded plants showed symptoms of toxicity. Repeated methanol treatments with glycine caused increased turgidity and stimulated plant growth without injury under indirect sunlight, but indoors with artificial illumination, foliar damage developed after 48 hr. Addition of glycerophosphate to glycine/methanol solutions allowed treatment of artificially illuminated plants indoors without injury. Plants with C4 metabolism showed no increase in productivity by methanol treatment. Plants given many applications of aqueous methanol showed symptoms of nutrient deficiency. Supplementation with a source of nitrogen sustained growth, eliminating symptoms of deficiency. Adjustment of carbon/nitrogen ratios was undertaken in the field by decreasing the source of nitrogen in the final application, resulting in early maturation; concomitantly, irrigation requirements were reduced. PMID:1409701

  8. 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.

  9. Pollinator shortage and global crop yield: Looking at the whole spectrum of pollinator dependency.

    PubMed

    Garibaldi, Lucas A; Aizen, Marcelo A; Cunningham, Saul A; Klein, Alexandra M

    2009-01-01

    A pollinator decline caused by environmental degradation might be compromising the production of pollinator-dependent crops. In a recent article, we compared 45 year series (1961-2006) in yield, production and cultivated area of pollinator-dependent and nondependent crop around the world. If pollinator shortage is occurring globally, we expected a lower annual growth rate in yield for pollinator-dependent than nondependent crops, but a higher growth in cultivated area to compensate the lower yield. We have found little evidence for the first "yield" prediction but strong evidence for the second "area" prediction. Here, we present an additional analysis to show that the first and second predictions are both supported for crops that vary in dependency levels from nondependent to moderate dependence (i.e., up to 65% average yield reduction without pollinators). However, those crops for which animal pollination is essential (i.e., 95% average yield reduction without pollinators) showed higher growth in yield and lower expansion in area than expected in a pollination shortage scenario. We propose that pollination management for highly pollinator-dependent crops, such us renting hives or hand pollination, might have compensated for pollinator limitation of yield.

  10. GEOGLAM Crop Assessment Tool: Adapting from global agricultural monitoring to food security monitoring

    NASA Astrophysics Data System (ADS)

    Humber, M. L.; Becker-Reshef, I.; Nordling, J.; Barker, B.; McGaughey, K.

    2014-12-01

    The GEOGLAM Crop Monitor's Crop Assessment Tool was released in August 2013 in support of the GEOGLAM Crop Monitor's objective to develop transparent, timely crop condition assessments in primary agricultural production areas, highlighting potential hotspots of stress/bumper crops. The Crop Assessment Tool allows users to view satellite derived products, best available crop masks, and crop calendars (created in collaboration with GEOGLAM Crop Monitor partners), then in turn submit crop assessment entries detailing the crop's condition, drivers, impacts, trends, and other information. Although the Crop Assessment Tool was originally intended to collect data on major crop production at the global scale, the types of data collected are also relevant to the food security and rangelands monitoring communities. In line with the GEOGLAM Countries at Risk philosophy of "foster[ing] the coordination of product delivery and capacity building efforts for national and regional organizations, and the development of harmonized methods and tools", a modified version of the Crop Assessment Tool is being developed for the USAID Famine Early Warning Systems Network (FEWS NET). As a member of the Countries at Risk component of GEOGLAM, FEWS NET provides agricultural monitoring, timely food security assessments, and early warnings of potential significant food shortages focusing specifically on countries at risk of food security emergencies. While the FEWS NET adaptation of the Crop Assessment Tool focuses on crop production in the context of food security rather than large scale production, the data collected is nearly identical to the data collected by the Crop Monitor. If combined, the countries monitored by FEWS NET and GEOGLAM Crop Monitor would encompass over 90 countries representing the most important regions for crop production and food security.

  11. Results and advantages of a spatially-variable technology for crop yield

    SciTech Connect

    Klemme, K.A.; Schumacher, J.A.; Froehlich, D.P.

    1992-12-31

    The Field Grid Sense system was adapted to locate and record crop yield in the field. Accurate measurement of yield in spatially variable fields is needed to achieve maximum profitability in crop production. The harvester system is composed of a laptop computer, data acquisition system, fifth wheel, and an ultrasonic level sensor assembled on a combine. The fifth wheel, in combination with travel lanes, is used to identify yield with position where yield is determined by the change of grain volume in the combine hopper. Yield maps can be generated from the collected data and then used as a production management tool in conjunction with other field characteristic information.

  12. Results and advantages of a spatially-variable technology for crop yield

    SciTech Connect

    Klemme, K.A.; Schumacher, J.A.; Froehlich, D.P.

    1992-01-01

    The Field Grid Sense system was adapted to locate and record crop yield in the field. Accurate measurement of yield in spatially variable fields is needed to achieve maximum profitability in crop production. The harvester system is composed of a laptop computer, data acquisition system, fifth wheel, and an ultrasonic level sensor assembled on a combine. The fifth wheel, in combination with travel lanes, is used to identify yield with position where yield is determined by the change of grain volume in the combine hopper. Yield maps can be generated from the collected data and then used as a production management tool in conjunction with other field characteristic information.

  13. Assessing future drought impacts on yields based on historical irrigation reaction to drought for four major crops in Kansas.

    PubMed

    Zhang, Tianyi; Lin, Xiaomao

    2016-04-15

    Evaluation of how historical irrigation reactions can adapt to future drought is indispensable to irrigation policy, however, such reactions are poorly quantified. In this paper, county-level irrigation data for maize, soybean, grain sorghum, and wheat crops in Kansas were compiled. Statistical models were developed to quantify changes of irrigation and yields in response to drought for each crop. These were then used to evaluate the ability of current irrigation to cope with future drought impacts on each crop based on an ensemble Palmer Drought Severity Index (PDSI) prediction under the Representative Concentration Pathways 4.5 scenario. Results indicate that irrigation in response to drought varies by crop; approximately 10 to 13% additional irrigation was applied when PDSI was reduced by one unit for maize, soybean, and grain sorghum. However, the irrigation reaction for wheat exhibits a large uncertainty, indicating a weaker irrigation reaction. Analysis of future climate conditions indicates that maize, soybean, and grain sorghum yields would decrease 2.2-12.4% at the state level despite additional irrigation application induced by drought (which was expected to increase 5.1-19.0%), suggesting that future drought will exceed the range that historical irrigation reactions can adapt to. In contrast, a lower reduction (-0.99 to -0.63%) was estimated for wheat yields because wetter climate was projected in the central section of the study area. Expanding wheat areas may be helpful in avoiding future drought risks for Kansas agriculture.

  14. Ground-level ozone in China: distribution and effects on crop yields.

    PubMed

    Wang, Xiaoke; Manning, William; Feng, Zongwei; Zhu, Yongguan

    2007-05-01

    Rapid economic development and an increasing demand for food in China have drawn attention to the role of ozone at pollution levels on crop yields. Some assessments of ozone effects on crop yields have been carried out in China. Determination of ozone distribution by geographical location and resulting crop loss estimations have been made by Chinese investigators and others from abroad. It is evident that surface level ozone levels in China exceed critical levels for occurrence of crop losses. Current levels of information from ozone dose/response studies are limited. Given the size of China, existing ozone monitoring sites are too few to provide enough data to scale ozone distribution to a national level. There are large uncertainties in the database for ozone effects on crop loss and for ozone distribution. Considerable research needs to be done to allow accurate estimation of crop losses caused by ozone in China.

  15. Multi-country evidence that crop diversification promotes ecological intensification of agriculture.

    PubMed

    Gurr, Geoff M; Lu, Zhongxian; Zheng, Xusong; Xu, Hongxing; Zhu, Pingyang; Chen, Guihua; Yao, Xiaoming; Cheng, Jiaan; Zhu, Zengrong; Catindig, Josie Lynn; Villareal, Sylvia; Van Chien, Ho; Cuong, Le Quoc; Channoo, Chairat; Chengwattana, Nalinee; Lan, La Pham; Hai, Le Huu; Chaiwong, Jintana; Nicol, Helen I; Perovic, David J; Wratten, Steve D; Heong, Kong Luen

    2016-02-22

    Global food security requires increased crop productivity to meet escalating demand(1-3). Current food production systems are heavily dependent on synthetic inputs that threaten the environment and human well-being(2,4,5). Biodiversity, for instance, is key to the provision of ecosystem services such as pest control(6,7), but is eroded in conventional agricultural systems. Yet the conservation and reinstatement of biodiversity is challenging(5,8,9), and it remains unclear whether the promotion of biodiversity can reduce reliance on inputs without penalizing yields on a regional scale. Here we present results from multi-site field studies replicated in Thailand, China and Vietnam over a period of four years, in which we grew nectar-producing plants around rice fields, and monitored levels of pest infestation, insecticide use and yields. Compiling the data from all sites, we report that this inexpensive intervention significantly reduced populations of two key pests, reduced insecticide applications by 70%, increased grain yields by 5% and delivered an economic advantage of 7.5%. Additional field studies showed that predators and parasitoids of the main rice pests, together with detritivores, were more abundant in the presence of nectar-producing plants. We conclude that a simple diversification approach, in this case the growth of nectar-producing plants, can contribute to the ecological intensification of agricultural systems.

  16. Soil carbon and crop yields affected by irrigation, tillage, crop rotation, and nitrogen fertilization

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Information on management practices is needed to increase surface residue and soil C sequestration to obtain farm C credit. The effects of irrigation, tillage, cropping system, and N fertilization were evaluated on the amount of crop biomass (stems and leaves) returned to the soil, surface residue C...

  17. Cropping sequence and nitrogen fertilization impact on surface residue, soil carbon sequestration, and crop yields

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Information is needed on the effect of management practices on soil C storage for obtaining C credit. The effects of tillage, cropping sequence, and N fertilization were evaluated on dryland crop and surface residue C and soil organic C (SOC) at the 0-120 cm depth in a Williams loam from 2006 to 201...

  18. Dryland soil chemical properties and crop yields affected by long-term tillage and cropping sequence

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Information on the effects of long-term tillage and cropping sequence on dryland soil nutrients and chemical properties is scanty. We examined the effect of 30 yr of tillage frequency and cropping sequence combination on dryland soil Olsen-P, exchangeable K, Ca, Mg, Na, SO4-S, and Zn contents, pH, e...

  19. Global Crop Yield Reductions due to Surface Ozone Exposure: Crop Production Losses and Economic Damage in 2000 and 2030 under Two Future Scenarios of O3 Pollution

    NASA Astrophysics Data System (ADS)

    Avnery, S.; Mauzerall, D. L.; Liu, J.; Horowitz, L. W.

    2011-12-01

    Field studies demonstrate that exposure to elevated concentrations of surface ozone (O3) may cause substantial reductions in the agricultural yields of many crops. As emissions of O3 precursors rise in many parts of the world over the next few decades, yield reductions from O3 exposure may increase the challenges of feeding a global population projected to grow from approximately 6 to 8 billion people between 2000 and 2030. This study estimates global yield reductions of three key staple crops (soybean, maize, and wheat) due to surface ozone exposure in 2000 and 2030 according to two trajectories of O3 pollution: the Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios (IPCC SRES) A2 and B1 storylines, which represent upper- and lower-boundary projections, respectively, of most O3 precursor emissions in 2030. Our results indicate that year 2000 O3-induced global yield reductions ranged, depending on the O3 exposure metric used, from 3.9-15% for wheat, 8.5-14% for soybean, and 2.2-5.5% for maize. Global crop production losses totaled 79-121 million metric tons, worth 11-18 billion annually (USD2000). In the 2030-A2 scenario we find global O3-induced yield loss of wheat to be 5.4-26% (a further reduction in yield of +1.5-10% from year 2000 values), 15-19% for soybean (reduction of +0.9-11%), and 4.4-8.7% for maize (reduction of +2.1-3.2%) depending on the metric used, with total global agricultural losses worth 17-35 billion USD2000 annually (an increase of +6-17 billion in losses from 2000). Under the 2030-B1 scenario, we project less severe but still substantial reductions in yields: 4.0-17% for wheat (a further decrease in yield of +0.1-1.8% from 2000), 9.5-15% for soybean (decrease of +0.7-1.0%), and 2.5-6.0% for maize (decrease of+ 0.3-0.5%), with total losses worth 12-21 billion annually (an increase of +$1-3 billion in losses from 2000). Because our analysis uses crop data from the year 2000, which likely underestimates agricultural

  20. African crop yield reductions due to increasingly unbalanced Nitrogen and Phosphorus consumption.

    PubMed

    van der Velde, Marijn; Folberth, Christian; Balkovič, Juraj; Ciais, Philippe; Fritz, Steffen; Janssens, Ivan A; Obersteiner, Michael; See, Linda; Skalský, Rastislav; Xiong, Wei; Peñuelas, Josep

    2014-04-01

    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(-1)), 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(-1)), 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.

  1. Genetic consequences of radioactive contamination by the Chernobyl fallout to agricultural crops.

    PubMed

    Geraskin, S A; Dikarev, V G; Zyablitskaya, Ye Ya; Oudalova, A A; Spirin, Ye V; Alexakhin, R M

    2003-01-01

    The genetic consequences of radioactive contamination by the fallout to agricultural crops after the accident at the Chernobyl NPP in 1986 have been studied. In the first, acute, period of this accident, when the absorbed dose was primarily due to external beta- and gamma-irradiation, the radiation injury of agricultural crops, according to the basic cytogenetic tests, resembled the effect produced by acute gamma-irradiation at comparable doses. The yield of cytogenetic damage in leaf meristem of plants grown in the 10-km zone of the ChNPP in 1987-1989 (the period of chronic, lower level radiation exposure) was shown to be enhanced and dependent on the level of radioactive contamination. The rate of decline with time in cytogenetic damage induced by chronic exposure lagged considerably behind that of the radiation exposure. Analysis of genetic variability in three sequential generations of rye and wheat revealed increased cytogenetic damage in plants exposed to chronic irradiation during the 2nd and 3rd years.

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

    PubMed Central

    Leng, Guoyong; Zhang, Xuesong; Huang, Maoyi; Asrar, Ghassem R.; Leung, L. Ruby

    2016-01-01

    The covariability of temperature (T), precipitation (P) and radiation (R) is an important aspect in understanding the climate influence on crop yields. Here, 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, 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. 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. PMID:27616326

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

    NASA Astrophysics Data System (ADS)

    Leng, Guoyong; Zhang, Xuesong; Huang, Maoyi; Asrar, Ghassem R.; Leung, L. Ruby

    2016-09-01

    The covariability of temperature (T), precipitation (P) and radiation (R) is an important aspect in understanding the climate influence on crop yields. Here, 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, 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. 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.

  4. Assessing the performance of dynamical and statistical downscaling techniques to simulate crop yield in West Africa

    NASA Astrophysics Data System (ADS)

    Sultan, B.; Oettli, P.; Vrac, M.; Baron, C.

    2010-12-01

    Global circulation models (GCM) are increasingly capable of making relevant predictions of seasonal and long-term climate variability, thus improving prospects of predicting impact on crop yields. This is particularly important for semi-arid West Africa where climate variability and drought threaten food security. Translating GCM outputs into attainable crop yields is difficult because GCM grid boxes are of larger scale than the processes governing yield, involving partitioning of rain among runoff, evaporation, transpiration, drainage and storage at plot scale. It therefore requires the use of downscaling methods. This study analyzes the performance of both dynamical and statistical downscaling techniques in simulating crop yield at local scale. A detailed case study is conducted using historical weather data for Senegal, applied to the crop model SARRAH for simulating several tropical cereals (sorghum, millet, maize) at local scale. This control simulation is used as a benchmark to evaluate a set of Regional Climate Models (RCM) simulations, forced by ERA-Interim, from the ENSEMBLES project and a statistical downscaling method, the CDF-Transform, used to correct biases in RCM outputs. We first evaluate each climate variable that drives the simulated yield in the control simulation (radiation, rainfall, temperatures). We then simulate crop yields with RCM outputs (with or without applying the CDG-Transform) and evaluate the performance of each RCM in regards to crop yield simulations.

  5. Tropospheric ozone pollution in India: effects on crop yield and product quality.

    PubMed

    Singh, Aditya Abha; Agrawal, S B

    2017-02-01

    Ozone (O3) in troposphere is the most critical secondary air pollutant, and being phytotoxic causes substantial losses to agricultural productivity. Its increasing concentration in India particularly in Indo-Gangetic plains is an issue of major concern as it is posing a threat to agriculture. In view of the issue of rising surface level of O3 in India, the aim of this compilation is to present the past and the prevailing concentrations of O3 and its important precursor (oxides of nitrogen) over the Indian region. The resulting magnitude of reductions in crop productivity as well as alteration in the quality of the product attributable to tropospheric O3 has also been taken up. Studies in relation to yield measurements have been conducted predominantly in open top chambers (OTCs) and also assessed by using antiozonant ethylene diurea (EDU). There is a substantial spatial difference in O3 distribution at different places displaying variable O3 concentrations due to seasonal and geographical variations. This review further recognizes the major information lacuna and also highlights future perspectives to get the grips with rising trend of ground level O3 pollution and also to formulate the policies to check the emissions of O3 precursors in India.

  6. Assessment of crop yield reduction due to drought effect using satellite remote sensing

    NASA Astrophysics Data System (ADS)

    Martyniak, L.; Dabrowska-Zielinska, K.; Kuzniar, A.; Szymczyk, R.; Gruszczynska, M.; Stankiewicz, K.

    The application of satellite derived indices for assessment of crop growth conditions in semiarid countries is well known. NOAA/NESDIS elaborated the indices, which have been applied worldwide arid and semiarid areas for drought detection and monitoring of vegetation conditions. It has been the great interest to apply and modify the indices for Poland, which is the country with sufficient water supply. Agricultural production in Poland is the main source of income for nearly 12% of population providing food for 40 million people of the entire country and the main contribution to the gross national product through the export of live animals, animals and vegetable products and prepared foodstuffs. The production of basic consumer cereals is to considerable extent weather dependent and in some years is not sufficient for needs within the country. The investigation has been performed for cereals using NOAA/AVHRR data. TCI and VCI indices have been applied for calculating cereals growth conditions and to assess the sensitivity of these indices in monitoring drought effect on yield. Also evapotranspiration and soil moisture has been calculated using energy budget method. The values have been statistically compared to modelled values of evapotranspiration and detailed ground observations of soil moisture and vegetation parameters, which are measured at special agricultural stations. It was proved that the method gives very good results.

  7. Longer-term potato cropping system effects on soilborne diseases and tuber yield

    Technology Transfer Automated Retrieval System (TEKTRAN)

    In field trials established in 2004, different 3-yr potato cropping systems focused on specific crop management goals of (SC) soil conservation, (SI) soil improvement, and (DS) disease-suppression were evaluated for their effects on soilborne diseases and tuber yield. These systems were compared to ...

  8. Yield, Grade, and Revenue of Double Cropped Green Bean and Sweet Corn with Cotton

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Double cropping green bean, (Phaseolus vulgaris L.; GB) and sweet corn (Zea mays L.; SC) with cotton (Gossypium hirsutum L.; CT) can increase the economic return but can also be at risk of crop failure due to inclement weather patterns. The objectives were to: 1) quantify the yield of GB and SC doub...

  9. Can novel management practice improve soil and environmental quality and sustain crop yield simultaneously?

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Little is known about management practices that can simultaneously improve soil and environmental quality and sustain crop yields. The effect of a combination of tillage, crop rotation, and N fertilization on soil C and N, global warming potential (GWP), greenhouse gas intensity (GHGI), and malt bar...

  10. 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.

  11. Climatic Droughts and the Impacts on Crop Yields in Northern India during the Past Century

    NASA Astrophysics Data System (ADS)

    Ge, Y.; Cai, X.; Zhu, T.

    2014-12-01

    Drought has become an increasingly severe threat to water and food security recently. This study presents a novel method to calculate the return period of drought, considering drought as event characterized by expected drought inter-arrival time, duration, severity and peak intensity. Recently, Copula distribution, a multivariable probability distribution, is used to deal with strongly correlated variables in analyzing complex hydrologic phenomenon. This study assesses drought conditions in Northern India, including 8 sites, in the past century using Palmer Drought Severity Index (PDSI) from two latest datasets, Dai (2011, 2013) and Sheffield et al. (2012), which concluded conflicting results about global average drought trend. Our results include the change of the severity, intensity and duration of drought events during the past century and the impact of the drought condition on crop yields in the region. It is found that drought variables are highly correlated, thus copulas joint distribution enables the estimation of multi-variate return period. Based on Dai's dataset from 1900 to 2012, for a fixed drought return period the severity and duration is lower for the period before1955 in sites close to the Indus basin (site 1) or off the coast of the Indian Ocean (Bay of Bengal) (site 8), while they are higher for the period after 1955 in other inland sites (sites 3-7), (e.g., severity in Fig.1). Projections based on two models (IPCC AR4 and AR5) in Dai (2011, 2013) suggested less severity and shorter duration in longer-year drought (e.g., 100-year drought), but larger in shorter-year drought (e.g., 2-year drought). Drought could bring nonlinear responses and unexpected losses in agriculture system, thus prediction and management are essential. Therefore, in the years with extreme drought conditions, impact assessment of drought on crop yield of corn, barley, wheat and sorghum will be also conducted through correlating crop yields with drought conditions during

  12. Gypsum effects on crop yield and chemistry of soil, crop tissue, and vadose zone water: A meta-analysis.

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Gypsum has various potential benefits as a soil amendment, but data are lacking on gypsum effects on crop yields and on environmental impacts across diverse field sites. Gypsum studies were conducted in six states using a common design with three rates each of mined and flue gas desulfurization (FGD...

  13. Characteristics of AVIRIS bands measurements in agricultural crops at Blythe area, California: II. Studies on kenaf, Hibiscus canabinus

    NASA Astrophysics Data System (ADS)

    Shakir Hanna, Safwat H.; Rethwisch, Michael D.

    2002-01-01

    AVIRIS data from Blythe,Calfornia , were acquired in June 1997 to study the agricultural spectra from different crops and for identification of crops in other areas with similar environmental factors and similar spectral properties. In this respect; the main objectives of this study are: 1) to compare the spectral and radiometric characteristics of AVIRIS data from agriculture crops with the spectra measured by FieldSpecR ASD radiometer; 2) to explore the use of AVIRIS images in identifying agriculture crops; and; 3) to build a spectral library for the crops that were studied. A long-term goal is to extend the spectral library for different vegetation or crops in different stages of growth. In order to support our study, on July 18-19, 2000 we collected spectra using the FieldSpecR ASD spectrometer from selected fields planted with different crops at Blythe area, California (at the Longitude 114 degree(s) 33.28 W and Latitude 33 degree(s) 25.42 N to Longitude 114 degree(s) 44.35 W and 33 degree(s) 39.77 N Latitude). The results of this study showed that there is a significant correlation between the data that were collected by AVIRIS image scene in 1997 and spectral data collected by the FieldSpecR spectrometer. This correlation allowed us to build a spectral library to be used in ENVI_IDL software. This leads to identification of different crops and in particular the visible part of the spectra. Furthermore, using IDL-ENVI algorithms of Spectral Angle Mapper classification (SAM), Spectral Feature Fitting (SFF) and Spectral Binary Encoding (SPE) showed that there is an excellent agreement between the predicted and the actual crop type (i.e. The correlation is between 85-90% match). Further use of the AVIRIS images can be of a value to crops identification or crops yield for commercial use. Kenaf crop spectra were studied. The kenaf varieties (Tainung 2, Everglades 41) were significantly differentiated by both the spectral data from AVIRIS and from the hand

  14. Attitudes of Agricultural Experts Toward Genetically Modified Crops: A Case Study in Southwest Iran.

    PubMed

    Ghanian, Mansour; Ghoochani, Omid M; Kitterlin, Miranda; Jahangiry, Sheida; Zarafshani, Kiumars; Van Passel, Steven; Azadi, Hossein

    2016-04-01

    The production of genetically modified (GM) crops is growing around the world, and with it possible opportunities to combat food insecurity and hunger, as well as solutions to current problems facing conventional agriculture. In this regard the use of GMOs in food and agricultural applications has increased greatly over the past decade. However, the development of GM crops has been a matter of considerable interest and worldwide public controversy. This, in addition to skepticism, has stifled the use of this practice on a large scale in many areas, including Iran. It stands to reason that a greater understanding of this practice could be formed after a review of the existing expert opinions surrounding GM crops. Therefore, the purpose of this study was to analyze the predictors that influence agricultural experts' attitudes toward the development of and policies related to GM crops. Using a descriptive correlational research method, questionnaire data was collected from 65 experts from the Agricultural Organization in the Gotvand district in Southwest Iran. Results indicated that agricultural experts were aware of the environmental benefits and possible risks associated with GM crops. The majority of participants agreed that GM crops could improve food security and accelerate rural development, and were proponents of labeling practices for GM crops. Finally, there was a positive correlation between the perception of benefits and attitudes towards GM crops.

  15. Impacts of El Niño Southern Oscillation on the global yields of major crops.

    PubMed

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

    2014-05-15

    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 Niño/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 Niño likely improves the global-mean soybean yield by 2.1-5.4% 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 Niña years tend to be below normal (-4.5 to 0.0%). Our findings highlight the importance of ENSO to global crop production.

  16. 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

  17. 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.

  18. A photorespiratory bypass increases plant growth and seed yield in biofuel crop Camelina sativa

    DOE PAGES

    Dalal, Jyoti; Lopez, Harry; Vasani, Naresh B.; ...

    2015-10-29

    Camelina sativa is an oilseed crop with great potential for biofuel production on marginal land. The seed oil from camelina has been converted to jet fuel and improved fuel efficiency in commercial and military test flights. Hydrogenation-derived renewable diesel from camelina is environmentally superior to that from canola due to lower agricultural inputs, and the seed meal is FDA approved for animal consumption. However, relatively low yield makes its farming less profitable. Our study is aimed at increasing camelina seed yield by reducing carbon loss from photorespiration via a photorespiratory bypass. Genes encoding three enzymes of the Escherichia coli glycolatemore » catabolic pathway were introduced: glycolate dehydrogenase (GDH), glyoxylate carboxyligase (GCL) and tartronic semialdehyde reductase (TSR). These enzymes compete for the photorespiratory substrate, glycolate, convert it to glycerate within the chloroplasts, and reduce photorespiration. As a by-product of the reaction, CO2 is released in the chloroplast, which increases photosynthesis. Camelina plants were transformed with either partial bypass (GDH), or full bypass (GDH, GCL and TSR) genes. Furthermore, transgenic plants were evaluated for physiological and metabolic traits.« less

  19. Impact of large-scale climate variability and change on crop yields in Africa: An observational assessment

    NASA Astrophysics Data System (ADS)

    Smoliak, B. V.; Po-Chedley, S.; Cullen, A. C.

    2011-12-01

    Assessments of the relationships between climate and agricultural production have progressed from opposite ends of the spatio-temporal spectrum. While studies of global-scale climate-yield relationships have provided estimates of the impact of multi-decadal trends in temperature and precipitation on recent production, studies of local weather impacts on yield have demonstrated the influence of temperature and precipitation variability on plant physiology, particularly with respect to the duration and timing of extremes. At intermediate spatial and temporal scales, somewhat of a gap in understanding exists. Our investigation contributes to better understanding climate-yield relationships at intermediate scales by assessing the impact of climate variability on crop yields at the country to continent scale on interannual to interdecadal timescales. Toward this end, we employ historical climatic data and reported cereal crop yields from the African continent, 1961 to 2009, in conjunction with principal component regression and partial least squares regression. Our results show that a discrete set of spatial patterns of climate variability account for up to half of the year-to-year variability in crop yields over portions of Africa. The impact of this climate variability is particularly strong in Sub-Saharan Africa, where large or prolonged deficits in yields can result in food shortages. The fundamental patterns of variability used to explain yield fluctuations are based on temperature and precipitation, chosen due to their influence on plant physiology; however, the time-varying behavior of the patterns may also be linked to coherent large-scale climate variability through regressions with sea surface temperature, sea level pressure and low-level wind fields. Results are distilled in terms of five UN designated geographic regions of Africa. Implications for short-term food security and future climate change are discussed.

  20. Characterizing spatial and temporal variability of crop yield caused by climate and irrigation in the North China Plain

    NASA Astrophysics Data System (ADS)

    Chen, Chao; Baethgen, Walter E.; Wang, Enli; Yu, Qiang

    2011-12-01

    Grain yields of wheat and maize were obtained from national statistics and simulated with an agricultural system model to investigate the effects of historical climate variability and irrigation on crop yield in the North China Plain (NCP). Both observed and simulated yields showed large temporal and spatial variability due to variations in climate and irrigation supply. Wheat yield under full irrigation (FI) was 8 t ha-1 or higher in 80% of seasons in the north, it ranged from 7 to 10 t ha-1 in 90% of seasons in central NCP, and less than 9 t ha-1 in 85% of seasons in the south. Reduced irrigation resulted in increased crop yield variability. Wheat yield under supplemental irrigation, i.e., to meet only 50% of irrigation water requirement [supplemental irrigation (SI)] ranged from 2.7 to 8.8 t ha-1 with the maximum frequency of seasons having the range of 4-6 t ha-1 in the north, 4-7 t ha-1 in central NCP, and 5-8 t ha-1 in the south. Wheat yield under no irrigation (NI) was lower than 1 t ha-1 in about 50% of seasons. Considering the NCP as a whole, simulated maize yield under FI ranged from 3.9 to 11.8 t ha-1 with similar frequency distribution in the range of 6-11.8 t ha-1 with the interval of 2 t ha-1. It ranged from 0 to 11.8 t ha-1, uniformly distributed into the range of 4-10 t ha-1 under SI, and NI. The results give an insight into the levels of regional crop production affected by climate and water management strategies.

  1. [Effect of plastic film mulching on crop yield and nitrogen efficiency in semiarid areas].

    PubMed

    Li, S; Li, F; Song, Q; Wang, J

    2001-04-01

    The effect of plastic film mulching, water storage in soil profile before sowing, and nitrogen fertilization on crop yield and nitrogen efficiency was examined in this paper. The study site was on the cultivated lossial soil in semiarid areas with 415 mm of annual rainfall and the test crop was spring wheat, Triticum aestivum. In order to study the effect of plastic film mulching, 4 levels of mulching were designed, including mulching of 0, 30 and 60 days after sowing and mulching over the whole growing period. The results showed that increase of soil water storage, plastic film mulching and nitrogen fertilization increased crop yield significantly(alpha < 0.01), and their effect followed in the order of nitrogen fertilization > increase of water storage > plastic film mulching. The effect of mulching on crop yield varied with water storage, nitrogen fertilization and mulching periods. When the water storage was low, there was no significant difference in crop yield between mulching and no mulching, although mulching increased crop yield slightly, and the nitrogen efficiency was higher for no mulching and mulching 30 days. When the water storage was high, the difference between the yield of mulching 60 days and no mulching was significant, but no difference in nitrogen efficiency was found for mulching 30 days, 60 days and over whole growing period. It was suggested that mulching over whole growing period was of less significance in practice.

  2. 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.

  3. 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.

  4. Effects of agricultural practices of three crops on the soil communities under Mediterranean conditions: field evaluation.

    NASA Astrophysics Data System (ADS)

    Leitão, Sara; José Cerejeira, Maria; Abreu, Manuela; Sousa, José Paulo

    2014-05-01

    Sustainable agricultural production relies on soil communities as the main actors in key soil processes necessary to maintain sustainable soil functioning. Soil biodiversity influences soil physical and chemical characteristics and thus the sustainability of crop and agro-ecosystems functioning. Agricultural practices (e.g.: soil tillage, pesticides and fertilizer applications, irrigation) may affects negatively or positively soil biodiversity and abundances by modifying the relationships between organisms in the soil ecosystem. The present study aimed to study the influence of agricultural practices of three crops (potato, onion and maize) under Mediterranean climate conditions on soil macro- and mesofauna during their entire crop cycles. Effects on soil communities were assessed at a higher tier of environmental risk assessment comprising field testing of indigenous edaphic communities in a selected study-site located in a major agriculture region of Central Portugal, Ribatejo e Oeste, neighbouring protected wetlands. A reference site near the agricultural field site was selected as a Control site to compare the terrestrial communities' composition and variation along the crop cycle. The field soil and Control site soil are sandy loam soils. Crops irrigation was performed by center-pivot (automated sprinkler that rotates in a half a circle area) and by sprinklers. Soil macro- and mesofauna were collected at both sites (field and Control) using two methodologies through pitfall trapping and soil sampling. The community of soil macro- and mesofauna of the three crops field varied versus control site along the crops cycles. Main differences were due to arachnids, coleopterans, ants and adult Diptera presence and abundance. The feeding activity of soil fauna between control site and crop areas varied only for potato and onion crops vs. control site but not among crops. Concentration of pesticides residues in soil did not cause apparent negative effects on the soil

  5. Crop Insurance Increases Water Withdrawals for Irrigation in Agriculture

    NASA Astrophysics Data System (ADS)

    Konar, M.; Deryugina, T.; Lin, X.

    2015-12-01

    Agricultural production remains particularly vulnerable to weather fluctuations and extreme events, such as droughts, floods, and heat waves. Crop insurance is a risk management tool that has been developed to mitigate some of this weather risk and protect farmer income in times of poor production. However, it is not clear what the implications of crop insurance are for crop irrigation. By providing a guaranteed level of income in case of crop failure, crop insurance can reduce the farmer's incentive to irrigate. Thus, crop insurance can decrease water use in times of drought and promote water sustainability. However, to minimize this "moral hazard", the insurer may require farmers to irrigate crops more than necessary. Further, by shifting crop production, crop insurance may increase demand for water. Thus, it is unclear whether crop insurance increases or decreases crop water use. Here, we determine the empirical relationship between crop insurance and irrigation withdrawals in the United States. To establish causality, we exploit variation in crop insurance policies over time, using an instrumental variables approach. We find that a 1% increase in insured crop acreage leads to a 0.223% increase in irrigation withdrawals, primarily from groundwater aquifers.

  6. Crop models capture the impacts of climate variability on corn yield

    NASA Astrophysics Data System (ADS)

    Niyogi, Dev; Liu, Xing; Andresen, Jeff; Song, Yang; Jain, Atul K.; Kellner, Olivia; Takle, Eugene S.; Doering, Otto C.

    2015-05-01

    We investigate the ability of three different crop models of varying complexity for capturing El Niño-Southern Oscillation-based climate variability impacts on the U.S. Corn Belt (1981-2010). Results indicate that crop models, irrespective of their complexity, are able to capture the impacts of climate variability on yield. Multiple-model ensemble analysis provides best results. There was no significant difference between using on-site and gridded meteorological data sets to drive the models. These results highlight the ability of using simpler crop models and gridded regional data sets for crop-climate assessments.

  7. Effect of crop residue incorporation on soil organic carbon (SOC) and greenhouse gas (GHG) emissions in European agricultural soils

    NASA Astrophysics Data System (ADS)

    Lehtinen, Taru; Schlatter, Norman; Baumgarten, Andreas; Bechini, Luca; Krüger, Janine; Grignani, Carlo; Zavattaro, Laura; Costamagna, Chiara; Spiegel, Heide

    2014-05-01

    Soil organic matter (SOM) improves soil physical (e.g. increased aggregate stability), chemical (e.g. cation exchange capacity) and biological (e.g. biodiversity, earthworms) properties. The sequestration of soil organic carbon (SOC) may mitigate climate change. However, as much as 25-75% of the initial SOC in world agricultural soils may have been lost due to intensive agriculture (Lal, 2013). The European Commission has described the decline of organic matter (OM) as one of the major threats to soils (COM(2006) 231). Incorporation of crop residues may be a sustainable and cost-efficient management practice to maintain the SOC levels and to increase soil fertility in European agricultural soils. Especially Mediterranean soils that have low initial SOC concentrations, and areas where stockless croplands predominate may be suitable for crop residue incorporation. In this study, we aim to quantify the effects of crop residue incorporation on SOC and GHG emissions (CO2 and N2O) in different environmental zones (ENZs, Metzger et al., 2005) in Europe. Response ratios for SOC and GHG emissions were calculated from pairwise comparisons between crop residue incorporation and removal. Specifically, we investigated whether ENZs, clay content and experiment duration influence the response ratios. In addition, we studied how response ratios of SOM and crop yields were correlated. A total of 718 response ratios (RR) were derived from a total of 39 publications, representing 50 experiments (46 field and 4 laboratory) and 15 countries. The SOC concentrations and stocks increased by approximately 10% following crop residue incorporation. In contrast, CO2 emissions were approximately six times and N2O emissions 12 times higher following crop residue incorporation. The effect of ENZ on the response ratios was not significant. For SOC concentration, the >35% clay content had significantly approximately 8% higher response ratios compared to 18-35% clay content. As the duration of the

  8. Growth and yield responses of crops and macronutrient balance influenced by commercial organic manure used as a partial substitute for chemical fertilizers in an intensive vegetable cropping system

    NASA Astrophysics Data System (ADS)

    Lu, H. J.; Ye, Z. Q.; Zhang, X. L.; Lin, X. Y.; Ni, W. Z.

    A long-term field experiment was conducted with an annual rotation of tomato-radish-pakchoi to assess the effects of a commercial organic manure (COM) used as a partial substitute for chemical fertilizers on crop yield and nutrient balance in an intensive vegetable cropping system. Four treatments as chemical fertilizers (T1), chemical fertilizers + lower rate of COM (T2), chemical fertilizers + medium rate of COM (T3), and chemical fertilizers + high rate of COM (T4) were designed in the present experiment. The supplied doses of N, P, and K were equal for all treatments. Results showed that there were no significant differences in shoot biomass and market yields of tomato, radish and pakchoi among treatments ( P > 0.05). It was found that positive P and K balance existed in the tomato-radish-pakchoi cropping system of all treatments. Compared with no manure treatment (T1), application of medium rate of COM (T3) decreased N, P runoff losses, increased N, P, K contents in crop tissues except N, P in pakchoi shoot, and lessened P, K accumulation in soils, accordingly, improved the efficiency of macronutrient. It was concluded that appropriate COM used as a partial substitute for chemical fertilizers could not only meet the crops’ nutrient requirement, but also improved the efficiency of macronutrient and remained positive balance of P and K in the intensive tomato-radish-pakchoi cropping system, which can be regarded as an effective measure for a contribution towards sustainable agriculture and a control pathway for reducing the potential risk of castoff to water environment.

  9. Impact of Bioenergy Crops in a Carbon Dioxide Constrained World: An Application of the MiniCAM Energy-Agriculture and Land Use Model

    SciTech Connect

    Gillingham, Kenneth; Smith, Steven J.; Sands, Ronald D.

    2007-10-01

    In the coming century, modern bioenergy crops have the potential to play a crucial role in the global energy mix, especially under policies to reduce carbon dioxide emissions as proposed by many in the international community. Previous studies have not fully addressed many of the dynamic interactions and effects of a policy-induced expansion of bioenergy crop production, particularly on crop yields and human food consumption. This study combines an updated agriculture and land use (AgLU) model with a well-developed energy-economic model to provide an analysis of the effects of bioenergy crops on energy, agricultural and land use systems. The results indicate that carbon mitigation policies can stimulate a large production of bioenergy crops, dependent on the severity of the policy. This production of bioenergy crops can lead to several impacts on the agriculture and land use system: decreases in forestland and unmanaged land, decreases in the average yield of food crops, increases in the prices of food crops, and decreases in the level of human consumption of calories.

  10. Plant growth promotion in cereal and leguminous agricultural important plants: from microorganism capacities to crop production.

    PubMed

    Pérez-Montaño, F; Alías-Villegas, C; Bellogín, R A; del Cerro, P; Espuny, M R; Jiménez-Guerrero, I; López-Baena, F J; Ollero, F J; Cubo, T

    2014-01-01

    Plant growth-promoting rhizobacteria (PGPR) are free-living bacteria which actively colonize plant roots, exerting beneficial effects on plant development. The PGPR may (i) promote the plant growth either by using their own metabolism (solubilizing phosphates, producing hormones or fixing nitrogen) or directly affecting the plant metabolism (increasing the uptake of water and minerals), enhancing root development, increasing the enzymatic activity of the plant or "helping" other beneficial microorganisms to enhance their action on the plants; (ii) or may promote the plant growth by suppressing plant pathogens. These abilities are of great agriculture importance in terms of improving soil fertility and crop yield, thus reducing the negative impact of chemical fertilizers on the environment. The progress in the last decade in using PGPR in a variety of plants (maize, rice, wheat, soybean and bean) along with their mechanism of action are summarized and discussed here.

  11. Phytotoxic risk assessment of ambient air pollution on agricultural crops in Selangor State, Malaysia.

    PubMed

    Ishii, S; Bell, J N B; Marshall, F M

    2007-11-01

    The phytotoxic risk of ambient air pollution to local vegetation was assessed in Selangor State, Malaysia. The AOT40 value was calculated by means of the continuously monitored daily maximum concentration and the local diurnal pattern of O3. Together with minor risks associated with the levels of NO2 and SO2, the study found that the monthly AOT40 values in these peri-urban sites were consistently over 1.0 ppm.h, which is well in exceedance of the given European critical level. Linking the O3 level to actual agricultural crop production in Selangor State also indicated that the extent of yield losses could have ranged from 1.6 to 5.0% (by weight) in 2000. Despite a number of uncertainties, the study showed a simple but useful methodological framework for phytotoxic risk assessment with a limited data set, which could contribute to appropriate policy discussion and countermeasures in countries under similar conditions.

  12. 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.

  13. The Role of Crop Systems Simulation in Agriculture and Environment

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Over the past 30 to 40 years, simulation of crop systems has advanced from a neophyte science with inadequate computing power into a robust and increasingly accepted science supported by improved software, languages, development tools, and computer capabilities. Crop system simulators contain mathe...

  14. Transgenic Crops and Sustainable Agriculture in the European Context

    ERIC Educational Resources Information Center

    Ponti, Luigi

    2005-01-01

    The rapid adoption of transgenic crops in the United States, Argentina, and Canada stands in strong contrast to the situation in the European Union (EU), where a de facto moratorium has been in place since 1998. This article reviews recent scientific literature relevant to the problematic introduction of transgenic crops in the EU to assess if…

  15. Cover Crop Chart: An Outreach Tool for Agricultural Producers

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Interest in cover crops by farmers and ranchers throughout the Northern Great Plains has increased the need for information on the suitability of a diverse portfolio of crops for different production and management resource goals. To help address this need, Northern Great Plains Research Laboratory...

  16. Effects of simulated sulfuric acid rain on yield, growth, and foliar injury of several crops

    SciTech Connect

    Lee, J.J.; Neely, G.E.; Perrigan, S.C.; Grothaus, L.C.

    1980-10-01

    This study was designed to reveal patterns of response of major United States crops to sulfuric acid rain. Potted plants were grown in field chambers and exposed to simulated sulfuric acid rain (pH 3.0, 3.5 or 4.0) or to a control rain (pH 5.6). At harvest, the weights of the marketable portion, total aboveground portion and roots were determined for 28 crops. Of these, marketable yield production was inhibited for 5 crops (radish, beet, carrot, mustard greens, broccoli), stimulated for 6 crops (tomato, green pepper, strawberry, alfalfa, orchardgrass, timothy), and ambiguously affected for 1 crop (potato). In addition, stem and leaf production of sweet corn was stimulated. Visible injury of tomatoes might have decreased their marketability. No statistically significant effects on yield were observed for the other 15 crops. The results suggest that the likelihood of yield being affected by acid rain depends on the part of the plant utilized, as well as on species. Effects on the aboveground portions of crops and on roots are also presented. Plants were regularly examined for foliar injury associated with acid rain. Of the 35 cultivars examined, the foliage of 31 was injured at pH 3.0, 28 at pH 3.5, and 5 at pH 4.0. Foliar injury was not generally related to effects on yield. However, foilar injury of swiss chard, mustard greens and spinach was severe enough to adversely affect marketability.

  17. 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; Gaydon, Donald; Marcaida, Manuel, III; Nakagawa, Hiroshi; Oriol, Philippe; Ruane, Alex C.; Ruget, Francoise; Singh, Balwinder; Singh, Upendra; Tang, Liang; Tao, Fulu; Wilkens, Paul; Yoshida, Hiroe; Zhang, Zhao; Bouman, Bas

    2014-01-01

    Predicting rice (Oryza sativa) productivity under future climates is important for global food security. Ecophysiological crop models in combination with climate model outputs are commonly used in yield prediction, but uncertainties associated with crop models remain largely unquantified. We evaluated 13 rice models against multi-year experimental yield data at four sites with diverse climatic conditions in Asia and examined whether different modeling approaches on major physiological processes attribute to the uncertainties of prediction to field measured yields and to the uncertainties of sensitivity to changes in temperature and CO2 concentration [CO2]. We also examined whether a use of an ensemble of crop models can reduce the uncertainties. Individual models did not consistently reproduce both experimental and regional yields well, and uncertainty was larger at the warmest and coolest sites. The variation in yield projections was larger among crop models than variation resulting from 16 global climate model-based scenarios. However, the mean of predictions of all crop models reproduced experimental data, with an uncertainty of less than 10 percent of measured yields. Using an ensemble of eight models calibrated only for phenology or five models calibrated in detail resulted in the uncertainty equivalent to that of the measured yield in well-controlled agronomic field experiments. Sensitivity analysis indicates the necessity to improve the accuracy in predicting both biomass and harvest index in response to increasing [CO2] and temperature.

  18. Uncertainties in predicting rice yield by current crop models under a wide range of climatic conditions.

    PubMed

    Li, Tao; Hasegawa, Toshihiro; Yin, Xinyou; Zhu, Yan; Boote, Kenneth; Adam, Myriam; Bregaglio, Simone; Buis, Samuel; Confalonieri, Roberto; Fumoto, Tamon; Gaydon, Donald; Marcaida, Manuel; Nakagawa, Hiroshi; Oriol, Philippe; Ruane, Alex C; Ruget, Françoise; Singh, Balwinder-; Singh, Upendra; Tang, Liang; Tao, Fulu; Wilkens, Paul; Yoshida, Hiroe; Zhang, Zhao; Bouman, Bas

    2015-03-01

    Predicting rice (Oryza sativa) productivity under future climates is important for global food security. Ecophysiological crop models in combination with climate model outputs are commonly used in yield prediction, but uncertainties associated with crop models remain largely unquantified. We evaluated 13 rice models against multi-year experimental yield data at four sites with diverse climatic conditions in Asia and examined whether different modeling approaches on major physiological processes attribute to the uncertainties of prediction to field measured yields and to the uncertainties of sensitivity to changes in temperature and CO2 concentration [CO2 ]. We also examined whether a use of an ensemble of crop models can reduce the uncertainties. Individual models did not consistently reproduce both experimental and regional yields well, and uncertainty was larger at the warmest and coolest sites. The variation in yield projections was larger among crop models than variation resulting from 16 global climate model-based scenarios. However, the mean of predictions of all crop models reproduced experimental data, with an uncertainty of less than 10% of measured yields. Using an ensemble of eight models calibrated only for phenology or five models calibrated in detail resulted in the uncertainty equivalent to that of the measured yield in well-controlled agronomic field experiments. Sensitivity analysis indicates the necessity to improve the accuracy in predicting both biomass and harvest index in response to increasing [CO2 ] and temperature.

  19. Monitoring Agricultural Cropping Patterns in the Great Lakes Basin Using MODIS-NDVI Time Series Data

    EPA Science Inventory

    This research examined changes in agricultural cropping patterns across the Great Lakes Basin (GLB) using the Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) data. Specific research objectives were to characterize the distribut...

  20. Fall cover cropping can increase arbuscular mycorrhizae in soils supporting intensive agricultural production

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Intensive agricultural practices, such as tillage, monocropping, seasonal fallow periods, and inorganic nutrient application have been shown to reduce arbuscular mycorrrhizal fungi (AMF) populations and thus may reduce benefits frequently provided to crops by AMF, such as nutrient acquisition, disea...

  1. Environmental enhancement using short-rotation woody crops and perennial grasses as alternative agricultural crops

    SciTech Connect

    Tolbert, V.R.; Schiller, A.

    1995-12-31

    Short-rotation woody crops and perennial grasses are grown as biomass feedstocks for energy and fiber. When replacing traditional row crops on similar lands, these alternative crops can provide multiple environmental benefits in addition to enhancing rural economies and providing valuable feedstock resources. The Department of Energy is supporting research to address how these crops can provide environmental benefits to soil, water and native wildlife species in addition to providing bioenergy feedstocks. Research is underway to address the potential for biomass crops to provide soil conservation and water quality improvements in crop settings. Replacement of traditional erosive row crops with biomass crops on marginal lands and establishment of biomass plantations as filter strips adjacent to streams and wetlands are being studied. The habitat value of different biomass crops for selected wildlife species is also under study. To date, these studies have shown that in comparison with row crops biomass plantings of both grass and tree crops increased biodiversity of birds; however, the habitat value of tree plantations is not equivalent to natural forests. The effects on native wildlife of establishing multiple plantations across a landscape are being studied. Combining findings on wildlife use of individual plantations with information on the cumulative effects of multiple plantations on wildlife populations can provide guidance for establishing and managing biomass crops to enhance biodiversity while providing biomass feedstocks. Data from site-specific environmental studies can provide input for evaluation of the probable effects of large-scale plantings at both landscape and regional levels of resolution.

  2. Climate-Induced Changes in Year-to-Year Variations in Yields of Major Crops

    NASA Astrophysics Data System (ADS)

    Iizumi, T.; Sakurai, G.; Ramankutty, N.

    2014-12-01

    Incidences of climatic extremes and associated crop failures in major food-producing regions have implications for commodity prices and generate concerns for national governments and commercial entities in import-dependent countries. While recent changes in temperature and precipitation extremes are evident, their impacts on the year-to-year variability of yield remain unclear. Here we present a global assessment of the impacts of recent climate change on year-to-year variations in yields of major crops using a global dataset of historical yields recently developed by merging satellite product and country-level crop statistics. We found that crop yield variability, in a large portion (24-53%) of the global harvested area, decreased from the earlier decade (1982—1993) to the later decade (1994—2005). However, yield variability also increased in a substantial portion (9—17%) of the harvested area. The changes in yield variability across 20—31% of the harvested area could be reasonably explained by changes in an agro-climatic index. Our findings reveal that climate change in the last two decades has led to more unstable yields in some regions. However, climate change has reduced yield variability in many more regions of the world. This suggests complex influences of climate change and agronomic technology on yield variability.

  3. The past impact of climate change on the yield of major crops

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

    Understanding the relationship between climate change and crop production is of paramount importance for food security. Previous statistical analyses of historical data have revealed the important impact of temperature increases on past crop yields. However, the direct effect of the [CO2] increase, known as CO2 fertilization effect, is difficult to estimate by simple statistical analysis because the average atmospheric [CO2] does not vary widely over space and time. Moreover, it is also difficult to estimate each climatic effect on crop yields with completely removing correlation among climatic factors. Although non-statistical approaches using process-based crop models may overcome these problems, the results of simple simulation studies may be misleading because of the uncertainty of the model parameters. In the present study, we applied a Bayesian statistical approach to estimate the parameters of a basic process-based model of crop growth (PRYSBI-2) and the past effect of each climatic factor on yields of major crops. 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. The datasets of maize, soybean, rice, and wheat yields during 1982-2006 with a spatial resolution of 1.125° × 1.125° were used for this purpose (Iizumi et al. 2013). The posterior distributions of model parameters were estimated for each spatial grid with 30 000 MCMC steps of 7 chains. Using this model, we produced maps of the estimated past impact of each climatic factor (including CO2 effect) on crop yields (see Figure for the effect of temperature changes on maize yield as an example). The results suggested large variations of the impact of the change in average temperature on major crop yields. The results also suggested a large impact of CO2 increase on C3 crops such as soybean, rice, and wheat. In some regions, the positive impact of CO2

  4. 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

  5. Elevated CO2 and the Sensitivity of Simulated Crop Yield to Variability in Climate

    NASA Astrophysics Data System (ADS)

    King, A. W.; Absar, M.; Surendran Nair, S.; Preston, B. L.

    2013-12-01

    It is known that the response of crop yields to elevated carbon dioxide (CO2) concentrations ('CO2 fertilization') can vary with climatic conditions (e.g., precipitation and soil moisture). Likewise, the sensitivity of crop yield to changes in climate may vary with atmospheric CO2 concentrations. The latter is an important consideration when extrapolating crop sensitivities derived from historical climate variability to a future world with higher levels of atmospheric CO2. Here we report on our investigation of how climate sensitivity of model simulated crop yield is influenced by rising and elevated CO2. Initial results from the EPIC crop model for simulated cotton yield at a site in southeastern Texas show very little if any difference in sensitivity to annual precipitation with static versus rising CO2 concentrations. These model results are consistent with experimental results from the Maricopa, Arizona Free Air CO2 Enrichment (FACE) experiment in which there was little or no difference in the productivity response of cotton under ample versus limited supplies of water. This contrasts with experimental results for wheat and sorghum, especially sorghum, in which the response to elevated CO2 was larger when water supply was limited. We report on the interaction between CO2 and the sensitivity of yield to climate with comparisons for different crops, between the EPIC and DSSAT crop models, across different indices of climate change, and between wet and dry climatic domains of the southern United States of America. This investigation is part of our ongoing effort better understand the sensitivity of crop yield to climate in order to inform regional integrated assessment modeling and considerations of adaption to climate change in the Gulf Coastal region of the southern United States.

  6. Scale-dependent effects of landscape composition and configuration on natural enemy diversity, crop herbivory, and yields.

    PubMed

    Martin, Emily A; Seo, Bumsuk; Park, Chan-Ryul; Reineking, Björn; Steffan-Dewenter, Ingolf

    2016-03-01

    (1) Land-use intensification in agricultural landscapes has led to changes in the way habitats and resources are distributed in space. Pests and their natural enemies are influenced by these changes, and by the farming intensity of crop fields. However, it is unknown whether the composition of landscapes (amount and diversity of land cover types) or their configuration (spatial arrangement of cover types) are more important for natural enemy diversity, and how they impact crop damage and yields. In addition, effects of interactions between local farming practices (organic vs. conventional) and landscape variables are unclear. (2) Here, we make use of a data set where landscape composition and configuration were uncorrelated across multiple spatial scales. Natural enemies, crop damage, and yields were sampled in 35 organic and conventional crop fields. Out of seven broad natural enemy taxa, five were positively affected by a complex landscape configuration. In contrast, only carabids were positively affected by the amount of seminatural habitat around fields. Increasing diversity of land cover types had positive effects on some, but negative effects on other taxa. Effect sizes varied among taxa but increased with increasing spatial scale, defined by circular areas of increasing radius around fields. (3) The diversity of aerial, but not of ground-dwelling enemies was higher in fields under organic than conventional management. Interactions of local and landscape variables were important for birds, but not other enemies. Bird richness was higher in organic fields in simple landscapes, but not in landscapes with complex configuration or high land cover diversity. (4) Crop damage decreased with landscape diversity, but increased in conventional fields with complex configuration. Yields increased with both parameters in conventional fields only, and were higher on average in organic compared to conventional fields. Enemy diversity was positively related to crop damage

  7. Biochar application to temperate soils - effects on soil fertility and crop yield

    NASA Astrophysics Data System (ADS)

    Kloss, S.; Zehetner, F.; Feichtmair, S.; Wimmer, B.; Zechmeister-Boltenstern, S.; Kitzler, B.; Watzinger, A.; Soja, G.

    2012-04-01

    Biochar (BC) application to soil as a potential soil amendment is currently intensively explored. Depending on feedstock and highest treatment temperature (HTT), BC application to soil may contribute to the soil nutrient status by directly adding nutrients to the soil as well as by increasing pH, cation exchange and water holding capacity. These parameters are known to play an important role in the soil nutrient status and nutrient availability. A positive effect on plant growth after BC application to tropical soils has been observed repeatedly; however, the effect of BC application to soils in temperate climate regions is much less explored. We investigated the effect of BC to temperate soils and crop yield using a randomized pot experiment in a greenhouse with three agricultural soils (Planosol, Cambisol, Chernozem) and four BC types (from straw, mixed woodchips and vineyard pruning, all pyrolyzed at 525°C). In order to analyze the effect of pyrolysis temperature, we additionally applied vineyard pruning BC pyrolyzed at 400°C. Selected treatments were planted with mustard (Sinapis alba L.), followed by barley (Hordeum vulgare). Soil sampling was carried out after barley harvest. Investigated soil parameters included pH, electrical conductivity (EC), C/N ratio, cation exchange capacity (CEC), CAL-extractable P and K, EDTA extractable Cu, Fe, Mn, Zn as well as nitrogen supplying potential (NSP). Biomass production of the two crops was determined as well as its elemental composition. Biochar application (3% wood-based BC) caused a considerable pH increase for the acidic Planosol. The effect of BC application on CEC was dependent on the original status of the soil, notably soil pH and texture. 3 % BC application (wood) decreased CEC by 3.5 % and 10 % for the Chernozem and Cambisol, respectively, but increased CEC by 35 % for the acidic, sandy Planosol, which may be due to the strong liming effect found for the Planosol. BC application significantly raised CAL

  8. Estimated winter wheat yield from crop growth predicted by LANDSAT

    NASA Technical Reports Server (NTRS)

    Kanemasu, E. T.

    1977-01-01

    An evapotranspiration and growth model for winter wheat is reported. The inputs are daily solar radiation, maximum temperature, minimum temperature, precipitation/irrigation and leaf area index. The meteorological data were obtained from National Weather Service while LAI was obtained from LANDSAT multispectral scanner. The output provides daily estimates of potential evapotranspiration, transpiration, evaporation, soil moisture (50 cm depth), percentage depletion, net photosynthesis and dry matter production. Winter wheat yields are correlated with transpiration and dry matter accumulation.

  9. Cover crops alter the soil microbial community and increase potato tuber yield and quality

    Technology Transfer Automated Retrieval System (TEKTRAN)

    An on-going study at a commercial farm operation in the San Luis Valley, CO is examining the effect of various summer cover crops (mustard, canola, sorghum-sudangrass, and a wet fallow control) on potato tuber yield and quality. In four of the five years, potato tuber yield and quality has shown si...

  10. Starter fertilizer for managing cover crop-based organic rotational no-till corn yields

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Weed control and N availability limit yield in organic corn production. Grass and legume cover crops are combined in mixtures to provide both weed and fertility management; however, additional fertility may be required to maximize corn yield. Research was conducted at Beltsville, MD, Kinston, NC, an...

  11. Meteorological fluctuations define long-term crop yield patterns in conventional and organic production systems

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Periodic variability in meteorological patterns presents significant challenges to crop production consistency and yield stability. Meteorological influences on corn and soybean grain yields were analyzed over an 18-year period at a long-term experiment in Beltsville, Maryland, U.S.A., comparing c...

  12. A scalable satellite-based crop yield mapper: Integrating satellites and crop models for field-scale estimation in India

    NASA Astrophysics Data System (ADS)

    Jain, M.; Singh, B.; Srivastava, A.; Lobell, D. B.

    2015-12-01

    Food security will be challenged over the upcoming decades due to increased food demand, natural resource degradation, and climate change. In order to identify potential solutions to increase food security in the face of these changes, tools that can rapidly and accurately assess farm productivity are needed. With this aim, we have developed generalizable methods to map crop yields at the field scale using a combination of satellite imagery and crop models, and implement this approach within Google Earth Engine. We use these methods to examine wheat yield trends in Northern India, which provides over 15% of the global wheat supply and where over 80% of farmers rely on wheat as a staple food source. In addition, we identify the extent to which farmers are shifting sow date in response to heat stress, and how well shifting sow date reduces the negative impacts of heat stress on yield. To identify local-level decision-making, we map wheat sow date and yield at a high spatial resolution (30 m) using Landsat satellite imagery from 1980 to the present. This unique dataset allows us to examine sow date decisions at the field scale over 30 years, and by relating these decisions to weather experienced over the same time period, we can identify how farmers learn and adapt cropping decisions based on weather through time.

  13. Effects of nitrification inhibitors (DCD and DMPP) on nitrous oxide emission, crop yield and nitrogen uptake in a wheat-maize cropping system

    NASA Astrophysics Data System (ADS)

    Liu, C.; Wang, K.; Zheng, X.

    2013-04-01

    The application of nitrification inhibitors together with ammonium-based fertilizers is proposed as a potent method to decrease nitrous oxide (N2O) emission while promoting crop yield and nitrogen use efficiency in fertilized agricultural fields. To evaluate the effects of nitrification inhibitors, we conducted year-round measurements of N2O fluxes, yield, aboveground biomass, plant carbon and nitrogen contents, soil inorganic nitrogen and dissolved organic carbon contents and the main environmental factors for urea (U), urea + dicyandiamide (DCD) and urea + 3,4-dimethylpyrazol phosphate (DMPP) treatments in a wheat-maize rotation field. The cumulative N2O emissions were calculated to be 4.49 ± 0.21, 2.93 ± 0.06 and 2.78 ± 0.16 kg N ha-1 yr-1 for the U, DCD and DMPP treatments, respectively. Therefore, the DCD and DMPP treatments significantly decreased the annual emissions by 35% and 38%, respectively (p < 0.01). The variations of soil temperature, moisture and inorganic nitrogen content regulated the seasonal fluctuation of N2O emissions. When the emissions presented clearly temporal variations, high-frequency measurements or optimized sampling schedule for intermittent measurements would likely provide more accurate estimations of annual cumulative emission and treatment effect. The application of nitrification inhibitors significantly increased the soil inorganic nitrogen content (p < 0.01); shifted the main soil inorganic nitrogen form from nitrate to ammonium; and tended to increase the dissolved organic carbon content, crop yield, aboveground biomass and nitrogen uptake by aboveground plant. The results demonstrate the roles the nitrification inhibitors play in enhancing yield and nitrogen use efficiency and reducing N2O emission from the wheat-maize cropping system.

  14. Dryland soil chemical properties and crop yields affected by long-term tillage and cropping sequence

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Information on the effect of long-term management on soil nutrients and chemical properties is scanty. We examined the 30-yr effect of tillage frequency and cropping sequence combination on dryland soil Olsen-P, K, Ca, Mg, Na, SO4-S, and Zn concentrations, pH, electrical conductivity (EC), and catio...

  15. Effects of Break Crops on Yield and Grain Protein Concentration of Barley in a Boreal Climate

    PubMed Central

    Zou, Ling; Yli-Halla, Markku; Stoddard, Frederick L.; Mäkelä, Pirjo S. A.

    2015-01-01

    Rotation with dicotyledonous crops to break cereal monoculture has proven to be beneficial to successive cereals. In two fields where the soil had been subjected to prolonged, continuous cereal production, two 3-year rotation trials were established. In the first year, faba bean, turnip rape and barley were grown, as first crops, in large blocks and their residues tilled into the soil after harvest. In the following year, barley, buckwheat, caraway, faba bean, hemp and white lupin were sown, as second crops, in each block and incorporated either at flowering stage (except barley) or after harvest. In the third year, barley was grown in all plots and its yield and grain protein concentration were determined. Mineral N in the plough layer was determined two months after incorporation of crops and again before sowing barley in the following year. The effect of faba bean and turnip rape on improving barley yields and grain protein concentration was still detectable two years after they were grown. The yield response of barley was not sensitive to the growth stage of second crops when they were incorporated, but was to different second crops, showing clear benefits averaging 6-7% after white lupin, faba bean and hemp but no benefit from caraway or buckwheat. The effect of increased N in the plough layer derived from rotation crops on barley yields was minor. Incorporation of plants at flowering stage slightly increased third-year barley grain protein concentration but posed a great potential for N loss compared with incorporation of crop residues after harvest, showing the value of either delayed incorporation or using catch crops. PMID:26076452

  16. [Effects of straw returning on the integrated soil fertility and crop yield in southern China].

    PubMed

    Yang, Fan; Dong, Yan; Xu, Ming-Gang; Bao, Yao-Xian

    2012-11-01

    Based on the data from 94 experiments of straw returning in Anhui, Jiangxi, Hunan, Hubei, Guangxi, Sichuan, and Chongqing, and by using mathematic modeling approach, this paper evaluated the effects of straw returning on the soil fertility and crop yield in southern China. Obvious regional differences were observed in the soil fertility index (SFI) and crop yield response. In study area, the croplands with the SFI of Grade III and Grade IV were predominant, occupying 69.1% and 21.3% of the total, respectively. Averagely, straw returning increased the SFI and crop yield by 6.8% and 4.4%, respectively, as compared with the control (no straw returning). The SFI was significantly linearly correlated with rice yield, and could well reflect the integrated soil fertility in study area. At present, straw returning with decomposing agent added is one of the most important measures to improve the integrated soil fertility in southern China, which should be widely popularized.

  17. Mutually beneficial pollinator diversity and crop yield outcomes in small and large farms.

    PubMed

    Garibaldi, Lucas A; Carvalheiro, Luísa G; Vaissière, Bernard E; Gemmill-Herren, Barbara; Hipólito, Juliana; Freitas, Breno M; Ngo, Hien T; Azzu, Nadine; Sáez, Agustín; Åström, Jens; An, Jiandong; Blochtein, Betina; Buchori, Damayanti; Chamorro García, Fermín J; Oliveira da Silva, Fabiana; Devkota, Kedar; Ribeiro, Márcia de Fátima; Freitas, Leandro; Gaglianone, Maria C; Goss, Maria; Irshad, Mohammad; Kasina, Muo; Pacheco Filho, Alípio J S; Kiill, Lucia H Piedade; Kwapong, Peter; Parra, Guiomar Nates; Pires, Carmen; Pires, Viviane; Rawal, Ranbeer S; Rizali, Akhmad; Saraiva, Antonio M; Veldtman, Ruan; Viana, Blandina F; Witter, Sidia; Zhang, Hong

    2016-01-22

    Ecological intensification, or the improvement of crop yield through enhancement of biodiversity, may be a sustainable pathway toward greater food supplies. Such sustainable increases may be especially important for the 2 billion people reliant on small farms, many of which are undernourished, yet we know little about the efficacy of this approach. Using a coordinated protocol across regions and crops, we quantify to what degree enhancing pollinator density and richness can improve yields on 344 fields from 33 pollinator-dependent crop systems in small and large farms from Africa, Asia, and Latin America. For fields less than 2 hectares, we found that yield gaps could be closed by a median of 24% through higher flower-visitor density. For larger fields, such benefits only occurred at high flower-visitor richness. Worldwide, our study demonstrates that ecological intensification can create synchronous biodiversity and yield outcomes.

  18. Assessment of crop productivity over intensively managed agriculture regions in India and Australia using solar-induced fluorescence remote sensing data

    NASA Astrophysics Data System (ADS)

    Devadas, R.; Huete, A. R.; Patel, N. R.; Padalia, H.; Restrepo-Coupe, N.; Kuruvilla, A.

    2015-12-01

    Satellite based estimation of solar-induced terrestrial fluorescence (SIF) is considered to be a direct measure of photosynthetic functional status of the vegetation. Prior studies have shown SIF to more accurately retrieve the productivity of intensively managed croplands, as in the U.S. corn belt. In this study, we assessed and compared agricultural productivity over two intensive crop production regions in Australia and India using SIF data, traditional spectral measures, and crop yield data. Regional level wheat yield data were obtained for the Indo-Gangetic Plains (IGP) in India and the Murray Darling Basin (MDB) in Australia for analyses with GOME-2 SIF satellite and MODIS VI measurements, and gross primary productivity from flux towers. We investigated the importance of integrating traditional meteorological parameters and ground based data with time-series vegetation indices for scaling of SIF to obtain robust yield prediction models for application across years and continents. This study further explored the relationship of inter annual variations in crop phenology metrics through SIF retrievals and its relationship with crop yields. The IGP study region showed systematic cycles of double cropping. MDB region on the other hand showed cycles of pronounced winter cropping and a weaker and variable second cropping over the analysis period. For various winter wheat crop seasons in IGP, from 2007 to 2012, SIF explained and accounted between 48 to 74 per cent of the variations in regional wheat yields. Similar results were obtained in the case of MDB also, however, the relationship between SIF and yield estimates was weaker (R2 = 0.44). SIF measurements, as a surrogate of crop productivity, were considerably higher over the highly productive IGP region in almost all the years considered. The SIF data shows immense potential for modelling agricultural productivity, particularly as the resolution of SIF retrievals continues to improve.

  19. 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

  20. [Prediction of winter wheat yield based on crop biomass estimation at regional scale].

    PubMed

    Ren, Jian-Qiang; Liu, Xing-Ren; Chen, Zhong-Xin; Zhou, Qing-Bo; Tang, Hua-Jun

    2009-04-01

    Based on the 2004 in situ data of crop yield, remote sensing inversed photosynthetically active radiation (PAR), fraction of photosynthetically active radiation (f(PAR)), climate, and soil moisture in 83 typical winter wheat sampling field of 45 counties in Shijiazhuang, Hengshui, and Xingtai of Hebei Province, a simplified model for calculating the light use efficiency (epsilon) of winter wheat in Huanghuaihai Plain was established. According to the crop accumulated biomass from March to May and corrected by harvest index, the quantitative relationship between crop biomass and crop yield for winter wheat was set up, and applied in the 235 counties in Huanghuaihai Plain region of Hebei Province and Shandong Province and validated by the official crop statistical data at county level in 2004. The results showed that the root mean square error (RMSE) of predicted winter wheat yield in study area was 238.5 kg x hm(-2), and the relative error was 4.28%, suggesting that it was feasible to predict winter wheat yield by crop biomass estimation based on remote sensing data.

  1. A synthesis of AOT40-based response functions and critical levels of ozone for agricultural and horticultural crops

    NASA Astrophysics Data System (ADS)

    Mills, G.; Buse, A.; Gimeno, B.; Bermejo, V.; Holland, M.; Emberson, L.; Pleijel, H.

    Crop-response data from over 700 published papers and conference proceedings have been analysed with the aim of establishing ozone dose-response functions for a wide range of European agricultural and horticultural crops. Data that met rigorous selection criteria (e.g. field-based, ozone concentrations within European range, full season exposure period) were used to derive AOT40-yield response functions for 19 crops by first converting the published ozone concentration data into AOT40 (AOT40 is the hourly mean ozone concentration accumulated over a threshold ozone concentration of 40 ppb during daylight hours, units ppm h). For any individual crop, there were no significant differences in the linear response functions derived for experiments conducted in the USA or Europe, or for individual cultivars. Three statistically independent groups were identified: ozone sensitive crops (wheat, water melon, pulses, cotton, turnip, tomato, onion, soybean and lettuce); moderately sensitive crops (sugar beet, potato, oilseed rape, tobacco, rice, maize, grape and broccoli) and ozone resistant (barley and fruit represented by plum and strawberry). Critical levels of a 3 month AOT40 of 3 ppm h and a 3.5 month AOT40 of 6 ppm h were derived from the functions for wheat and tomato, respectively.

  2. Environmental enhancement using short-rotation woody crops and perennial grasses as alternative agricultural crops

    SciTech Connect

    Tolbert, V.R.; Schiller, A.

    1996-10-01

    Short-rotation woody crops and perennial grasses are grown as biomass feedstocks for energy and fiber. When replacing traditional row crops on similar lands, these alternative crops can provide multiple environmental benefits in addition to enhancing rural economies and providing valuable resources. The DOE is supporting research to address how these crops can provide environmental benefits to soil, water, and native wildlife species in addition to providing bioenergy feedstocks. Research is underway to address the potential for biomass crops to provide soils conservation and water quality improvements in crop settings. Replacement of traditional erosive row drops with biomass crops on marginal lands and establishment of biomass plantations as filter strips adjacent to streams and wetlands are being studied. The habitat value of different crops for wildlife species is also considered. Combining findings on wildlife use of individual plantations with information on the cumulative effects of multiple plantations on wildlife populations can provide guidance for establishing and managing biomass crops to enhance biodiversity while providing feedstocks. Data from site-specific environmental studies can provide input for evaluation of the effects of large-scale plantings at both landscape and regional levels of resolution.

  3. Impacts of Different Assimilation Methodologies on Crop Yield Estimates Using Active and Passive Microwave Dataset at L-Band

    NASA Astrophysics Data System (ADS)

    Liu, P.; Bongiovanni, T. E.; Monsivais-Huertero, A.; Bindlish, R.; Judge, J.

    2013-12-01

    Accurate estimates of crop yield are important for managing agricultural production and food security. Although the crop growth models, such as the Decision Support System Agrotechnology Transfer (DSSAT), have been used to simulate crop growth and development, the crop yield estimates still diverge from the reality due to different sources of errors in the models and computation. Auxiliary observations may be incorporated into such dynamic models to improve predictions using data assimilation. Active and passive (AP) microwave observations at L-band (1-2 GHz) are sensitive to dielectric and geometric properties of soil and vegetation, including soil moisture (SM), vegetation water content (VWC), surface roughness, and vegetation structure. Because SM and VWC are one of the governing factors in estimating crop yield, microwave observations may be used to improve crop yield estimates. Current studies have shown that active observations are more sensitive to the surface roughness of soil and vegetation structure during the growing season, while the passive observations are more sensitive to the SM. Backscatter and emission models linked with the DSSAT model (DSSAT-A-P) allow assimilation of microwave observations of backscattering coefficient (σ0) and brightness temperature (TB) may provide biophysically realistic estimates of model states and parameters. The present ESA Soil Moisture Ocean Salinity (SMOS) mission provides passive observations at 1.41 GHz at 25 km every 2-3 days, and the NASA/CNDAE Aquarius mission provides L-band AP observations at spatial resolution of 150 km with a repeat coverage of 7 days for global SM products. In 2014, the planned NASA Soil Moisture Active Passive mission will provide AP observations at 1.26 and 1.41 GHz at the spatial resolutions of 3 and 30 km, respectively, with a repeat coverage of 2-3 days. The goal of this study is to understand the impacts of assimilation of asynchronous and synchronous AP observations on crop yield

  4. Role of native shrubs of the Sahel in mitigating water and nutrient stresses of agricultural crops

    NASA Astrophysics Data System (ADS)

    Bayala, R.; Ghezzehei, T. A.; Bogie, N. A.; Diedhiou, I.; Dick, R.

    2015-12-01

    In the semi arid zone of the Sahel native woody shrubs are present in many farmers' fields. The native density of these shrubs is fairly low at around 200 to 300 individuals per hectare. An ongoing study in the Peanut Basin, Senegal has shown a vast improvement in crop yields when annual food crops are planted with the shrub Guiera senegalensis, especially in years of low or irregular precipitation. Shrubs in field plots established in 2003 where a rotation of peanuts and millet are grown are planted at a much higher density of 1500-1830 individuals per hectare. In order to increase the density of shrubs on the landscape, the shrubs must be cultivated. We monitored soil moisture, soil temperature, and growth of recently transplanted individuals at a field station in Thies, Senegal.This study seeks to determine the growth characteristics and water use of young shrubs in order to inform possible future plantations of the shrubs in a more intensely managed agroecosystem. If this technique of intercropping is to be expanded we must not exceed the carrying capacity of the landscape. In vulnerable ecosystems where natural resources are scarce and farming inputs are low, we must work to determine ways of exploiting the adaptation of local agroecosystems to increase the sustainability of agriculture in the region.

  5. New oilseed crops for fuels and chemicals: ecological and agricultural considerations

    SciTech Connect

    Draper, H.M. III

    1982-01-01

    A new approach to agriculture involving oilseed crops for fuels and chemicals is proposed. Such an approach to biomass energy would be designed to benefit the limited-resource farmer in the United States and the Third World, while at the same time not aggravating global ecological problems such as deforestation and desertification. Since food versus fuel conflicts arise when plants are grown for industrial uses on good lands, productivity questions are examined, with the conclusion that fundamental biological constraints will limit yields on marginal lands. Conventional vegetable oil crops are limited in their climatic requirements or are not well adapted to limited-resource farming; therefore, new oilseeds more adaptable to small farming are proposed. Such plants would be for specialty chemicals or to meet local energy needs. Chemicals produced would be low-volume, labor-intensive, and possibly high-priced. A list of 281 potential new oilseeds is provided, and each is classified according to potential, multiple product potential, and vegetative characteristics. Using climatic data which are available for most areas, a method of making rough productivity estimates for unconventional wild plant oilseeds is proposed, and example resource estimates are provided for the southeastern United States.

  6. Activated Carbon Derived from Fast Pyrolysis Liquids Production of Agricultural Residues and Energy Crops

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Fast pyrolysis is a thermochemical method that can be used for processing energy crops such as switchgrass, alfalfa, soybean straw, corn stover as well as agricultural residuals (broiler litter) for bio-oil production. Researchers with the Agriculture Research Service (ARS) of the USDA developed a 2...

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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,...

  8. Simulating county-level crop yields in the Conterminous United States using the Community Land Model: The effects of optimizing irrigation and fertilization: IMPROVING CROP YIELD SIMULATIONS IN CLM

    SciTech Connect

    Leng, Guoyong; Zhang, Xuesong; Huang, Maoyi; Yang, Qichun; Rafique, Rashid; Asrar, Ghassem R.; Ruby Leung, L.

    2016-12-19

    Representing agricultural systems explicitly in Earth system models is important for understanding the water-energy-food nexus under climate change. In this study, we applied Version 4.5 of the Community Land Model (CLM) at a 0.125 degree resolution to provide the first county-scale validation of the model in simulating crop yields over the Conterminous United States (CONUS). We focused on corn and soybean that are both important grain crops and biofuel feedstocks (corn for bioethanol; soybean for biodiesel). We find that the default model substantially under- or over-estimate yields of corn and soybean as compared to the US Department of Agriculture (USDA) census data, with corresponding county-level root-mean square error (RMSE) of 45.3 Bu/acre and 12.9 Bu/acre, or 42% and 38% of the US mean yields for these crops, respectively. Based on the numerical experiments, the lack of proper representation of agricultural management practices, such as irrigation and fertilization, was identified as a major cause for the model's poor performance. After implementing an irrigation management scheme calibrated against county-level US Geological Survey (USGS) census data, the county-level RMSE for corn yields reduced to 42.6 Bu/acre. We then incorporated an optimized fertilizer scheme in rate and timing, which is achieved by the constraining annual total fertilizer amount against the USDA data, considering the dynamics between fertilizer demand and supply and adopting a calibrated fertilizer scheduling map. The proposed approach is shown to be effective in increasing the fertilizer use efficiency for corn yields, with county-level RMSE reduced to 23.8 Bu/acre (or 22% of the US mean yield). In regions with similar annual fertilizer applied as in the default, the improvements in corn yield simulations are mainly attributed to application of longer fertilization periods and consideration of the dynamics between fertilizer demand and supply. For soybean which is capable of fixing

  9. Decreasing, not increasing, leaf area will raise crop yields under global atmospheric change.

    PubMed

    Srinivasan, Venkatraman; Kumar, Praveen; Long, Stephen P

    2017-04-01

    Without new innovations, present rates of increase in yields of food crops globally are inadequate to meet the projected rising food demand for 2050 and beyond. A prevailing response of crops to rising [CO2 ] is an increase in leaf area. This is especially marked in soybean, the world's fourth largest food crop in terms of seed production, and the most important vegetable protein source. Is this increase in leaf area beneficial, with respect to increasing yield, or is it detrimental? It is shown from theory and experiment using open-air whole-season elevation of atmospheric [CO2 ] that it is detrimental not only under future conditions of elevated [CO2 ] but also under today's [CO2 ]. A mechanistic biophysical and biochemical model of canopy carbon exchange and microclimate (MLCan) was parameterized for a modern US Midwest soybean cultivar. Model simulations showed that soybean crops grown under current and elevated (550 [ppm]) [CO2 ] overinvest in leaves, and this is predicted to decrease productivity and seed yield 8% and 10%, respectively. This prediction was tested in replicated field trials in which a proportion of emerging leaves was removed prior to expansion, so lowering investment in leaves. The experiment was conducted under open-air conditions for current and future elevated [CO2 ] within the Soybean Free Air Concentration Enrichment facility (SoyFACE) in central Illinois. This treatment resulted in a statistically significant 8% yield increase. This is the first direct proof that a modern crop cultivar produces more leaf than is optimal for yield under today's and future [CO2 ] and that reducing leaf area would give higher yields. Breeding or bioengineering for lower leaf area could, therefore, contribute very significantly to meeting future demand for staple food crops given that an 8% yield increase across the USA alone would amount to 6.5 million metric tons annually.

  10. Reduced nitrogen losses following conversion of row crop agriculture to perennial biofuel crops

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Current biofuel feedstock crops such as corn lead to large environmental losses of N through nitrate leaching and N2O emissions, and require large inputs of N fertilizer. Second generation cellulosic crops have the potential to reduce these N losses, and provide even greater biomass for conversion t...

  11. Changes in water budgets and sediment yields from a hypothetical agricultural field as a function of landscape and management characteristics--A unit field modeling approach

    USGS Publications Warehouse

    Roth, Jason L.; Capel, Paul D.

    2012-01-01

    Crop agriculture occupies 13 percent of the conterminous United States. Agricultural management practices, such as crop and tillage types, affect the hydrologic flow paths through the landscape. Some agricultural practices, such as drainage and irrigation, create entirely new hydrologic flow paths upon the landscapes where they are implemented. These hydrologic changes can affect the magnitude and partitioning of water budgets and sediment erosion. Given the wide degree of variability amongst agricultural settings, changes in the magnitudes of hydrologic flow paths and sediment erosion induced by agricultural management practices commonly are difficult to characterize, quantify, and compare using only field observations. The Water Erosion Prediction Project (WEPP) model was used to simulate two landscape characteristics (slope and soil texture) and three agricultural management practices (land cover/crop type, tillage type, and selected agricultural land management practices) to evaluate their effects on the water budgets of and sediment yield from agricultural lands. An array of sixty-eight 60-year simulations were run, each representing a distinct natural or agricultural scenario with various slopes, soil textures, crop or land cover types, tillage types, and select agricultural management practices on an isolated 16.2-hectare field. Simulations were made to represent two common agricultural climate regimes: arid with sprinkler irrigation and humid. These climate regimes were constructed with actual climate and irrigation data. The results of these simulations demonstrate the magnitudes of potential changes in water budgets and sediment yields from lands as a result of landscape characteristics and agricultural practices adopted on them. These simulations showed that variations in landscape characteristics, such as slope and soil type, had appreciable effects on water budgets and sediment yields. As slopes increased, sediment yields increased in both the arid and

  12. Improvement of red pepper yield and soil environment by summer catch aquatic crops in greenhouses

    NASA Astrophysics Data System (ADS)

    Du, X. F.; Wang, L. Z.; Peng, J.; Wang, G. L.; Guo, X. S.; Wen, T. G.; Gu, D. L.; Wang, W. Z.; Wu, C. W.

    2016-08-01

    To investigate effects of the rotation of summer catch crops on remediation retrogressed soils in continuous cropping, a field experiment was conducted. Rice, water spinach, or cress were selected as summer catch crops; bare fallow during summer fallow was used as the control group. Results showed that aquatic crops grown in summer fallow period could effectively reduce soil bulk density and pH, facilitate soil nutrient release, and improve soil physical and chemical properties compared with those grown in fallow period. Paddy-upland rotation could improve soil microbial members and increase bacterial and actinomycete populations; by contrast, paddy-upland rotation could reduce fungal populations and enhance bacterium-to-fungus ratio. Paddy-upland rotation could also actively promote activities of soil enzymes, such as urease, phosphatase, invertase, and catalase. The proposed paddy-upland rotation significantly affected the growth of red pepper; the yield and quality of the grown red pepper were enhanced. Summer catch crops, such as rice, water spinach, and cress significantly increased pepper yield in the following growing season by 15.4%, 10.2% and 14.0%, respectively, compared with those grown in fallow treatment. Therefore, the proposed paddy-upland crop rotation could be a useful method to alleviate continuous cropping problems involved in cultivating red pepper in greenhouses.

  13. A coupled hydrologic and process-based crop dynamics model for studying climate change impacts on water resources and agricultural production

    NASA Astrophysics Data System (ADS)

    Chinnayakanahalli, K.; Adam, J. C.; Stöckle, C. O.; Nelson, R. L.; Barber, M. E.

    2010-12-01

    The hydrology of the Pacific Northwest (PNW), a prominent agricultural region in the U.S., is expected to be affected by climate change. Previous climate change studies in the PNW region suggest a likelihood of increasing temperatures and a shift in precipitation patterns, with precipitation higher in the winter and lower in the summer. The climate change-induced stress on the availability of water resources during the growing season may constrain irrigation and agricultural practices which will in turn affect crop production. In order to assess the climate change impacts on PNW agriculture, it is essential that we understand the relationships between crop dynamics and the hydrological cycle. The Variable Infiltration Capacity (VIC) hydrologic model, which solves the coupled water and energy balances of the hydrological cycle at the macro scale, has been previously used and calibrated for the PNW region. In order to improve the VIC model’s simulation of agricultural water dynamics, a crop growth sub-model based on the CropSyst cropping system model was developed and integrated into VIC. The U. S. Department of Agriculture (USDA) cropland data layer was used to identify agricultural land use patterns. For land uses identified as agricultural regions, the VIC model applies the crop sub-model to simulate biomass growth, crop yield, transpiration, and irrigation water demand. This coupled model presents opportunities for studying the impacts of climate change on irrigation water demand and agricultural production of the region. The historical period 1970 - 2000 was simulated to establish a baseline for surface water availability, irrigation demand, and biomass production in the Columbia River basin. The model will then be applied under a future (2030s) climate change scenario derived from statistically-downscaled Global Circulation Models output, in order to assess these climate change impacts. The results from this modeling approach are expected to help stakeholders

  14. Predicting the Impacts of Climate Change on Agricultural Yields and Water Resources in the Maumee River Watershed

    NASA Astrophysics Data System (ADS)

    Nagelkirk, R. L.; Kendall, A. D.; Basso, B.; Hyndman, D. W.

    2012-12-01

    Climate change will likely have considerable effects on agriculture in the Midwestern United States. Under current climate projections, end-of-century temperatures rise by approximately 4 C, while precipitation stays relatively unchanged despite a potential increase in heavy rainfall events. These trends have already been observed over the last century: rising temperatures have extended the growing season two days per decade and heavy rainfall events have become twice as common. In an effort to understand the likely effects of climate change on agriculture, maize and soybean yields in the Maumee River Watershed were simulated using the Systems Approach to Land Use Sustainability (SALUS) crop model. SALUS calculates daily crop growth in response to changing climate, soil, and management conditions. We test the hypotheses that 1) despite any positive effects of CO2 fertilization and allowing for higher yielding varieties, longer and warmer growing seasons will lead to excessive water- and heat-stress, lowering yields under current management practices, and 2) that double-cropping maize and soybeans successively in the same season to offset these losses may become feasible if sufficient late-season soil moisture is made available. Outputs of daily Leaf Area Index (LAI) and root mass from a range of SALUS models are then distributed spatially to drive regional hydrologic simulations using the Integrated Landscape Hydrology Model (ILHM). These coupled simulations demonstrate the response of streamflow and groundwater levels to different management strategies.

  15. Uncertainty in soil data can outweigh climate impact signals in global crop yield simulations

    PubMed Central

    Folberth, Christian; Skalský, Rastislav; Moltchanova, Elena; Balkovič, Juraj; Azevedo, Ligia B.; Obersteiner, Michael; van der Velde, Marijn

    2016-01-01

    Global gridded crop models (GGCMs) are increasingly used for agro-environmental assessments and estimates of climate change impacts on food production. Recently, the influence of climate data and weather variability on GGCM outcomes has come under detailed scrutiny, unlike the influence of soil data. Here we compare yield variability caused by the soil type selected for GGCM simulations to weather-induced yield variability. Without fertilizer application, soil-type-related yield variability generally outweighs the simulated inter-annual variability in yield due to weather. Increasing applications of fertilizer and irrigation reduce this variability until it is practically negligible. Importantly, estimated climate change effects on yield can be either negative or positive depending on the chosen soil type. Soils thus have the capacity to either buffer or amplify these impacts. Our findings call for improvements in soil data available for crop modelling and more explicit accounting for soil variability in GGCM simulations. PMID:27323866

  16. Identifying opportunities to reduce excess nitrogen in croplands while maintaining current crop yields

    NASA Astrophysics Data System (ADS)

    West, P. C.; Mueller, N. D.; Foley, J. A.

    2011-12-01

    Use of synthetic nitrogen fertilizer has greatly contributed to the increased crop yields brought about by the Green Revolution. Unfortunately, it also has also contributed to substantial excess nitrogen in the environment. Application of excess nitrogen not only is a waste of energy and other resources used to produce, transport and apply it, it also pollutes aquatic ecosystems and has led to the development of more than 200 hypoxic-or "dead"-zones in coastal areas around the world. How can we decrease use of excess nitrogen without compromising crop yields? To help address this challenge, our study (1) quantified hot spots of excess nitrogen, and (2) estimated how much nitrogen reduction is possible in these areas while still maintaining yields. We estimated excess nitrogen for major crops using a mass balance approach and global spatial data sets of crop area and yield, fertilizer application rates, and nitrogen deposition. Hot spots of excess nitrogen were identified by quantifying the smallest area within large river basins that contributed 25% and 50% of the total load within each basin. Nitrogen reduction scenarios were developed using a yield response model to estimate nitrogen application rates needed to maintain current yields. Our research indicated that excess nitrogen is concentrated in very small portions of croplands within river basins, with 25% of the total nitrogen load in each basin from ~10% of the cropland, and 50% of the total nitrogen load in each basin from ~25% of the cropland. Targeting reductions in application rates in these hot spots can allow us to maintain current crop yields while greatly reducing nitrogen loading to coastal areas and creating the opportunity to reallocate resources to boost yields on nitrogen-limited croplands elsewhere.

  17. Modeling the impact of ozone x drought interactions on regional crop yields.

    PubMed

    King, D A

    1988-01-01

    The influence of soil moisture stress on crop sensitivity to O3 was evaluated for corn (Zea mays L.), cotton (Gossypium hirsutum L.), soybean (Glycine max L. Merr.), and wheat (Triticum aestivum L.) grown in the United States. This assessment was accomplished by using yield forecasting models to estimate the influence of soil moisture deficits on regional yield and a previously developed model to predict moisture stress x O3 interactions. Reduced crop sensitivity to O3 was predicted for those regions and years for which soil moisture stress reduced yield. The models predicted a drought-induced reduction in crop sensitivity to O3 of approximately 20% for the 1979 to 1983 period; i.e. a hypothetical O3-induced yield reduction of 5% for adequately watered crops would have been reduced to a 4% effect by the 1979 to 1983 distribution of soil moisture deficits. However, predicted drought effects varied between crops, regions, and years. Uncertainties in the model predictions are also discussed.

  18. Subsistence Agriculture versus Cash Cropping: The Social Repercussions.

    ERIC Educational Resources Information Center

    Rennie, Sandra Joy

    1991-01-01

    The introduction of cash cropping in the Solomon Islands and Tonga has had negative effects on women, leading to deterioration in their status, decreased leisure time, fewer opportunities to earn cash, increased birth rate (to help with the increased workload), and more sharply defined sex roles. (SV)

  19. Genetically Engineered Crops and Certified Organic Agriculture for Improving Nutrition Security in Africa and South Asia.

    PubMed

    Pray, Carl; Ledermann, Samuel

    2016-01-01

    In Africa and South Asia, where nutrition insecurity is severe, two of the most prominent production technologies are genetically modified (GM) crops and certified organic agriculture. We analyze the potential impact pathways from agricultural production to nutrition. Our review of data and the literature reveals increasing farm-level income from cash crop production as the main pathway by which organic agriculture and GM agriculture improve nutrition. Potential secondary pathways include reduced prices of important food crops like maize due to GM maize production and increased food production using organic technology. Potential tertiary pathways are improvements in health due to reduced insecticide use. Challenges to the technologies achieving their impact include the politics of GM agriculture and the certification costs of organic agriculture. Given the importance of agricultural production in addressing nutrition security, accentuated by the post-2015 sustainable development agenda, the chapter concludes by stressing the importance of private and public sector research in improving the productivity and adoption of both GM and organic crops. In addition, the chapter reminds readers that increased farm income and productivity require complementary investments in health, education, food access and women's empowerment to actually improve nutrition security.

  20. Potential alternative fuel sources for agricultural crops and plant components

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The changing landscape of agricultural production is placing unprecedented demands on farmers as they face increasing global competition and greater natural resource conservation challenges. However, shrinking profit margins due to increasing input costs, particularly of fuel and fertilizer, can res...

  1. Assessing Agricultural Risks of Climate Change in the 21st Century in a Global Gridded Crop Model Intercomparison

    NASA Technical Reports Server (NTRS)

    Rosenzweig, Cynthia E.; Elliott, Joshua; Deryng, Delphine; Ruane, Alex C.; Mueller, Christoph; Arneth, Almut; Boote, Kenneth J.; Folberth, Christian; Glotter, Michael; Khabarov, Nikolay

    2014-01-01

    Here we present the results from an intercomparison of multiple global gridded crop models (GGCMs) within the framework of the Agricultural Model Intercomparison and Improvement Project and the Inter-Sectoral Impacts Model Intercomparison Project. Results indicate strong negative effects of climate change, especially at higher levels of warming and at low latitudes; models that include explicit nitrogen stress project more severe impacts. Across seven GGCMs, five global climate models, and four representative concentration pathways, model agreement on direction of yield changes is found in many major agricultural regions at both low and high latitudes; however, reducing uncertainty in sign of response in mid-latitude regions remains a challenge. Uncertainties related to the representation of carbon dioxide, nitrogen, and high temperature effects demonstrated here show that further research is urgently needed to better understand effects of climate change on agricultural production and to devise targeted adaptation strategies.

  2. Assessing agricultural risks of climate change in the 21st century in a global gridded crop model intercomparison.

    PubMed

    Rosenzweig, Cynthia; Elliott, Joshua; Deryng, Delphine; Ruane, Alex C; Müller, Christoph; Arneth, Almut; Boote, Kenneth J; Folberth, Christian; Glotter, Michael; Khabarov, Nikolay; Neumann, Kathleen; Piontek, Franziska; Pugh, Thomas A M; Schmid, Erwin; Stehfest, Elke; Yang, Hong; Jones, James W

    2014-03-04

    Here we present the results from an intercomparison of multiple global gridded crop models (GGCMs) within the framework of the Agricultural Model Intercomparison and Improvement Project and the Inter-Sectoral Impacts Model Intercomparison Project. Results indicate strong negative effects of climate change, especially at higher levels of warming and at low latitudes; models that include explicit nitrogen stress project more severe impacts. Across seven GGCMs, five global climate models, and four representative concentration pathways, model agreement on direction of yield changes is found in many major agricultural regions at both low and high latitudes; however, reducing uncertainty in sign of response in mid-latitude regions remains a challenge. Uncertainties related to the representation of carbon dioxide, nitrogen, and high temperature effects demonstrated here show that further research is urgently needed to better understand effects of climate change on agricultural production and to devise targeted adaptation strategies.

  3. Multiyear high-resolution carbon exchange over European croplands from the integration of observed crop yields into CarbonTracker Europe

    NASA Astrophysics Data System (ADS)

    Combe, Marie; Vilà-Guerau de Arellano, Jordi; de Wit, Allard; Peters, Wouter

    2016-04-01

    Carbon exchange over croplands plays an important role in the European carbon cycle over daily-to-seasonal time scales. Not only do crops occupy one fourth of the European land area, but their photosynthesis and respiration are large and affect CO2 mole fractions at nearly every atmospheric CO2 monitoring site. A better description of this crop carbon exchange in our CarbonTracker Europe data assimilation system - which currently treats crops as unmanaged grasslands - could strongly improve its ability to constrain terrestrial carbon fluxes. Available long-term observations of crop yield, harvest, and cultivated area allow such improvements, when combined with the new crop-modeling framework we present. This framework can model the carbon fluxes of 10 major European crops at high spatial and temporal resolution, on a 12x12 km grid and 3-hourly time-step. The development of this framework is threefold: firstly, we optimize crop growth using the process-based WOrld FOod STudies (WOFOST) agricultural crop growth model. Simulated yields are downscaled to match regional crop yield observations from the Statistical Office of the European Union (EUROSTAT) by estimating a yearly regional parameter for each crop species: the yield gap factor. This step allows us to better represent crop phenology, to reproduce the observed multiannual European crop yields, and to construct realistic time series of the crop carbon fluxes (gross primary production, GPP, and autotrophic respiration, Raut) on a fine spatial and temporal resolution. Secondly, we combine these GPP and Raut fluxes with a simple soil respiration model to obtain the total ecosystem respiration (TER) and net ecosystem exchange (NEE). And thirdly, we represent the horizontal transport of carbon that follows crop harvest and its back-respiration into the atmosphere during harvest consumption. We distribute this carbon using observations of the density of human and ruminant populations from EUROSTAT. We assess the model

  4. Precision agriculture in the 21st Century: Geospatial and information technologies in crop management

    SciTech Connect

    1997-12-31

    Agricultural managers have for decades taken advantage of new technologies, including information technologies, that enabled better management decision making and improved economic efficiency of operations. The extent and rate of change now occurring in the development of information technologies have opened the way for significant change in crop production management and agricultural decision making. This vision is reflected in the concept of precision agriculture. Precision agriculture is a phrase that captures the imagination of many concerned with the production of food, feed, and fiber. The concepts embodied in precision agriculture offer the promise of increasing productivity while decreasing production costs and minimizing environmental impacts. Precision agriculture conjures up images of farmers overcoming the elements with computerized machinery that is precisely controlled via satellites and local sensors and using planning software that accurately predicts crop development. This image has been called the future of agriculture. Such high-tech images are engaging. Precision agriculture, however, is in early and rapidly changing phases of innovation. Techniques and practices not anticipated by the committee will likely become common in the future, and some techniques and practices thought to hold high promise today may turn out to be less desirable than anticipated. This report defines precision agriculture as a management strategy that uses information technologies to bring data from multiple sources to bear on decisions associated with crop production. Precision agriculture has three components: capture of data at an appropriate scale and frequency, interpretation and analysis of that data, and implementation of a management response at an appropriate scale and time. The most significant impact of precision agriculture is likely to be on how management decisions address spatial and temporal variability in crop production systems.

  5. Modelling crop canopy and residue rainfall interception effects on soil hydrological components for semi-arid agriculture

    NASA Astrophysics Data System (ADS)

    Kozak, Joseph A.; Ahuja, Lajpat R.; Green, Timothy R.; Ma, Liwang

    2007-01-01

    Crop canopies and residues have been shown to intercept a significant amount of rainfall. However, rainfall or irrigation interception by crops and residues has often been overlooked in hydrologic modelling. Crop canopy interception is controlled by canopy density and rainfall intensity and duration. Crop residue interception is a function of crop residue type, residue density and cover, and rainfall intensity and duration. We account for these controlling factors and present a model for both interception components based on Merriam's approach. The modified Merriam model and the current modelling approaches were examined and compared with two field studies and one laboratory study. The Merriam model is shown to agree well with measurements and was implemented within the Agricultural Research Service's Root Zone Water Quality Model (RZWQM). Using this enhanced version of RZWQM, three simulation studies were performed to examine the quantitative effects of rainfall interception by corn and wheat canopies and residues on soil hydrological components. Study I consisted of 10 separate hypothetical growing seasons (1991-2000) for canopy effects and 10 separate non-growing seasons (1991-2000) for residue effects for eastern Colorado conditions. For actual management practices in a no-till wheat-corn-fallow cropping sequence at Akron, Colorado (study II), a continuous 10-year RZWQM simulation was performed to examine the cumulative changes on water balance components and crop growth caused by canopy and residue rainfall interception. Finally, to examine a higher precipitation environment, a hypothetical, no-till wheat-corn-fallow rotation scenario at Corvallis, Oregon, was simulated (study III). For all studies, interception was shown to decrease infiltration, runoff, evapotranspiration from soil, deep seepage of water and chemical transport, macropore flow, leaf area index, and crop/grain yield. Because interception decreased both infiltration and soil evapotranspiration

  6. [Effects of tobacco garlic crop rotation and intercropping on tobacco yield and rhizosphere soil phosphorus fractions].

    PubMed

    Tang, Biao; Zhang, Xi-zhou; Yang, Xian-bin

    2015-07-01

    A field plot experiment was conducted to investigate the tobacco yield and different forms of soil phosphorus under tobacco garlic crop rotation and intercropping patterns. The results showed that compared with tobacco monoculture, the tobacco yield and proportion of middle/high class of tobacco leaves to total leaves were significantly increased in tobacco garlic crop rotation and intercropping, and the rhizosphere soil available phosphorus contents were 1.3 and 1.7 times as high as that of tobacco monoculture at mature stage of lower leaf. For the inorganic phosphorus in rhizosphere and non-rhizosphere soil in different treatments, the contents of O-P and Fe-P were the highest, followed by Ca2-P and Al-P, and Ca8-P and Ca10-P were the lowest. Compared with tobacco monoculture and tobacco garlic crop intercropping, the Ca2-P concentration in rhizosphere soil under tobacco garlic crop rotation at mature stage of upper leaf, the Ca8-P concentration at mature stage of lower leaf, and the Ca10-P concentration at mature stage of middle leaf were lowest. The Al-P concentrations under tobacco garlic crop rotation and intercropping were 1.6 and 1.9 times, and 1.2 and 1.9 times as much as that under tobacco monoculture in rhizosphere soil at mature stages of lower leaf and middle leaf, respectively. The O-P concentrations in rhizosphere soil under tobacco garlic crop rotation and intercropping were significantly lower than that under tobacco monoculture. Compared with tobacco garlic crop intercropping, the tobacco garlic crop rotation could better improve tobacco yield and the proportion of high and middle class leaf by activating O-P, Ca10-P and resistant organic phosphorus in soil.

  7. Evaluation of the performance of SiBcrop model in predicting carbon fluxes and crop yields in the croplands of the US mid continental region

    NASA Astrophysics Data System (ADS)

    Lokupitiya, E.; Denning, S.; Paustian, K.; Corbin, K.; Baker, I.; Schaefer, K.

    2008-12-01

    The accurate representation of phenology, physiology, and major crop variables is important in the land- atmosphere carbon models being used to predict carbon and other exchanges of the man-made cropland ecosystems. We evaluated the performance of SiBcrop model (which is the Simple Biosphere model (SiB) with a new scheme for crop phenology and physiology) in predicting carbon exchanges of the US mid continental region which has several major crops. The use of the new phenology scheme within SiB remarkably improved the prediction of LAI and carbon fluxes for corn, soybean, and wheat crops as compared with the observed data at several Ameriflux eddy covariance flux tower sites with those crops. SiBcrop better predicted the onset and end of the growing season, harvest, interannual variability associated with crop rotation, day time carbon draw down, and day to day variability in the carbon exchanges. The model has been coupled with RAMS, the regional Atmospheric Modeling System (developed at Colorado State University), and the coupled SiBcrop-RAMS has predicted better carbon and other fluxes compared to the original SiB-RAMS. SiBcrop also predicted daily variation in biomass in different plant pools (i.e. roots, leaves, stems, and products). In this study, we further evaluated the performance of SiBcrop by comparing the yield estimates based on the grain/seed biomass at harvest predicted by SiBcrop for relevant major crops, against the county-level crop yields reported by the US National Agricultural Statistics Service (NASS). Initially, the model runs were based on crop maps scaled at 40 km resolution; the maps were used to derive the fraction of corn, soybean, and wheat at each grid cell across the US Mid Continental Intensive (MCI) region under the North American Carbon Program (NACP). The yield biomass carbon values (at harvest) predicted for each grid cell by SiBcrop were extrapolated to derive the county-level yield biomass carbon values, which were then

  8. 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.

  9. Quantifying the weather-signal in national crop-yield variability

    NASA Astrophysics Data System (ADS)

    Frieler, K.; Arneth, A.; Balkovic, J.; Chryssanthacopoulos, J.; Deryng, D.; Elliott, J. W.; Folberth, C.; Khabarov, N.; Mueller, C.; Olin, S.; Pugh, T.; Schaphoff, S.; Schewe, J.; Schmid, E.; Schauberger, B.; Warszawski, L.; Levermann, A.

    2015-12-01

    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 particularly severe consequences for people in developing countries. The fluctuations can be induced by weather conditions but also by management decisions, diseases, and pests. To get a better understanding of future sensitivities to climate change it is important to quantify the degree to which historical crop yields are determined by weather fluctuations. This separation from other influences is usually done by highly simplified empirical models. In contrast, here we provide a conservative estimate of the fraction of the observed national yield variability that is caused by weather, using state-of-the-art process-based crop model simulations. As these models provide a detailed representation of our current understanding of the underlying processes they are also suitable to assess potential adaptation options. We provide an identification of the countries where the weather induced variability of crop yields is particularly high (explained variance > 50%). In addition, inhibiting water stress by simulating yields assuming full irrigation shows that water limitation is the main driver of the observed variations in most of these countries.

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

    PubMed

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

    2016-10-27

    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.

  11. Ensiling of crops for biogas production: effects on methane yield and total solids determination

    PubMed Central

    2011-01-01

    Background Ensiling is a common method of preserving energy crops for anaerobic digestion, and many scientific studies report that ensiling increases the methane yield. In this study, the ensiling process and the methane yields before and after ensiling were studied for four crop materials. Results The changes in wet weight and total solids (TS) during ensiling were small and the loss of energy negligible. The methane yields related to wet weight and to volatile solids (VS) were not significantly different before and after ensiling when the VS were corrected for loss of volatile compounds during TS and VS determination. However, when the TS were measured according to standard methods and not corrected for losses of volatile compounds, the TS loss during ensiling was overestimated for maize and sugar beet. The same methodological error leads to overestimation of methane yields; when TS and VS were not corrected the methane yield appeared to be 51% higher for ensiled than fresh sugar beet. Conclusions Ensiling did not increase the methane yield of the studied crops. Published methane yields, as well as other information on silage related to uncorrected amounts of TS and VS, should be regarded with caution. PMID:22032645

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

    NASA Astrophysics Data System (ADS)

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

    2016-10-01

    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.

  13. Does agricultural crop diversity enhance soil microbial biomass and organic matter dynamics? A meta-analysis.

    PubMed

    McDaniel, M D; Tiemann, L K; Grandy, A S

    2014-04-01

    Our increasing dependence on a small number of agricultural crops, such as corn, is leading to reductions in agricultural biodiversity. Reductions in the number of crops in rotation or the replacement of rotations by monocultures are responsible for this loss of biodiversity. The belowground implications of simplifying agricultural plant communities remain unresolved; however, agroecosystem sustainability will be severely compromised if reductions in biodiversity reduce soil C and N concentrations, alter microbial communities, and degrade soil ecosystem functions as reported in natural communities. We conducted a meta-analysis of 122 studies to examine crop rotation effects on total soil C and N concentrations, and the faster cycling microbial biomass C and N pools that play key roles in soil nutrient cycling and physical processes such as aggregate formation. We specifically examined how rotation crop type and management practices influence C and N dynamics in different climates and soil types. We found that adding one or more crops in rotation to a monoculture increased total soil C by 3.6% and total N by 5.3%, but when rotations included a cover crop (i.e., crops that are not harvested but produced to enrich the soil and capture inorganic N), total C increased by 8.5% and total N 12.8%. Rotations substantially increased the soil microbial biomass C (20.7%) and N (26.1%) pools, and these overwhelming effects on microbial biomass were not moderated by crop type or management practices. Crop rotations, especially those that include cover crops, sustain soil quality and productivity by enhancing soil C, N, and microbial biomass, making them a cornerstone for sustainable agroecosystems.

  14. Agricultural Classification of Multi-Temporal MODIS Imagery in Northwest Argentina Using Kansas Crop Phenologies

    NASA Astrophysics Data System (ADS)

    Keifer, Jarrett Alexander

    Subtropical deforestation in Latin America is thought to be driven by demand for agricultural land, particularly to grow soybeans. However, existing remote sensing methods that can differentiate crop types to verify this hypothesis require high spatial or spectral resolution data, or extensive ground truth information to develop training sites, none of which are freely available for much of the world. I developed a new method of crop classification based on the phenological signatures of crops extracted from multi-temporal MODIS vegetation indices. I tested and refined this method using the USDA Cropland Data Layer from Kansas, USA as a reference. I then applied the method to classify crop types for a study site in Pellegrini, Santiago Del Estero, Argentina. The results show that this method is unable to effectively separate summer crops in Pellegrini, but can differentiate summer