Adapting crop rotations to climate change in regional impact modelling assessments.

PubMed

Teixeira, Edmar I; de Ruiter, John; Ausseil, Anne-Gaelle; Daigneault, Adam; Johnstone, Paul; Holmes, Allister; Tait, Andrew; Ewert, Frank

2018-03-01

The environmental and economic sustainability of future cropping systems depends on adaptation to climate change. Adaptation studies commonly rely on agricultural systems models to integrate multiple components of production systems such as crops, weather, soil and farmers' management decisions. Previous adaptation studies have mostly focused on isolated monocultures. However, in many agricultural regions worldwide, multi-crop rotations better represent local production systems. It is unclear how adaptation interventions influence crops grown in sequences. We develop a catchment-scale assessment to investigate the effects of tactical adaptations (choice of genotype and sowing date) on yield and underlying crop-soil factors of rotations. Based on locally surveyed data, a silage-maize followed by catch-crop-wheat rotation was simulated with the APSIM model for the RCP 8.5 emission scenario, two time periods (1985-2004 and 2080-2100) and six climate models across the Kaituna catchment in New Zealand. Results showed that direction and magnitude of climate change impacts, and the response to adaptation, varied spatially and were affected by rotation carryover effects due to agronomical (e.g. timing of sowing and harvesting) and soil (e.g. residual nitrogen, N) aspects. For example, by adapting maize to early-sowing dates under a warmer climate, there was an advance in catch crop establishment which enhanced residual soil N uptake. This dynamics, however, differed with local environment and choice of short- or long-cycle maize genotypes. Adaptation was insufficient to neutralize rotation yield losses in lowlands but consistently enhanced yield gains in highlands, where other constraints limited arable cropping. The positive responses to adaptation were mainly due to increases in solar radiation interception across the entire growth season. These results provide deeper insights on the dynamics of climate change impacts for crop rotation systems. Such knowledge can be used

Climate change impacts on crop yield in the Euro-Mediterranean region

NASA Astrophysics Data System (ADS)

Toreti, Andrea; Ceglar, Andrej; Dentener, Frank; Niemeyer, Stefan; Dosio, Alessandro; Fumagalli, Davide

2017-04-01

Agriculture is strongly influenced by climate variability, climate extremes and climate changes. Recent studies on past decades have identified and analysed the effects of climate variability and extremes on crop yields in the Euro-Mediterranean region. As these effects could be amplified in a changing climate context, it is essential to analyse available climate projections and investigate the possible impacts on European agriculture in terms of crop yield. In this study, five model runs from the Euro-CORDEX initiative under two scenarios (RCP4.5 and RCP8.5) have been used. Climate model data have been bias corrected and then used to feed a mechanistic crop growth model. The crop model has been run under different settings to better sample the intrinsic uncertainties. Among the main results, it is worth to report a weak but significant and spatially homogeneous increase in potential wheat yield at mid-century (under a CO2 fertilisation effect scenario). While more complex changes seem to characterise potential maize yield, with large areas in the region showing a weak-to-moderate decrease.

Assessing Biofuel Crop Invasiveness: A Case Study

PubMed Central

Buddenhagen, Christopher Evan; Chimera, Charles; Clifford, Patti

2009-01-01

Background There is widespread interest in biofuel crops as a solution to the world's energy needs, particularly in light of concerns over greenhouse-gas emissions. Despite reservations about their adverse environmental impacts, no attempt has been made to quantify actual, relative or potential invasiveness of terrestrial biofuel crops at an appropriate regional or international scale, and their planting continues to be largely unregulated. Methodology/Principal Findings Using a widely accepted weed risk assessment system, we analyzed a comprehensive list of regionally suitable biofuel crops to show that seventy percent have a high risk of becoming invasive versus one-quarter of non-biofuel plant species and are two to four times more likely to establish wild populations locally or be invasive in Hawaii or in other locations with a similar climate. Conclusions/Significance Because of climatic and ecological similarities, predictions of biofuel crop invasiveness in Hawaii are applicable to other vulnerable island and subtropical ecosystems worldwide. We demonstrate the utility of an accessible and scientifically proven risk assessment protocol that allows users to predict if introduced species will become invasive in their region of interest. Other evidence supports the contention that propagule pressure created by extensive plantings will exacerbate invasions, a scenario expected with large-scale biofuel crop cultivation. Proactive measures, such as risk assessments, should be employed to predict invasion risks, which could then be mitigated via implementation of appropriate planting policies and adoption of the “polluter-pays” principle. PMID:19384412

Ammonia volatilization from crop residues and frozen green manure crops

NASA Astrophysics Data System (ADS)

de Ruijter, F. J.; Huijsmans, J. F. M.; Rutgers, B.

2010-09-01

Agricultural systems can lose substantial amounts of nitrogen (N). To protect the environment, the European Union (EU) has adopted several directives that set goals to limit N losses. National Emission Ceilings (NEC) are prescribed in the NEC directive for nitrogen oxides and ammonia. Crop residues may contribute to ammonia volatilization, but sufficient information on their contribution to the national ammonia volatilization is lacking. Experiments were carried out with the aim to assess the ammonia volatilization of crop residues left on the soil surface or incorporated into the soil under the conditions met in practice in the Netherlands during late autumn and winter. Ammonia emission from residues of broccoli, leek, sugar beet, cut grass, fodder radish (fresh and frozen) and yellow mustard (frozen) was studied during two winter seasons using volatilization chambers. Residues were either placed on top of soil or mixed with soil. Mixing residues with soil gave insignificant ammonia volatilization, whereas volatilization was 5-16 percent of the N content of residues when placed on top of soil. Ammonia volatilization started after at least 4 days. Total ammonia volatilization was related to C/N-ratio and N concentration of the plant material. After 37 days, cumulative ammonia volatilization was negligible from plant material with N concentration below 2 percent, and was 10 percent of the N content of plant material with 4 percent N. These observations can be explained by decomposition of plant material by micro-organisms. After an initial built up of the microbial population, NH 4+ that is not needed for their own growth is released and can easily emit as NH 3 at the soil surface. The results of the experiments were used to estimate the contribution of crop residues to ammonia volatilization in the Netherlands. Crop residues of arable crops and residues of pasture topping may contribute more than 3 million kg NH 3-N to the national ammonia volatilization of the

Reducing the negative human-health impacts of bioenergy crop emissions through region-specific crop selection

DOE PAGES

Porter, William C.; Rosenstiel, Todd N.; Guenther, Alex; ...

2015-05-06

An expected global increase in bioenergy-crop cultivation as an alternative to fossil fuels will have consequences on both global climate and local air quality through changes in biogenic emissions of volatile organic compounds (VOCs). While greenhouse gas emissions may be reduced through the substitution of next-generation bioenergy crops such as eucalyptus, giant reed, and switchgrass for fossil fuels, the choice of species has important ramifications for human health, potentially reducing the benefits of conversion due to increases in ozone (O₃) and fine particulate matter (PM₂̣₅) levels as a result of large changes in biogenic emissions. Using the Community Earth Systemmore » Model we simulate the conversion of marginal and underutilized croplands worldwide to bioenergy crops under varying future anthropogenic emissions scenarios. A conservative global replacement using high VOC-emitting crop profiles leads to modeled population-weighted O₃ increases of 5–27 ppb in India, 1–9 ppb in China, and 1–6 ppb in the United States, with peak PM₂̣₅ increases of up to 2 μgm⁻³. We present a metric for the regional evaluation of candidate bioenergy crops, as well as results for the application of this metric to four representative emissions profiles using four replacement scales (10–100% maximum estimated available land). Finally, we assess the total health and climate impacts of biogenic emissions, finding that the negative consequences of using high-emitting crops could exceed 50% of the positive benefits of reduced fossil fuel emissions in value.« less

Reducing the negative human-health impacts of bioenergy crop emissions through region-specific crop selection

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

Porter, William C.; Rosenstiel, Todd N.; Guenther, Alex

An expected global increase in bioenergy-crop cultivation as an alternative to fossil fuels will have consequences on both global climate and local air quality through changes in biogenic emissions of volatile organic compounds (VOCs). While greenhouse gas emissions may be reduced through the substitution of next-generation bioenergy crops such as eucalyptus, giant reed, and switchgrass for fossil fuels, the choice of species has important ramifications for human health, potentially reducing the benefits of conversion due to increases in ozone (O₃) and fine particulate matter (PM₂̣₅) levels as a result of large changes in biogenic emissions. Using the Community Earth Systemmore » Model we simulate the conversion of marginal and underutilized croplands worldwide to bioenergy crops under varying future anthropogenic emissions scenarios. A conservative global replacement using high VOC-emitting crop profiles leads to modeled population-weighted O₃ increases of 5–27 ppb in India, 1–9 ppb in China, and 1–6 ppb in the United States, with peak PM₂̣₅ increases of up to 2 μgm⁻³. We present a metric for the regional evaluation of candidate bioenergy crops, as well as results for the application of this metric to four representative emissions profiles using four replacement scales (10–100% maximum estimated available land). Finally, we assess the total health and climate impacts of biogenic emissions, finding that the negative consequences of using high-emitting crops could exceed 50% of the positive benefits of reduced fossil fuel emissions in value.« less

Reducing the negative human-health impacts of bioenergy crop emissions through region-specific crop selection

NASA Astrophysics Data System (ADS)

Porter, William C.; Rosenstiel, Todd N.; Guenther, Alex; Lamarque, Jean-Francois; Barsanti, Kelley

2015-05-01

An expected global increase in bioenergy-crop cultivation as an alternative to fossil fuels will have consequences on both global climate and local air quality through changes in biogenic emissions of volatile organic compounds (VOCs). While greenhouse gas emissions may be reduced through the substitution of next-generation bioenergy crops such as eucalyptus, giant reed, and switchgrass for fossil fuels, the choice of species has important ramifications for human health, potentially reducing the benefits of conversion due to increases in ozone (O3) and fine particulate matter (PM2.5) levels as a result of large changes in biogenic emissions. Using the Community Earth System Model we simulate the conversion of marginal and underutilized croplands worldwide to bioenergy crops under varying future anthropogenic emissions scenarios. A conservative global replacement using high VOC-emitting crop profiles leads to modeled population-weighted O3 increases of 5-27 ppb in India, 1-9 ppb in China, and 1-6 ppb in the United States, with peak PM2.5 increases of up to 2 μg m-3. We present a metric for the regional evaluation of candidate bioenergy crops, as well as results for the application of this metric to four representative emissions profiles using four replacement scales (10-100% maximum estimated available land). Finally, we assess the total health and climate impacts of biogenic emissions, finding that the negative consequences of using high-emitting crops could exceed 50% of the positive benefits of reduced fossil fuel emissions in value.

Global crop production forecasting: An analysis of the data system problems and their solutions

NASA Technical Reports Server (NTRS)

Neiers, J.; Graf, H.

1978-01-01

Data related problems in the acquisition and use of satellite data necessary for operational forecasting of global crop production are considered for the purpose of establishing a measurable baseline. For data acquisition the world was divided into 37 crop regions in 22 countries. These regions represent approximately 95 percent of the total world production of the selected crops of interest, i.e., wheat, corn, soybeans, and rice. Targets were assigned to each region. Limited time periods during which data could be taken (windows) were assigned to each target. Each target was assigned to a cloud region. The DSDS was used to measure the success of obtaining data for each target during the specified windows for the regional cloud conditions and the specific alternatives being analyzed. The results of this study suggest several approaches for an operational system that will perform satisfactorily with two LANDSAT type satellites.

Historical development of crop-related water footprints and inter-regional virtual water flows within China

NASA Astrophysics Data System (ADS)

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

2015-04-01

China is facing water-related challenges, including an uneven distribution of water resources, both temporally and spatially, and an increasing competition over the limited water resources among different sectors. This issue has been widely researched and was finally included into the National Plan 2011 (the 2011 No. 1 Document by the State Council of China). However, there is still lack of information on how population growth and rapid urbanization have affected the water resources in China over the last decades. The current study aims at investigating (i) the intra-annual variation of green and blue water footprints (WFs) of crop production in China over the period 1978-2009 at a spatial resolution of 5 by 5 arc-minute; (ii) the yearly virtual water (VW) balances of 31 provinces within China, related water savings for the country, as well as the VW flows among eight economic regions resulting from inter-regional crop trade over the same period; and (iii) the development of the WF related to crop consumption by Chinese consumers. Results show that, over the period 1978-2009, the total WF related to crop production within China increased by only 4%), but regional changes were significant. From the 1980s to the 2000s, the shift of the cropping centre from the South to the North resulted in an increase of about 16% in the blue WF and 19% in the green WF in the North and a reduction of the blue and green WF in the South by 11% and 3%, respectively. China as a whole was a net virtual water importer related to crop trade, thus saving domestic water resources. China's inter-regional crop trade generated a blue water 'loss' annually by transferring crops from provinces with relatively low crop water productivity to provinces with relatively high productivity. Over the decades, the original VW flow from the South coastal region to the Northeast was reversed. Rice was the all-time dominant crop in the inter-regional VW flows (accounting for 34% in 2009), followed by wheat

7 CFR 1405.6 - Crop insurance requirement.

Code of Federal Regulations, 2010 CFR

2010-01-01

... eligibility for emergency crop loss assistance in connection with the crop, if insurance is available in the... waiver that waives any eligibility for crop loss assistance in connection with the producer's crop. (b... contributed in the previous year, or is expected to contribute in the current crop year, 10 percent or more of...

Sensitivity of simulated maize crop yields to regional climate in the Southwestern United States

NASA Astrophysics Data System (ADS)

Kim, S.; Myoung, B.; Stack, D.; Kim, J.; Hatzopoulos, N.; Kafatos, M.

2013-12-01

The sensitivity of maize yield to the regional climate in the Southwestern United States (SW US) has been investigated by using a crop-yield simulation model (APSIM) in conjunction with meteorological forcings (daily minimum and maximum temperature, precipitation, and radiation) from the North American Regional Reanalysis (NARR) dataset. The primary focus of this study is to look at the effects of interannual variations of atmospheric components on the crop productivity in the SW US over the 21-year period (1991 to 2011). First of all, characteristics and performance of APSIM was examined by comparing simulated maize yields with observed yields from United States Department of Agriculture (USDA) and the leaf-area index (LAI) from MODIS satellite data. Comparisons of the simulated maize yield with the available observations show that the crop model can reasonably reproduce observed maize yields. Sensitivity tests were performed to assess the relative contribution of each climate driver to regional crop yield. Sensitivity experiments show that potential crop production responds nonlinearly to climate drivers and the yield sensitivity varied among geographical locations depending on their mean climates. Lastly, a detailed analysis of both the spatial and temporal variations of each climate driver in the regions where maize is actually grown in three states (CA, AZ, and NV) in the SW US was performed.

Opportunistic Market-Driven Regional Shifts of Cropping Practices Reduce Food Production Capacity of China

NASA Astrophysics Data System (ADS)

Yuan, Wenping; Liu, Shuguang; Liu, Wei; Zhao, Shuqing; Dong, Wenjie; Tao, Fulu; Chen, Min; Lin, Hui

2018-04-01

China is facing the challenge of feeding a growing population with the declining cropland and increasing shortage of water resources under the changing climate. This study identified that the opportunistic profit-driven shifts of planting areas and crop species composition have strongly reduced the food production capacity of China. First, the regional cultivation patterns of major crops in China have substantially shifted during the past five decades. Southeast and South China, the regions with abundant water resources and fewer natural disasters, have lost large planting areas of cropland in order to pursue industry and commerce. Meanwhile, Northeast and Northwest China, the regions with low water resources and frequent natural disasters, have witnessed increases in planting areas. These macroshifts have reduced the national food production by 1.02% per year. The lost grain production would have been enough to feed 13 million people. Second, the spatial shifts have been accompanied by major changes in crop species composition, with substantial increases in planting area and production of maize, due to its low water consumption and high economic returns. Consequently, the stockpile of maize in China has accounted for more than half of global stockpile, and the stock to use ratio of maize in China has exceeded the reliable level. Market-driven regional shifts of cropping practices have resulted in larger irrigation requirements and aggravated environmental stresses. Our results highlighted the need for Chinese food policies to consider the spatial shifts in cultivation, and the planting crop compositions limited by regional water resources and climate change.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Future Climate Impacts on Crop Water Demand and Groundwater Longevity in Agricultural Regions

NASA Astrophysics Data System (ADS)

Russo, T. A.; Sahoo, S.; Elliott, J. W.; Foster, I.

2016-12-01

Improving groundwater management practices under future drought conditions in agricultural regions requires three steps: 1) estimating the impacts of climate and drought on crop water demand, 2) projecting groundwater availability given climate and demand forcing, and 3) using this information to develop climate-smart policy and water use practices. We present an innovative combination of models to address the first two steps, and inform the third. Crop water demand was simulated using biophysical crop models forced by multiple climate models and climate scenarios, with one case simulating climate adaptation (e.g. modify planting or harvest time) and another without adaptation. These scenarios were intended to represent a range of drought projections and farm management responses. Nexty, we used projected climate conditions and simulated water demand across the United States as inputs to a novel machine learning-based groundwater model. The model was applied to major agricultural regions relying on the High Plains and Mississippi Alluvial aquifer systems in the US. The groundwater model integrates input data preprocessed using single spectrum analysis, mutual information, and a genetic algorithm, with an artificial neural network model. Model calibration and test results indicate low errors over the 33 year model run, and strong correlations to groundwater levels in hundreds of wells across each aquifer. Model results include a range of projected groundwater level changes from the present to 2050, and in some regions, identification and timeframe of aquifer depletion. These results quantify aquifer longevity under climate and crop scenarios, and provide decision makers with the data needed to compare scenarios of crop water demand, crop yield, and groundwater response, as they aim to balance water sustainability with food security.

Regional simulation of soil nitrogen dynamics and balance in Swiss cropping systems

NASA Astrophysics Data System (ADS)

Lee, Juhwan; Necpalova, Magdalena; Six, Johan

2017-04-01

We evaluated the regional-scale potential of various crop and soil management practices to reduce the dependency of crop N demand on external N inputs and N losses to the environment. The estimates of soil N balance were simulated and compared under alternative and conventional crop production across all Swiss cropland. Alternative practices were all combinations of organic fertilization, reduced tillage and winter cover cropping. Using the DayCent model, we simulated changes in crop N yields as well as the contribution of inputs and outputs to soil N balance by alternative practices, which was complemented with corresponding measurements from available long-term field experiments and site-level simulations. In addition, the effects of reducing (between 0% and 80% of recommended application rates) or increasing chemical fertilizer input rates (between 120% and 300% of recommended application rates) on system-level N dynamics were also simulated. Modeled yields at recommended N rates were only 37-87% of the maximum yield potential across common Swiss crops, and crop productivity were sensitive to the level of external N inputs, except for grass-clover mixture, soybean and peas. Overall, differences in soil N input and output decreased or increased proportionally with changing the amount of N input only from the recommended rate. As a result, there was no additional difference in soil N balance in response to N application rates. Nitrate leaching accounted for 40-81% of total N output differences, while up to 47% of total N output occurred through harvest and straw removal. Regardless of crops, yield potential became insensitive to high N rates. Differences in N2O and N2 emissions slightly increased with increasing N inputs, in which each gas was only responsible for about 1% of changes in total N output. Overall, there was a positive soil N balance under alternative practices. Particularly, considerable improvement in soil N balance was expected when slowly

Application of Regional Drought and Crop Yield Information System to enhance drought monitoring and forecasting in Lower Mekong region

NASA Astrophysics Data System (ADS)

Jayasinghe, S.; Dutta, R.; Basnayake, S. B.; Granger, S. L.; Andreadis, K. M.; Das, N.; Markert, K. N.; Cutter, P. G.; Towashiraporn, P.; Anderson, E.

2017-12-01

The Lower Mekong Region has been experiencing frequent and prolonged droughts resulting in severe damage to agricultural production leading to food insecurity and impacts on livelihoods of the farming communities. Climate variability further complicates the situation by making drought harder to forecast. The Regional Drought and Crop Yield Information System (RDCYIS), developed by SERVIR-Mekong, helps decision makers to take effective measures through monitoring, analyzing and forecasting of drought conditions and providing early warnings to farmers to make adjustments to cropping calendars. The RDCYIS is built on regionally calibrated Regional Hydrologic Extreme Assessment System (RHEAS) framework that integrates the Variable Infiltration Capacity (VIC) and Decision Support System for Agro-technology Transfer (DSSAT) models, allowing both nowcast and forecast of drought. The RHEAS allows ingestion of numerus freely available earth observation and ground observation data to generate and customize drought related indices, variables and crop yield information for better decision making. The Lower Mekong region has experienced severe drought in 2016 encompassing the region's worst drought in 90 years. This paper presents the simulation of the 2016 drought event using RDCYIS based on its hindcast and forecast capabilities. The regionally calibrated RDCYIS can help capture salient features of drought through a variety of drought indices, soil variables, energy balance variables and water balance variables. The RDCYIS is capable of assimilating soil moisture data from different satellite products and perform ensemble runs to further reduce the uncertainty of it outputs. The calibrated results have correlation coefficient around 0.73 and NSE between 0.4-0.5. Based on the acceptable results of the retrospective runs, the system has the potential to generate reliable drought monitoring and forecasting information to improve decision-makings at operational, technological and

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.

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

PubMed

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

2018-05-31

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

Improving crop classification through attention to the timing of airborne radar acquisitions

NASA Technical Reports Server (NTRS)

Brisco, B.; Ulaby, F. T.; Protz, R.

1984-01-01

Radar remote sensors may provide valuable input to crop classification procedures because of (1) their independence of weather conditions and solar illumination, and (2) their ability to respond to differences in crop type. Manual classification of multidate synthetic aperture radar (SAR) imagery resulted in an overall accuracy of 83 percent for corn, forest, grain, and 'other' cover types. Forests and corn fields were identified with accuracies approaching or exceeding 90 percent. Grain fields and 'other' fields were often confused with each other, resulting in classification accuracies of 51 and 66 percent, respectively. The 83 percent correct classification represents a 10 percent improvement when compared to similar SAR data for the same area collected at alternate time periods in 1978. These results demonstrate that improvements in crop classification accuracy can be achieved with SAR data by synchronizing data collection times with crop growth stages in order to maximize differences in the geometric and dielectric properties of the cover types of interest.

NASA Earth Science Research Results for Improved Regional Crop Yield Prediction

NASA Astrophysics Data System (ADS)

Mali, P.; O'Hara, C. G.; Shrestha, B.; Sinclair, T. R.; G de Goncalves, L. G.; Salado Navarro, L. R.

2007-12-01

spatial and temporal resolution remote sensing datasets; improved time-series meteorological inputs required for crop growth models; and regional prediction capability through geo-processing-based yield modeling.

Regional disparities in the beneficial effects of rising CO2 concentrations on crop water productivity

NASA Astrophysics Data System (ADS)

Deryng, Delphine; Elliott, Joshua; Folberth, Christian; Müller, Christoph; Pugh, Thomas A. M.; Boote, Kenneth J.; Conway, Declan; Ruane, Alex C.; Gerten, Dieter; Jones, James W.; Khabarov, Nikolay; Olin, Stefan; Schaphoff, Sibyll; Schmid, Erwin; Yang, Hong; Rosenzweig, Cynthia

2016-08-01

Rising atmospheric CO2 concentrations ([CO2]) are expected to enhance photosynthesis and reduce crop water use. However, there is high uncertainty about the global implications of these effects for future crop production and agricultural water requirements under climate change. Here we combine results from networks of field experiments and global crop models to present a spatially explicit global perspective on crop water productivity (CWP, the ratio of crop yield to evapotranspiration) for wheat, maize, rice and soybean under elevated [CO2] and associated climate change projected for a high-end greenhouse gas emissions scenario. We find CO2 effects increase global CWP by 10[047]%-27[737]% (median[interquartile range] across the model ensemble) by the 2080s depending on crop types, with particularly large increases in arid regions (by up to 48[25;56]% for rainfed wheat). If realized in the fields, the effects of elevated [CO2] could considerably mitigate global yield losses whilst reducing agricultural consumptive water use (4-17%). We identify regional disparities driven by differences in growing conditions across agro-ecosystems that could have implications for increasing food production without compromising water security. Finally, our results demonstrate the need to expand field experiments and encourage greater consistency in modelling the effects of rising [CO2] across crop and hydrological modelling communities.

Regional Disparities in the Beneficial Effects of Rising CO2 Emissions on Crop Water Productivity

NASA Technical Reports Server (NTRS)

Deryng, Delphine; Elliott, Joshua; Folberth, Christian; Meuller, Christoph; Pugh, Thomas A. M.; Boote, Kenneth J.; Conway, Declan; Ruane, Alex C.; Gerten, Dieter; Jones, James W.;

Regional modelling of nitrate leaching from Swiss organic and conventional cropping systems under climate change

NASA Astrophysics Data System (ADS)

Calitri, Francesca; Necpalova, Magdalena; Lee, Juhwan; Zaccone, Claudio; Spiess, Ernst; Herrera, Juan; Six, Johan

2016-04-01

Organic cropping systems have been promoted as a sustainable alternative to minimize the environmental impacts of conventional practices. Relatively little is known about the potential to reduce NO3-N leaching through the large-scale adoption of organic practices. Moreover, the potential to mitigate NO3-N leaching and thus the N pollution under future climate change through organic farming remain unknown and highly uncertain. Here, we compared regional NO3-N leaching from organic and conventional cropping systems in Switzerland using a terrestrial biogeochemical process-based model DayCent. The objectives of this study are 1) to calibrate and evaluate the model for NO3-N leaching measured under various management practices from three experiments at two sites in Switzerland; 2) to estimate regional NO3-N leaching patterns and their spatial uncertainty in conventional and organic cropping systems (with and without cover crops) for future climate change scenario A1B; 3) to explore the sensitivity of NO3-N leaching to changes in soil and climate variables; and 4) to assess the nitrogen use efficiency for conventional and organic cropping systems with and without cover crops under climate change. The data for model calibration/evaluation were derived from field experiments conducted in Liebefeld (canton Bern) and Eschikon (canton Zürich). These experiments evaluated effects of various cover crops and N fertilizer inputs on NO3-N leaching. The preliminary results suggest that the model was able to explain 50 to 83% of the inter-annual variability in the measured soil drainage (RMSE from 12.32 to 16.89 cm y-1). The annual NO3-N leaching was also simulated satisfactory (RMSE = 3.94 to 6.38 g N m-2 y-1), although the model had difficulty to reproduce the inter-annual variability in the NO3-N leaching losses correctly (R2 = 0.11 to 0.35). Future climate datasets (2010-2099) from the 10 regional climate models (RCM) were used in the simulations. Regional NO3-N leaching

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

PubMed

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

2018-02-01

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

A generic probability based model to derive regional patterns of crops in time and space

NASA Astrophysics Data System (ADS)

Wattenbach, Martin; Luedtke, Stefan; Redweik, Richard; van Oijen, Marcel; Balkovic, Juraj; Reinds, Gert Jan

2015-04-01

Croplands are not only the key to human food supply, they also change the biophysical and biogeochemical properties of the land surface leading to changes in the water cycle, energy portioning, they influence soil erosion and substantially contribute to the amount of greenhouse gases entering the atmosphere. The effects of croplands on the environment depend on the type of crop and the associated management which both are related to the site conditions, economic boundary settings as well as preferences of individual farmers. The method described here is designed to predict the most probable crop to appear at a given location and time. The method uses statistical crop area information on NUTS2 level from EUROSTAT and the Common Agricultural Policy Regionalized Impact Model (CAPRI) as observation. These crops are then spatially disaggregated to the 1 x 1 km grid scale within the region, using the assumption that the probability of a crop appearing at a given location and a given year depends on a) the suitability of the land for the cultivation of the crop derived from the MARS Crop Yield Forecast System (MCYFS) and b) expert knowledge of agricultural practices. The latter includes knowledge concerning the feasibility of one crop following another (e.g. a late-maturing crop might leave too little time for the establishment of a winter cereal crop) and the need to combat weed infestations or crop diseases. The model is implemented in R and PostGIS. The quality of the generated crop sequences per grid cell is evaluated on the basis of the given statistics reported by the joint EU/CAPRI database. The assessment is given on NUTS2 level using per cent bias as a measure with a threshold of 15% as minimum quality. The results clearly indicates that crops with a large relative share within the administrative unit are not as error prone as crops that allocate only minor parts of the unit. However, still roughly 40% show an absolute per cent bias above the 15% threshold. This

United States benefits of improved worldwide wheat crop information from a LANDSAT system

NASA Technical Reports Server (NTRS)

Heiss, K. P.; Sand, F.; Seidel, A.; Warner, D.; Sheflin, N.; Bhattacharyya, R.; Andrews, J.

1975-01-01

The value of worldwide information improvements on wheat crops, promised by LANDSAT, is measured in the context of world wheat markets. These benefits are based on current LANDSAT technical goals and assume that information is made available to all (United States and other countries) at the same time. A detailed empirical sample demonstration of the effect of improved information is given; the history of wheat commodity prices for 1971-72 is reconstructed and the price changes from improved vs. historical information are compared. The improved crop forecasting from a LANDSAT system assumed include wheat crop estimates of 90 percent accuracy for each major wheat producing region. Accurate, objective worldwide wheat crop information using space systems may have a very stabilizing influence on world commodity markets, in part making possible the establishment of long-term, stable trade relationships.

Seed fates in crop-wild hybrid sunflower: crop allele and maternal effects.

PubMed

Pace, Brian A; Alexander, Helen M; Emry, Jason D; Mercer, Kristin L

2015-02-01

Domestication has resulted in selection upon seed traits found in wild populations, yet crop-wild hybrids retain some aspects of both parental phenotypes. Seed fates of germination, dormancy, and mortality can influence the success of crop allele introgression in crop-wild hybrid zones, especially if crop alleles or crop-imparted seed coverings result in out-of-season germination. We performed a seed burial experiment using crop, wild, and diverse hybrid sunflower (Helianthus annuus) cross types to test how a cross type's maternal parent and nuclear genetic composition might affect its fate under field conditions. We observed higher maladaptive fall germination in the crop- and F1- produced seeds than wild-produced seeds and, due to an interaction with percent crop alleles, fall germination was higher for cross types with more crop-like nuclear genetics. By spring, crop-produced cross types had the highest overwintering mortality, primarily due to higher fall germination. Early spring germination was identical across maternal types, but germination continued for F1-produced seeds. In conclusion, the more wild-like the maternal parent or the less proportion of the cross type's genome contributed by the crop, the greater likelihood a seed will remain ungerminated than die. Wild-like dormancy may facilitate introgression through future recruitment from the soil seed bank.

Developing High-resolution Soil Database for Regional Crop Modeling in East Africa

NASA Astrophysics Data System (ADS)

Han, E.; Ines, A. V. M.

2014-12-01

The most readily available soil data for regional crop modeling in Africa is the World Inventory of Soil Emission potentials (WISE) dataset, which has 1125 soil profiles for the world, but does not extensively cover countries Ethiopia, Kenya, Uganda and Tanzania in East Africa. Another dataset available is the HC27 (Harvest Choice by IFPRI) in a gridded format (10km) but composed of generic soil profiles based on only three criteria (texture, rooting depth, and organic carbon content). In this paper, we present a development and application of a high-resolution (1km), gridded soil database for regional crop modeling in East Africa. Basic soil information is extracted from Africa Soil Information Service (AfSIS), which provides essential soil properties (bulk density, soil organic carbon, soil PH and percentages of sand, silt and clay) for 6 different standardized soil layers (5, 15, 30, 60, 100 and 200 cm) in 1km resolution. Soil hydraulic properties (e.g., field capacity and wilting point) are derived from the AfSIS soil dataset using well-proven pedo-transfer functions and are customized for DSSAT-CSM soil data requirements. The crop model is used to evaluate crop yield forecasts using the new high resolution soil database and compared with WISE and HC27. In this paper we will present also the results of DSSAT loosely coupled with a hydrologic model (VIC) to assimilate root-zone soil moisture. Creating a grid-based soil database, which provides a consistent soil input for two different models (DSSAT and VIC) is a critical part of this work. The created soil database is expected to contribute to future applications of DSSAT crop simulation in East Africa where food security is highly vulnerable.

Long-term observations of CO2 exchange over agricultural crops in two regional climates of Southwest Germany

NASA Astrophysics Data System (ADS)

Poyda, Arne; Wizemann, Hans-Dieter; Ingwersen, Joachim; Wulfmeyer, Volker; Streck, Thilo

2017-04-01

The impact of agricultural land use on soil organic carbon (SOC) dynamics has been widely studied in the past few decades, particularly in context of the SOC forcing or mitigation potential of global climate change. Grassland utilization can increase or maintain SOC stocks. Arable cropping tends to decrease SOC stocks, at least for some time after land use change (SMITH, 2008). In the long run, it can be assumed that SOC reaches a steady state where the production of roots and aboveground crop residues and possibly organic fertilization level out soil respiration. To study the effects of crop type, year and regional site conditions on CO2 exchange and C budgets of arable cropping systems in Southwest Germany, eddy covariance measurements were conducted on a total of six sites in the two climatically contrasting regions of Kraichgau and Swabian Alb since 2009. Main crops were winter wheat, silage maize and winter rapeseed but also winter barley, summer barley and spelt were cultivated on the Swabian Alb sites. Cover crops were grown between winter and summer crops on all sites. Net ecosystem exchange (NEE) data were gap-filled following REICHSTEIN et al. (2005) and partitioned into ecosystem respiration (RECO) and gross primary production (GPP) using seasonally differing temperature response functions of nighttime NEE. Furthermore, different approaches for filling long data gaps of several months in winter were evaluated. Considering C inputs by organic fertilizers and C removals by harvest, C budgets were calculated per site and year. First results indicate that the variability of NEE fluxes between different crops is much higher compared to the variability between different years of a certain crop. However, regional differences in soil and weather conditions significantly influence plant growth dynamics and thus CO2 exchange.

How willing are landowners to supply land for bioenergy crops in the Northern Great Lakes Region?

DOE PAGES

Swinton, Scott M.; Tanner, Sophia; Barham, Bradford L.; ...

2016-04-30

Land to produce biomass is essential if the United States is to expand bioenergy supply. Use of agriculturally marginal land avoids the food vs. fuel problems of food price rises and carbon debt that are associated with crop and forestland. Recent remote sensing studies have identified large areas of US marginal land deemed suitable for bioenergy crops. Yet the sustainability benefits of growing bioenergy crops on marginal land only pertain if land is economically available. Scant attention has been paid to the willingness of landowners to supply land for bioenergy crops. Focusing on the northern tier of the Great Lakes,more » where grassland transitions to forest and land prices are low, this contingent valuation study reports on the willingness of a representative sample of 1124 private, noncorporate landowners to rent land for three bioenergy crops: corn, switchgrass, and poplar. Of the 11% of land that was agriculturally marginal, they were willing to make available no more than 21% for any bioenergy crop (switchgrass preferred on marginal land) at double the prevailing land rental rate in the region. At the same generous rental rate, of the 28% that is cropland, they would rent up to 23% for bioenergy crops (corn preferred), while of the 55% that is forestland, they would rent up to 15% for bioenergy crops (poplar preferred). Regression results identified deterrents to land rental for bioenergy purposes included appreciation of environmental amenities and concern about rental disamenities. In sum, like landowners in the southern Great Lakes region, landowners in the Northern Tier are reluctant to supply marginal land for bioenergy crops. If rental markets existed, they would rent more crop and forestland for bioenergy crops than they would marginal land, which would generate carbon debt and opportunity costs in wood product and food markets.« less

How willing are landowners to supply land for bioenergy crops in the Northern Great Lakes Region?

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

Swinton, Scott M.; Tanner, Sophia; Barham, Bradford L.

Land to produce biomass is essential if the United States is to expand bioenergy supply. Use of agriculturally marginal land avoids the food vs. fuel problems of food price rises and carbon debt that are associated with crop and forestland. Recent remote sensing studies have identified large areas of US marginal land deemed suitable for bioenergy crops. Yet the sustainability benefits of growing bioenergy crops on marginal land only pertain if land is economically available. Scant attention has been paid to the willingness of landowners to supply land for bioenergy crops. Focusing on the northern tier of the Great Lakes,more » where grassland transitions to forest and land prices are low, this contingent valuation study reports on the willingness of a representative sample of 1124 private, noncorporate landowners to rent land for three bioenergy crops: corn, switchgrass, and poplar. Of the 11% of land that was agriculturally marginal, they were willing to make available no more than 21% for any bioenergy crop (switchgrass preferred on marginal land) at double the prevailing land rental rate in the region. At the same generous rental rate, of the 28% that is cropland, they would rent up to 23% for bioenergy crops (corn preferred), while of the 55% that is forestland, they would rent up to 15% for bioenergy crops (poplar preferred). Regression results identified deterrents to land rental for bioenergy purposes included appreciation of environmental amenities and concern about rental disamenities. In sum, like landowners in the southern Great Lakes region, landowners in the Northern Tier are reluctant to supply marginal land for bioenergy crops. If rental markets existed, they would rent more crop and forestland for bioenergy crops than they would marginal land, which would generate carbon debt and opportunity costs in wood product and food markets.« less

Multi-Data Approach for remote sensing-based regional crop rotation mapping: A case study for the Rur catchment, Germany

NASA Astrophysics Data System (ADS)

Waldhoff, Guido; Lussem, Ulrike; Bareth, Georg

2017-09-01

Spatial land use information is one of the key input parameters for regional agro-ecosystem modeling. Furthermore, to assess the crop-specific management in a spatio-temporal context accurately, parcel-related crop rotation information is additionally needed. Such data is scarcely available for a regional scale, so that only modeled crop rotations can be incorporated instead. However, the spectrum of the occurring multiannual land use patterns on arable land remains unknown. Thus, this contribution focuses on the mapping of the actually practiced crop rotations in the Rur catchment, located in the western part of Germany. We addressed this by combining multitemporal multispectral remote sensing data, ancillary information and expert-knowledge on crop phenology in a GIS-based Multi-Data Approach (MDA). At first, a methodology for the enhanced differentiation of the major crop types on an annual basis was developed. Key aspects are (i) the usage of physical block data to separate arable land from other land use types, (ii) the classification of remote sensing scenes of specific time periods, which are most favorable for the differentiation of certain crop types, and (iii) the combination of the multitemporal classification results in a sequential analysis strategy. Annual crop maps of eight consecutive years (2008-2015) were combined to a crop sequence dataset to have a profound data basis for the mapping of crop rotations. In most years, the remote sensing data basis was highly fragmented. Nevertheless, our method enabled satisfying crop mapping results. As an example for the annual crop mapping workflow, the procedure and the result of 2015 are illustrated. For the generation of the crop sequence dataset, the eight annual crop maps were geometrically smoothened and integrated into a single vector data layer. The resulting dataset informs about the occurring crop sequence for individual areas on arable land, so that crop rotation schemes can be derived. The

Field-scale and Regional Variability in Evapotranspiration over Crops in California using Eddy Covariance and Surface Renewal

NASA Astrophysics Data System (ADS)

Kent, E. R.; Clay, J. M.; Leinfelder-Miles, M.; Lambert, J. J.; Little, C.; Monteiro, R. O. C.; Monteiro, P. F. C.; Shapiro, K.; Rice, S.; Snyder, R. L.; Daniele, Z.; Paw U, K. T.

2016-12-01

Evapotranspiration (ET) estimated using a single crop coefficient and a grass reference largely ignores variability due to heterogeneity in microclimate, soils, and crop management. We employ a relatively low cost energy balance residual method using surface renewal and eddy covariance measurements to continuously estimate half-hourly and daily ET across more than 15 fields and orchards spanning four crops and two regions of California. In the Sacramento-San Joaquin River Delta, measurements were taken in corn, pasture, and alfalfa fields, with 4-5 stations in each crop type spread across the region. In the Southern San Joaquin Valley, measurements were taken in three different pistachio orchards, with one orchard having six stations instrumented to examine salinity-induced heterogeneity. We analyze field-scale and regional variability in ET and measured surface energy balance components. Cross comparisons between the eddy covariance and the surface renewal measurements confirm the robustness of the surface renewal method. A hybrid approach in which remotely sensed net radiation is combined with in situ measurements of sensible heat flux is also investigated. This work will provide ground-truth data for satellite and aerial-based ET estimates and will inform water management at the field and regional scales.

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

PubMed

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

2011-05-01

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

Using simulation and data envelopment analysis to evaluate Iraqi regions in producing strategic crops

NASA Astrophysics Data System (ADS)

Chaloob, Ibrahim Z.; Ramli, Razamin; Nawawi, Mohd Kamal Mohd

2014-12-01

Productivity of the agriculture sector in Iraq has yet to reach an acceptable level. In this paper, we introduce a practical method to help manage Iraqi agriculture sector to control resources and increase production to meet the modern century requirements of good crops. These important resources are identified as water, fertilizer, natural fertilizer, pesticides and labour. The current agricultural patterns in Iraq affect the strategic crops cultivation in the country and lessen agricultural production to some life-threatening limits. Data Envelopment Analysis (DEA), which is a non-parametric tool, is proposed to identify solutions that can maximize farmers' net benefit making an optimal use of the five resources. This model also improves optimal mix of the resources. In reference to the production of each one of the three strategic crops in Iraq, the DEA model is used to find the efficiency of one region among four others in its agriculture sector, with the main problem being the constraint in the number of lands available in the situation. Hence, the simulation technique is used to generate additional regions to the four main regions adopted. This is to resolve the constriction of DEA when the decision making unit is less than the number of variables (outputs and inputs). The result is expected to show the efficiency of each of the evaluated region.

Annual crop type classification of the U.S. Great Plains for 2000 to 2011

USGS Publications Warehouse

Howard, Daniel M.; Wylie, Bruce K.

2014-01-01

The purpose of this study was to increase the spatial and temporal availability of crop classification data. In this study, nearly 16.2 million crop observation points were used in the training of the US Great Plains classification tree crop type model (CTM). Each observation point was further defined by weekly Normalized Difference Vegetation Index, annual climate, and a number of other biogeophysical environmental characteristics. This study accounted for the most prevalent crop types in the region, including, corn, soybeans, winter wheat, spring wheat, cotton, sorghum, and alfalfa. Annual CTM crop maps of the US Great Plains were created for 2000 to 2011 at a spatial resolution of 250 meters. The CTM achieved an 87 percent classification success rate on 1.8 million observation points that were withheld from model training. Product validation was performed on greater than 15,000 county records with a coefficient of determination of R2 = 0.76.

Agricultural water use, crop water footprints and irrigation strategies in the seasonally dry Guanacaste region in Costa Rica

NASA Astrophysics Data System (ADS)

Morillas, Laura; Johnson, Mark S.; Hund, Silja V.; Steyn, Douw G.

2017-04-01

Agriculture is the main productive sector and a major water-consuming sector in the seasonally-dry Guanacaste region of north-western Costa Rica. Agriculture in the region is intensifying at the same time that seasonal water scarcity is increasing. The climate of this region is characterized by a prolonged dry season from December to March, followed by a bimodal wet season from April to November. The wet season has historically experienced periodic oscillations in rainfall timing and amounts resulting from variations of several large-scale climatic features (El Niño Southern Oscillation, the Pacific Decadal Oscillation, the Atlantic Multidecadal Oscillation and the North Atlantic Oscillation). However, global circulation models now project more recurrent variations in total annual rainfall, changes in rainfall temporal distribution, and increased temperatures in this region. This may result in a lengthening of the dry season and an increase in water scarcity and water-related conflicts as water resources are already limited and disputed in this area. In fact, this region has just undergone a four-year drought over the 2012-2015 period, which has intensified water related conflicts and put agricultural production at risk. In turn, the recent drought has also increased awareness of the local communities regarding the regional threat of water scarcity and the need of a regional water planning. The overall goal of this research is to generate data to characterize water use by the agricultural sector in this region and asses its sustainability in the regional context. Towards this goal, eddy-covariance flux towers were deployed on two extensive farms growing regionally-representative crops (melon/rice rotation and sugarcane) to evaluate, monitor and quantify water use in large-scale farms. The two identically instrumented stations provide continuous measurements of evapotranspiration and CO2 fluxes, and are equipped with additional instrumentation to monitor

7 CFR 1405.6 - Crop insurance requirement.

Code of Federal Regulations, 2011 CFR

2011-01-01

... contributed in the previous year, or is expected to contribute in the current crop year, 10 percent or more of... 7 Agriculture 10 2011-01-01 2011-01-01 false Crop insurance requirement. 1405.6 Section 1405.6 Agriculture Regulations of the Department of Agriculture (Continued) COMMODITY CREDIT CORPORATION, DEPARTMENT...

Regional Climate Implications of Large-scale Cultivation of Biofuel Crops

NASA Astrophysics Data System (ADS)

Rowe, C. M.; Oglesby, R. J.; Hays, C. J.; van Etten, A. R.

2008-12-01

Conversion from corn-based ethanol to cellulosic ethanol has the potential to dramatically alter the production of biofuels in the United States and could result in large-scale changes in the agricultural landscape of vast areas of the country. Regions currently dominated by corn production could see widespread planting of switchgrass and other fast-growing, water-efficient sources of cellulose biomass. An often overlooked side effect of these land-cover changes could be a significant alteration of the energy fluxes between the land surface and the atmosphere with profound local, regional, and continental impacts on the climate system. Changes in the surface energy balance result primarily from differences in the seasonality of transpiration from corn versus switchgrass and could be enhanced as a result of a reduced need for irrigation of switchgrass in areas where corn can be produced only under irrigation. Preliminary modeling results using a simple "bucket" land surface model coupled to the WRF mesoscale model have demonstrated increases in summertime average daily maximum temperature of up to 4° C, smaller increases of up to 2° C in nighttime minimum temperatures and reductions in precipitation by up to 25% when corn was changed to switchgrass over the central United States. Improved parameterization of biofuel crops in more sophisticated land surface models will allow us to refine these preliminary estimates and assess the impacts of large-scale conversion to cellulosic biofuel crops, relative to greenhouse gas induced regional climate change.

Cover crops to improve soil health and pollinator habitat in nut orchards: Part II

Treesearch

Jerry Van Sambeek

2017-01-01

Integrating cover crops into a nut orchard can have some unique benefits and problems not found when used cover crops during the fallow period between cash crops. Studies show ground covers can reduce hardwood tree growth anywhere from a few percent to more than 70 percent in the case of tall fescue. This means if it takes 3 years to put on one inch of diameter growth...

Influence of ecohydrologic feedbacks from simulated crop growth on integrated regional hydrologic simulations under climate scenarios

NASA Astrophysics Data System (ADS)

van Walsum, P. E. V.; Supit, I.

2012-06-01

Hydrologic climate change modelling is hampered by climate-dependent model parameterizations. To reduce this dependency, we extended the regional hydrologic modelling framework SIMGRO to host a two-way coupling between the soil moisture model MetaSWAP and the crop growth simulation model WOFOST, accounting for ecohydrologic feedbacks in terms of radiation fraction that reaches the soil, crop coefficient, interception fraction of rainfall, interception storage capacity, and root zone depth. Except for the last, these feedbacks are dependent on the leaf area index (LAI). The influence of regional groundwater on crop growth is included via a coupling to MODFLOW. Two versions of the MetaSWAP-WOFOST coupling were set up: one with exogenous vegetation parameters, the "static" model, and one with endogenous crop growth simulation, the "dynamic" model. Parameterization of the static and dynamic models ensured that for the current climate the simulated long-term averages of actual evapotranspiration are the same for both models. Simulations were made for two climate scenarios and two crops: grass and potato. In the dynamic model, higher temperatures in a warm year under the current climate resulted in accelerated crop development, and in the case of potato a shorter growing season, thus partly avoiding the late summer heat. The static model has a higher potential transpiration; depending on the available soil moisture, this translates to a higher actual transpiration. This difference between static and dynamic models is enlarged by climate change in combination with higher CO2 concentrations. Including the dynamic crop simulation gives for potato (and other annual arable land crops) systematically higher effects on the predicted recharge change due to climate change. Crop yields from soils with poor water retention capacities strongly depend on capillary rise if moisture supply from other sources is limited. Thus, including a crop simulation model in an integrated

Improving plot- and regional-scale crop models for simulating impacts of climate variability and extremes

NASA Astrophysics Data System (ADS)

Tao, F.; Rötter, R.

2013-12-01

Many studies on global climate report that climate variability is increasing with more frequent and intense extreme events1. There are quite large uncertainties from both the plot- and regional-scale models in simulating impacts of climate variability and extremes on crop development, growth and productivity2,3. One key to reducing the uncertainties is better exploitation of experimental data to eliminate crop model deficiencies and develop better algorithms that more adequately capture the impacts of extreme events, such as high temperature and drought, on crop performance4,5. In the present study, in a first step, the inter-annual variability in wheat yield and climate from 1971 to 2012 in Finland was investigated. Using statistical approaches the impacts of climate variability and extremes on wheat growth and productivity were quantified. In a second step, a plot-scale model, WOFOST6, and a regional-scale crop model, MCWLA7, were calibrated and validated, and applied to simulate wheat growth and yield variability from 1971-2012. Next, the estimated impacts of high temperature stress, cold damage, and drought stress on crop growth and productivity based on the statistical approaches, and on crop simulation models WOFOST and MCWLA were compared. Then, the impact mechanisms of climate extremes on crop growth and productivity in the WOFOST model and MCWLA model were identified, and subsequently, the various algorithm and impact functions were fitted against the long-term crop trial data. Finally, the impact mechanisms, algorithms and functions in WOFOST model and MCWLA model were improved to better simulate the impacts of climate variability and extremes, particularly high temperature stress, cold damage and drought stress for location-specific and large area climate impact assessments. Our studies provide a good example of how to improve, in parallel, the plot- and regional-scale models for simulating impacts of climate variability and extremes, as needed for

[Soil quality assessment under different cropping system and straw management in farmland of arid oasis region].

PubMed

Zhang, Peng Peng; Pu, Xiao Zhen; Zhang, Wang Feng

2018-03-01

To reveal the regulatory mechanism of agricultural management practices on soil quality, an experiment was carried out to study the different cropping system and straw management on soil organic carbon and fractions and soil enzyme activity in farmland of arid oasis region, which would provide a scientific basic for enhancing agricultural resources utilization and sustainable development. In crop planting planning area, we took the mainly crop (cotton, wheat, maize) as research objects and designed long-term continues cropping and crop rotation experiments. The results showed that the soil organic carbon (SOC), soil microbial biomass C, labile C, water-soluble organic C, and hot-water-soluble organic C content were increased by 3.6%-9.9%, 41.8%-98.9%, 3.3%-17.0%, 11.1%-32.4%, 4.6%-27.5% by crop rotation compared to continues cropping, and 12%-35.9%, 22.4%-49.7%, 30.7%-51.0%, 10.6%-31.9%, 41.0%-96.4% by straw incorporated compared to straw removed, respectively. The soil catalase, dehydrogenase, β-glucosidase, invertase glucose, cellulase glucose activity were increased by 6.4%-10.9%, 6.6%-18.8%, 5.9%-15.3%, 10.0%-27.4%, 28.1%-37.5% by crop rotation compared to continues cropping, and 31.4%-47.5%, 19.9%-46.6%, 13.8%-20.7%, 19.8%-55.6%, 54.1%-70.9% by straw incorporated compared to straw removed, respectively. There were significant positive linear correlations among SOC, labile SOC fractions and soil enzyme. Therefore, we concluded that labile SOC fractions and soil enzyme were effective index for evaluating the change of SOC and soil quality. Based on factor analysis, in arid region, developing agricultural production using cropland management measures, such as straw-incorporated and combined short-term continues cotton and crop rotation, could enhance SOC and labile SOC fractions contents and soil enzyme activity, which could improve soil quality and be conducive to agricultural sustainable development.

Capturing field-scale variability in crop performance across a regional-scale climosequence

NASA Astrophysics Data System (ADS)

Brooks, E. S.; Poggio, M.; Anderson, T. R.; Gasch, C.; Yourek, M. A.; Ward, N. K.; Magney, T. S.; Brown, D. J.; Huggins, D. R.

2014-12-01

With the increasing availability of variable rate technology for applying fertilizers and other agrichemicals in dryland agricultural production systems there is a growing need to better capture and understand the processes driving field scale variability in crop yield and soil water. This need for a better understanding of field scale variability has led to the recent designation of the R. J. Cook Agronomy Farm (CAF) (Pullman, WA, USA) as a United States Department of Agriculture Long-Term Agro-Ecosystem Research (LTAR) site. Field scale variability at the CAF is closely monitored using extensive environmental sensor networks and intensive hand sampling. As investigating land-soil-water dynamics at CAF is essential for improving precision agriculture, transferring this knowledge across the regional-scale climosequence is challenging. In this study we describe the hydropedologic functioning of the CAF in relation to five extensively instrumented field sites located within 50 km in the same climatic region. The formation of restrictive argillic soil horizons in the wetter, cooler eastern edge of the region results in the development of extensive perched water tables, surface saturation, and surface runoff, whereas excess water is not an issue in the warmer, drier, western edge of the region. Similarly, crop and tillage management varies across the region as well. We discuss the implications of these regional differences on field scale management decisions and demonstrate how we are using proximal soil sensing and remote sensing imagery to better understand and capture field scale variability at a particular field site.

Conservation tillage issues: cover crop-based organic rotational no-till grain production in the mid-atlantic region

USDA-ARS?s Scientific Manuscript database

Organic producers in the mid-Atlantic region are interested in reducing tillage, labor, and time requirements for grain production. Cover crop-based organic rotational no-till grain production is one approach to accomplishing these goals. Advancements in a system for planting crops into a mat of cov...

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

USDA-ARS?s Scientific Manuscript database

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

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.

Regional-scale yield simulations using crop and climate models: assessing uncertainties, sensitivity to temperature and adaptation options

NASA Astrophysics Data System (ADS)

Challinor, A. J.

2010-12-01

Recent progress in assessing the impacts of climate variability and change on crops using multiple regional-scale simulations of crop and climate (i.e. ensembles) is presented. Simulations for India and China used perturbed responses to elevated carbon dioxide constrained using observations from FACE studies and controlled environments. Simulations with crop parameter sets representing existing and potential future adapted varieties were also carried out. The results for India are compared to sensitivity tests on two other crop models. For China, a parallel approach used socio-economic data to account for autonomous farmer adaptation. Results for the USA analysed cardinal temperatures under a range of local warming scenarios for 2711 varieties of spring wheat. The results are as follows: 1. Quantifying and reducing uncertainty. The relative contribution of uncertainty in crop and climate simulation to the total uncertainty in projected yield changes is examined. The observational constraints from FACE and controlled environment studies are shown to be the likely critical factor in maintaining relatively low crop parameter uncertainty. Without these constraints, crop simulation uncertainty in a doubled CO2 environment would likely be greater than uncertainty in simulating climate. However, consensus across crop models in India varied across different biophysical processes. 2. The response of yield to changes in local mean temperature was examined and compared to that found in the literature. No consistent response to temperature change was found across studies. 3. Implications for adaptation. China. The simulations of spring wheat in China show the relative importance of tolerance to water and heat stress in avoiding future crop failures. The greatest potential for reducing the number of harvests less than one standard deviation below the baseline mean yield value comes from alleviating water stress; the greatest potential for reducing harvests less than two

Improving Crop Productions Using the Irrigation & Crop Production Model Under Drought

NASA Astrophysics Data System (ADS)

Shin, Y.; Lee, T.; Lee, S. H.; Kim, J.; Jang, W.; Park, S.

2017-12-01

We aimed to improve crop productions by providing optimal irrigation water amounts (IWAs) for various soils and crops using the Irrigation & Crop Production (ICP) model under various hydro-climatic regions. We selected the Little Washita (LW 13/21) and Bangdong-ri sites in Oklahoma (United States of America) and Chuncheon (Republic of Korea) for the synthetic studies. Our results showed that the ICP model performed well for improving crop productions by providing optimal IWAs during the study period (2000 to 2016). Crop productions were significantly affected by the solar radiation and precipitation, but the maximum and minimum temperature showed less impact on crop productions. When we considerd that the weather variables cannot be adjusted by artifical activities, irrigation might be the only solution for improving crop productions under drought. Also, the presence of shallow ground water (SGW) table depths higlhy influences on crop production. Although certainties exist in the synthetic studies, our results showed the robustness of the ICP model for improving crop productions under the drought condition. Thus, the ICP model can contribute to efficient water management plans under drought in regions at where water availability is limited.

Regression model estimation of early season crop proportions: North Dakota, some preliminary results

NASA Technical Reports Server (NTRS)

Lin, K. K. (Principal Investigator)

1982-01-01

To estimate crop proportions early in the season, an approach is proposed based on: use of a regression-based prediction equation to obtain an a priori estimate for specific major crop groups; modification of this estimate using current-year LANDSAT and weather data; and a breakdown of the major crop groups into specific crops by regression models. Results from the development and evaluation of appropriate regression models for the first portion of the proposed approach are presented. The results show that the model predicts 1980 crop proportions very well at both county and crop reporting district levels. In terms of planted acreage, the model underpredicted 9.1 percent of the 1980 published data on planted acreage at the county level. It predicted almost exactly the 1980 published data on planted acreage at the crop reporting district level and overpredicted the planted acreage by just 0.92 percent.

Effective crop evapotranspiration measurement using time-domain reflectometry technique in a sub-humid region

NASA Astrophysics Data System (ADS)

Srivastava, R. K.; Panda, R. K.; Halder, Debjani

2017-08-01

The primary objective of this study was to evaluate the performance of the time-domain reflectometry (TDR) technique for daily evapotranspiration estimation of peanut and maize crop in a sub-humid region. Four independent methods were used to estimate crop evapotranspiration (ETc), namely, soil water balance budgeting approach, energy balance approach—(Bowen ratio), empirical methods approach, and Pan evaporation method. The soil water balance budgeting approach utilized the soil moisture measurement by gravimetric and TDR method. The empirical evapotranspiration methods such as combination approach (FAO-56 Penman-Monteith and Penman), temperature-based approach (Hargreaves-Samani), and radiation-based approach (Priestley-Taylor, Turc, Abetw) were used to estimate the reference evapotranspiration (ET0). The daily ETc determined by the FAO-56 Penman-Monteith, Priestley-Taylor, Turc, Pan evaporation, and Bowen ratio were found to be at par with the ET values derived from the soil water balance budget; while the methods Abetw, Penman, and Hargreaves-Samani were not found to be ideal for the determination of ETc. The study illustrates the in situ applicability of the TDR method in order to make it possible for a user to choose the best way for the optimum water consumption for a given crop in a sub-humid region. The study suggests that the FAO-56 Penman-Monteith, Turc, and Priestley-Taylor can be used for the determination of crop ETc using TDR in comparison to soil water balance budget.

Evaluating regional water scarcity: Irrigated crop water budgets for groundwater management in the Wisconsin Central Sands

NASA Astrophysics Data System (ADS)

Nocco, M. A.; Kucharik, C. J.; Kraft, G.

2013-12-01

Regional water scarcity dilemmas between agricultural and aquatic land users pervade the humid northern lake states of Wisconsin, Minnesota, and Michigan, where agricultural irrigation relies on groundwater drawn from shallow aquifers. As these aquifers have strong connectivity to surface waters, irrigation lowers water levels in lakes and wetlands and reduces stream discharges. Irrigation expansion has cultivated a 60-year water scarcity dilemma in The Wisconsin Central Sands, the largest irrigated region in the humid northern lake states, dedicated to potato, maize, and processing vegetable production. Irrigation has depleted Wisconsin Central Sands surface waters, lowering levels in some lakes by over 2 m and drying some coldwater trout streams. Aquatic ecosystems, property values, and recreational uses in some surface waters have been devastated. While the causal link between pumping and surface water stress is established, understanding crop-mediated processes, such as the timing and magnitude of groundwater consumption by evapotranspiration (ET) and groundwater recharge, will be useful in management of groundwater, irrigated cropping systems, and surface water health. Previous modeling and field efforts have compared irrigated crop water use to a natural reference condition on a net annual basis. As a result, we presently understand that for irrigated potatoes and maize, the average annual ET is greater and therefore, the average annual recharge is less than rainfed row crops, grasslands, and both coniferous and deciduous forests. However, we have a limited understanding of the magnitude and timing of ET and recharge from irrigated cropping systems on shorter time scales that proceed with the annual cropping cycle (i.e. planting, full canopy, harvest, residue cover). We seek to understand the spatiotemporal variability of crop water budgets and associated water scarcity in the Wisconsin Central Sands through detailed measurements of drainage (potential

Benchmark data on the separability among crops in the southern San Joaquin Valley of California

NASA Technical Reports Server (NTRS)

Morse, A.; Card, D. H.

1984-01-01

Landsat MSS data were input to a discriminant analysis of 21 crops on each of eight dates in 1979 using a total of 4,142 fields in southern Fresno County, California. The 21 crops, which together account for over 70 percent of the agricultural acreage in the southern San Joaquin Valley, were analyzed to quantify the spectral separability, defined as omission error, between all pairs of crops. On each date the fields were segregated into six groups based on the mean value of the MSS7/MSS5 ratio, which is correlated with green biomass. Discriminant analysis was run on each group on each date. The resulting contingency tables offer information that can be profitably used in conjunction with crop calendars to pick the best dates for a classification. The tables show expected percent correct classification and error rates for all the crops. The patterns in the contingency tables show that the percent correct classification for crops generally increases with the amount of greenness in the fields being classified. However, there are exceptions to this general rule, notably grain.

7 CFR 457.165 - Millet crop insurance provisions.

Code of Federal Regulations, 2012 CFR

2012-01-01

... Provisions, will be reduced by: (a) One percent per day for the first through the tenth day; and (b) Three percent per day for the eleventh through the twentieth day. 12. Prevented Planting Your prevented planting... Provisions for that purpose. Harvest. Combining or threshing the millet for grain. A crop that is swathed...

7 CFR 457.165 - Millet crop insurance provisions.

Code of Federal Regulations, 2013 CFR

2013-01-01

... Provisions, will be reduced by: (a) One percent per day for the first through the tenth day; and (b) Three percent per day for the eleventh through the twentieth day. 12. Prevented Planting Your prevented planting... Provisions for that purpose. Harvest. Combining or threshing the millet for grain. A crop that is swathed...

7 CFR 457.165 - Millet crop insurance provisions.

Code of Federal Regulations, 2014 CFR

2014-01-01

... Provisions, will be reduced by: (a) One percent per day for the first through the tenth day; and (b) Three percent per day for the eleventh through the twentieth day. 12. Prevented Planting Your prevented planting... Provisions for that purpose. Harvest. Combining or threshing the millet for grain. A crop that is swathed...

Evaluation of reference crop evapotranspiration methods in arid, semi-arid and humid regions

USDA-ARS?s Scientific Manuscript database

It is necessary to find a simpler method in different climatic regions to calculate reference crop evapotranspiration (ETo) since the application of the FAO-56 Penman-Monteith method is often restricted due to unavailability of a full weather data set. Seven ETo methods, the de facto standard FAO-56...

Food security: crops for people not for cars.

PubMed

Kullander, Sven

2010-05-01

Humankind is currently faced with the huge challenge of securing a sustainable energy supply and biofuels constitute one of the major options. However, the commercially traded edible crops are barely sufficient to meet food demand of the present world population. Certain regions, for example EU-27, do not even have a sufficient indigenous crop production. Of this follows that motor biofuels based on edible crops should be avoided. To replace more than some percent of the fossil motor fuels, non-edible biomass-rest products and wastes-should instead be considered for conversion to biofuels. In this way, about 10% of the current fossil fuels can be replaced. Feeding a world population expected to grow by some 50% during the next 50 years will be a major challenge. For environmental reasons it seems that agricultural land cannot be expanded very much, maybe not at all. The solution to the increasing food demand seems therefore to be using the present crop production more efficiently and increasing output from present agricultural land, maintaining biodiversity and climate stability within reasonable limits. In the future, agriculture will need more energy and more water irrigation. Food production is, however, already very energy demanding, requiring several times more externally provided energy than the energy content of the food itself. A sufficient energy supply will be a key issue for the future farming!

Crop monoculture rather than agriculture reduces the spatial turnover of soil bacterial communities at a regional scale.

PubMed

Figuerola, Eva L M; Guerrero, Leandro D; Türkowsky, Dominique; Wall, Luis G; Erijman, Leonardo

2015-03-01

The goal of this study was to investigate the spatial turnover of soil bacterial communities in response to environmental changes introduced by the practices of soybean monoculture or crop rotations, relative to grassland soils. Amplicon sequencing of the 16S rRNA gene was used to analyse bacterial diversity in producer fields through three successive cropping cycles within one and a half years, across a regional scale of the Argentinean Pampas. Unlike local diversity, which was not significantly affected by land use type, agricultural management had a strong influence on β-diversity patterns. Distributions of pairwise distances between all soils samples under soybean monoculture had significantly lower β-diversity and narrower breadth compared with distributions of pairwise distances between soils managed with crop rotation. Interestingly, good agricultural practices had similar degree of β-diversity as natural grasslands. The higher phylogenetic relatedness of bacterial communities in soils under monoculture across the region was likely determined by the observed loss of endemic species, and affected mostly to phyla with low regional diversity, such as Acidobacteria, Verrucomicrobia and the candidates phyla SPAM and WS3. These results suggest that the implementation of good agricultural practices, including crop rotation, may be critical for the long-term conservation of soil biodiversity. © 2014 Society for Applied Microbiology and John Wiley & Sons Ltd.

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

Average Amount and Stability of Available Agro-Climate Resources in the Main Maize Cropping Regions in China during 1981-2010

NASA Astrophysics Data System (ADS)

Zhao, Jin; Yang, Xiaoguang

2018-02-01

The available agro-climate resources that can be absorbed and converted into dry matter could directly affect crop growth and yield under climate change. Knowledge of the average amount and stability of available agro-climate resources for maize in the main cropping regions of China under climate change is essential for farmers and advisors to optimize cropping choices and develop adaptation strategies under limited resources. In this study, the three main maize cropping regions in China—the North China spring maize region (NCS), the Huanghuaihai summer maize region (HS), and the Southwest China mountain maize region (SCM)—were selected as study regions. Based on observed solar radiation, temperature, and precipitation data, we analyzed the spatial distributions and temporal trends in the available agro-climate resources for maize during 1981-2010. During this period, significantly prolonged climatological growing seasons for maize [3.3, 2.0, and 4.7 day (10 yr)-1 in NCS, HS, and SCM] were found in all three regions. However, the spatiotemporal patterns of the available agro-climate resources differed among the three regions. The available heating resources for maize increased significantly in the three regions, and the rates of increase were higher in NCS [95.5°C day (10 yr)-1] and SCM [93.5°C day (10 yr)-1] than that in HS [57.7°C day (10 yr)-1]. Meanwhile, decreasing trends in the available water resources were found in NCS [-5.3 mm (10 yr)-1] and SCM [-5.8 mm (10 yr)-1], whereas an increasing trend was observed in HS [3.0 mm (10 yr)-1]. Increasing trends in the available radiation resources were found in NCS [20.9 MJ m-2 (10 yr)-1] and SCM [25.2 MJ m-2 (10 yr)-1], whereas a decreasing trend was found in HS [11.6 MJ m-2 (10 yr)-1]. Compared with 1981-90, the stability of all three resource types decreased during 1991-2000 and 2001-10 in the three regions. More consideration should be placed on the extreme events caused by more intense climate fluctuations

Influence of feedbacks from simulated crop growth on integrated regional hydrologic simulations under climate scenarios

NASA Astrophysics Data System (ADS)

van Walsum, P. E. V.

2011-11-01

Climate change impact modelling of hydrologic responses is hampered by climate-dependent model parameterizations. Reducing this dependency was one of the goals of extending the regional hydrologic modelling system SIMGRO with a two-way coupling to the crop growth simulation model WOFOST. The coupling includes feedbacks to the hydrologic model in terms of the root zone depth, soil cover, leaf area index, interception storage capacity, crop height and crop factor. For investigating whether such feedbacks lead to significantly different simulation results, two versions of the model coupling were set up for a test region: one with exogenous vegetation parameters, the "static" model, and one with endogenous simulation of the crop growth, the "dynamic" model WOFOST. The used parameterization methods of the static/dynamic vegetation models ensure that for the current climate the simulated long-term average of the actual evapotranspiration is the same for both models. Simulations were made for two climate scenarios. Owing to the higher temperatures in combination with a higher CO2-concentration of the atmosphere, a forward time shift of the crop development is simulated in the dynamic model; the used arable land crop, potatoes, also shows a shortening of the growing season. For this crop, a significant reduction of the potential transpiration is simulated compared to the static model, in the example by 15% in a warm, dry year. In consequence, the simulated crop water stress (the unit minus the relative transpiration) is lower when the dynamic model is used; also the simulated increase of crop water stress due to climate change is lower; in the example, the simulated increase is 15 percentage points less (of 55) than when a static model is used. The static/dynamic models also simulate different absolute values of the transpiration. The difference is most pronounced for potatoes at locations with ample moisture supply; this supply can either come from storage release of a

Origins of food crops connect countries worldwide

PubMed Central

Achicanoy, Harold A.; Bjorkman, Anne D.; Navarro-Racines, Carlos; Guarino, Luigi; Flores-Palacios, Ximena; Engels, Johannes M. M.; Wiersema, John H.; Dempewolf, Hannes; Sotelo, Steven; Ramírez-Villegas, Julian; Castañeda-Álvarez, Nora P.; Fowler, Cary; Jarvis, Andy; Rieseberg, Loren H.; Struik, Paul C.

2016-01-01

Research into the origins of food plants has led to the recognition that specific geographical regions around the world have been of particular importance to the development of agricultural crops. Yet the relative contributions of these different regions in the context of current food systems have not been quantified. Here we determine the origins (‘primary regions of diversity’) of the crops comprising the food supplies and agricultural production of countries worldwide. We estimate the degree to which countries use crops from regions of diversity other than their own (‘foreign crops’), and quantify changes in this usage over the past 50 years. Countries are highly interconnected with regard to primary regions of diversity of the crops they cultivate and/or consume. Foreign crops are extensively used in food supplies (68.7% of national food supplies as a global mean are derived from foreign crops) and production systems (69.3% of crops grown are foreign). Foreign crop usage has increased significantly over the past 50 years, including in countries with high indigenous crop diversity. The results provide a novel perspective on the ongoing globalization of food systems worldwide, and bolster evidence for the importance of international collaboration on genetic resource conservation and exchange.

Deforestation risk due to commodity crop expansion in sub-Saharan Africa

NASA Astrophysics Data System (ADS)

Ordway, Elsa M.; Asner, Gregory P.; Lambin, Eric F.

2017-04-01

Rapid integration of global agricultural markets and subsequent cropland displacement in recent decades increased large-scale tropical deforestation in South America and Southeast Asia. Growing land scarcity and more stringent land use regulations in these regions could incentivize the offshoring of export-oriented commodity crops to sub-Saharan Africa (SSA). We assess the effects of domestic- and export-oriented agricultural expansion on deforestation in SSA in recent decades. Analyses were conducted at the global, regional and local scales. We found that commodity crops are expanding in SSA, increasing pressure on tropical forests. Four Congo Basin countries, Sierra Leone, Liberia, and Côte d’Ivoire were most at risk in terms of exposure, vulnerability and pressures from agricultural expansion. These countries averaged the highest percent forest cover (58% ± 17.93) and lowest proportions of potentially available cropland outside forest areas (1% ± 0.89). Foreign investment in these countries was concentrated in oil palm production (81%), with a median investment area of 41 582 thousand ha. Cocoa, the fastest expanding export-oriented crop across SSA, accounted for 57% of global expansion in 2000-2013 at a rate of 132 thousand ha yr-1. However, cocoa only amounted to 0.89% of foreign land investment. Commodity crop expansion in SSA appears largely driven by small- and medium-scale farmers rather than industrial plantations. Land-use changes associated with large-scale investments remain to be observed in many countries. Although domestic demand for commodity crops was associated with most agricultural expansion, we provide evidence of a growing influence of distant markets on land-use change in SSA.

Priority regions for research on dryland cereals and legumes

PubMed Central

Hyman, Glenn; Barona, Elizabeth; Biradar, Chandrashekhar; Guevara, Edward; Dixon, John; Beebe, Steve; Castano, Silvia Elena; Alabi, Tunrayo; Gumma, Murali Krishna; Sivasankar, Shoba; Rivera, Ovidio; Espinosa, Herlin; Cardona, Jorge

2016-01-01

Dryland cereals and legumes  are important crops in farming systems across the world.  Yet they are frequently neglected among the priorities for international agricultural research and development, often due to lack of information on their magnitude and extent. Given what we know about the global distribution of dryland cereals and legumes, what regions should be high priority for research and development to improve livelihoods and food security? This research evaluated the geographic dimensions of these crops and the farming systems where they are found worldwide. The study employed geographic information science and data to assess the key farming systems and regions for these crops. Dryland cereal and legume crops should be given high priority in 18 farming systems worldwide, where their cultivated area comprises more than 160 million ha. These regions include the dryer areas of South Asia, West and East Africa, the Middle East and North Africa, Central America and other parts of Asia. These regions are prone to drought and heat stress, have limiting soil constraints, make up half of the global population and account for 60 percent of the global poor and malnourished. The dryland cereal and legume crops and farming systems merit more research and development attention to improve productivity and address development problems. This project developed an open access dataset and information resource that provides the basis for future analysis of the geographic dimensions of dryland cereals and legumes. PMID:27303632

40 CFR 264.276 - Food-chain crops.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 40 Protection of Environment 27 2012-07-01 2012-07-01 false Food-chain crops. 264.276 Section 264... Treatment § 264.276 Food-chain crops. The Regional Administrator may allow the growth of food-chain crops in... Regional Administrator will specify in the facility permit the specific food-chain crops which may be grown...

40 CFR 264.276 - Food-chain crops.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 26 2011-07-01 2011-07-01 false Food-chain crops. 264.276 Section 264... Treatment § 264.276 Food-chain crops. The Regional Administrator may allow the growth of food-chain crops in... Regional Administrator will specify in the facility permit the specific food-chain crops which may be grown...

40 CFR 264.276 - Food-chain crops.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 25 2010-07-01 2010-07-01 false Food-chain crops. 264.276 Section 264... Treatment § 264.276 Food-chain crops. The Regional Administrator may allow the growth of food-chain crops in... Regional Administrator will specify in the facility permit the specific food-chain crops which may be grown...

40 CFR 264.276 - Food-chain crops.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 40 Protection of Environment 27 2013-07-01 2013-07-01 false Food-chain crops. 264.276 Section 264... Treatment § 264.276 Food-chain crops. The Regional Administrator may allow the growth of food-chain crops in... Regional Administrator will specify in the facility permit the specific food-chain crops which may be grown...

40 CFR 264.276 - Food-chain crops.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 26 2014-07-01 2014-07-01 false Food-chain crops. 264.276 Section 264... Treatment § 264.276 Food-chain crops. The Regional Administrator may allow the growth of food-chain crops in... Regional Administrator will specify in the facility permit the specific food-chain crops which may be grown...

Improved regional-scale Brazilian cropping systems' mapping based on a semi-automatic object-based clustering approach

NASA Astrophysics Data System (ADS)

Bellón, Beatriz; Bégué, Agnès; Lo Seen, Danny; Lebourgeois, Valentine; Evangelista, Balbino Antônio; Simões, Margareth; Demonte Ferraz, Rodrigo Peçanha

2018-06-01

Cropping systems' maps at fine scale over large areas provide key information for further agricultural production and environmental impact assessments, and thus represent a valuable tool for effective land-use planning. There is, therefore, a growing interest in mapping cropping systems in an operational manner over large areas, and remote sensing approaches based on vegetation index time series analysis have proven to be an efficient tool. However, supervised pixel-based approaches are commonly adopted, requiring resource consuming field campaigns to gather training data. In this paper, we present a new object-based unsupervised classification approach tested on an annual MODIS 16-day composite Normalized Difference Vegetation Index time series and a Landsat 8 mosaic of the State of Tocantins, Brazil, for the 2014-2015 growing season. Two variants of the approach are compared: an hyperclustering approach, and a landscape-clustering approach involving a previous stratification of the study area into landscape units on which the clustering is then performed. The main cropping systems of Tocantins, characterized by the crop types and cropping patterns, were efficiently mapped with the landscape-clustering approach. Results show that stratification prior to clustering significantly improves the classification accuracies for underrepresented and sparsely distributed cropping systems. This study illustrates the potential of unsupervised classification for large area cropping systems' mapping and contributes to the development of generic tools for supporting large-scale agricultural monitoring across regions.

Incorporating Medium-Range Weather Forecasts in Seasonal Crop Scenarios over the Greater Horn of Africa to Support National/Regional/Local Decision Makers

NASA Astrophysics Data System (ADS)

Shukla, S.; Husak, G. J.; Funk, C. C.; Verdin, J. P.

2015-12-01

The USAID's Famine Early Warning Systems Network (FEWS NET) provides seasonal assessments of crop conditions over the Greater Horn of Africa (GHA) and other food insecure regions. These assessments and current livelihood, nutrition, market conditions and conflicts are used to generate food security scenarios that help national, regional and local decision makers target their resources and mitigate socio-economic losses. Among the various tools that FEWS NET uses is the FAO's Water Requirement Satisfaction Index (WRSI). The WRSI is a simple yet powerful crop assessment model that incorporates current moisture conditions (at the time of the issuance of forecast), precipitation scenarios, potential evapotranspiration and crop parameters to categorize crop conditions into different classes ranging from "failure" to "very good". The WRSI tool has been shown to have a good agreement with local crop yields in the GHA region. At present, the precipitation scenarios used to drive the WRSI are based on either a climatological forecast (that assigns equal chances of occurrence to all possible scenarios and has no skill over the forecast period) or a sea-surface temperature anomaly based scenario (which at best have skill at the seasonal scale). In both cases, the scenarios fail to capture the skill that can be attained by initial atmospheric conditions (i.e., medium-range weather forecasts). During the middle of a cropping season, when a week or two of poor rains can have a devastating effect, two weeks worth of skillful precipitation forecasts could improve the skill of the crop scenarios. With this working hypothesis, we examine the value of incorporating medium-range weather forecasts in improving the skill of crop scenarios in the GHA region. We use the NCEP's Global Ensemble Forecast system (GEFS) weather forecasts and examine the skill of crop scenarios generated using the GEFS weather forecasts with respect to the scenarios based solely on the climatological forecast

Assessment of energy crops alternative to maize for biogas production in the Greater Region.

PubMed

Mayer, Frédéric; Gerin, Patrick A; Noo, Anaïs; Lemaigre, Sébastien; Stilmant, Didier; Schmit, Thomas; Leclech, Nathael; Ruelle, Luc; Gennen, Jerome; von Francken-Welz, Herbert; Foucart, Guy; Flammang, Jos; Weyland, Marc; Delfosse, Philippe

2014-08-01

The biomethane yield of various energy crops, selected among potential alternatives to maize in the Greater Region, was assessed. The biomass yield, the volatile solids (VS) content and the biochemical methane potential (BMP) were measured to calculate the biomethane yield per hectare of all plant species. For all species, the dry matter biomass yield and the VS content were the main factors that influence, respectively, the biomethane yield and the BMP. Both values were predicted with good accuracy by linear regressions using the biomass yield and the VS as independent variable. The perennial crop miscanthus appeared to be the most promising alternative to maize when harvested as green matter in autumn and ensiled. Miscanthus reached a biomethane yield of 5.5 ± 1 × 10(3)m(3)ha(-1) during the second year after the establishment, as compared to 5.3 ± 1 × 10(3)m(3)ha(-1) for maize under similar crop conditions. Copyright © 2014. Published by Elsevier Ltd.

Weather-based forecasts of California crop yields

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

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

2005-09-26

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

The interactive effects of soil transplant into colder regions and cropping on soil microbiology and biogeochemistry.

PubMed

Liu, Shanshan; Wang, Feng; Xue, Kai; Sun, Bo; Zhang, Yuguang; He, Zhili; Van Nostrand, Joy D; Zhou, Jizhong; Yang, Yunfeng

2015-03-01

Soil transplant into warmer regions has been shown to alter soil microbiology. In contrast, little is known about the effects of soil transplant into colder regions, albeit that climate cooling has solicited attention in recent years. To address this question, we transplanted bare fallow soil over large transects from southern China (subtropical climate zone) to central (warm temperate climate zone) and northern China (cold temperate climate zone). After an adaptation period of 4 years, soil nitrogen components, microbial biomass and community structures were altered. However, the effects of soil transplant on microbial communities were dampened by maize cropping, unveiling a negative interaction between cropping and transplant. Further statistical analyses with Canonical correspondence analysis and Mantel tests unveiled annual average temperature, relative humidity, aboveground biomass, soil pH and NH4 (+) -N content as environmental attributes closely correlated with microbial functional structures. In addition, average abundances of amoA-AOA (ammonia-oxidizing archaea) and amoA-AOB (ammonia-oxidizing bacteria) genes were significantly (P < 0.05) correlated with soil nitrification capacity, hence both AOA and AOB contributed to the soil functional process of nitrification. These results suggested that the soil nitrogen cycle was intimately linked with microbial community structure, and both were subjected to disturbance by soil transplant to colder regions and plant cropping. © 2014 Society for Applied Microbiology and John Wiley & Sons Ltd.

Improvement of Alternative Crop Phenology Detection Algorithms using MODIS NDVI Time Series Data in US Corn Belt Region

NASA Astrophysics Data System (ADS)

Lee, J.; Kang, S.; Seo, B.; Lee, K.

2017-12-01

Predicting crop phenology is important for understanding of crop development and growth processes and improving the accuracy of crop model. Remote sensing offers a feasible tool for monitoring spatio-temporal patterns of crop phenology in region and continental scales. Various methods have been developed to determine the timing of crop phenological stages using spectral vegetation indices (i.e. NDVI and EVI) derived from satellite data. In our study, it was compared four alternative detection methods to identify crop phenological stages (i.e. the emergence and harvesting date) using high quality NDVI time series data derived from MODIS. Also we investigated factors associated with crop development rate. Temperature and photoperiod are the two main factors which would influence the crop's growth pattern expressed in the VI data. Only the effect of temperature on crop development rate was considered. The temperature response function in the Wang-Engel (WE) model was used, which simulates crop development using nonlinear models with response functions that range from zero to one. It has attempted at the state level over 14 years (2003-2016) in Iowa and Illinois state of USA, where the estimated phenology date by using four methods for both corn and soybean. Weekly crop progress reports produced by the USDA NASS were used to validate phenology detection algorithms effected by temperature. All methods showed substantial uncertainty but the threshold method showed relatively better agreement with the State-level data for soybean phenology.

Agronomic responses to late-seeded cover crops in a semiarid region

USDA-ARS?s Scientific Manuscript database

Intensification of cropping systems in the Great Plains beyond annual cropping practices may be limited by inadequate precipitation, short growing seasons, and highly variable climatic conditions. Inclusion of cover crops in dryland cropping systems may serve as an effective intensification strateg...

A Spatial Allocation Procedure to Downscale Regional Crop Production Estimates from an Integrated Assessment Model

NASA Astrophysics Data System (ADS)

Moulds, S.; Djordjevic, S.; Savic, D.

2017-12-01

The Global Change Assessment Model (GCAM), an integrated assessment model, provides insight into the interactions and feedbacks between physical and human systems. The land system component of GCAM, which simulates land use activities and the production of major crops, produces output at the subregional level which must be spatially downscaled in order to use with gridded impact assessment models. However, existing downscaling routines typically consider cropland as a homogeneous class and do not provide information about land use intensity or specific management practices such as irrigation and multiple cropping. This paper presents a spatial allocation procedure to downscale crop production data from GCAM to a spatial grid, producing a time series of maps which show the spatial distribution of specific crops (e.g. rice, wheat, maize) at four input levels (subsistence, low input rainfed, high input rainfed and high input irrigated). The model algorithm is constrained by available cropland at each time point and therefore implicitly balances extensification and intensification processes in order to meet global food demand. It utilises a stochastic approach such that an increase in production of a particular crop is more likely to occur in grid cells with a high biophysical suitability and neighbourhood influence, while a fall in production will occur more often in cells with lower suitability. User-supplied rules define the order in which specific crops are downscaled as well as allowable transitions. A regional case study demonstrates the ability of the model to reproduce historical trends in India by comparing the model output with district-level agricultural inventory data. Lastly, the model is used to predict the spatial distribution of crops globally under various GCAM scenarios.

Integrated weed management strategies in cover crop-based, organic rotational no-till corn and soybean in the mid-Atlantic region

USDA-ARS?s Scientific Manuscript database

Cover crop-based, organic rotational no-till (CCORNT) corn and soybean systems have been developed in the mid-Atlantic region to build soil health, increase management flexibility, and reduce labor. In this system, a roll-crimped cover crop mulch provides within-season weed suppression in no-till co...

Investigation of Effectiveness of a Wing Equipped with a 50-percent-chord Sliding Flap, a 30-percent-chord Slotted Flap, and a 30-percent-chord Slat in Deflecting Propeller Slipstreams Downward for Vertical Take-off

NASA Technical Reports Server (NTRS)

Kuhn, Richard E

1957-01-01

Results are presented of an investigation of the effectiveness of a wing equipped with a 50-percent-chord sliding flap and a 30-percent-chord slotted flap in deflecting a propeller slipstream downward for vertical take-off. Tests were conducted at zero forward speed in a large room and included the effects of flap deflection, proximity to the ground, a leading-edge slat, and end plates. A turning angle of about 70 degrees and a resultant force of about 100 percent of the thrust were achieved near the ground. Out of the ground-effect region, the turning angle was also about 70 degrees but the resultant force was reduced to about 86 percent of the thrust.

GEOGLAM Crop Monitor Assessment Tool: Developing Monthly Crop Condition Assessments

NASA Astrophysics Data System (ADS)

McGaughey, K.; Becker Reshef, I.; Barker, B.; Humber, M. L.; Nordling, J.; Justice, C. O.; Deshayes, M.

2014-12-01

The Group on Earth Observations (GEO) developed the Global Agricultural Monitoring initiative (GEOGLAM) to improve existing agricultural information through a network of international partnerships, data sharing, and operational research. This presentation will discuss the Crop Monitor component of GEOGLAM, which provides the Agricultural Market Information System (AMIS) with an international, multi-source, and transparent consensus assessment of crop growing conditions, status, and agro-climatic conditions likely to impact global production. This activity covers the four primary crop types (wheat, maize, rice, and soybean) within the main agricultural producing regions of the AMIS countries. These assessments have been produced operationally since September 2013 and are published in the AMIS Market Monitor Bulletin. The Crop Monitor reports provide cartographic and textual summaries of crop conditions as of the 28th of each month, according to crop type. This presentation will focus on the building of international networks, data collection, and data dissemination.

The use of ERTS-1 multispectral imagery for crop identification in a semi-arid climate

NASA Technical Reports Server (NTRS)

Stockton, J. G.; Bauer, M. E.; Blair, B. O.; Baumgardner, M. F.

1975-01-01

Crop identification using multispectral satellite imagery and multivariate pattern recognition was used to identify wheat accurately in Greeley County, Kansas. A classification accuracy of 97 percent was found for wheat and the wheat estimate in hectares was within 5 percent of the USDA's Statistical Reporting Service estimate for 1973. The multispectral response of cotton and sorghum in Texas was not unique enough to distinguish between them nor to separate them from other cultivated crops.

Rye cover crop effects on soil quality in no-till corn silage-soybean cropping systems

USDA-ARS?s Scientific Manuscript database

Corn and soybean farmers in the upper Midwest are showing increasing interest in winter cover crops. Known benefits of winter cover crops include reductions in nutrient leaching, erosion prevention, and weed suppression; however, the effects of winter cover crops on soil quality in this region have ...

AgRISTARS: Supporting research. US crop calendars in support of the early warning project

NASA Technical Reports Server (NTRS)

Hodges, T. (Principal Investigator)

1981-01-01

The crop calendars produced for the Large Area Crop Inventory Experiment (LACIE) and crop calendar samples for Colorado, Iowa, Kansas, Minnesota, Montana, Nebraska, North Dakota, South Dakota, and Texas are presented. These calendars are based on weekly crop reporting district level observations of the percentage of various crops at several growth stages. A sample of the statistical treatments of the weekly data is provided. Four to five years of 50-percent dates for stages on a crop reporting district level for Arkansas, Iowa, Kentucky, Louisiana, Michigan, Mississippi, Ohio and Wisconsin are also given.

Genomic regions in crop–wild hybrids of lettuce are affected differently in different environments: implications for crop breeding

PubMed Central

Hartman, Yorike; Hooftman, Danny A P; Uwimana, Brigitte; van de Wiel, Clemens C M; Smulders, Marinus J M; Visser, Richard G F; van Tienderen, Peter H

2012-01-01

Many crops contain domestication genes that are generally considered to lower fitness of crop–wild hybrids in the wild environment. Transgenes placed in close linkage with such genes would be less likely to spread into a wild population. Therefore, for environmental risk assessment of GM crops, it is important to know whether genomic regions with such genes exist, and how they affect fitness. We performed quantitative trait loci (QTL) analyses on fitness(-related) traits in two different field environments employing recombinant inbred lines from a cross between cultivated Lactuca sativa and its wild relative Lactuca serriola. We identified a region on linkage group 5 where the crop allele consistently conferred a selective advantage (increasing fitness to 212% and 214%), whereas on linkage group 7, a region conferred a selective disadvantage (reducing fitness to 26% and 5%), mainly through delaying flowering. The probability for a putative transgene spreading would therefore depend strongly on the insertion location. Comparison of these field results with greenhouse data from a previous study using the same lines showed considerable differences in QTL patterns. This indicates that care should be taken when extrapolating experiments from the greenhouse, and that the impact of domestication genes has to be assessed under field conditions. PMID:23028403

Old Dog New Tricks: Use of Point-based Crop Models in Grid-based Regional Assessment of Crop Management Technologies Impact on Future Food Security

NASA Astrophysics Data System (ADS)

Koo, J.; Wood, S.; Cenacchi, N.; Fisher, M.; Cox, C.

2012-12-01

HarvestChoice (harvestchoice.org) generates knowledge products to guide strategic investments to improve the productivity and profitability of smallholder farming systems in sub-Saharan Africa (SSA). A keynote component of the HarvestChoice analytical framework is a grid-based overlay of SSA - a cropping simulation platform powered by process-based, crop models. Calibrated around the best available representation of cropping production systems in SSA, the simulation platform engages the DSSAT Crop Systems Model with the CENTURY Soil Organic Matter model (DSSAT-CENTURY) and provides a virtual experimentation module with which to explore the impact of a range of technological, managerial and environmental metrics on future crop productivity and profitability, as well as input use. For each of 5 (or 30) arc-minute grid cells in SSA, a stack of model input underlies it: datasets that cover soil properties and fertility, historic and future climate scenarios and farmers' management practices; all compiled from analyses of existing global and regional databases and consultations with other CGIAR centers. Running a simulation model is not always straightforward, especially when certain cropping systems or management practices are not even practiced by resource-poor farmers yet (e.g., precision agriculture) or they were never included in the existing simulation framework (e.g., water harvesting). In such cases, we used DSSAT-CENTURY as a function to iteratively estimate relative responses of cropping systems to technology-driven changes in water and nutrient balances compared to zero-adoption by farmers, while adjusting model input parameters to best mimic farmers' implementation of technologies in the field. We then fed the results of the simulation into to the economic and food trade model framework, IMPACT, to assess the potential implications on future food security. The outputs of the overall simulation analyses are packaged as a web-accessible database and published

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.

Patterns of crop cover under future climates.

PubMed

Porfirio, Luciana L; Newth, David; Harman, Ian N; Finnigan, John J; Cai, Yiyong

2017-04-01

We study changes in crop cover under future climate and socio-economic projections. This study is not only organised around the global and regional adaptation or vulnerability to climate change but also includes the influence of projected changes in socio-economic, technological and biophysical drivers, especially regional gross domestic product. The climatic data are obtained from simulations of RCP4.5 and 8.5 by four global circulation models/earth system models from 2000 to 2100. We use Random Forest, an empirical statistical model, to project the future crop cover. Our results show that, at the global scale, increases and decreases in crop cover cancel each other out. Crop cover in the Northern Hemisphere is projected to be impacted more by future climate than the in Southern Hemisphere because of the disparity in the warming rate and precipitation patterns between the two Hemispheres. We found that crop cover in temperate regions is projected to decrease more than in tropical regions. We identified regions of concern and opportunities for climate change adaptation and investment.

Computing the biomass potentials for maize and two alternative energy crops, triticale and cup plant (Silphium perfoliatum L.), with the crop model BioSTAR in the region of Hannover (Germany).

PubMed

Bauböck, Roland; Karpenstein-Machan, Marianne; Kappas, Martin

2014-01-01

Lower Saxony (Germany) has the highest installed electric capacity from biogas in Germany. Most of this electricity is generated with maize. Reasons for this are the high yields and the economic incentive. In parts of Lower Saxony, an expansion of maize cultivation has led to ecological problems and a negative image of bioenergy as such. Winter triticale and cup plant have both shown their suitability as alternative energy crops for biogas production and could help to reduce maize cultivation. The model Biomass Simulation Tool for Agricultural Resources (BioSTAR) has been validated with observed yield data from the region of Hannover for the cultures maize and winter wheat. Predicted yields for the cultures show satisfactory error values of 9.36% (maize) and 11.5% (winter wheat). Correlations with observed data are significant ( P  < 0.01) with R  = 0.75 for maize and 0.6 for winter wheat. Biomass potential calculations for triticale and cup plant have shown both crops to be high yielding and a promising alternative to maize in the region of Hanover and other places in Lower Saxony. The model BioSTAR simulated yields for maize and winter wheat in the region of Hannover at a good overall level of accuracy (combined error 10.4%). Due to input data aggregation, individual years show high errors though (up to 30%). Nevertheless, the BioSTAR crop model has proven to be a functioning tool for the prediction of agricultural biomass potentials under varying environmental and crop management frame conditions.

Crop identification for the delineation of irrigated regions under scarce data conditions: a new approach based on chaos theory

NASA Astrophysics Data System (ADS)

Mangiarotti, S.; Muddu, S.; Sharma, A. K.; Corgne, S.; Ruiz, L.; Hubert-Moy, L.

2015-12-01

Groundwater is one of the main water reservoirs used for irrigation in regions of scarce water resources. For this reason, crop irrigation is expected to have a direct influence on this reservoir. To understand the time evolution of the groundwater table and its storage changes, it is important to delineate irrigated crops, whose evaporative demand is relatively higher. Such delineation may be performed based on classical classification approaches using optical remote sensing. However, it remains a difficult problem in regions where plots do not exceed a few hectares and exhibit a very heterogeneous pattern with multiple crops. This difficulty is emphasized in South India where two or three months of cloudy conditions during the monsoon period can hide crop growth during the year. An alternative approach is introduced here that takes advantage of such scarce signal. Ten different crops are considered in the present study. A bank of crop models is first established based on the global modeling technique [1]. These models are then tested using original time series (from which models were obtained) in order to evaluate the information that can be deduced from these models in an inverse approach. The approach is then tested on an independent data set and is finally applied to a large ensemble of 10,000 time series of plot data extracted from the Berambadi catchment (AMBHAS site) part of the Kabini River basin CZO, South India. Results show that despite the important two-month gap in satellite observations in the visible band, interpolated vegetation index remains an interesting indicator for identification of crops in South India. [1] S. Mangiarotti, R. Coudret, L. Drapeau, & L. Jarlan, Polynomial search and global modeling: Two algorithms for modeling chaos, Phys. Rev. E, 86(4), 046205 (2012).

Nitrous Oxide Emissions from Biofuel Crops and Atmospheric Aerosols: Associations with Air Quality and Regional Climate

NASA Astrophysics Data System (ADS)

Pillai, Priya Ramachandran

Emissions of greenhouse gases (GHG) and primary release and secondary formation of aerosols alter the earth's radiative balance and therefore have important climatic implications. Savings in carbon dioxide (CO2) emissions accomplished by replacing fossil fuels with biofuels may increase the nitrous oxide (N2O) emissions. Among various atmospheric trace gases, N2O, irrespective of its low atmospheric concentration, is the fourth most important gas in causing the global greenhouse effect. Major processes, those affect the concentration of atmospheric N2O, are soil microbial activities leading to nitrification and denitrification. Therefore, anthropogenic activities such as industrial emissions, and agricultural practices including application of nitrogenous fertilizers, land use changes, biomass combustion all contribute to the atmospheric N2O concentration. The emission rates of N2O related to biofuel production depend on the nitrogen (N) fertilizer uptake efficiency of biofuel crops. However, crops with less N demand, such as switchgrass may have more favorable climate impacts when compared to crops with high N demands, such as corn. Despite its wide environmental tolerance, the regional adaptability of the potential biofuel crop switch grass varies considerably. Therefore, it is important to regionally quantify the GHG emissions and crop yield in response to N-fertilization. A major objective of this study is to quantify soil emissions of N2O from switchgrass and corn fields as a function of N-fertilization. The roles of soil moisture and soil temperature on N2O fluxes were analyzed. These N2O observations may be used to parameterize the biogeochemical models to better understand the impact of different N2O emission scenarios. This study allows for improvements in climate models that focus on understanding the environmental impacts of the climate change mitigation strategy of replacing fossil fuels with biofuels. As a second major objective, the top of the

Chat (Catha edulis): a socio economic crop in Harar Region, Eastern Ethiopia.

PubMed

Kandari, Laxman S; Yadav, Hiranmai R; Thakur, Ashok K; Kandari, Tripti

2014-01-01

Chat (Catha edulis) is an important perennial crop and its leaves are chewed for a stimulating effect. It is widely cultivated in the Ethiopian highlands of Oromia region and is figured as Ethiopia's second largest foreign exchange earner. Its cultivation accounts for about 70% of farmer's income in the study area. The common effect of its consumption leads to insomnia, a condition that the users sometimes try to overcome with sedatives or alcohol. The present study is an attempt to survey and assess the impact of crop on the community. It has been observed to implicate health problems, reduces savings and nutritional standards of the family members. The chat yields in the area ranges from 1500-1800 kg/ha through monoculture. During the study, the average monthly income of the family practicing chat cultivation was from Birr 8, 533.00 to 13, 166.00 kg/ha per year in Baate and Genede cultivating areas. When the average cost per/ha was rupees 60/kg. The present study shows that during the recent past, leaf consumption has increased significantly. Chat growers are not only producers but also traders and consumers. Its consumption has become a widespread habit from secondary schools. Highest number of consumers was found to be among drivers followed by students and shopkeepers. The consumption of the plant is not considered a taboo but on contrary a status symbol in the region. It has no legal or moral implications and is considered as a part of custom and habit of local people. High value cash crop like vegetables and orchard fruits needs to be used as a replacement for chat which could be a regular source of income to farmers. Alternative sources of income for farmers needs to be scientifically worked out and proposed keeping in view the proportion of agricultural land reserved under chat cultivation and to increase the production of food grains being produced.

Active microwave responses - An aid in improved crop classification

NASA Technical Reports Server (NTRS)

Rosenthal, W. D.; Blanchard, B. J.

1984-01-01

A study determined the feasibility of using visible, infrared, and active microwave data to classify agricultural crops such as corn, sorghum, alfalfa, wheat stubble, millet, shortgrass pasture and bare soil. Visible through microwave data were collected by instruments on board the NASA C-130 aircraft over 40 agricultural fields near Guymon, OK in 1978 and Dalhart, TX in 1980. Results from stepwise and discriminant analysis techniques indicated 4.75 GHz, 1.6 GHz, and 0.4 GHz cross-polarized microwave frequencies were the microwave frequencies most sensitive to crop type differences. Inclusion of microwave data in visible and infrared classification models improved classification accuracy from 73 percent to 92 percent. Despite the results, further studies are needed during different growth stages to validate the visible, infrared, and active microwave responses to vegetation.

Evaluating the crop coefficient using spectral reflectance

USGS Publications Warehouse

Heilman, J. L.; Heilman, W. E.; Moore, Donald G.

1982-01-01

Significant linear relationships were found between PVI and percent cover (r2 = 0.911), and between Kc and percent cover (r2 = 0.815). In addition, the position of the PVl intersection on the soil background line changed as a result of soil moisture increases following irrigation, even at high percent cover. Thus, once experimental relationships between Kc and crop growth are established, a mean Kc can be determined from spectral estimates of stage of development and the soil background component of PVI can be used to adjust the mean K, for increased evaporation following irrigation because the ratio of actual to potential evapotranspiration will approach 1 when the soil surface is wet.

Noah-MP-Crop: Introducing dynamic crop growth in the Noah-MP land surface model

NASA Astrophysics Data System (ADS)

Liu, Xing; Chen, Fei; Barlage, Michael; Zhou, Guangsheng; Niyogi, Dev

2016-12-01

Croplands are important in land-atmosphere interactions and in the modification of local and regional weather and climate; however, they are poorly represented in the current version of the coupled Weather Research and Forecasting/Noah with multiparameterization (Noah-MP) land surface modeling system. This study introduced dynamic corn (Zea mays) and soybean (Glycine max) growth simulations and field management (e.g., planting date) into Noah-MP and evaluated the enhanced model (Noah-MP-Crop) at field scales using crop biomass data sets, surface heat fluxes, and soil moisture observations. Compared to the generic dynamic vegetation and prescribed-leaf area index (LAI)-driven methods in Noah-MP, the Noah-MP-Crop showed improved performance in simulating leaf area index (LAI) and crop biomass. This model is able to capture the seasonal and annual variability of LAI and to differentiate corn and soybean in peak values of LAI as well as the length of growing seasons. Improved simulations of crop phenology in Noah-MP-Crop led to better surface heat flux simulations, especially in the early period of growing season where current Noah-MP significantly overestimated LAI. The addition of crop yields as model outputs expand the application of Noah-MP-Crop to regional agriculture studies. There are limitations in the use of current growing degree days (GDD) criteria to predict growth stages, and it is necessary to develop a new method that combines GDD with other environmental factors, to more accurately define crop growth stages. The capability introduced in Noah-MP allows further crop-related studies and development.

An optimal staggered harvesting strategy for herbaceous biomass energy crops

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

Bhat, M.G.; English, B.C.

1993-12-31

Biofuel research over the past two decades indicates lignocellulosic crops are a reliable source of feedstock for alternative energy. However, under the current technology of producing, harvesting and converting biomass crops, the cost of biofuel is not competitive with conventional biofuel. Cost of harvesting biomass feedstock is a single largest component of feedstock cost so there is a cost advantage in designing a biomass harvesting system. Traditional farmer-initiated harvesting operation causes over investment. This study develops a least-cost, time-distributed (staggered) harvesting system for example switch grass, that calls for an effective coordination between farmers, processing plant and a single third-partymore » custom harvester. A linear programming model explicitly accounts for the trade-off between yield loss and benefit of reduced machinery overhead cost, associated with the staggered harvesting system. Total cost of producing and harvesting switch grass will decline by 17.94 percent from conventional non-staggered to proposed staggered harvesting strategy. Harvesting machinery cost alone experiences a significant reduction of 39.68 percent from moving from former to latter. The net return to farmers is estimated to increase by 160.40 percent. Per tonne and per hectare costs of feedstock production will decline by 17.94 percent and 24.78 percent, respectively. These results clearly lend support to the view that the traditional system of single period harvesting calls for over investment on agricultural machinery which escalates the feedstock cost. This social loss to the society in the form of escalated harvesting cost can be avoided if there is a proper coordination among farmers, processing plant and custom harvesters as to when and how biomass crop needs to be planted and harvested. Such an institutional arrangement benefits producers, processing plant and, in turn, end users of biofuels.« less

Application of water footprint combined with a unified virtual crop pattern to evaluate crop water productivity in grain production in China.

PubMed

Wang, Y B; Wu, P T; Engel, B A; Sun, S K

2014-11-01

Water shortages are detrimental to China's grain production while food production consumes a great deal of water causing water crises and ecological impacts. Increasing crop water productivity (CWP) is critical, so China is devoting significant resources to develop water-saving agricultural systems based on crop planning and agricultural water conservation planning. A comprehensive CWP index is necessary for such planning. Existing indices such as water use efficiency (WUE) and irrigation efficiency (IE) have limitations and are not suitable for the comprehensive evaluation of CWP. The water footprint (WF) index, calculated using effective precipitation and local water use, has advantages for CWP evaluation. Due to regional differences in crop patterns making the CWP difficult to compare directly across different regions, a unified virtual crop pattern is needed to calculate the WF. This project calculated and compared the WF of each grain crop and the integrated WFs of grain products with actual and virtual crop patterns in different regions of China for 2010. The results showed that there were significant differences for the WF among different crops in the same area or among different areas for the same crop. Rice had the highest WF at 1.39 m(3)/kg, while corn had the lowest at 0.91 m(3)/kg among the main grain crops. The WF of grain products was 1.25 m(3)/kg in China. Crop patterns had an important impact on WF of grain products because significant differences in WF were found between actual and virtual crop patterns in each region. The CWP level can be determined based on the WF of a virtual crop pattern, thereby helping optimize spatial distribution of crops and develop agricultural water savings to increase CWP. Copyright © 2014 Elsevier B.V. All rights reserved.

Assessment of future crop yield and agricultural sustainable water use in north china plain using multiple crop models

NASA Astrophysics Data System (ADS)

Huang, G.

2016-12-01

Currently, studying crop-water response mechanism has become an important part in the development of new irrigation technology and optimal water allocation in water-scarce regions, which is of great significance to crop growth guidance, sustainable utilization of agricultural water, as well as the sustainable development of regional agriculture. Using multiple crop models(AquaCrop,SWAP,DNDC), this paper presents the results of simulating crop growth and agricultural water consumption of the winter-wheat and maize cropping system in north china plain. These areas are short of water resources, but generates about 23% of grain production for China. By analyzing the crop yields and the water consumption of the traditional flooding irrigation, the paper demonstrates quantitative evaluation of the potential amount of water use that can be reduced by using high-efficient irrigation approaches, such as drip irrigation. To maintain food supply and conserve water resources, the research concludes sustainable irrigation methods for the three provinces for sustainable utilization of agricultural water.

7 CFR 760.817 - Quality losses for 2005, 2006, and 2007 crops.

Code of Federal Regulations, 2010 CFR

2010-01-01

... economic value due to the reduction in quality. (d) Participants may not be compensated under this section... losses of 25 percent or greater of the value that all affected production of the crop would have had if... production based on harvested acres, multiplied by 42 percent of the per unit average market value based on...

7 CFR 760.817 - Quality losses for 2005, 2006, and 2007 crops.

Code of Federal Regulations, 2011 CFR

2011-01-01

... economic value due to the reduction in quality. (d) Participants may not be compensated under this section... losses of 25 percent or greater of the value that all affected production of the crop would have had if... production based on harvested acres, multiplied by 42 percent of the per unit average market value based on...

Regional hybrid broccoli trials provide a means to further breeding efforts of this increasingly important vegetable crop

USDA-ARS?s Scientific Manuscript database

A Coordinated Agricultural Project (CAP) entitled “Establishing an Eastern Broccoli Industry” is funded under the Specialty Crop Research Initiative (SCRI), and a primary component of the project is a system of regional hybrid broccoli trials conducted along the eastern seaboard. Hybrids currently ...

Mapping croplands, cropping patterns, and crop types using MODIS time-series data

NASA Astrophysics Data System (ADS)

Chen, Yaoliang; Lu, Dengsheng; Moran, Emilio; Batistella, Mateus; Dutra, Luciano Vieira; Sanches, Ieda Del'Arco; da Silva, Ramon Felipe Bicudo; Huang, Jingfeng; Luiz, Alfredo José Barreto; de Oliveira, Maria Antonia Falcão

2018-07-01

The importance of mapping regional and global cropland distribution in timely ways has been recognized, but separation of crop types and multiple cropping patterns is challenging due to their spectral similarity. This study developed a new approach to identify crop types (including soy, cotton and maize) and cropping patterns (Soy-Maize, Soy-Cotton, Soy-Pasture, Soy-Fallow, Fallow-Cotton and Single crop) in the state of Mato Grosso, Brazil. The Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) time series data for 2015 and 2016 and field survey data were used in this research. The major steps of this proposed approach include: (1) reconstructing NDVI time series data by removing the cloud-contaminated pixels using the temporal interpolation algorithm, (2) identifying the best periods and developing temporal indices and phenological parameters to distinguish croplands from other land cover types, and (3) developing crop temporal indices to extract cropping patterns using NDVI time-series data and group cropping patterns into crop types. Decision tree classifier was used to map cropping patterns based on these temporal indices. Croplands from Landsat imagery in 2016, cropping pattern samples from field survey in 2016, and the planted area of crop types in 2015 were used for accuracy assessment. Overall accuracies of approximately 90%, 73% and 86%, respectively were obtained for croplands, cropping patterns, and crop types. The adjusted coefficients of determination of total crop, soy, maize, and cotton areas with corresponding statistical areas were 0.94, 0.94, 0.88 and 0.88, respectively. This research indicates that the proposed approach is promising for mapping large-scale croplands, their cropping patterns and crop types.

Tolerance of interseeded annual ryegrass and red clover cover crops to residual herbicides in Mid-Atlantic corn cropping systems

USDA-ARS?s Scientific Manuscript database

In the Mid-Atlantic region, there is increasing interest in the use of relay-cropping strategies to establish cover crops in corn cropping systems. Recent studies have demonstrated the potential to establish annual ryegrass and red clover cover crops at the V5 corn growth stage using a high-clearan...

The California Biomass Crop Adoption Model estimates biofuel feedstock crop production across diverse agro-ecological zones within the state, under different future climates

NASA Astrophysics Data System (ADS)

Kaffka, S.; Jenner, M.; Bucaram, S.; George, N.

2012-12-01

Both regulators and businesses need realistic estimates for the potential production of biomass feedstocks for biofuels and bioproducts. This includes the need to understand how climate change will affect mid-tem and longer-term crop performance and relative advantage. The California Biomass Crop Adoption Model is a partial mathematical programming optimization model that estimates the profit level needed for new crop adoption, and the crop(s) displaced when a biomass feedstock crop is added to the state's diverse set of cropping systems, in diverse regions of the state. Both yield and crop price, as elements of profit, can be varied. Crop adoption is tested against current farmer preferences derived from analysis of 10 years crop production data for all crops produced in California, collected by the California Department of Pesticide Regulation. Analysis of this extensive data set resulted in 45 distinctive, representative farming systems distributed across the state's diverse agro-ecological regions. Estimated yields and water use are derived from field trials combined with crop simulation, reported elsewhere. Crop simulation is carried out under different weather and climate assumptions. Besides crop adoption and displacement, crop resource use is also accounted, derived from partial budgets used for each crop's cost of production. Systematically increasing biofuel crop price identified areas of the state where different types of crops were most likely to be adopted. Oilseed crops like canola that can be used for biodiesel production had the greatest potential to be grown in the Sacramento Valley and other northern regions, while sugar beets (for ethanol) had the greatest potential in the northern San Joaquin Valley region, and sweet sorghum in the southern San Joaquin Valley. Up to approximately 10% of existing annual cropland in California was available for new crop adoption. New crops are adopted if the entire cropping system becomes more profitable. In

Carbon balance of the typical grain crop rotation in Moscow region assessed by eddy covariance method

NASA Astrophysics Data System (ADS)

Meshalkina, Joulia; Yaroslavtsev, Alexis; Vassenev, Ivan

2017-04-01

Croplands could have equal or even greater net ecosystem production than several natural ecosystems (Hollinger et al., 2004), so agriculture plays a substantial role in mitigation strategies for the reduction of carbon dioxide emissions. In Central Russia, where agricultural soils carbon loses are 9 time higher than natural (forest's) soils ones (Stolbovoi, 2002), the reduction of carbon dioxide emissions in agroecosystems must be the central focus of the scientific efforts. Although the balance of the CO2 mostly attributed to management practices, limited information exists regarding the crop rotation overall as potential of C sequestration. In this study, we present data on carbon balance of the typical grain crop rotation in Moscow region followed for 4 years by measuring CO2 fluxes by paired eddy covariance stations (EC). The study was conducted at the Precision Farming Experimental Fields of the Russian Timiryazev State Agricultural University, Moscow, Russia. The experimental site has a temperate and continental climate and situated in south taiga zone with Arable Sod-Podzoluvisols (Albeluvisols Umbric). Two fields of the four-course rotation were studied in 2013-2016. Crop rotation included winter wheat (Triticum sativum L.), barley (Hordeum vulgare L.), potato crop (Solanum tuberosum L.) and cereal-legume mixture (Vicia sativa L. and Avena sativa L.). Crops sowing occurred during the period from mid-April to mid-May depending on weather conditions. Winter wheat was sown in the very beginning of September and the next year it occurred from under the snow in the phase of tillering. White mustard (Sinapis alba) was sown for green manure after harvesting winter wheat in mid of July. Barley was harvested in mid of August, potato crop was harvested in September. Cereal-legume mixture on herbage was collected depending on the weather from early July to mid-August. Carbon uptake (NEE negative values) was registered only for the fields with winter wheat and white

Hydroponic Crop Production using Recycled Nutrients from Inedible Crop Residues

NASA Technical Reports Server (NTRS)

Garland, Jay L.; Mackowiak, Cheryl L.; Sager, John C.

1993-01-01

The coupling of plant growth and waste recycling systems is an important step toward the development of bioregenerative life support systems. This research examined the effectiveness of two alternative methods for recycling nutrients from the inedible fraction (residue) of candidate crops in a bioregenerative system as follows: (1) extraction in water, or leaching, and (2) combustion at 550 C, with subsequent reconstitution of the ash in acid. The effectiveness of the different methods was evaluated by (1) comparing the percent recovery of nutrients, and (2) measuring short- and long-term plant growth in hydroponic solutions, based on recycled nutrients.

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

Embodied crop calories in animal products

NASA Astrophysics Data System (ADS)

Pradhan, Prajal; Lüdeke, Matthias K. B.; Reusser, Dominik E.; Kropp, Jürgen P.

2013-12-01

Increases in animal products consumption and the associated environmental consequences have been a matter of scientific debate for decades. Consequences of such increases include rises in greenhouse gas emissions, growth of consumptive water use, and perturbation of global nutrients cycles. These consequences vary spatially depending on livestock types, their densities and their production system. In this letter, we investigate the spatial distribution of embodied crop calories in animal products. On a global scale, about 40% of the global crop calories are used as livestock feed (we refer to this ratio as crop balance for livestock) and about 4 kcal of crop products are used to generate 1 kcal of animal products (embodied crop calories of around 4). However, these values vary greatly around the world. In some regions, more than 100% of the crops produced is required to feed livestock requiring national or international trade to meet the deficit in livestock feed. Embodied crop calories vary between less than 1 for 20% of the livestock raising areas worldwide and greater than 10 for another 20% of the regions. Low values of embodied crop calories are related to production systems for ruminants based on fodder and forage, while large values are usually associated with production systems for non-ruminants fed on crop products. Additionally, we project the future feed demand considering three scenarios: (a) population growth, (b) population growth and changes in human dietary patterns and (c) changes in population, dietary patterns and feed conversion efficiency. When considering dietary changes, we project the global feed demand to be almost doubled (1.8-2.3 times) by 2050 compared to 2000, which would force us to produce almost equal or even more crops to raise our livestock than to directly nourish ourselves in the future. Feed demand is expected to increase over proportionally in Africa, South-Eastern Asia and Southern Asia, putting additional stress on these

Simulation of temporal and spatial distribution of required irrigation water by crop models and the pan evaporation coefficient method

NASA Astrophysics Data System (ADS)

Yang, Yan-min; Yang, Yonghui; Han, Shu-min; Hu, Yu-kun

2009-07-01

Hebei Plain is the most important agricultural belt in North China. Intensive irrigation, low and uneven precipitation have led to severe water shortage on the plain. This study is an attempt to resolve this crucial issue of water shortage for sustainable agricultural production and water resources management. The paper models distributed regional irrigation requirement for a range of cultivated crops on the plain. Classic crop models like DSSAT- wheat/maize and COTTON2K are used in combination with pan-evaporation coefficient method to estimate water requirements for wheat, corn, cotton, fruit-trees and vegetables. The approach is more accurate than the static approach adopted in previous studies. This is because the combination use of crop models and pan-evaporation coefficient method dynamically accounts for irrigation requirement at different growth stages of crops, agronomic practices, and field and climatic conditions. The simulation results show increasing Required Irrigation Amount (RIA) with time. RIA ranges from 5.08×109 m3 to 14.42×109 m3 for the period 1986~2006, with an annual average of 10.6×109 m3. Percent average water use by wheat, fruit trees, vegetable, corn and cotton is 41%, 12%, 12%, 11%, 7% and 17% respectively. RIA for April and May (the period with the highest irrigation water use) is 1.78×109 m3 and 2.41×109 m3 respectively. The counties in the piedmont regions of Mount Taihang have high RIA while the central and eastern regions/counties have low irrigation requirement.

Crop Species Diversity Changes in the United States: 1978–2012

PubMed Central

Aguilar, Jonathan; Gramig, Greta G.; Hendrickson, John R.; Archer, David W.; Forcella, Frank; Liebig, Mark A.

2015-01-01

Anecdotal accounts regarding reduced US cropping system diversity have raised concerns about negative impacts of increasingly homogeneous cropping systems. However, formal analyses to document such changes are lacking. Using US Agriculture Census data, which are collected every five years, we quantified crop species diversity from 1978 to 2012, for the contiguous US on a county level basis. We used Shannon diversity indices expressed as effective number of crop species (ENCS) to quantify crop diversity. We then evaluated changes in county-level crop diversity both nationally and for each of the eight Farm Resource Regions developed by the National Agriculture Statistics Service. During the 34 years we considered in our analyses, both national and regional ENCS changed. Nationally, crop diversity was lower in 2012 than in 1978. However, our analyses also revealed interesting trends between and within different Resource Regions. Overall, the Heartland Resource Region had the lowest crop diversity whereas the Fruitful Rim and Northern Crescent had the highest. In contrast to the other Resource Regions, the Mississippi Portal had significantly higher crop diversity in 2012 than in 1978. Also, within regions there were differences between counties in crop diversity. Spatial autocorrelation revealed clustering of low and high ENCS and this trend became stronger over time. These results show that, nationally counties have been clustering into areas of either low diversity or high diversity. Moreover, a significant trend of more counties shifting to lower rather than to higher crop diversity was detected. The clustering and shifting demonstrates a trend toward crop diversity loss and attendant homogenization of agricultural production systems, which could have far-reaching consequences for provision of ecosystem system services associated with agricultural systems as well as food system sustainability. PMID:26308552

National Variation in Crop Yield Production Functions

NASA Astrophysics Data System (ADS)

Devineni, N.; Rising, J. A.

2017-12-01

A new multilevel model for yield prediction at the county scale using regional climate covariates is presented in this paper. A new crop specific water deficit index, growing degree days, extreme degree days, and time-trend as an approximation of technology improvements are used as predictors to estimate annual crop yields for each county from 1949 to 2009. Every county in the United States is allowed to have unique parameters describing how these weather predictors are related to yield outcomes. County-specific parameters are further modeled as varying according to climatic characteristics, allowing the prediction of parameters in regions where crops are not currently grown and into the future. The structural relationships between crop yield and regional climate as well as trends are estimated simultaneously. All counties are modeled in a single multilevel model with partial pooling to automatically group and reduce estimation uncertainties. The model captures up to 60% of the variability in crop yields after removing the effect of technology, does well in out of sample predictions and is useful in relating the climate responses to local bioclimatic factors. We apply the predicted growing models in a cost-benefit analysis to identify the most economically productive crop in each county.

Combined use of Landsat-8 and Sentinel-2A images for winter crop mapping and winter wheat yield assessment at regional scale.

PubMed

Skakun, Sergii; Vermote, Eric; Roger, Jean-Claude; Franch, Belen

2017-01-01

Timely and accurate information on crop yield is critical to many applications within agriculture monitoring. Thanks to its coverage and temporal resolution, coarse spatial resolution satellite imagery has always been a source of valuable information for yield forecasting and assessment at national and regional scales. With availability of free images acquired by Landsat-8 and Sentinel-2 remote sensing satellites, it becomes possible to enable temporal resolution of an image every 3-5 days, and therefore, to develop next generation agriculture products at higher spatial resolution (30 m). This paper explores the combined use of Landsat-8 and Sentinel-2A for winter crop mapping and winter wheat assessment at regional scale. For the former, we adapt a previously developed approach for Moderate Resolution Imaging Spectroradiometer (MODIS) at 250 m resolution that allows automatic mapping of winter crops taking into account knowledge on crop calendar and without ground truth data. For the latter, we use a generalized winter wheat yield model that is based on NDVI-peak estimation and MODIS data, and further downscaled to be applicable at 30 m resolution. We show that integration of Landsat-8 and Sentinel-2A has a positive impact both for winter crop mapping and winter wheat yield assessment. In particular, the error of winter wheat yield estimates can be reduced up to 1.8 times comparing to the single satellite usage.

The virtual water content of major grain crops and virtual water flows between regions in China.

PubMed

Sun, Shi-Kun; Wu, Pu-Te; Wang, Yu-Bao; Zhao, Xi-Ning

2013-04-01

The disproportionate distribution of arable land and water resources has become a bottleneck for guaranteeing food security in China. Virtual water and virtual water trade theory have provided a potential solution to improve water resources management in agriculture and alleviate water crises in water-scarce regions. The present study evaluates the green and blue virtual water content of wheat, maize and rice at the regional scale in China. It then assesses the water-saving benefits of virtual water flows related to the transfer of the three crops between regions. The national average virtual water content of wheat, maize and rice were 1071 m(3) per ton (50.98% green water, 49.02% blue water ), 830 m(3) per ton (76.27% green water, 23.73% blue water) and 1294 m(3) per ton (61.90% green water, 38.10% blue water), respectively. With the regional transfer of wheat, maize and rice, virtual water flows reached 30.08 Gm(3) (59.91% green water, 40.09% blue water). Meanwhile, China saved 11.47 Gm(3) green water, while it consumed 7.84 Gm(3) more blue water than with a no-grain transfer scenario in 2009. In order to guarantee food security in China, the government should improve water productivity (reduce virtual water content of crops) during the grain production process. Meanwhile, under the preconditions of economic feasibility and land-water resources availability, China should guarantee the grain-sown area in southern regions for taking full advantage of green water resources and to alleviate the pressure on water resources. © 2012 Society of Chemical Industry.

Globally Increased Crop Growth and Cropping Intensity from the Long-Term Satellite-Based Observations

NASA Astrophysics Data System (ADS)

Chen, Bin

2018-04-01

Understanding the spatiotemporal change trend of global crop growth and multiple cropping system under climate change scenarios is a critical requirement for supporting the food security issue that maintains the function of human society. Many studies have predicted the effects of climate changes on crop production using a combination of filed studies and models, but there has been limited evidence relating decadal-scale climate change to global crop growth and the spatiotemporal distribution of multiple cropping system. Using long-term satellite-derived Normalized Difference Vegetation Index (NDVI) and observed climate data from 1982 to 2012, we investigated the crop growth trend, spatiotemporal pattern trend of agricultural cropping intensity, and their potential correlations with respect to the climate change drivers at a global scale. Results show that 82.97 % of global cropland maximum NDVI witnesses an increased trend while 17.03 % of that shows a decreased trend over the past three decades. The spatial distribution of multiple cropping system is observed to expand from lower latitude to higher latitude, and the increased cropping intensity is also witnessed globally. In terms of regional major crop zones, results show that all nine selected zones have an obvious upward trend of crop maximum NDVI (p < 0.001), and as for climatic drivers, the gradual temperature and precipitation changes have had a measurable impact on the crop growth trend.

7 CFR 457.106 - Texas citrus tree crop insurance provisions.

Code of Federal Regulations, 2010 CFR

2010-01-01

... proper times. Root stock—A root or a piece of a root of one tree variety onto which a bud from another... will be increased by 46 percent as a result of the additional six months of coverage for that crop year...

An evaluation of 10 percent and 20 percent benzocaine gels in patients with acute toothaches

PubMed Central

Hersh, Elliot V.; Ciancio, Sebastian G.; Kuperstein, Arthur S.; Stoopler, Eric T.; Moore, Paul A.; Boynes, Sean G.; Levine, Steven C.; Casamassimo, Paul; Leyva, Rina; Mathew, Tanya; Shibly, Othman; Creighton, Paul; Jeffers, Gary E.; Corby, Patricia M.A.; Turetzky, Stanley N.; Papas, Athena; Wallen, Jillian; Idzik-Starr, Cynthia; Gordon, Sharon M.

2013-01-01

Background The authors evaluated the efficacy and tolerability of 10 percent and 20 percent benzocaine gels compared with those of a vehicle (placebo) gel for the temporary relief of toothache pain. They also assessed the compliance with the label dose administration directions on the part of participants with toothache pain. Methods Under double-masked conditions, 576 participants self-applied study gel to an open tooth cavity and surrounding oral tissues. Participants evaluated their pain intensity and pain relief for 120 minutes. The authors determined the amount of gel the participants applied. Results The responders’ rates (the primary efficacy parameter), defined as the percentage of participants who had an improvement in pain intensity as exhibited by a pain score reduction of at least one unit on the dental pain scale from baseline for two consecutive assessments any time between the five- and 20-minute points, were 87.3 percent, 80.7 percent and 70.4 percent, respectively, for 20 percent benzocaine gel, 10 percent benzocaine gel and vehicle gel. Both benzocaine gels were significantly (P ≤ .05) better than vehicle gel; the 20 percent benzocaine gel also was significantly (P ≤ .05) better than the 10 percent benzocaine gel. The mean amount of gel applied was 235.6 milligrams, with 88.2 percent of participants applying 400 mg or less. Conclusions Both 10 percent and 20 percent benzocaine gels were more efficacious than the vehicle gel, and the 20 percent benzocaine gel was more efficacious than the 10 percent benzocaine gel. All treatments were well tolerated by participants. Practical Implications Patients can use 10 percent and 20 percent benzocaine gels to temporarily treat toothache pain safely. PMID:23633700

Economic evaluation of crop acreage estimation by multispectral remote sensing. [Michigan

NASA Technical Reports Server (NTRS)

Manderscheid, L. V.; Nalepka, R. F. (Principal Investigator); Myers, W.; Safir, G.; Ilhardt, D.; Morgenstern, J. P.; Sarno, J.

1976-01-01

The author has identified the following significant results. Photointerpretation of S190A and S190B imagery showed significantly better resolution with the S190B system. A small tendancy to underestimate acreage was observed. This averaged 6 percent and varied with field size. The S190B system had adequate resolution for acreage measurement but the color film did not provide adequate contrast to allow detailed classification of ground cover from imagery of a single date. In total 78 percent of the fields were correctly classified but with 56 percent correct for the major crop, corn.

The Impact of Insects on Second-Year Cone Crops in Red Pine Seed-Production Areas

Treesearch

William J. Mattson

1968-01-01

Second-year cone crops in red pine seed-production areas have been severely damaged by five species of insects. Control of the two most destructive pests could increase present seed yields in most areas by at least 50 percent. Some seed-production areas may not produce harvestable seed crops until cone-insect populations are suppressed.

Drought mitigation in perennial crops by fertilization and adjustments of regional yield models for future climate variability

NASA Astrophysics Data System (ADS)

Kantola, I. B.; Blanc-Betes, E.; Gomez-Casanovas, N.; Masters, M. D.; Bernacchi, C.; DeLucia, E. H.

2017-12-01

Increased variability and intensity of precipitation in the Midwest agricultural belt due to climate change is a major concern. The success of perennial bioenergy crops in replacing maize for bioethanol production is dependent on sustained yields that exceed maize, and the marketing of perennial crops often emphasizes the resilience of perennial agriculture to climate stressors. Land conversion from maize for bioethanol to Miscanthus x giganteus (miscanthus) increases yields and annual evapotranspiration rates (ET). However, establishment of miscanthus also increases biome water use efficiency (the ratio between net ecosystem productivity after harvest and ET), due to greater belowground biomass in miscanthus than in maize or soybean. In 2012, a widespread drought reduced the yield of 5-year-old miscanthus plots in central Illinois by 36% compared to the previous two years. Eddy covariance data indicated continued soil water deficit during the hydrologically-normal growing season in 2013 and miscanthus yield failed to rebound as expected, lagging behind pre-drought yields by an average of 53% over the next three years. In early 2014, nitrogen fertilizer was applied to half of mature (7-year-old) miscanthus plots in an effort to improve yields. In plots with annual post-emergence application of 60 kg ha-1 of urea, peak biomass was 29% greater than unfertilized miscanthus in 2014, and 113% greater in 2015, achieving statistically similar yields to the pre-drought average. Regional-scale models of perennial crop productivity use 30-year climate averages that are inadequate for predicting long-term effects of short-term extremes on perennial crops. Modeled predictions of perennial crop productivity incorporating repeated extreme weather events, observed crop response, and the use of management practices to mitigate water deficit demonstrate divergent effects on predicted yields.

Smoking Behavior and the Tobacco Crop.

ERIC Educational Resources Information Center

Wilson, Richard W.; Higgins, C. Wayne

1984-01-01

The influence of the physical and economic presence of tobacco crops on smoking behavior and related attitudes of students in tobacco-raising regions was measured by a Tobacco Crop Intensity variable. Implications for government agricultural and educational policy are discussed. (Author/DF)

An automated multi-model based evapotranspiration estimation framework for understanding crop-climate interactions in India

NASA Astrophysics Data System (ADS)

Bhattarai, N.; Jain, M.; Mallick, K.

2017-12-01

A remote sensing based multi-model evapotranspiration (ET) estimation framework is developed using MODIS and NASA Merra-2 reanalysis data for data poor regions, and we apply this framework to the Indian subcontinent. The framework eliminates the need for in-situ calibration data and hence estimates ET completely from space and is replicable across all regions in the world. Currently, six surface energy balance models ranging from widely-used SEBAL, METRIC, and SEBS to moderately-used S-SEBI, SSEBop, and a relatively new model, STIC1.2 are being integrated and validated. Preliminary analysis suggests good predictability of the models for estimating near- real time ET under clear sky conditions from various crop types in India with coefficient of determination 0.32-0.55 and percent bias -15%-28%, when compared against Bowen Ratio based ET estimates. The results are particularly encouraging given that no direct ground input data were used in the analysis. The framework is currently being extended to estimate seasonal ET across the Indian subcontinent using a model-ensemble approach that uses all available MODIS 8-day datasets since 2000. These ET products are being used to monitor inter-seasonal and inter-annual dynamics of ET and crop water use across different crop and irrigation practices in India. Particularly, the potential impacts of changes in precipitation patterns and extreme heat (e.g., extreme degree days) on seasonal crop water consumption is being studied. Our ET products are able to locate the water stress hotspots that need to be targeted with water saving interventions to maintain agricultural production in the face of climate variability and change.

Probabilistic graphlet transfer for photo cropping.

PubMed

Zhang, Luming; Song, Mingli; Zhao, Qi; Liu, Xiao; Bu, Jiajun; Chen, Chun

2013-02-01

As one of the most basic photo manipulation processes, photo cropping is widely used in the printing, graphic design, and photography industries. In this paper, we introduce graphlets (i.e., small connected subgraphs) to represent a photo's aesthetic features, and propose a probabilistic model to transfer aesthetic features from the training photo onto the cropped photo. In particular, by segmenting each photo into a set of regions, we construct a region adjacency graph (RAG) to represent the global aesthetic feature of each photo. Graphlets are then extracted from the RAGs, and these graphlets capture the local aesthetic features of the photos. Finally, we cast photo cropping as a candidate-searching procedure on the basis of a probabilistic model, and infer the parameters of the cropped photos using Gibbs sampling. The proposed method is fully automatic. Subjective evaluations have shown that it is preferred over a number of existing approaches.

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

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

Lobell, D; Field, C; Cahill, K

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 multiplemore » 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.« less

Water footprint of crop production for different crop structures in the Hebei southern plain, North China

NASA Astrophysics Data System (ADS)

Chu, Yingmin; Shen, Yanjun; Yuan, Zaijian

2017-06-01

The North China Plain (NCP) has a serious shortage of freshwater resources, and crop production consumes approximately 75 % of the region's water. To estimate water consumption of different crops and crop structures in the NCP, the Hebei southern plain (HSP) was selected as a study area, as it is a typical region of groundwater overdraft in the NCP. In this study, the water footprint (WF) of crop production, comprised of green, blue and grey water footprints, and its annual variation were analyzed. The results demonstrated the following: (1) the WF from the production of main crops was 41.8 km3 in 2012. Winter wheat, summer maize and vegetables were the top water-consuming crops in the HSP. The water footprint intensity (WFI) of cotton was the largest, and for vegetables, it was the smallest; (2) the total WF, WFblue, WFgreen and WFgrey for 13 years (2000-2012) of crop production were 604.8, 288.5, 141.3 and 175.0 km3, respectively, with an annual downtrend from 2000 to 2012; (3) winter wheat, summer maize and vegetables consumed the most groundwater, and their blue water footprint (WFblue) accounted for 74.2 % of the total WFblue in the HSP; (4) the crop structure scenarios analysis indicated that, with approximately 20 % of arable land cultivated with winter wheat-summer maize in rotation, 38.99 % spring maize, 10 % vegetables and 10 % fruiters, a sustainable utilization of groundwater resources can be promoted, and a sufficient supply of food, including vegetables and fruits, can be ensured in the HSP.

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

PubMed

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

2016-05-01

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

Combined use of Landsat-8 and Sentinel-2A images for winter crop mapping and winter wheat yield assessment at regional scale

PubMed Central

Skakun, Sergii; Vermote, Eric; Roger, Jean-Claude; Franch, Belen

2018-01-01

Timely and accurate information on crop yield is critical to many applications within agriculture monitoring. Thanks to its coverage and temporal resolution, coarse spatial resolution satellite imagery has always been a source of valuable information for yield forecasting and assessment at national and regional scales. With availability of free images acquired by Landsat-8 and Sentinel-2 remote sensing satellites, it becomes possible to enable temporal resolution of an image every 3–5 days, and therefore, to develop next generation agriculture products at higher spatial resolution (30 m). This paper explores the combined use of Landsat-8 and Sentinel-2A for winter crop mapping and winter wheat assessment at regional scale. For the former, we adapt a previously developed approach for Moderate Resolution Imaging Spectroradiometer (MODIS) at 250 m resolution that allows automatic mapping of winter crops taking into account knowledge on crop calendar and without ground truth data. For the latter, we use a generalized winter wheat yield model that is based on NDVI-peak estimation and MODIS data, and further downscaled to be applicable at 30 m resolution. We show that integration of Landsat-8 and Sentinel-2A has a positive impact both for winter crop mapping and winter wheat yield assessment. In particular, the error of winter wheat yield estimates can be reduced up to 1.8 times comparing to the single satellite usage. PMID:29888751

Combined Use of Landsat-8 and Sentinel-2A Images for Winter Crop Mapping and Winter Wheat Yield Assessment at Regional Scale

NASA Technical Reports Server (NTRS)

Skakun, Sergii; Vermote, Eric; Roger, Jean-Claude; Franch, Belen

2017-01-01

Timely and accurate information on crop yield and production is critical to many applications within agriculture monitoring. Thanks to its coverage and temporal resolution, coarse spatial resolution satellite imagery has always been a source of valuable information for yield forecasting and assessment at national and regional scales. With availability of free images acquired by Landsat-8 and Sentinel-2 remote sensing satellites, it becomes possible to provide temporal resolution of an image every 3-5 days, and therefore, to develop next generation agriculture products at higher spatial resolution (10-30 m). This paper explores the combined use of Landsat-8 and Sentinel-2A for winter crop mapping and winter wheat yield assessment at regional scale. For the former, we adapt a previously developed approach for the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument at 250 m resolution that allows automatic mapping of winter crops taking into account a priori knowledge on crop calendar. For the latter, we use a generalized winter wheat yield forecasting model that is based on estimation of the peak Normalized Difference Vegetation Index (NDVI) from MODIS image time-series, and further downscaled to be applicable at 30 m resolution. We show that integration of Landsat-8 and Sentinel-2A improves both winter crop mapping and winter wheat yield assessment. In particular, the error of winter wheat yield estimates can be reduced up to 1.8 times compared to using a single satellite.

A methodological approach for deriving regional crop rotations as basis for the assessment of the impact of agricultural strategies using soil erosion as example.

PubMed

Lorenz, Marco; Fürst, Christine; Thiel, Enrico

2013-09-01

Regarding increasing pressures by global societal and climate change, the assessment of the impact of land use and land management practices on land degradation and the related decrease in sustainable provision of ecosystem services gains increasing interest. Existing approaches to assess agricultural practices focus on the assessment of single crops or statistical data because spatially explicit information on practically applied crop rotations is mostly not available. This provokes considerable uncertainties in crop production models as regional specifics have to be neglected or cannot be considered in an appropriate way. In a case study in Saxony, we developed an approach to (i) derive representative regional crop rotations by combining different data sources and expert knowledge. This includes the integration of innovative crop sequences related to bio-energy production or organic farming and different soil tillage, soil management and soil protection techniques. Furthermore, (ii) we developed a regionalization approach for transferring crop rotations and related soil management strategies on the basis of statistical data and spatially explicit data taken from so called field blocks. These field blocks are the smallest spatial entity for which agricultural practices must be reported to apply for agricultural funding within the frame of the European Agricultural Fund for Rural Development (EAFRD) program. The information was finally integrated into the spatial decision support tool GISCAME to assess and visualize in spatially explicit manner the impact of alternative agricultural land use strategies on soil erosion risk and ecosystem services provision. Objective of this paper is to present the approach how to create spatially explicit information on agricultural management practices for a study area around Dresden, the capital of the German Federal State Saxony. Copyright © 2013 Elsevier Ltd. All rights reserved.

Food Crops Response to Climate Change

NASA Astrophysics Data System (ADS)

Butler, E.; Huybers, P.

2009-12-01

Projections of future climate show a warming world and heterogeneous changes in precipitation. Generally, warming temperatures indicate a decrease in crop yields where they are currently grown. However, warmer climate will also open up new areas at high latitudes for crop production. Thus, there is a question whether the warmer climate with decreased yields but potentially increased growing area will produce a net increase or decrease of overall food crop production. We explore this question through a multiple linear regression model linking temperature and precipitation to crop yield. Prior studies have emphasised temporal regression which indicate uniformly decreased yields, but neglect the potentially increased area opened up for crop production. This study provides a compliment to the prior work by exploring this spatial variation. We explore this subject with a multiple linear regression model from temperature, precipitation and crop yield data over the United States. The United States was chosen as the training region for the model because there are good crop data available over the same time frame as climate data and presumably the yield from crops in the United States is optimized with respect to potential yield. We study corn, soybeans, sorghum, hard red winter wheat and soft red winter wheat using monthly averages of temperature and precipitation from NCEP reanalysis and yearly yield data from the National Agriculture Statistics Service for 1948-2008. The use of monthly averaged temperature and precipitation, which neglect extreme events that can have a significant impact on crops limits this study as does the exclusive use of United States agricultural data. The GFDL 2.1 model under a 720ppm CO2 scenario provides temperature and precipitation fields for 2040-2100 which are used to explore how the spatial regions available for crop production will change under these new conditions.

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;

A regional scale modeling framework combining biogeochemical model with life cycle and economic analysis for integrated assessment of cropping systems.

PubMed

Tabatabaie, Seyed Mohammad Hossein; Bolte, John P; Murthy, Ganti S

2018-06-01

The goal of this study was to integrate a crop model, DNDC (DeNitrification-DeComposition), with life cycle assessment (LCA) and economic analysis models using a GIS-based integrated platform, ENVISION. The integrated model enables LCA practitioners to conduct integrated economic analysis and LCA on a regional scale while capturing the variability of soil emissions due to variation in regional factors during production of crops and biofuel feedstocks. In order to evaluate the integrated model, the corn-soybean cropping system in Eagle Creek Watershed, Indiana was studied and the integrated model was used to first model the soil emissions and then conduct the LCA as well as economic analysis. The results showed that the variation in soil emissions due to variation in weather is high causing some locations to be carbon sink in some years and source of CO 2 in other years. In order to test the model under different scenarios, two tillage scenarios were defined: 1) conventional tillage (CT) and 2) no tillage (NT) and analyzed with the model. The overall GHG emissions for the corn-soybean cropping system was simulated and results showed that the NT scenario resulted in lower soil GHG emissions compared to CT scenario. Moreover, global warming potential (GWP) of corn ethanol from well to pump varied between 57 and 92gCO 2 -eq./MJ while GWP under the NT system was lower than that of the CT system. The cost break-even point was calculated as $3612.5/ha in a two year corn-soybean cropping system and the results showed that under low and medium prices for corn and soybean most of the farms did not meet the break-even point. Copyright © 2017 Elsevier B.V. All rights reserved.

Tracing organic and inorganic pollution sources of agricultural crops and water resources in Güzelhisar Basin of the Aegean Region - Turkey

NASA Astrophysics Data System (ADS)

Czarnecki, Sezin; Colak Esetlili, Bihter; Esetlili, Tolga; Tepecik, Mahmut; Anac, Dilek; Düring, Rolf-Alexander

2014-05-01

The study area Güzelhisar Basin is 6 km far from the city Aliaga, Aegean Region in Turkey which represents a rather industrialized area having five large iron and steel factories, but also areas of agriculture. Steel industry in Aliaga is causing metal pollution. Around Güzelhisar Basin and nearby, the dominant crop fields are cotton, maize, vegetables, olive trees and vineyards. Güzelhisar stream and dam water is used for irrigation of the agricultural land. Due to contamination from metal industry in Aliaga, organic farming is not allowed in this region. Industrial activities in the region present a threat on sustainable agriculture. The region is a multi-impacted area in terms of several pollutant sources affecting soil and water quality. The overall objective of the project is to trace back plant nutrients (N, P, K, Ca, Mg, Na, Fe, Mn, Zn, Cu, and B), hazardous substances (i. e. persistent organic pollutants), radionuclides (40K, 232Th, 226Ra/238U), and metal contents (As, Cd, Cr, Co, Cu, Hg, Mn, Ni, Pb, and Zn) by examining the soils, agricultural crops and natural plants from Güzelhisar Basin and water and sediments from Güzelhisar stream and dam. Spatial distribution of pollution will be evaluated by regionalization methods. For this, an advanced analytical methodology will be applied which provides an understanding of sources and occurrence of the respective substances of concern. An innovative multi-tracer approach comprising organic and inorganic marker substances, will identify and quantitatively assess sources and their impact on water pollution and the pollutant pathways in this agricultural crop production system.

Investment risk in bioenergy crops

DOE PAGES

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

2015-11-18

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

Investment risk in bioenergy crops

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

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

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

Noah-MP-Crop: Enhancing cropland representation in the community land surface modeling system

NASA Astrophysics Data System (ADS)

Liu, X.; Chen, F.; Barlage, M. J.; Zhou, G.; Niyogi, D.

2015-12-01

Croplands are important in land-atmosphere interactions and in modifying local and regional weather and climate. Despite their importance, croplands are poorly represented in the current version of the coupled Weather Research and Forecasting (WRF)/ Noah land-surface modeling system, resulting in significant surface temperature and humidity biases across agriculture- dominated regions of the United States. This study aims to improve the WRF weather forecasting and regional climate simulations during the crop growing season by enhancing the representation of cropland in the Noah-MP land model. We introduced dynamic crop growth parameterization into Noah-MP and evaluated the enhanced model (Noah-MP-Crop) at both the field and regional scales with multiple crop biomass datasets, surface fluxes and soil moisture/temperature observations. We also integrated a detailed cropland cover map into WRF, enabling the model to simulate corn and soybean field across the U.S. Great Plains. Results show marked improvement in the Noah-MP-Crop performance in simulating leaf area index (LAI), crop biomass, soil temperature, and surface fluxes. Enhanced cropland representation is not only crucial for improving weather forecasting but can also help assess potential impacts of weather variability on regional hydrometeorology and crop yields. In addition to its applications to WRF, Noah-MP-Crop can be applied in high-spatial-resolution regional crop yield modeling and drought assessments

Development of a Distributed Parallel Computing Framework to Facilitate Regional/Global Gridded Crop Modeling with Various Scenarios

NASA Astrophysics Data System (ADS)

Jang, W.; Engda, T. A.; Neff, J. C.; Herrick, J.

2017-12-01

Many crop models are increasingly used to evaluate crop yields at regional and global scales. However, implementation of these models across large areas using fine-scale grids is limited by computational time requirements. In order to facilitate global gridded crop modeling with various scenarios (i.e., different crop, management schedule, fertilizer, and irrigation) using the Environmental Policy Integrated Climate (EPIC) model, we developed a distributed parallel computing framework in Python. Our local desktop with 14 cores (28 threads) was used to test the distributed parallel computing framework in Iringa, Tanzania which has 406,839 grid cells. High-resolution soil data, SoilGrids (250 x 250 m), and climate data, AgMERRA (0.25 x 0.25 deg) were also used as input data for the gridded EPIC model. The framework includes a master file for parallel computing, input database, input data formatters, EPIC model execution, and output analyzers. Through the master file for parallel computing, the user-defined number of threads of CPU divides the EPIC simulation into jobs. Then, Using EPIC input data formatters, the raw database is formatted for EPIC input data and the formatted data moves into EPIC simulation jobs. Then, 28 EPIC jobs run simultaneously and only interesting results files are parsed and moved into output analyzers. We applied various scenarios with seven different slopes and twenty-four fertilizer ranges. Parallelized input generators create different scenarios as a list for distributed parallel computing. After all simulations are completed, parallelized output analyzers are used to analyze all outputs according to the different scenarios. This saves significant computing time and resources, making it possible to conduct gridded modeling at regional to global scales with high-resolution data. For example, serial processing for the Iringa test case would require 113 hours, while using the framework developed in this study requires only approximately 6

Adverse weather impacts on arable cropping systems

NASA Astrophysics Data System (ADS)

Gobin, Anne

2016-04-01

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

Water Stress & Biomass Monitoring and SWAP Modeling of Irrigated Crops in Saratov Region of Russia

NASA Astrophysics Data System (ADS)

Zeyliger, Anatoly; Ermolaeva, Olga

2016-04-01

results of analyzing water stress during growing season of 2012 and yielded biomass of crops three types of crops alfalfa, corn and soya irrigated by sprinkling machines at left bank of Volga River at Saratov Region of Russia are presented and analyzed. For that a combination of data received from satellite, local meteorological station and farmers as well as SWAP model was used. Analyze of data sets of monitored water deficit of each crop averaged for irrigation period was done by linear regression with yielded biomass values. Following analyze of effectiveness of irrigation water application was done by SWAP agrohydrological model.

Crop yield response to climate change varies with crop spatial distribution pattern

DOE PAGES

Leng, Guoyong; Huang, Maoyi

2017-05-03

The linkage between crop yield and climate variability has been confirmed in numerous studies using statistical approaches. A crucial assumption in these studies is that crop spatial distribution pattern is constant over time. Here, we explore how changes in county-level corn spatial distribution pattern modulate the response of its yields to climate change at the state level over the Contiguous United States. Our results show that corn yield response to climate change varies with crop spatial distribution pattern, with distinct impacts on the magnitude and even the direction at the state level. Corn yield is predicted to decrease by 20~40%more » by 2050s when considering crop spatial distribution pattern changes, which is 6~12% less than the estimates with fixed cropping pattern. The beneficial effects are mainly achieved by reducing the negative impacts of daily maximum temperature and strengthening the positive impacts of precipitation. Our results indicate that previous empirical studies could be biased in assessing climate change impacts by ignoring the changes in crop spatial distribution pattern. As a result, this has great implications for understanding the increasing debates on whether climate change will be a net gain or loss for regional agriculture.« less

Crop yield response to climate change varies with crop spatial distribution pattern

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

Leng, Guoyong; Huang, Maoyi

The linkage between crop yield and climate variability has been confirmed in numerous studies using statistical approaches. A crucial assumption in these studies is that crop spatial distribution pattern is constant over time. Here, we explore how changes in county-level corn spatial distribution pattern modulate the response of its yields to climate change at the state level over the Contiguous United States. Our results show that corn yield response to climate change varies with crop spatial distribution pattern, with distinct impacts on the magnitude and even the direction at the state level. Corn yield is predicted to decrease by 20~40%more » by 2050s when considering crop spatial distribution pattern changes, which is 6~12% less than the estimates with fixed cropping pattern. The beneficial effects are mainly achieved by reducing the negative impacts of daily maximum temperature and strengthening the positive impacts of precipitation. Our results indicate that previous empirical studies could be biased in assessing climate change impacts by ignoring the changes in crop spatial distribution pattern. As a result, this has great implications for understanding the increasing debates on whether climate change will be a net gain or loss for regional agriculture.« less

Lost crops of the Incas: Origins of domestication of the Andean pulse crop tarwi, Lupinus mutabilis.

PubMed

Atchison, Guy W; Nevado, Bruno; Eastwood, Ruth J; Contreras-Ortiz, Natalia; Reynel, Carlos; Madriñán, Santiago; Filatov, Dmitry A; Hughes, Colin E

2016-09-01

The Andean highlands are a hotspot of domestication, yet our understanding of the origins of early Andean agriculture remains fragmentary. Key questions of where, when, how many times, and from what progenitors many Andean crops were domesticated remain unanswered. The Andean lupine crop tarwi (Lupinus mutabilis) is a regionally important pulse crop with exceptionally high seed protein and oil content and is the focus of modern breeding efforts, but its origins remain obscure. A large genome-wide DNA polymorphism data set was generated using nextRADseq to infer relationships among more than 200 accessions of Andean Lupinus species, including 24 accessions of L. mutabilis and close relatives. Phylogenetic and demographic analyses were used to identify the likely progenitor of tarwi and elucidate the area and timing of domestication in combination with archaeological evidence. We infer that tarwi was domesticated once in northern Peru, most likely in the Cajamarca region within, or adjacent to the extant distribution of L. piurensis, which is the most likely wild progenitor. Demographic analyses suggest that tarwi split from L. piurensis around 2600 BP and suffered a classical domestication bottleneck. The earliest unequivocal archaeological evidence of domesticated tarwi seeds is from the Mantaro Valley, central Peru ca. 1800 BP. A single origin of tarwi from L. piurensis in northern Peru provides a robust working hypothesis for the domestication of this regionally important crop and is one of the first clear-cut examples of a crop originating in the highlands of northern Peru. © 2016 Botanical Society of America.

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

Integrating future scenario‐based crop expansion and crop conditions to map switchgrass biofuel potential in eastern Nebraska, USA

USGS Publications Warehouse

Gu, Yingxin; Wylie, Bruce K.

2018-01-01

Switchgrass (Panicum virgatum) has been evaluated as one potential source for cellulosic biofuel feedstocks. Planting switchgrass in marginal croplands and waterway buffers can reduce soil erosion, improve water quality, and improve regional ecosystem services (i.e. it serves as a potential carbon sink). In previous studies, we mapped high risk marginal croplands and highly erodible cropland buffers that are potentially suitable for switchgrass development, which would improve ecosystem services and minimally impact food production. In this study, we advance our previous study results and integrate future crop expansion information to develop a switchgrass biofuel potential ensemble map for current and future croplands in eastern Nebraska. The switchgrass biomass productivity and carbon benefits (i.e. NEP: net ecosystem production) for the identified biofuel potential ensemble areas were quantified. The future scenario‐based (‘A1B’) land use and land cover map for 2050, the US Geological Survey crop type and Compound Topographic Index (CTI) maps, and long‐term (1981–2010) averaged annual precipitation data were used to identify future crop expansion regions that are suitable for switchgrass development. Results show that 2528 km2 of future crop expansion regions (~3.6% of the study area) are potentially suitable for switchgrass development. The total estimated biofuel potential ensemble area (including cropland buffers, marginal croplands, and future crop expansion regions) is 4232 km2 (~6% of the study area), potentially producing 3.52 million metric tons of switchgrass biomass per year. Converting biofuel ensemble regions to switchgrass leads to potential carbon sinks (the total NEP for biofuel potential areas is 0.45 million metric tons C) and is environmentally sustainable. Results from this study improve our understanding of environmental conditions and ecosystem services of current and future cropland systems in eastern Nebraska and provide

Origins of food crops connect countries worldwide.

USDA-ARS?s Scientific Manuscript database

Crop genetic diversity is concentrated within specific geographic regions worldwide. While access to this diversity is critical to continued increases in agricultural productivity, the geopolitical significance of the geography of crop diversity has not been quantified. We assess the degree to which...

Prioritizing Crop Management to Increase Nitrogen Use Efficiency in Australian Sugarcane Crops.

PubMed

Thorburn, Peter J; Biggs, Jody S; Palmer, Jeda; Meier, Elizabeth A; Verburg, Kirsten; Skocaj, Danielle M

2017-01-01

Sugarcane production relies on the application of large amounts of nitrogen (N) fertilizer. However, application of N in excess of crop needs can lead to loss of N to the environment, which can negatively impact ecosystems. This is of particular concern in Australia where the majority of sugarcane is grown within catchments that drain directly into the World Heritage listed Great Barrier Reef Marine Park. Multiple factors that impact crop yield and N inputs of sugarcane production systems can affect N use efficiency (NUE), yet the efficacy many of these factors have not been examined in detail. We undertook an extensive simulation analysis of NUE in Australian sugarcane production systems to investigate (1) the impacts of climate on factors determining NUE, (2) the range and drivers of NUE, and (3) regional variation in sugarcane N requirements. We found that the interactions between climate, soils, and management produced a wide range of simulated NUE, ranging from ∼0.3 Mg cane (kg N) -1 , where yields were low (i.e., <50 Mg ha -1 ) and N inputs were high, to >5 Mg cane (kg N) -1 in plant crops where yields were high and N inputs low. Of the management practices simulated (N fertilizer rate, timing, and splitting; fallow management; tillage intensity; and in-field traffic management), the only practice that significantly influenced NUE in ratoon crops was N fertilizer application rate. N rate also influenced NUE in plant crops together with the management of the preceding fallow. In addition, there is regional variation in N fertilizer requirement that could make N fertilizer recommendations more specific. While our results show that complex interrelationships exist between climate, crop growth, N fertilizer rates and N losses to the environment, they highlight the priority that should be placed on optimizing N application rate and fallow management to improve NUE in Australian sugarcane production systems. New initiatives in seasonal climate forecasting

Prioritizing Crop Management to Increase Nitrogen Use Efficiency in Australian Sugarcane Crops

PubMed Central

Thorburn, Peter J.; Biggs, Jody S.; Palmer, Jeda; Meier, Elizabeth A.; Verburg, Kirsten; Skocaj, Danielle M.

2017-01-01

Sugarcane production relies on the application of large amounts of nitrogen (N) fertilizer. However, application of N in excess of crop needs can lead to loss of N to the environment, which can negatively impact ecosystems. This is of particular concern in Australia where the majority of sugarcane is grown within catchments that drain directly into the World Heritage listed Great Barrier Reef Marine Park. Multiple factors that impact crop yield and N inputs of sugarcane production systems can affect N use efficiency (NUE), yet the efficacy many of these factors have not been examined in detail. We undertook an extensive simulation analysis of NUE in Australian sugarcane production systems to investigate (1) the impacts of climate on factors determining NUE, (2) the range and drivers of NUE, and (3) regional variation in sugarcane N requirements. We found that the interactions between climate, soils, and management produced a wide range of simulated NUE, ranging from ∼0.3 Mg cane (kg N)-1, where yields were low (i.e., <50 Mg ha-1) and N inputs were high, to >5 Mg cane (kg N)-1 in plant crops where yields were high and N inputs low. Of the management practices simulated (N fertilizer rate, timing, and splitting; fallow management; tillage intensity; and in-field traffic management), the only practice that significantly influenced NUE in ratoon crops was N fertilizer application rate. N rate also influenced NUE in plant crops together with the management of the preceding fallow. In addition, there is regional variation in N fertilizer requirement that could make N fertilizer recommendations more specific. While our results show that complex interrelationships exist between climate, crop growth, N fertilizer rates and N losses to the environment, they highlight the priority that should be placed on optimizing N application rate and fallow management to improve NUE in Australian sugarcane production systems. New initiatives in seasonal climate forecasting, decisions

Selected fretting-wear-resistant coatings for titanium - 6-percent-aluminum - 4-percent-vanadium alloy

NASA Technical Reports Server (NTRS)

Bill, R. C.

1976-01-01

A titanium - 6-percent-aluminum - 4-percent-vanadium alloy (Ti-6Al-4V) was subjected to fretting-wear exposures against uncoated Ti-6Al-4V as a baseline and against various coatings and surface treatments applied to Ti-6Al-4V. The coatings evaluated included plasma-sprayed tungsten carbide with 12 percent cobalt, aluminum oxide with 13 percent titanium oxide, chromium oxide, and aluminum bronze with 10 percent aromatic polyester; polymer-bonded polyimide, polyimide with graphite fluoride, polyimide with molybdenum disulfide (MoS2), and methyl phenyl silicone bonded MoS2, preoxidation surface treatment, a nitride surface treatment, and a sputtered MoS2 coating. Results of wear measurements on both the coated and uncoated surfaces after 300,000 fretting cycles indicated that the polyimide coating was the most wear resistant and caused the least wear to the uncoated mating surface.

A clinical evaluation of 10 percent vs. 15 percent carbamide peroxide tooth-whitening agents.

PubMed

Kihn, P W; Barnes, D M; Romberg, E; Peterson, K

2000-10-01

Agents with carbamide peroxide, or CP, in various concentrations are widely prescribed for at-home tooth whitening. It is not clear, however, if the more concentrated gels will whitening teeth to a greater extent, as no controlled clinical trials have been reported. The authors conducted a double-blind study of human subjects to evaluate whether a 15 percent CP tooth-whitening system was more effective than a 10 percent CP system, and to determine if tooth sensitivity increased with use of the higher concentration. The authors recruited 57 subjects with maxillary anterior teeth of shade A3 or darker (as gauged against a value-oriented shade guide). The subjects were 18 to 65 years of age and in good general and dental health. After matching the subjects by sex and age, the authors randomly assigned them to either a control group, which used a 10 percent CP whitening agent, or an experimental group, which used a 15 percent CP agent. The results indicated that there was no significant difference in shade change between the groups after one week of treatment (t = 1.455, P = .05), but there was a significant difference at the end of the treatment period (t = 2.303, P < .05), as well as two weeks after treatment concluded (t = 2.248, P < .05). There was no significant difference in sensitivity (t = 1.399, P > .05). There was a significant difference in color change between the 10 percent CP and 15 percent CP groups at the end of the study period. There was no significant difference in level of tooth sensitivity between the two groups, and the incidence was equal; there was, however, a significant difference in variability of tooth sensitivity between the two groups. If performed under the careful guidance of a dentist, at-home whitening is an effective treatment, regardless of whether 10 percent CP or 15 percent CP is used. There may be added color change and varying sensitivity with the use of 15 percent CP.

Climate Impacts of Cover Crops

NASA Astrophysics Data System (ADS)

Lombardozzi, D.; Wieder, W. R.; Bonan, G. B.; Morris, C. K.; Grandy, S.

2016-12-01

Cover crops are planted in agricultural rotation with the intention of protecting soil rather than harvest. Cover crops have numerous environmental benefits that include preventing soil erosion, increasing soil fertility, and providing weed and pest control- among others. In addition to localized environmental benefits, cover crops can have important regional or global biogeochemical impacts by increasing soil organic carbon, changing emissions of greenhouse trace gases like nitrous oxide and methane, and reducing hydrologic nitrogen losses. Cover crops may additionally affect climate by changing biogeophysical processes, like albedo and latent heat flux, though these potential changes have not yet been evaluated. Here we use the coupled Community Atmosphere Model (CAM5) - Community Land Model (CLM4.5) to test how planting cover crops in the United States may change biogeophysical fluxes and climate. We present seasonal changes in albedo, heat fluxes, evaporative partitioning, radiation, and the resulting changes in temperature. Preliminary analyses show that during seasons when cover crops are planted, latent heat flux increases and albedo decreases, changing the evaporative fraction and surface temperatures. Understanding both the biogeophysical changes caused by planting cover crops in this study and the biogeochemical changes found in other studies will give a clearer picture of the overall impacts of cover crops on climate and atmospheric chemistry, informing how this land use strategy will impact climate in the future.

Modelling crop land use change derived from influencing factors selected and ranked by farmers in North temperate agricultural regions.

PubMed

Mehdi, Bano; Lehner, Bernhard; Ludwig, Ralf

2018-08-01

To develop meaningful land use scenarios, drivers that affect changes in the landscape are required. In this study, driving factors that influence farmers to change crops on their farm were determined. A questionnaire was administered to four independent groups of farmers who identified and ranked influencing factors pertaining to their choices of crops. The farmers were located in two mid-latitude agricultural watersheds (in Germany and Canada). The ranked influencing factors were used to develop a "farmer driven" scenario to 2040 in both watersheds. Results showed that the most important influencing factors for farmers to change crops were the "economic return of the crop" and "market factors". Yet, when the drivers of crop land use change were grouped into two categories of "financial" and "indirectly-related financial" factors, the "financial" factors made up approximately half of the influencing factors. For some responses, the "indirectly-related financial" factors (i.e. "access to farm equipment", the "farm experience", and "climate") ranked higher than or just as high as the financial factors. Overall, in the four farmer groups the differences between the rankings of the influencing factors were minor, indicating that drivers may be transferable between farms if the farmers are full-time and the farming regions have comparable growing seasons, access to markets, similar technology, and government programs for farm income. In addition to the "farmer driven" scenario, a "policy driven" scenario was derived for each watershed based only on available information on the financial incentives provided to farmers (i.e. agricultural subsidies, income support, crop insurance). The influencing factors ranked by the farmers provided in-depth information that was not captured by the "policy driven" scenario and contributed to improving predictions for crop land use development. This straight-forward method to rank qualitative data provided by farmers can easily be

On the error in crop acreage estimation using satellite (LANDSAT) data

NASA Technical Reports Server (NTRS)

Chhikara, R. (Principal Investigator)

1983-01-01

The problem of crop acreage estimation using satellite data is discussed. Bias and variance of a crop proportion estimate in an area segment obtained from the classification of its multispectral sensor data are derived as functions of the means, variances, and covariance of error rates. The linear discriminant analysis and the class proportion estimation for the two class case are extended to include a third class of measurement units, where these units are mixed on ground. Special attention is given to the investigation of mislabeling in training samples and its effect on crop proportion estimation. It is shown that the bias and variance of the estimate of a specific crop acreage proportion increase as the disparity in mislabeling rates between two classes increases. Some interaction is shown to take place, causing the bias and the variance to decrease at first and then to increase, as the mixed unit class varies in size from 0 to 50 percent of the total area segment.

Sensitivity analysis of the Aquacrop and SAFYE crop models for the assessment of water limited winter wheat yield in regional scale applications.

PubMed

Silvestro, Paolo Cosmo; Pignatti, Stefano; Yang, Hao; Yang, Guijun; Pascucci, Simone; Castaldi, Fabio; Casa, Raffaele

2017-01-01

Process-based models can be usefully employed for the assessment of field and regional-scale impact of drought on crop yields. However, in many instances, especially when they are used at the regional scale, it is necessary to identify the parameters and input variables that most influence the outputs and to assess how their influence varies when climatic and environmental conditions change. In this work, two different crop models, able to represent yield response to water, Aquacrop and SAFYE, were compared, with the aim to quantify their complexity and plasticity through Global Sensitivity Analysis (GSA), using Morris and EFAST (Extended Fourier Amplitude Sensitivity Test) techniques, for moderate to strong water limited climate scenarios. Although the rankings of the sensitivity indices was influenced by the scenarios used, the correlation among the rankings, higher for SAFYE than for Aquacrop, assessed by the top-down correlation coefficient (TDCC), revealed clear patterns. Parameters and input variables related to phenology and to water stress physiological processes were found to be the most influential for Aquacrop. For SAFYE, it was found that the water stress could be inferred indirectly from the processes regulating leaf growth, described in the original SAFY model. SAFYE has a lower complexity and plasticity than Aquacrop, making it more suitable to less data demanding regional scale applications, in case the only objective is the assessment of crop yield and no detailed information is sought on the mechanisms of the stress factors affecting its limitations.

Sensitivity analysis of the Aquacrop and SAFYE crop models for the assessment of water limited winter wheat yield in regional scale applications

PubMed Central

Pignatti, Stefano; Yang, Hao; Yang, Guijun; Pascucci, Simone; Castaldi, Fabio

2017-01-01

Process-based models can be usefully employed for the assessment of field and regional-scale impact of drought on crop yields. However, in many instances, especially when they are used at the regional scale, it is necessary to identify the parameters and input variables that most influence the outputs and to assess how their influence varies when climatic and environmental conditions change. In this work, two different crop models, able to represent yield response to water, Aquacrop and SAFYE, were compared, with the aim to quantify their complexity and plasticity through Global Sensitivity Analysis (GSA), using Morris and EFAST (Extended Fourier Amplitude Sensitivity Test) techniques, for moderate to strong water limited climate scenarios. Although the rankings of the sensitivity indices was influenced by the scenarios used, the correlation among the rankings, higher for SAFYE than for Aquacrop, assessed by the top-down correlation coefficient (TDCC), revealed clear patterns. Parameters and input variables related to phenology and to water stress physiological processes were found to be the most influential for Aquacrop. For SAFYE, it was found that the water stress could be inferred indirectly from the processes regulating leaf growth, described in the original SAFY model. SAFYE has a lower complexity and plasticity than Aquacrop, making it more suitable to less data demanding regional scale applications, in case the only objective is the assessment of crop yield and no detailed information is sought on the mechanisms of the stress factors affecting its limitations. PMID:29107963

Crop-associated virus reduces the rooting depth of non-crop perennial native grass more than non-crop-associated virus with known viral suppressor of RNA silencing (VSR).

PubMed

Malmstrom, Carolyn M; Bigelow, Patrick; Trębicki, Piotr; Busch, Anna K; Friel, Colleen; Cole, Ellen; Abdel-Azim, Heba; Phillippo, Colin; Alexander, Helen M

2017-09-15

As agricultural acreage expanded and came to dominate landscapes across the world, viruses gained opportunities to move between crop and wild native plants. In the Midwestern USA, virus exchange currently occurs between widespread annual Poaceae crops and remnant native perennial prairie grasses now under consideration as bioenergy feedstocks. In this region, the common aphid species Rhopalosiphum padi L. (the bird cherry-oat aphid) transmits several virus species in the family Luteoviridae, including Barley yellow dwarf virus (BYDV-PAV, genus Luteovirus) and Cereal yellow dwarf virus (CYDV-RPV and -RPS, genus Polerovirus). The yellow dwarf virus (YDV) species in these two genera share genetic similarities in their 3'-ends, but diverge in the 5'-regions. Most notably, CYDVs encode a P0 viral suppressor of RNA silencing (VSR) absent in BYDV-PAV. Because BYDV-PAV has been reported more frequently in annual cereals and CYDVs in perennial non-crop grasses, we examine the hypothesis that the viruses' genetic differences reflect different affinities for crop and non-crop hosts. Specifically, we ask (i) whether CYDVs might persist within and affect a native non-crop grass more strongly than BYDV-PAV, on the grounds that the polerovirus VSR could better moderate the defenses of a well-defended perennial, and (ii) whether the opposite pattern of effects might occur in a less defended annual crop. Because previous work found that the VSR of CYDV-RPS possessed greater silencing suppressor efficiency than that of CYDV-RPV, we further explored (iii) whether a novel grass-associated CYDV-RPS isolate would influence a native non-crop grass more strongly than a comparable CYDV-RPV isolate. In growth chamber studies, we found support for this hypothesis: only grass-associated CYDV-RPS stunted the shoots and crowns of Panicum virgatum L. (switchgrass), a perennial native North American prairie grass, whereas crop-associated BYDV-PAV (and coinfection with BYDV-PAV and CYDV-RPS) most

Machine-assisted analysis of Landsat data in the study of crop-soils relationships

USGS Publications Warehouse

Draeger, William C.

1976-01-01

To date, relatively few studies have dealt with crop-soil interactions as they affect the appearance of agricultural areas on Landsat imagery, and hence crop and soil classification or the analysis of agricultural land use.The Image 100, a computer-based data analysis system which allows an interpreter to interact directly and rapidly with Landsat computer compatible tape data, provided a tool to assist in the evaluation of the extent and significance of these interactions. Used with timely and accurate ground data, the system made possible a determination of the variability in crop spectral appearance, from soil type to soil type, as recorded on Landsat data. Information was provided in the form of spectral distribution histrograms for each crop-soil class on each Landsat band. Several crop categories in a test area in  rookings County, South Dakota, were classified using training fields that were selected to be representative of each major crop-soil class. Accuracies in each case, on a total acreage basis, were greater than 90 percent.

Update to the Ground-Water Withdrawals Database for the Death Valley Regional Ground-Water Flow System, Nevada and California, 1913-2003

USGS Publications Warehouse

Moreo, Michael T.; Justet, Leigh

2008-01-01

Ground-water withdrawal estimates from 1913 through 2003 for the Death Valley regional ground-water flow system are compiled in an electronic database to support a regional, three-dimensional, transient ground-water flow model. This database updates a previously published database that compiled estimates of ground-water withdrawals for 1913-1998. The same methodology is used to construct each database. Primary differences between the 2 databases are an additional 5 years of ground-water withdrawal data, well locations in the updated database are restricted to Death Valley regional ground-water flow system model boundary, and application rates are from 0 to 1.5 feet per year lower than original estimates. The lower application rates result from revised estimates of crop consumptive use, which are based on updated estimates of potential evapotranspiration. In 2003, about 55,700 acre-feet of ground water was pumped in the DVRFS, of which 69 percent was used for irrigation, 13 percent for domestic, and 18 percent for public supply, commercial, and mining activities.

Australia’s food system is highly dependent on foreign crop diversity

USDA-ARS?s Scientific Manuscript database

The food crops that are now produced or consumed in Australia were initially domesticated and evolved over time in specific geographic regions across the planet. Genetic diversity within these crops and their wild relatives is considered to be historically particularly rich within these regions. Los...

Determining the spatial variability of crop yields of two different climatic regions in Southwest Germany

NASA Astrophysics Data System (ADS)

Eshonkulov, Ravshan; Poyda, Arne; Ingwersen, Joachim; Streck, Thilo

2017-04-01

Assessing the spatial variability of soil physical properties is crucial for agricultural land management. We determined the spatial variability within two agricultural fields in the regions of Kraichgau and Swabian Jura in Southwest Germany. We determined soil physical properties and recorded the temporal development of soil mineral nitrogen (N) and water content as well as that of plant variables (phenology, biomass, leaf area index (LAI), N content, green vegetation fraction (GVF). The work was conducted during the vegetation periods of 2015 and 2016 in winter wheat, and winter rapeseed in Kraichgau and winter barley and silage maize on Swabian Jura. Measurements were taken in three-weekly intervals. On each field, we identified three plots with reduced plant development using high-resolution (RapidEye) satellite images ("cold spots"). Measurements taken on these cold spots were compared to those from five established (long-term) reference plots representing the average field variability. The software EXPERT-N was used to simulate the soil crop system at both cold spots and reference plots. Sensitivity analyses were conducted to identify the most important parameters for the determination of spatial variability in crop growth dynamics.

The relationship of nitrate concentrations in streams to row crop land use in Iowa

USGS Publications Warehouse

Schilling, K.E.; Libra, R.D.

2000-01-01

The relationship between row crop land use and nitrate N concentrations in surface water was evaluated for 15 Iowa watersheds ranging from 1002 to 2774 km2 and 10 smaller watersheds ranging from 47 to 775 km2 for the period 1996 to 1998. The percentage of land in row crop varied from 24 to >87% in the 15 large watersheds, and mean annual NO3-N concentrations ranged from 0.5 to 10.8 mg/L. In the small watersheds, row crop percentage varied from 28 to 87% and mean annual NO3-N concentrations ranged from 3.0 to 10.5 mg/L. In both cases, nitrate N concentrations were directly related to the percentage of row crop in the watershed (p 87% in the 15 large watersheds, and mean annual NO3-N concentrations ranged from 0.5 to 10.8 mg/L. In the small watersheds, row crop percentage varied from 28 to 87% and mean annual NO3-N concentrations ranged from 3.0 to 10.5 mg/L. In both cases, nitrate N concentrations were directly related to the percentage of row crop in the watershed (p<0.0003). Linear regression showed similar slope for both sets of watersheds (0.11) suggesting that average annual surface water nitrate concentrations in Iowa, and possibly similar agricultural areas in the midwestern USA, can be approximated by multiplying a watershed's row crop percentage by 0.1. Comparing the Iowa watershed data with similar data collected at a subwatershed scale in Iowa (0.1 to 8.1 km2) and a larger midcontinent scale (7300 to 237 100 km2) suggests that watershed scale affects the relationship of nitrate concentration and land use. The slope of nitrate concentration versus row crop percentage decreases with increasing watershed size.Mean nitrate concentrations and row crop land use were summarized for 15 larger and ten smaller watersheds in Iowa, and the relationship between NO3 concentration and land use was examined. Linear regression of mean NO3 concentration and percent row crop was highly significant for both sets of watershed data, but a stronger correlation was noted in the

Dynamic drought risk assessment using crop model and remote sensing techniques

NASA Astrophysics Data System (ADS)

Sun, H.; Su, Z.; Lv, J.; Li, L.; Wang, Y.

2017-02-01

Drought risk assessment is of great significance to reduce the loss of agricultural drought and ensure food security. The normally drought risk assessment method is to evaluate its exposure to the hazard and the vulnerability to extended periods of water shortage for a specific region, which is a static evaluation method. The Dynamic Drought Risk Assessment (DDRA) is to estimate the drought risk according to the crop growth and water stress conditions in real time. In this study, a DDRA method using crop model and remote sensing techniques was proposed. The crop model we employed is DeNitrification and DeComposition (DNDC) model. The drought risk was quantified by the yield losses predicted by the crop model in a scenario-based method. The crop model was re-calibrated to improve the performance by the Leaf Area Index (LAI) retrieved from MODerate Resolution Imaging Spectroradiometer (MODIS) data. And the in-situ station-based crop model was extended to assess the regional drought risk by integrating crop planted mapping. The crop planted area was extracted with extended CPPI method from MODIS data. This study was implemented and validated on maize crop in Liaoning province, China.

Fluorescence of crop residue: postmortem analysis of crop conditions

NASA Astrophysics Data System (ADS)

McMurtrey, James E., III; Kim, Moon S.; Daughtry, Craig S. T.; Corp, Lawrence A.; Chappelle, Emmett W.

1997-07-01

Fluorescence of crop residues at the end of the growing season may provide an indicator of the past crop's vegetative condition. Different levels of nitrogen (N) fertilization were applied to field grown corn and wheat at Beltsville, Maryland. The N fertilizer treatments produce a range of physiological conditions, pigment concentrations, biomass levels, and grain yields that resulted in varying growth and stress conditions in the living crops. After normal harvesting procedures the crop residues remained. The fluorescence spectral characteristics of the plant residues from crops grown under different levels of N nutrition were analyzed. The blue-green fluorescence response of in-vitro residue biomass of the N treated field corn had different magnitudes. A blue-green- yellow algorithm, (460/525)*600 nm, gave the best separations between prior corn growth conditions at different N fertilization levels. Relationships between total dry biomass, the grain yield, and fluorescence properties in the 400 - 670 nm region of the spectrum were found in both corn and wheat residues. The wheat residue was analyzed to evaluate the constituents responsible for fluorescence. A ratio of the blue-green, 450/550 nm, images gave the best separation among wheat residues at different N fertilization levels. Fluorescence of extracts from wheat residues showed inverse fluorescence intensities as a function of N treatments compared to that of the intact wheat residue or ground residue samples. The extracts also had an additional fluorescence emission peak in the red, 670 nm. Single band fluorescence intensity in corn and wheat residues is due mostly to the quantity of the material on the soil surface. Ratios of fluorescence bands varied as a result of the growth conditions created by the N treatments and are thought to be indicative of the varying concentrations of the plant residues fluorescing constituents. Estimates of the amount and cost effectiveness of N fertilizers to satisfy

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…

Perspectives on genetically modified crops and food detection.

PubMed

Lin, Chih-Hui; Pan, Tzu-Ming

2016-01-01

Genetically modified (GM) crops are a major product of the global food industry. From 1996 to 2014, 357 GM crops were approved and the global value of the GM crop market reached 35% of the global commercial seed market in 2014. However, the rapid growth of the GM crop-based industry has also created controversies in many regions, including the European Union, Egypt, and Taiwan. The effective detection and regulation of GM crops/foods are necessary to reduce the impact of these controversies. In this review, the status of GM crops and the technology for their detection are discussed. As the primary gap in GM crop regulation exists in the application of detection technology to field regulation, efforts should be made to develop an integrated, standardized, and high-throughput GM crop detection system. We propose the development of an integrated GM crop detection system, to be used in combination with a standardized international database, a decision support system, high-throughput DNA analysis, and automated sample processing. By integrating these technologies, we hope that the proposed GM crop detection system will provide a method to facilitate comprehensive GM crop regulation. Copyright © 2015. Published by Elsevier B.V.

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

PubMed

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

2011-10-01

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

Cloning crops in a CELSS via tissue culture: Prospects and problems

NASA Technical Reports Server (NTRS)

Carman, John G.; Hess, J. Richard

1990-01-01

Micropropagation is currently used to clone fruits, nuts, and vegetables and involves controlling the outgrowth in vitro of basal, axillary, or adventitious buds. Following clonal multiplication, shoots are divided and rooted. This process has greatly reduced space and energy requirements in greenhouses and field nurseries and has increased multiplication rates by greater than 20 fold for some vegetatively propagated crops and breeding lines. Cereal and legume crops can also be cloned by tissue culture through somatic embryogenesis. Somatic embryos can be used to produce 'synthetic seed', which can tolerate desiccation and germinate upon rehydration. Synthetic seed of hybrid wheat, rice, soybean and other crops could be produced in a controlled ecological life support system. Thus, yield advantages of hybreds over inbreds (10 to 20 percent) could be exploited without having to provide additional facilities and energy for parental-line and hybrid seed nurseries.

Genomics of crop wild relatives: expanding the gene pool for crop improvement.

PubMed

Brozynska, Marta; Furtado, Agnelo; Henry, Robert J

2016-04-01

Plant breeders require access to new genetic diversity to satisfy the demands of a growing human population for more food that can be produced in a variable or changing climate and to deliver the high-quality food with nutritional and health benefits demanded by consumers. The close relatives of domesticated plants, crop wild relatives (CWRs), represent a practical gene pool for use by plant breeders. Genomics of CWR generates data that support the use of CWR to expand the genetic diversity of crop plants. Advances in DNA sequencing technology are enabling the efficient sequencing of CWR and their increased use in crop improvement. As the sequencing of genomes of major crop species is completed, attention has shifted to analysis of the wider gene pool of major crops including CWR. A combination of de novo sequencing and resequencing is required to efficiently explore useful genetic variation in CWR. Analysis of the nuclear genome, transcriptome and maternal (chloroplast and mitochondrial) genome of CWR is facilitating their use in crop improvement. Genome analysis results in discovery of useful alleles in CWR and identification of regions of the genome in which diversity has been lost in domestication bottlenecks. Targeting of high priority CWR for sequencing will maximize the contribution of genome sequencing of CWR. Coordination of global efforts to apply genomics has the potential to accelerate access to and conservation of the biodiversity essential to the sustainability of agriculture and food production. © 2015 Society for Experimental Biology, Association of Applied Biologists and John Wiley & Sons Ltd.

COLT: seasonal prediction of crop irrigation needs

NASA Astrophysics Data System (ADS)

Villani, Giulia; Spisni, Andrea; Mariani, Maria Cristina; Pratizzoli, William; Pavan, Valentina; Tomei, Fausto; Botarelli, Lucio; Marletto, Vittorio

2013-04-01

COLT is an operational chain to predict summer (June, July, August) crop irrigation needs in Emilia-Romagna (Northern Italy) at the regional and lower scales. Set up by ARPA-SIMC in 2010, it has been applied since with good results. COLT predicts summer irrigation needs in May, i.e. at the beginning of the irrigation season in Emilia-Romagna. COLT is based on the production of yearly updated land use maps, observed daily weather data, a regional soil map and ensemble probabilistic seasonal weather forecasts obtained from the EUROSIP multi-model operational system and a geographical soil water balance model (CRITERIA). The first step of the operational scheme is the supervised classification of crops through field surveys and a set of multitemporal satellite images acquired during the first months of the growing period. As the identification of all crop species during the satellite working windows is not feasible, they are grouped in six classes: summer field crops (including corn, sorghum, tomato, sugar beet, potato and others), winter crops (wheat, barley, oat, etc.), perennial grasses (alfa-alfa and meadows), rice, vineyards and orchards, on the whole regional plain, covering about 775000 ha. The second step involves the statistical downscaling of the EUROSIP ensemble predictions over Emilia-Romagna and the use of a weather generator to synthetically produce a number (usually 50) replicated meteorological summer daily data series, consistent with the predicted and downscaled summer anomalies of temperature, rainfall and other related indices. During the final step the CRITERIA model computes crop development and soil water balance on the crop classification map using observed meteorological daily data up to the end of May. Afterword forecasts are used up to the end of the summer irrigation season, i.e. August 31st. The statistical distribution projections of summer irrigation needs at the regional and reclamation consortia scale are then issued and disseminated

Estimating cropland NPP using national crop inventory and MODIS derived crop specific parameters

NASA Astrophysics Data System (ADS)

Bandaru, V.; West, T. O.; Ricciuto, D. M.

2011-12-01

Estimates of cropland net primary production (NPP) are needed as input for estimates of carbon flux and carbon stock changes. Cropland NPP is currently estimated using terrestrial ecosystem models, satellite remote sensing, or inventory data. All three of these methods have benefits and problems. Terrestrial ecosystem models are often better suited for prognostic estimates rather than diagnostic estimates. Satellite-based NPP estimates often underestimate productivity on intensely managed croplands and are also limited to a few broad crop categories. Inventory-based estimates are consistent with nationally collected data on crop yields, but they lack sub-county spatial resolution. Integrating these methods will allow for spatial resolution consistent with current land cover and land use, while also maintaining total biomass quantities recorded in national inventory data. The main objective of this study was to improve cropland NPP estimates by using a modification of the CASA NPP model with individual crop biophysical parameters partly derived from inventory data and MODIS 8day 250m EVI product. The study was conducted for corn and soybean crops in Iowa and Illinois for years 2006 and 2007. We used EVI as a linear function for fPAR, and used crop land cover data (56m spatial resolution) to extract individual crop EVI pixels. First, we separated mixed pixels of both corn and soybean that occur when MODIS 250m pixel contains more than one crop. Second, we substituted mixed EVI pixels with nearest pure pixel values of the same crop within 1km radius. To get more accurate photosynthetic active radiation (PAR), we applied the Mountain Climate Simulator (MTCLIM) algorithm with the use of temperature and precipitation data from the North American Land Data Assimilation System (NLDAS-2) to generate shortwave radiation data. Finally, county specific light use efficiency (LUE) values of each crop for years 2006 to 2007 were determined by application of mean county inventory

Development and implementation of a GEOGLAM Crop Monitor web interface

NASA Astrophysics Data System (ADS)

Oliva, P.; Sanchez, A.; Humber, M. L.; Becker-Reshef, I.; Justice, C. J.; McGaughey, K.; Barker, B.

2016-12-01

Beginning in September 2013, the GEOGLAM Crop Monitor activity has provided earth observation (EO) data to a network of partners and collected crop assessments on a subnational basis through a web interface known as the Crop Assessment Tool. Based on the collection of monthly crop assessments, a monthly crop condition bulletin is published in the Agricultural Market Information System (AMIS) Market Monitor report. This workflow has been successfully applied to food security applications through the Early Warning Crop Monitor activity. However, a lack of timely and accurate information on crop conditions and prospects at the national scale is a critical issue in the majority of southern and eastern African countries and some South American countries. Such information is necessary for informed and prompt decision making in the face of emergencies, food insecurity and planning requirements for agricultural markets. This project addresses these needs through the development of relevant, user-friendly remote sensing monitor systems, collaborative internet technology, and collaboration with national and regional agricultural monitoring networks. By building on current projects and relationships established through the various GEOGLAM Crop Monitor activities, this project aims to ultimately provide EO-informed crop condition maps and charts designed for economics and policy oriented audiences, thereby providing quick and easy to understand products on crop conditions as the season progresses. Integrating these data and assessments vertically throughout the system provides a basis for regional sharing and collaboration in food security applications.

Soil wet aggregate stability in dryland Pacific Northwest intensified crop rotations

USDA-ARS?s Scientific Manuscript database

Improving soil aggregation in the semiarid inland Pacific Northwest cropping region can reduce the erodibility and improve water infiltration in the silt loam soils. We compared the individual crop phases of six different crop rotations in plots located in 300 mm mean annual precipitation area of t...

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

The present status of commercialized and developed biotech (GM) crops, results of evaluation of plum 'HoneySweet" for resistance to plum pox virus in the Czech Republic

USDA-ARS?s Scientific Manuscript database

Commercialization of biotech (GM) crops started in 1996. A significant increase of 9 million hectars was realized in 1996-2009. In the years 2010-2011, it was already 12 million hectars (8 percent of total crop area). 16.7 million farmers in 29 countries planted 160 million hectars of GM crops in...

Asia Rice Crop Estimation and Monitoring (Asia-RiCE) for GEOGLAM

NASA Astrophysics Data System (ADS)

Oyoshi, K.; Tomiyama, N.; Okumura, T.; Sobue, S.

2013-12-01

Food security is a critical issue for the international community because of rapid population and economic growth, and climate change. In June 2011, the meeting of G20 agriculture ministers was held to discuss food security and food price volatility, and they agreed on an 'Action Plan on Food Price Volatility and Agriculture'. This plan includes a GEO Global Agricultural Monitoring (GEOGLAM) initiative. The aim of GEOGLAM is to reinforce the international community's ability to produce and disseminate relevant, timely, and accurate forecasts of agricultural production on regional, national, and global scales by utilizing remote sensing technology. GEOGLAM focused on four major grain crops, wheat, maize, soybeans and rice. In particular, Asian countries are responsible for approximately 90% of the world rice production and consumption, rice is the most significant cereal crop in Asian region. Hence, Asian space and agricultural agencies with an interest in the development of rice crop monitoring technology launched an Asia-Rice Crop Estimation & Monitoring (Asia-RiCE) component for the GEOGLAM initiative. In Asian region, rice is mainly cultivated in rainy season, and a large amount of cloud limits rice crop monitoring with optical sensors. But, Synthetic Aperture RADAR (SAR) is all-weather sensor and can observe land surface even if the area is covered by cloud. Therefore, SAR technology would be powerful tool to monitor rice crop in Asian region. Asia-RiCE team required mainly SAR observation data including ALOS-2, RISAT-1, Sentinel-1 and RADARSAT, TerraSAR-X, COSMO-SkyMed for Asia-RiCE GEOGLAM Phase 1 implementation (2013-2015) to the Committee on Earth Observations (CEOS) in the GEOGLAM-CEOS Global Agricultural Monitoring Co-community Meeting held in June 2013. And also, rice crop has complicated cropping systems such as rein-fed or irrigated cultivation, single, double or sometimes triple cropping. In addition, each agricultural field is smaller than that of

Spatial distribution of unspecified chronic kidney disease in El Salvador by crop area cultivated and ambient temperature.

PubMed

VanDervort, Darcy R; López, Dina L; Orantes, Carlos M; Rodríguez, David S

2014-04-01

Chronic kidney disease of unknown etiology is occurring in various geographic areas worldwide. Cases lack typical risk factors associated with chronic kidney disease, such as diabetes and hypertension. It is epidemic in El Salvador, Central America, where it is diagnosed with increasing frequency in young, otherwise-healthy male farmworkers. Suspected causes include agrochemical use (especially in sugarcane fields), physical heat stress, and heavy metal exposure. To evaluate the geographic relationship between unspecified chronic kidney disease (unCKD) and nondiabetic chronic renal failure (ndESRD) hospital admissions in El Salvador with the proximity to cultivated crops and ambient temperatures. Data on unCKD and ndESRD were compared with environmental variables, crop area cultivated (indicator of agrochemical use) and high ambient temperatures. Using geographically weighted regression analysis, two model sets were created using reported municipal hospital admission rates are per thousand population for unCKD 2006-2010 and rates of ndESRD 2005-2010 [corrected]. These were assessed against local percent of land cultivated by crop (sugarcane, coffee, corn, cotton, sorghum, and beans) and mean maximum ambient temperature, with Moran's indices determining data clustering. Two-dimensional geographic models illustrated parameter spatial distribution. Bivariate geographically weighted regressions showed statistically significant correlations between percent area of sugarcane, corn, cotton, coffee, and bean cultivation, as well as mean maximum ambient temperature with both unCKD and ndESRD hospital admission rates. Percent area of sugarcane cultivation had greatest statistical weight (p ≤ 0.001; Rp2 = 0.77 for unCKD). The most statistically significant multivariate geographically weighted regression model for unCKD included percent area of sugarcane, cotton and corn cultivation (p ≤ 0.001; Rp2 = 0.80), while, for ndESRD, it included the percent area of sugarcane, corn

GIS-based agroecological assessment of land suitability for food crop development at a regional scale: A study case of Buton Island.

NASA Astrophysics Data System (ADS)

Ramlan, A.; Baja, S.; Arif, S.; Neswati, R.

2018-05-01

Agriculture has long become a prime sector for regional development in Buton Island, although local government emphasis on perennial crops. Food crop have been developed in very limited land areas, mainly on transmigration areas, as parts of central government programs. Today, the central government has launched a national strategic program on food self-sufficiency and has imposed the local government to optimize available land for cultivating food crop. The primary aim of study is to develop rapid assessment on a spatial basis using GIS for agricultural land suitability evaluation of agriculture commodities, i.e., rice (irrigated paddy field, rainfed rice) and corn (Zea maize L.). The study was undertaken using the following procedures: (i) conducting reconnaissance soil survey based on land units; (ii) constructing soil database in a GIS; and (iii) classifying land suitability using the FAO method. Spatial data were generated from digital topographic map, soil survey, soil characteristics, as well as climate data. Preliminary results indicate that quite large area available for food crop cultivation both in the context of land suitability (mostly in S2 and S3 classes) and land availability. All data bases were managed in GIS, then it is amenable to various operations in GIS to accommodate possible additional assessment including socio-economic and policy assessment.

Air-quality and Climatic Consequences of Bioenergy Crop Cultivation

NASA Astrophysics Data System (ADS)

Porter, William Christian

Bioenergy is expected to play an increasingly significant role in the global energy budget. In addition to the use of liquid energy forms such as ethanol and biodiesel, electricity generation using processed energy crops as a partial or full coal alternative is expected to increase, requiring large-scale conversions of land for the cultivation of bioenergy feedstocks such as cane, grasses, or short rotation coppice. With land-use change identified as a major contributor to changes in the emission of biogenic volatile organic compounds (BVOCs), many of which are known contributors to the pollutants ozone (O 3) and fine particulate matter (PM2.5), careful review of crop emission profiles and local atmospheric chemistry will be necessary to mitigate any unintended air-quality consequences. In this work, the atmospheric consequences of bioenergy crop replacement are examined using both the high-resolution regional chemical transport model WRF/Chem (Weather Research and Forecasting with Chemistry) and the global climate model CESM (Community Earth System Model). Regional sensitivities to several representative crop types are analyzed, and the impacts of each crop on air quality and climate are compared. Overall, the high emitting crops (eucalyptus and giant reed) were found to produce climate and human health costs totaling up to 40% of the value of CO 2 emissions prevented, while the related costs of the lowest-emitting crop (switchgrass) were negligible.

Future generation energy crops

USDA-ARS?s Scientific Manuscript database

Although cropping systems in the Midwest that emphasize corn (Zea mays), soybean (Glycine max), and wheat (Triticum aestivum) are some of the most highly productive in the US, the growing lack of agricultural diversity in this region threatens to jeopardize long-term sustainability. Added to this co...

Impact of climate variability on various Rabi crops over Northwest India

NASA Astrophysics Data System (ADS)

Nageswararao, M. M.; Dhekale, B. S.; Mohanty, U. C.

2018-01-01

The Indian agriculture with its two prominent cropping seasons [summer ( Kharif) and winter ( Rabi)] is the mainstay of the rural economy. Northwest India (NWI) is an important region for the cultivation of Rabi crops grown during the period from October to April. In the present study, state wise impact analysis is carried out to ascertain the influence of climate indices Nino3.4 region Sea Surface Temperature (SST), Southern Oscillation Index (SOI), Arctic Oscillation (AO), North Atlantic Oscillation (NAO) and local precipitation, soil moisture, minimum ( T min), maximum ( T max) and mean ( T mean) temperatures on different Rabi crops (wheat, gram, rapeseed-mustard, oilseeds, and total Rabi food grains) over NWI during the years 1966-2011. To study the impact of climate variability on different Rabi crops, firstly, the influence of technology on the productivity of these crops has been removed by using linear function, as linear trend has noticed in all the time series. Correlation analysis provides an indication of the influence of local precipitation, soil moisture, T min, T max and T mean and some of its potential predictors (Nino3.4 region SST, SOI, AO, and NAO) on the productivity of different Rabi crops. Overall impact analysis indicates that the productivity of different Rabi crops in most of the places of NWI is most likely influenced by variability in local temperatures. Moreover, Nino3.4 region SST (SOI) positively (negatively) affects the productivity of gram, rapeseed-mustard, and total Rabi oilseeds in most of the states. The results of this study are useful in determining the strategies for increasing sustainable production through better agronomic practices.

Agricultural pesticide emissions associated with common crops in the United States

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

Benjey, W.G.

Annual emissions for the year 1987 from the application of agricultural pesticides have been estimated by crop type by county for the United States using a geographic information system. The emissions estimates are based upon computed volatilization rates accounting for the properties of each pesticide, evaporation rates, mode of application (surface or soil incorporation) and percent of interception by leaves. Key pesticide properties include the Henry's Law constant, half-life in soil and the organic carbon partitioning coefficient. The volatilization rates are multiplied by the amount of pesticide applied by crop acreage in each county as determined from agricultural census andmore » pesticide sales data. The geographic distribution of the dominant emissions, such as atrazine and diazinon, etc. are presented by crop type and state. For a given pesticide, the geographic variability is controlled principally by amount applied and water availability as reflected in evaporation rates.« less

Cardiovascular effects of intraosseous injections of 2 percent lidocaine with 1:100,000 epinephrine and 3 percent mepivacaine.

PubMed

Replogle, K; Reader, A; Nist, R; Beck, M; Weaver, J; Meyers, W J

1999-05-01

Because a number of patients have reported an increase in heart rate with the intraosseous, or i.o., injection, it is important to evaluate changes in the cardiovascular system with this injection technique. The purpose of this study was to determine the cardiovascular effects of an i.o. injection of 2 percent lidocaine with 1:100,000 epinephrine and 3 percent mepivacaine. With the use of a repeated-measures design, the authors randomly assigned 42 subjects to receive i.o. injections of 1.8 milliliters of 2 percent lidocaine with 1:100,000 epinephrine or 1.8 mL of 3 percent mepivacaine in a double-blinded manner at two appointments. At each appointment the authors monitored electrocardiographic findings, cardiac rate, systolic and diastolic blood pressure, and mean arterial pressure before, during and after administration of anesthetic solutions. With the 2 percent lidocaine with 1:100,000 epinephrine solution, 28 (67 percent) of 42 subjects experienced an increase in heart rate that might be attributed to the effect of the epinephrine. In 22 (79 percent) of these subjects, the heart rate returned to within 5 beats of baseline values within four minutes after solution deposition. The authors found no significant increase in heart rate in subjects receiving the 3 percent mepivacaine. No significant differences (P > .05) were found in mean diastolic, mean systolic or mean arterial blood pressure values between the subjects receiving 2 percent lidocaine with 1:100,000 epinephrine and those receiving 3 percent mepivacaine. The majority of subjects receiving the i.o. injection of the 2 percent lidocaine-epinephrine solution experienced a transient increase in heart rate. No significant increase in heart rate was seen with the i.o. injection of 3 percent mepivacaine. While patients would likely notice the heart rate increase with the lidocaine-epinephrine solution, it would not be clinically significant in most healthy patients. In patients whose medical condition, drug

Declining groundwater level caused by irrigation to row crops in the Lower Mississippi River Basin, Current Situation and Trends

NASA Astrophysics Data System (ADS)

Feng, G.; Gao, F.; Ouyang, Y.

2017-12-01

The Mississippi River is North America's largest river and the second largest watershed in the world. It flows over 3,700 km through America's heartland to the Gulf of Mexico. Over 3 million hectares in the Lower Mississippi River Basin represent irrigated cropland and 90 percent of those lands currently rely on the groundwater supply. The primary crops grown in this region are soybean, corn, cotton, and rice. Increased water withdrawals for irrigating those crops and stagnant recharging jeopardize the long-term availability of the aquifer and place irrigation agriculture in the region on an unsustainable path. The objectives of this study were to: 1) analyze the current groundwater level in the Lower Mississippi River Basin based on the water table depth observed by Yazoo Mississippi Delta Joint Water Management District from 2000 and 2016; 2) determine trends of change in groundwater level under conventional and groundwater saving irrigation management practices (ET or soil moisture based full irrigation scheduling using all groundwater or different percentages of ground and surface water). The coupled SWAT and MODFLOW model was applied to investigate the trends. Observed results showed that the groundwater level has declined from 33 to 26 m at an annual decrease rate of 0.4 m in the past 17 years. Simulated results revealed that the groundwater storage was decreased by 26 cm/month due to irrigation in crop season. It is promising that the groundwater storage was increased by 23 cm/month, sometimes even 60 cm/month in crop off-growing season because of recharge from rainfall. Our results suggest that alternative ET or soil moisture based groundwater saving irrigation scheduling with conjunctive use of surface water is a sustainable practice for irrigated agriculture in in the Lower Mississippi River Basin.

Modeling perceptions of climatic risk in crop production.

PubMed

Reinmuth, Evelyn; Parker, Phillip; Aurbacher, Joachim; Högy, Petra; Dabbert, Stephan

2017-01-01

In agricultural production, land-use decisions are components of economic planning that result in the strategic allocation of fields. Climate variability represents an uncertainty factor in crop production. Considering yield impact, climatic influence is perceived during and evaluated at the end of crop production cycles. In practice, this information is then incorporated into planning for the upcoming season. This process contributes to attitudes toward climate-induced risk in crop production. In the literature, however, the subjective valuation of risk is modeled as a risk attitude toward variations in (monetary) outcomes. Consequently, climatic influence may be obscured by political and market influences so that risk perceptions during the production process are neglected. We present a utility concept that allows the inclusion of annual risk scores based on mid-season risk perceptions that are incorporated into field-planning decisions. This approach is exemplified and implemented for winter wheat production in the Kraichgau, a region in Southwest Germany, using the integrated bio-economic simulation model FarmActor and empirical data from the region. Survey results indicate that a profitability threshold for this crop, the level of "still-good yield" (sgy), is 69 dt ha-1 (regional mean Kraichgau sample) for a given season. This threshold governs the monitoring process and risk estimators. We tested the modeled estimators against simulation results using ten projected future weather time series for winter wheat production. The mid-season estimators generally proved to be effective. This approach can be used to improve the modeling of planning decisions by providing a more comprehensive evaluation of field-crop response to climatic changes from an economic risk point of view. The methodology further provides economic insight in an agrometeorological context where prices for crops or inputs are lacking, but farmer attitudes toward risk should still be included in

Modeling perceptions of climatic risk in crop production

PubMed Central

Parker, Phillip; Aurbacher, Joachim; Högy, Petra; Dabbert, Stephan

2017-01-01

In agricultural production, land-use decisions are components of economic planning that result in the strategic allocation of fields. Climate variability represents an uncertainty factor in crop production. Considering yield impact, climatic influence is perceived during and evaluated at the end of crop production cycles. In practice, this information is then incorporated into planning for the upcoming season. This process contributes to attitudes toward climate-induced risk in crop production. In the literature, however, the subjective valuation of risk is modeled as a risk attitude toward variations in (monetary) outcomes. Consequently, climatic influence may be obscured by political and market influences so that risk perceptions during the production process are neglected. We present a utility concept that allows the inclusion of annual risk scores based on mid-season risk perceptions that are incorporated into field-planning decisions. This approach is exemplified and implemented for winter wheat production in the Kraichgau, a region in Southwest Germany, using the integrated bio-economic simulation model FarmActor and empirical data from the region. Survey results indicate that a profitability threshold for this crop, the level of “still-good yield” (sgy), is 69 dt ha-1 (regional mean Kraichgau sample) for a given season. This threshold governs the monitoring process and risk estimators. We tested the modeled estimators against simulation results using ten projected future weather time series for winter wheat production. The mid-season estimators generally proved to be effective. This approach can be used to improve the modeling of planning decisions by providing a more comprehensive evaluation of field-crop response to climatic changes from an economic risk point of view. The methodology further provides economic insight in an agrometeorological context where prices for crops or inputs are lacking, but farmer attitudes toward risk should still be included

Report on 1960 forest tree seed crop in New England

Treesearch

Thomas W. McConkey

1961-01-01

The 1960 forest tree seed crop in New England was generally a medium one, according to reports received from observers in five of the six states. The crop was fairly uniform throughout the region; there were only few reports of marked differences between different sections. On the whole, the crop was somewhat better than that in 1959, and very much better for some...

Using radar imagery for crop discrimination: a statistical and conditional probability study

USGS Publications Warehouse

Haralick, R.M.; Caspall, F.; Simonett, D.S.

1970-01-01

A number of the constraints with which remote sensing must contend in crop studies are outlined. They include sensor, identification accuracy, and congruencing constraints; the nature of the answers demanded of the sensor system; and the complex temporal variances of crops in large areas. Attention is then focused on several methods which may be used in the statistical analysis of multidimensional remote sensing data.Crop discrimination for radar K-band imagery is investigated by three methods. The first one uses a Bayes decision rule, the second a nearest-neighbor spatial conditional probability approach, and the third the standard statistical techniques of cluster analysis and principal axes representation.Results indicate that crop type and percent of cover significantly affect the strength of the radar return signal. Sugar beets, corn, and very bare ground are easily distinguishable, sorghum, alfalfa, and young wheat are harder to distinguish. Distinguishability will be improved if the imagery is examined in time sequence so that changes between times of planning, maturation, and harvest provide additional discriminant tools. A comparison between radar and photography indicates that radar performed surprisingly well in crop discrimination in western Kansas and warrants further study.

Using Imaging Spectrometry to Approach Crop Classification from a Water Management Perspective

NASA Astrophysics Data System (ADS)

Shivers, S.; Roberts, D. A.

2017-12-01

We use hyperspectral remote sensing imagery to classify crops in the Central Valley of California at a level that would be of use to water managers. In California irrigated agriculture uses 80 percent of the state's water supply with differences in water application rate varying by as large as a factor of three, dependent on crop type. Therefore, accurate water resource accounting is dependent upon accurate crop mapping. While on-the-ground crop accounting at the county level requires significant labor and time inputs, remote sensing has the potential to map crops over a greater spatial area with more frequent time intervals. Specifically, imaging spectrometry with its wide spectral range has the ability to detect small spectral differences at the field-level scale that may be indiscernible to multispectral sensors such as Landsat. In this study, crops in the Central Valley were classified into nine categories defined and used by the California Department of Water Resources as having similar water usages. We used the random forest classifier on Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) imagery from June 2013, 2014 and 2015 to analyze accuracy of multi-temporal images and to investigate the extent to which cropping patterns have changed over the course of the 2013-2015 drought. Initial results show accuracies of over 90% for all three years, indicating that hyperspectral imagery has the potential to identify crops by water use group at a single time step with a single sensor, allowing cropping patterns to be monitored in anticipation of water needs.

Characterization of protein and carbohydrate mid-IR spectral features in crop residues

NASA Astrophysics Data System (ADS)

Xin, Hangshu; Zhang, Yonggen; Wang, Mingjun; Li, Zhongyu; Wang, Zhibo; Yu, Peiqiang

2014-08-01

To the best of our knowledge, a few studies have been conducted on inherent structure spectral traits related to biopolymers of crop residues. The objective of this study was to characterize protein and carbohydrate structure spectral features of three field crop residues (rice straw, wheat straw and millet straw) in comparison with two crop vines (peanut vine and pea vine) by using Fourier transform infrared spectroscopy (FTIR) technique with attenuated total reflectance (ATR). Also, multivariate analyses were performed on spectral data sets within the regions mainly related to protein and carbohydrate in this study. The results showed that spectral differences existed in mid-IR peak intensities that are mainly related to protein and carbohydrate among these crop residue samples. With regard to protein spectral profile, peanut vine showed the greatest mid-IR band intensities that are related to protein amide and protein secondary structures, followed by pea vine and the rest three field crop straws. The crop vines had 48-134% higher spectral band intensity than the grain straws in spectral features associated with protein. Similar trends were also found in the bands that are mainly related to structural carbohydrates (such as cellulosic compounds). However, the field crop residues had higher peak intensity in total carbohydrates region than the crop vines. Furthermore, spectral ratios varied among the residue samples, indicating that these five crop residues had different internal structural conformation. However, multivariate spectral analyses showed that structural similarities still exhibited among crop residues in the regions associated with protein biopolymers and carbohydrate. Further study is needed to find out whether there is any relationship between spectroscopic information and nutrition supply in various kinds of crop residue when fed to animals.

Characterization of protein and carbohydrate mid-IR spectral features in crop residues.

PubMed

Xin, Hangshu; Zhang, Yonggen; Wang, Mingjun; Li, Zhongyu; Wang, Zhibo; Yu, Peiqiang

2014-08-14

To the best of our knowledge, a few studies have been conducted on inherent structure spectral traits related to biopolymers of crop residues. The objective of this study was to characterize protein and carbohydrate structure spectral features of three field crop residues (rice straw, wheat straw and millet straw) in comparison with two crop vines (peanut vine and pea vine) by using Fourier transform infrared spectroscopy (FTIR) technique with attenuated total reflectance (ATR). Also, multivariate analyses were performed on spectral data sets within the regions mainly related to protein and carbohydrate in this study. The results showed that spectral differences existed in mid-IR peak intensities that are mainly related to protein and carbohydrate among these crop residue samples. With regard to protein spectral profile, peanut vine showed the greatest mid-IR band intensities that are related to protein amide and protein secondary structures, followed by pea vine and the rest three field crop straws. The crop vines had 48-134% higher spectral band intensity than the grain straws in spectral features associated with protein. Similar trends were also found in the bands that are mainly related to structural carbohydrates (such as cellulosic compounds). However, the field crop residues had higher peak intensity in total carbohydrates region than the crop vines. Furthermore, spectral ratios varied among the residue samples, indicating that these five crop residues had different internal structural conformation. However, multivariate spectral analyses showed that structural similarities still exhibited among crop residues in the regions associated with protein biopolymers and carbohydrate. Further study is needed to find out whether there is any relationship between spectroscopic information and nutrition supply in various kinds of crop residue when fed to animals. Copyright © 2014 Elsevier B.V. All rights reserved.

Monitoring Global Crop Condition Indicators Using a Web-Based Visualization Tool

Treesearch

Bob Tetrault; Bob Baldwin

2006-01-01

Global crop condition information for major agricultural regions in the world can be monitored using the web-based application called Crop Explorer. With this application, U.S. and international producers, traders, researchers, and the public can access remote sensing information used by agricultural economists and scientists who predict crop production worldwide. For...

Comparing crop rotations between organic and conventional farming.

PubMed

Barbieri, Pietro; Pellerin, Sylvain; Nesme, Thomas

2017-10-23

Cropland use activities are major drivers of global environmental changes and of farming system resilience. Rotating crops is a critical land-use driver, and a farmers' key strategy to control environmental stresses and crop performances. Evidence has accumulated that crop rotations have been dramatically simplified over the last 50 years. In contrast, organic farming stands as an alternative production way that promotes crop diversification. However, our understanding of crop rotations is surprisingly limited. In order to understand if organic farming would result in more diversified and multifunctional landscapes, we provide here a novel, systematic comparison of organic-to-conventional crop rotations at the global scale based on a meta-analysis of the scientific literature, paired with an independent analysis of organic-to-conventional land-use. We show that organic farming leads to differences in land-use compared to conventional: overall, crop rotations are 15% longer and result in higher diversity and evener crop species distribution. These changes are driven by a higher abundance of temporary fodders, catch and cover-crops, mostly to the detriment of cereals. We also highlighted differences in organic rotations between Europe and North-America, two leading regions for organic production. This increased complexity of organic crop rotations is likely to enhance ecosystem service provisioning to agroecosystems.

Large scale maps of cropping intensity in Asia from MODIS

NASA Astrophysics Data System (ADS)

Gray, J. M.; Friedl, M. A.; Frolking, S. E.; Ramankutty, N.; Nelson, A.

2013-12-01

Agricultural systems are geographically extensive, have profound significance to society, and also affect regional energy, carbon, and water cycles. Since most suitable lands worldwide have been cultivated, there is growing pressure to increase yields on existing agricultural lands. In tropical and sub-tropical regions, multi-cropping is widely used to increase food production, but regional-to-global information related to multi-cropping practices is poor. Such information is of critical importance to ensure sustainable food production while mitigating against negative environmental impacts associated with agriculture such as contamination and depletion of freshwater resources. Unfortunately, currently available large-area inventory statistics are inadequate because they do not capture important spatial patterns in multi-cropping, and are generally not available in a timeframe that can be used to help manage cropping systems. High temporal resolution sensors such as MODIS provide an excellent source of information for addressing this need. However, relative to studies that document agricultural extensification, systematic assessment of agricultural intensification via multi-cropping has received relatively little attention. The goal of this work is to help close this methodological and information gap by developing methods that use multi-temporal remote sensing to map multi-cropping systems in Asia. Image time series analysis is especially challenging in Asia because atmospheric conditions including clouds and aerosols lead to high frequencies of missing or low quality remote sensing observations, especially during the Asian Monsoon. The methodology that we use for this work builds upon the algorithm used to produce the MODIS Land Cover Dynamics product (MCD12Q2), but employs refined methods to segment, smooth, and gap-fill 8-day EVI time series calculated from MODIS BRDF corrected surface reflectances. Crop cycle segments are identified based on changes in slope

38 CFR 4.31 - Zero percent evaluations.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 38 Pensions, Bonuses, and Veterans' Relief 1 2010-07-01 2010-07-01 false Zero percent evaluations... FOR RATING DISABILITIES General Policy in Rating § 4.31 Zero percent evaluations. In every instance where the schedule does not provide a zero percent evaluation for a diagnostic code, a zero percent...

38 CFR 4.31 - Zero percent evaluations.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 38 Pensions, Bonuses, and Veterans' Relief 1 2014-07-01 2014-07-01 false Zero percent evaluations... FOR RATING DISABILITIES General Policy in Rating § 4.31 Zero percent evaluations. In every instance where the schedule does not provide a zero percent evaluation for a diagnostic code, a zero percent...

38 CFR 4.31 - Zero percent evaluations.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 38 Pensions, Bonuses, and Veterans' Relief 1 2012-07-01 2012-07-01 false Zero percent evaluations... FOR RATING DISABILITIES General Policy in Rating § 4.31 Zero percent evaluations. In every instance where the schedule does not provide a zero percent evaluation for a diagnostic code, a zero percent...

38 CFR 4.31 - Zero percent evaluations.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 38 Pensions, Bonuses, and Veterans' Relief 1 2013-07-01 2013-07-01 false Zero percent evaluations... FOR RATING DISABILITIES General Policy in Rating § 4.31 Zero percent evaluations. In every instance where the schedule does not provide a zero percent evaluation for a diagnostic code, a zero percent...

38 CFR 4.31 - Zero percent evaluations.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 38 Pensions, Bonuses, and Veterans' Relief 1 2011-07-01 2011-07-01 false Zero percent evaluations... FOR RATING DISABILITIES General Policy in Rating § 4.31 Zero percent evaluations. In every instance where the schedule does not provide a zero percent evaluation for a diagnostic code, a zero percent...

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Crop Frequency Mapping for Land Use Intensity Estimation During Three Decades

NASA Astrophysics Data System (ADS)

Schmidt, Michael; Tindall, Dan

2016-08-01

Crop extent and frequency maps are an important input to inform the debate around land value and competitive land uses, food security and sustainability of agricultural practices. Such spatial datasets are likely to support decisions on natural resource management, planning and policy. The complete Landsat Time Series (LTS) archive for 23 Landsat footprints in western Queensland from 1987 to 2015 was used in a multi-temporal mapping approach. Spatial, spectral and temporal information were combined in multiple crop-modelling steps, supported by on ground training data sampled across space and time for the classes Crop and No-Crop. Temporal information within summer and winter growing seasons for each year were summarised, and combined with various vegetation indices and band ratios computed from a mid-season spectral-composite image. All available temporal information was spatially aggregated to the scale of image segments in the mid- season composite for each growing season and used to train a random forest classifier for a Crop and No- Crop classification. Validation revealed that the predictive accuracy varied by growing season and region to be within k = 0.88 to 0.97 and are thus suitable for mapping current and historic cropping activity. Crop frequency maps were produced for all regions at different time intervals. The crop frequency maps were validated separately with a historic crop information time series. Different land use intensities and conversions e.g. from agricultural to pastures are apparent and potential drivers of these conversions are discussed.

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.

Intensifying a semi-arid dryland crop rotation by replacing fallow with pea

USDA-ARS?s Scientific Manuscript database

Increasing dryland cropping system intensity in the semi-arid central Great Plains by reducing frequency of fallow can add diversity to cropping systems and decrease erosion potential. However elimination of the periodic fallow phase has been shown to reduce yields of subsequent crops in this region...

Breeding and genomics of vegetable crops for climate-resilience traits

USDA-ARS?s Scientific Manuscript database

Vegetable crop improvement is being pursued extensively and globally by seed companies, NGOs, universities, and governmental organizations, including several CGIAR research centers. Globally and regionally, many crops are identified as vegetables, and among them, breeding and genomics is well-develo...

Remote sensing applications for estimating changes on crop evapotranspiration of the most water intensive crops, due to climate change in Cyprus

NASA Astrophysics Data System (ADS)

Papadavid, G.; Neocleous, D.; Stylianou, A.; Markou, M.; Kountios, G.; Hadjimitsis, D.

2016-08-01

Water allocation to crops, and especially to the most water intensive ones, has always been of great importance in agricultural process. Deficit or excess water irrigation quantities could create either crop health related problems or water over-consumption situation which lead to stored water reduction and toxic material depletion to deeper ground layers, respectively. In this context, and under the current conditions, where Cyprus is facing effects of climate changes, purpose of this study is basically to estimate the needed crop water requirements of the past (1995-2004) and the corresponding ones of the present (2005-2015) in order to test if there were any significant changes regarding the crop water requirements of the most water intensive trees in Cyprus. Mediterranean region has been identified as the region that will suffer the most from climate change. Thus the paper refers to effects of climate changes on crop evapotranspiration (ETc) using remotely sensed data from Landsat TM/ ETM+ / OLI employing a sound methodology used worldwide, the Surface Energy Balance Algorithm for Land (SEBAL). Though the general feeling is that of changes on climate will consequently affect ETc, the results have indicated that there is no significant effect of climate change on crop evapotranspiration, despite the fact that some climatic factors have changed. Applying Student's T-test, the mean values for the most water intensive trees in Cyprus of the 1994-2004 decade have shown no statistical difference from the mean values of 2005-2015 decade's for all the cases, concluding that the climate change taking place the last decades in Cyprus have either not affected the crop evapotranspiration or the crops have manage to adapt into the new environmental conditions through time.

75 FR 59057 - Common Crop Insurance Regulations, Cotton Crop Insurance Provisions and Macadamia Nut Crop...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-09-27

... Crop Insurance Regulations, Cotton Crop Insurance Provisions and Macadamia Nut Crop Insurance... cotton and macadamia nuts that published March 30, 2010. DATES: Effective Date: September 27, 2010. FOR... Common Crop Insurance Regulations, Basic Provisions and applicable Crop Provisions, including the Cotton...

Diverse effects of crop distribution and climate change on crop production in the agro-pastoral transitional zone of China

NASA Astrophysics Data System (ADS)

Qiao, Jianmin; Yu, Deyong; Wang, Qianfeng; Liu, Yupeng

2018-06-01

Both crop distribution and climate change are important drivers for crop production and can affect food security, which is an important requirement for sustainable development. However, their effects on crop production are confounded and warrant detailed investigation. As a key area for food production that is sensitive to climate change, the agro-pastoral transitional zone (APTZ) plays a significant role in regional food security. To investigate the respective effects of crop distribution and climate change on crop production, the well-established GIS-based Environmental Policy Integrated Climate (EPIC) model was adopted with different scenario designs in this study. From 1980 to 2010, the crop distribution for wheat, maize, and rice witnessed a dramatic change due to agricultural policy adjustments and ecological engineering-related construction in the APTZ. At the same time, notable climate change was observed. The simulation results indicated that the climate change had a positive impact on the crop production of wheat, maize, and rice, while the crop distribution change led to an increase in the production of maize and rice, but a decrease in the wheat production. Comparatively, crop distribution change had a larger impact on wheat (-1.71 × 106 t) and maize (8.53 × 106 t) production, whereas climate change exerted a greater effect on rice production (0.58 × 106 t), during the period from 1980 to 2010 in the APTZ. This study is helpful to understand the mechanism of the effects of crop distribution and climate change on crop production, and aid policy makers in reducing the threat of future food insecurity.

Diverse effects of crop distribution and climate change on crop production in the agro-pastoral transitional zone of China

NASA Astrophysics Data System (ADS)

Qiao, Jianmin; Yu, Deyong; Wang, Qianfeng; Liu, Yupeng

2017-07-01

Both crop distribution and climate change are important drivers for crop production and can affect food security, which is an important requirement for sustainable development. However, their effects on crop production are confounded and warrant detailed investigation. As a key area for food production that is sensitive to climate change, the agro-pastoral transitional zone (APTZ) plays a significant role in regional food security. To investigate the respective effects of crop distribution and climate change on crop production, the well-established GIS-based Environmental Policy Integrated Climate (EPIC) model was adopted with different scenario designs in this study. From 1980 to 2010, the crop distribution for wheat, maize, and rice witnessed a dramatic change due to agricultural policy adjustments and ecological engineering-related construction in the APTZ. At the same time, notable climate change was observed. The simulation results indicated that the climate change had a positive impact on the crop production of wheat, maize, and rice, while the crop distribution change led to an increase in the production of maize and rice, but a decrease in the wheat production. Comparatively, crop distribution change had a larger impact on wheat (-1.71 × 106 t) and maize (8.53 × 106 t) production, whereas climate change exerted a greater effect on rice production (0.58 × 106 t), during the period from 1980 to 2010 in the APTZ. This study is helpful to understand the mechanism of the effects of crop distribution and climate change on crop production, and aid policy makers in reducing the threat of future food insecurity.

Carbon Dynamics of Bioenergy Cropping Systems Compared to Conventional Cotton Cropping Systems in the Southern Cotton Belt Region of the U.S.

NASA Astrophysics Data System (ADS)

Rajan, N.; Sharma, S.; Casey, K.; Maas, S. J.

2015-12-01

We are facing an unprecedented challenge in securing America's energy future. To address this challenge, increased biofuel crop production is needed. Second-generation biofuels are made from the by-products of intensive agriculture or from less-intensive agriculture on more marginal lands. The Southwestern U.S. Cotton Belt can play a significant role in this effort through a change from more conventional crops (like continuous cotton) to second-generation biofuel feedstocks (biomass sorghum and perennial grasses). We have established eddy covariance flux towers in producer fields in the Southern High Plains region. Among the four land uses compared, the net carbon uptake was the highest for the biomass sorghum field. During the year 2014, the biomass sorghum field gained approximately 672 gC m-2y-1. The next highest carbon uptake was recorded for the Old World Bluestem grass field, which was approximately 301 gC m-2y-1. The dominant land use in the region is cotton. While the forage sorghum and grass fields acted as net carbon sinks, the irrigated cotton field acted as a net carbon source to the atmosphere during the same period. The irrigated cotton field exhibited a net carbon loss of approximately 246 gC m-2y-1. In contrast, the dryland cotton field acted as a net carbon sink, with a total uptake of approximately 58 g C m-2y-1. The net primary production of the irrigated cotton field was higher than that of the dryland cotton field, yet the irrigated field was a significant carbon source to the atmosphere. This was due to conventional tillage practices combined with irrigation which enhanced the ecosystem respiration significantly compared to the dryland field. In 2014, an early spring cold front caused poor germination of seeds in the majority of the cotton fields in the region, including the eddy covariance site. This site was re-planted on 9 June, which shortened the growing season for cotton. This was also a contributing factor to this field being a net

Inspiration: One Percent and Rising

ERIC Educational Resources Information Center

Walling, Donovan R.

2009-01-01

Inventor Thomas Edison once famously declared, "Genius is one percent inspiration and ninety-nine percent perspiration." If that's the case, then the students the author witnessed at the International Student Media Festival (ISMF) last November in Orlando, Florida, are geniuses and more. The students in the ISMF pre-conference workshop…

Reversed-polarity regions

NASA Technical Reports Server (NTRS)

Tang, F.

1980-01-01

The 58 RPRS studied have a lifespan comparable to normal active regions and have no tendency to rotate toward a more normal alignment. They seem to have stable configurations with no apparent evidence suggesting stress due to their anomalous magnetic alignment. Magnetic complexity in RPRs is the key to flare productivity just as it is in normal regions - weak field RPRs produced no flares and regions with complex spots produced more flares than regions with noncomplex spots by a factor of 5. The RPRs however, differ from normal regions in the frequency of having complex spots, particularly the long lived complex spots, in them. Less than 17 percent of normal ARs have complex spots; less than 1.8 percent have long lived complex spots. In contrast, 41 percent of RPRs have complex spots and 24 percent have long lived complex spots.

[Accuracy improvement of spectral classification of crop using microwave backscatter data].

PubMed

Jia, Kun; Li, Qiang-Zi; Tian, Yi-Chen; Wu, Bing-Fang; Zhang, Fei-Fei; Meng, Ji-Hua

2011-02-01

In the present study, VV polarization microwave backscatter data used for improving accuracies of spectral classification of crop is investigated. Classification accuracy using different classifiers based on the fusion data of HJ satellite multi-spectral and Envisat ASAR VV backscatter data are compared. The results indicate that fusion data can take full advantage of spectral information of HJ multi-spectral data and the structure sensitivity feature of ASAR VV polarization data. The fusion data enlarges the spectral difference among different classifications and improves crop classification accuracy. The classification accuracy using fusion data can be increased by 5 percent compared to the single HJ data. Furthermore, ASAR VV polarization data is sensitive to non-agrarian area of planted field, and VV polarization data joined classification can effectively distinguish the field border. VV polarization data associating with multi-spectral data used in crop classification enlarges the application of satellite data and has the potential of spread in the domain of agriculture.

Origins of food crops connect countries worldwide

USDA-ARS?s Scientific Manuscript database

Research into the origins of food plants has led to the recognition that specific geographic regions around the world have been of particular importance to the development of agricultural crops. Yet the relative contributions of these different regions in the context of current food systems have not...

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.

Cover crop biomass production and water use in the Central Great Plains

USDA-ARS?s Scientific Manuscript database

The water-limited environment of the semi-arid central Great Plains may not have potential to produce enough cover crop biomass to generate benefits associated with cover crop use in more humid regions. There have been reports that cover crops grown in mixtures produce more biomass with greater wate...

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;

Percents Are Not Natural Numbers

ERIC Educational Resources Information Center

Jacobs, Jennifer A.

2013-01-01

Adults are prone to treating percents, one representational format of rational numbers, as novel cases of natural number. This suggests that percent values are not differentiated from natural numbers; a conceptual shift from the natural numbers to the rational numbers has not yet occurred. This is most surprising, considering people are inundated…

Ozone risk for crops and pastures in present and future climates

NASA Astrophysics Data System (ADS)

Fuhrer, Jürg

2009-02-01

Ozone is the most important regional-scale air pollutant causing risks for vegetation and human health in many parts of the world. Ozone impacts on yield and quality of crops and pastures depend on precursor emissions, atmospheric transport and leaf uptake and on the plant’s biochemical defence capacity, all of which are influenced by changing climatic conditions, increasing atmospheric CO2 and altered emission patterns. In this article, recent findings about ozone effects under current conditions and trends in regional ozone levels and in climatic factors affecting the plant’s sensitivity to ozone are reviewed in order to assess implications of these developments for future regional ozone risks. Based on pessimistic IPCC emission scenarios for many cropland regions elevated mean ozone levels in surface air are projected for 2050 and beyond as a result of both increasing emissions and positive effects of climate change on ozone formation and higher cumulative ozone exposure during an extended growing season resulting from increasing length and frequency of ozone episodes. At the same time, crop sensitivity may decline in areas where warming is accompanied by drying, such as southern and central Europe, in contrast to areas at higher latitudes where rapid warming is projected to occur in the absence of declining air and soil moisture. In regions with rapid industrialisation and population growth and with little regulatory action, ozone risks are projected to increase most dramatically, thus causing negative impacts major staple crops such as rice and wheat and, consequently, on food security. Crop improvement may be a way to increase crop cross-tolerance to co-occurring stresses from heat, drought and ozone. However, the review reveals that besides uncertainties in climate projections, parameters in models for ozone risk assessment are also uncertain and model improvements are necessary to better define specific targets for crop improvements, to identify regions

Large-scale alcohol production from corn, grain sorghum, and crop residues

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

Turhollow, A.F. Jr.

1982-01-01

The potential impacts that large-scale alcohol production from corn, grain sorghum, and crop residues may have on US agriculture in the year 2000 are investigated. A one-land-group interregional linear-programming model is used. The objective function is to minimize the cost of production in the agricultural sector, given specified crop demands and constrained resources. The impacts that levels of alcohol production, ranging from zero to 12 billion gallons, have at two projected levels of crop demands, two grain-to-alcohol conversion and two milling methods, wet and dry, rates are considered. The impacts that large-scale fuel alcohol production has on US agriculture aremore » small. The major impacts that occur are the substitution of milling by-products, DDG, gluten feed, and gluten meal, for soybean meal in livestock feed rations. Production of 12 billion gallons of alcohol is estimated to be equivalent to an 18 percent increase in crop exports. Improving the grain-to-alcohol conversion rate from 2.6 to 3.0 gallons per bushels reduces the overall cost of agricultural production by $989 billion when 12 billion gallons of alcohol are produced.« less

Compatibility of switchgrass as an energy crop in farming systems of the southeastern USA

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

Bransby, D.I.; Rodriguez-Kabana, R.; Sladden, S.E.

1993-12-31

The objective of this paper is to examine the compatibility of switchgrass as an energy crop in farming systems in the southeastern USA, relative to other regions. In particular, the issues addressed are (1) competition between switchgrass as an energy crop and existing farm enterprises, based primarily on economic returns, (2) complementarity between switchgrass and existing farm enterprises, and (3) environmental benefits. Because projected economic returns for switchgrass as an energy crop are highest in the Southeast, and returns from forestry and beef pastures (the major existing enterprises) are low, there is a very strong economic incentive in this region.more » In contrast, based on current information, economic viability of switchgrass as an energy crop in other regions appears doubtful. In addition, switchgrass in the southeastern USA would complement forage-livestock production, row crop production and wildlife and would provide several additional environmental benefits. It is concluded that the southeastern USA offers the greatest opportunity for developing switchgrass as an economically viable energy crop.« less

Effect of Mixed Systems on Crop Productivity

NASA Astrophysics Data System (ADS)

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

2017-04-01

The goals of this non-irrigated research has been to determine the effect of mixed systems integration on crop, soil, and beef cattle production in the northern Great Plains region of the United States. Over a 5-year period, growing spring wheat (HRSW-C) continuously year after year was compared to a 5-year crop rotation that included spring wheat (HRSW-R), cover crop (dual crop consisting of winter triticale/hairy vetch seeded in the fall and harvested for hay followed by a 7-species cover crop that was seeded in June after hay harvest), forage corn, field pea/barley, and sunflower. Control 5-year HRSW yield was 2690 kg/ha compared to 2757 kg/ha for HRSW grown in rotation. Available soil nitrogen (N) is often the most important limitation for crop production. Expensive fertilizer inputs were reduced in this study due to the mixed system's complementarity in which the rotation system that included beef cattle grazing sustained N availability and increased nutrient cycling, which had a positive effect on all crops grown in the rotation. Growing HRSW continuously requires less intensive management and in this research was 14.5% less profitable. Whereas, when crop management increased and complementing crops were grown in rotation to produce crops and provide feed for grazing livestock, soil nutrient cycling improved. Increased nutrient cycling increased crop rotation yields and yearling beef cattle steers that grazing annual forages in the rotation gain more body weight than similar steers grazing NGP native range. Results of this long-term research will be presented in a PICO format for participant discussion.

Impact of nowcasting on the production and processing of agricultural crops. [in the US

NASA Technical Reports Server (NTRS)

Dancer, W. S.; Tibbitts, T. W.

1973-01-01

The value was studied of improved weather information and weather forecasting to farmers, growers, and agricultural processing industries in the United States. The study was undertaken to identify the production and processing operations that could be improved with accurate and timely information on changing weather patterns. Estimates were then made of the potential savings that could be realized with accurate information about the prevailing weather and short term forecasts for up to 12 hours. This weather information has been termed nowcasting. The growing, marketing, and processing operations of the twenty most valuable crops in the United States were studied to determine those operations that are sensitive to short-term weather forecasting. Agricultural extension specialists, research scientists, growers, and representatives of processing industries were consulted and interviewed. The value of the crops included in this survey and their production levels are given. The total value for crops surveyed exceeds 24 billion dollars and represents more than 92 percent of total U.S. crop value.

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. Copyright © 2010. Published by Elsevier B.V.

The commercial use of satellite data to monitor the potato crop in the Columbia Basin

NASA Technical Reports Server (NTRS)

Waddington, George R., Jr.; Lamb, Frank G.

1990-01-01

The imaging of potato crops with satellites is described and evaluated in terms of the commercial application of the remotely sensed data. The identification and analysis of the crops is accomplished with multiple images acquired from the Landsat MSS and TM systems. The data are processed on a PC with image-procesing software which produces images of the seven 1024 x 1024 pixel windows which are subdivided into 21 512 x 512 pixel windows. Maximization of imaged data throughout the year aids in the identification of crop types by IR reflectance. The classification techniques involve the use of six or seven spectral classes for particular image dates. Comparisons with ground-truth data show good agreement; for example, potato fields are identified correctly 90 percent of the time. Acreage estimates and crop-condition assessments can be made from satellite data and used for corrective agricultural action.

Trade-Offs between Economic and Environmental Impacts of Introducing Legumes into Cropping Systems

PubMed Central

Reckling, Moritz; Bergkvist, Göran; Watson, Christine A.; Stoddard, Frederick L.; Zander, Peter M.; Walker, Robin L.; Pristeri, Aurelio; Toncea, Ion; Bachinger, Johann

2016-01-01

Europe's agriculture is highly specialized, dependent on external inputs and responsible for negative environmental impacts. Legume crops are grown on less than 2% of the arable land and more than 70% of the demand for protein feed supplement is imported from overseas. The integration of legumes into cropping systems has the potential to contribute to the transition to a more resource-efficient agriculture and reduce the current protein deficit. Legume crops influence the production of other crops in the rotation making it difficult to evaluate the overall agronomic effects of legumes in cropping systems. A novel assessment framework was developed and applied in five case study regions across Europe with the objective of evaluating trade-offs between economic and environmental effects of integrating legumes into cropping systems. Legumes resulted in positive and negative impacts when integrated into various cropping systems across the case studies. On average, cropping systems with legumes reduced nitrous oxide emissions by 18 and 33% and N fertilizer use by 24 and 38% in arable and forage systems, respectively, compared to systems without legumes. Nitrate leaching was similar with and without legumes in arable systems and reduced by 22% in forage systems. However, grain legumes reduced gross margins in 3 of 5 regions. Forage legumes increased gross margins in 3 of 3 regions. Among the cropping systems with legumes, systems could be identified that had both relatively high economic returns and positive environmental impacts. Thus, increasing the cultivation of legumes could lead to economic competitive cropping systems and positive environmental impacts, but achieving this aim requires the development of novel management strategies informed by the involvement of advisors and farmers. PMID:27242870

Trade-Offs between Economic and Environmental Impacts of Introducing Legumes into Cropping Systems.

PubMed

Reckling, Moritz; Bergkvist, Göran; Watson, Christine A; Stoddard, Frederick L; Zander, Peter M; Walker, Robin L; Pristeri, Aurelio; Toncea, Ion; Bachinger, Johann

2016-01-01

Europe's agriculture is highly specialized, dependent on external inputs and responsible for negative environmental impacts. Legume crops are grown on less than 2% of the arable land and more than 70% of the demand for protein feed supplement is imported from overseas. The integration of legumes into cropping systems has the potential to contribute to the transition to a more resource-efficient agriculture and reduce the current protein deficit. Legume crops influence the production of other crops in the rotation making it difficult to evaluate the overall agronomic effects of legumes in cropping systems. A novel assessment framework was developed and applied in five case study regions across Europe with the objective of evaluating trade-offs between economic and environmental effects of integrating legumes into cropping systems. Legumes resulted in positive and negative impacts when integrated into various cropping systems across the case studies. On average, cropping systems with legumes reduced nitrous oxide emissions by 18 and 33% and N fertilizer use by 24 and 38% in arable and forage systems, respectively, compared to systems without legumes. Nitrate leaching was similar with and without legumes in arable systems and reduced by 22% in forage systems. However, grain legumes reduced gross margins in 3 of 5 regions. Forage legumes increased gross margins in 3 of 3 regions. Among the cropping systems with legumes, systems could be identified that had both relatively high economic returns and positive environmental impacts. Thus, increasing the cultivation of legumes could lead to economic competitive cropping systems and positive environmental impacts, but achieving this aim requires the development of novel management strategies informed by the involvement of advisors and farmers.

The green, blue and grey water footprint of crops and derived crop products

NASA Astrophysics Data System (ADS)

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

2011-01-01

This study quantifies the green, blue and grey water footprint of global crop production in a spatially-explicit way for the period 1996-2005. The assessment is global and improves upon earlier research by taking a high-resolution approach, estimating the water footprint of 126 crops at a 5 by 5 arc min grid. We have used a grid-based dynamic water balance model to calculate crop water use over time, with a time step of one day. The model takes into account the daily soil water balance and climatic conditions for each grid cell. In addition, the water pollution associated with the use of nitrogen fertilizer in crop production is estimated for each grid cell. The crop evapotranspiration of additional 20 minor crops is calculated with the CROPWAT model. In addition, we have calculated the water footprint of more than two hundred derived crop products, including various flours, beverages, fibres and biofuels. We have used the water footprint assessment framework as in the guideline of the water footprint network. Considering the water footprints of primary crops, we see that global average water footprint per ton of crop increases from sugar crops (roughly 200 m3 ton-1), vegetables (300 m3 ton-1), roots and tubers (400 m3 ton-1), fruits (1000 m3 ton-1), cereals} (1600 m3 ton-1), oil crops (2400 m3 ton-1) to pulses (4000 m3 ton-1). The water footprint varies, however, across different crops per crop category and per production region as well. Besides, if one considers the water footprint per kcal, the picture changes as well. When considered per ton of product, commodities with relatively large water footprints are: coffee, tea, cocoa, tobacco, spices, nuts, rubber and fibres. The analysis of water footprints of different biofuels shows that bio-ethanol has a lower water footprint (in m3 GJ-1) than biodiesel, which supports earlier analyses. The crop used matters significantly as well: the global average water footprint of bio-ethanol based on sugar beet amounts to 51

The green, blue and grey water footprint of crops and derived crop products

NASA Astrophysics Data System (ADS)

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

2011-05-01

This study quantifies the green, blue and grey water footprint of global crop production in a spatially-explicit way for the period 1996-2005. The assessment improves upon earlier research by taking a high-resolution approach, estimating the water footprint of 126 crops at a 5 by 5 arc minute grid. We have used a grid-based dynamic water balance model to calculate crop water use over time, with a time step of one day. The model takes into account the daily soil water balance and climatic conditions for each grid cell. In addition, the water pollution associated with the use of nitrogen fertilizer in crop production is estimated for each grid cell. The crop evapotranspiration of additional 20 minor crops is calculated with the CROPWAT model. In addition, we have calculated the water footprint of more than two hundred derived crop products, including various flours, beverages, fibres and biofuels. We have used the water footprint assessment framework as in the guideline of the Water Footprint Network. Considering the water footprints of primary crops, we see that the global average water footprint per ton of crop increases from sugar crops (roughly 200 m3 ton-1), vegetables (300 m3 ton-1), roots and tubers (400 m3 ton-1), fruits (1000 m3 ton-1), cereals (1600 m3 ton-1), oil crops (2400 m3 ton-1) to pulses (4000 m3 ton-1). The water footprint varies, however, across different crops per crop category and per production region as well. Besides, if one considers the water footprint per kcal, the picture changes as well. When considered per ton of product, commodities with relatively large water footprints are: coffee, tea, cocoa, tobacco, spices, nuts, rubber and fibres. The analysis of water footprints of different biofuels shows that bio-ethanol has a lower water footprint (in m3 GJ-1) than biodiesel, which supports earlier analyses. The crop used matters significantly as well: the global average water footprint of bio-ethanol based on sugar beet amounts to 51 m3 GJ-1

Increased food production and reduced water use through optimized crop distribution

NASA Astrophysics Data System (ADS)

Davis, Kyle Frankel; Rulli, Maria Cristina; Seveso, Antonio; D'Odorico, Paolo

2017-12-01

Growing demand for agricultural commodities for food, fuel and other uses is expected to be met through an intensification of production on lands that are currently under cultivation. Intensification typically entails investments in modern technology — such as irrigation or fertilizers — and increases in cropping frequency in regions suitable for multiple growing seasons. Here we combine a process-based crop water model with maps of spatially interpolated yields for 14 major food crops to identify potential differences in food production and water use between current and optimized crop distributions. We find that the current distribution of crops around the world neither attains maximum production nor minimum water use. We identify possible alternative configurations of the agricultural landscape that, by reshaping the global distribution of crops within current rainfed and irrigated croplands based on total water consumption, would feed an additional 825 million people while reducing the consumptive use of rainwater and irrigation water by 14% and 12%, respectively. Such an optimization process does not entail a loss of crop diversity, cropland expansion or impacts on nutrient and feed availability. It also does not necessarily invoke massive investments in modern technology that in many regions would require a switch from smallholder farming to large-scale commercial agriculture with important impacts on rural livelihoods.

Cover crops support ecological intensification of arable cropping systems

NASA Astrophysics Data System (ADS)

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

2017-02-01

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

Winter Crop Mapping for Improving Crop Production Estimates in Argentina Using Moderation Resolution Satellite Imagery

NASA Astrophysics Data System (ADS)

Humber, M. L.; Copati, E.; Sanchez, A.; Sahajpal, R.; Puricelli, E.; Becker-Reshef, I.

2017-12-01

Accurate crop production data is fundamental for reducing uncertainly and volatility in the domestic and international agricultural markets. The Agricultural Estimates Department of the Buenos Aires Grain Exchange has worked since 2000 on the estimation of different crop production data. With this information, the Grain Exchange helps different actors of the agricultural chain, such as producers, traders, seed companies, market analyst, policy makers, into their day to day decision making. Since 2015/16 season, the Grain Exchange has worked on the development of a new earth observations-based method to identify winter crop planted area at a regional scale with the aim of improving crop production estimates. The objective of this new methodology is to create a reliable winter crop mask at moderate spatial resolution using Landsat-8 imagery by exploiting bi-temporal differences in the phenological stages of winter crops as compared to other landcover types. In collaboration with the University of Maryland, the map has been validated by photointerpretation of a stratified statistically random sample of independent ground truth data in the four largest producing provinces of Argentina: Buenos Aires, Cordoba, La Pampa, and Santa Fe. In situ measurements were also used to further investigate conditions in the Buenos Aires province. Preliminary results indicate that while there are some avenues for improvement, overall the classification accuracy of the cropland and non-cropland classes are sufficient to improve downstream production estimates. Continuing research will focus on improving the methodology for winter crop mapping exercises on a yearly basis as well as improving the sampling methodology to optimize collection of validation data in the future.

Estimating crop yields and crop evapotranspiration distributions from remote sensing and geospatial agricultural data

NASA Astrophysics Data System (ADS)

Smith, T.; McLaughlin, D.

2017-12-01

Growing more crops to provide a secure food supply to an increasing global population will further stress land and water resources that have already been significantly altered by agriculture. The connection between production and resource use depends on crop yields and unit evapotranspiration (UET) rates that vary greatly, over both time and space. For regional and global analyses of food security it is appropriate to treat yield and UET as uncertain variables conditioned on climatic and soil properties. This study describes how probability distributions of these variables can be estimated by combining remotely sensed land use and evapotranspiration data with in situ agronomic and soils data, all available at different resolutions and coverages. The results reveal the influence of water and temperature stress on crop yield at large spatial scales. They also provide a basis for stochastic modeling and optimization procedures that explicitly account for uncertainty in the environmental factors that affect food production.

Characterization of the Water Soluble Component of Inedible Residue from Candidate CELSS Crops

NASA Technical Reports Server (NTRS)

Garland, Jay

1992-01-01

Recycling of inorganic nutrients required for plant growth will be a necessary component of a fully closed, bioregenerative life support system. This research characterized the recovery of plant nutrients from the inedible fraction of three crop types (wheat, potato, and soybean) by soaking, or leaching, in water. A considerable portion of the dry weight of the inedible biomass was readily soluble (29 percent for soybean, 43 percent for wheat, and 52 percent for potato). Greater weight loss from potato was a result of higher tissue concentrations of potassium, nitrate, and phosphate. Approximately 25 percent of the organic content of the biomass was water soluble, while the majority of most inorganic nutrients, except for calcium and iron, were recovered in the leachate. Direct use of the leachates in hydroponic media could provide between 40-90 percent of plant nutrient demands for wheat, and 20-50 percent of demand for soybean and potato. Further evaluation of leaching as a component of resource recovery scheme in a bioregenerative system requires study of (1) utilization of plant leachates in hydroponic plant culture; and (2) conversion of organic material (both soluble and insoluble) into edible, or other useful, products.

7 CFR 457.128 - Guaranteed production plan of fresh market tomato crop insurance provisions.

Code of Federal Regulations, 2011 CFR

2011-01-01

... policy provisions, the order of priority is as follows: (1) The Catastrophic Risk Protection Endorsement... field for the purpose of picking all or a portion of the crop. First fruit set—The date when 30 percent.... Harvest—Picking of marketable tomatoes. Mature green tomato—A tomato that: (a) Has a heightened gloss due...

Integrated crop pollination: Combining strategies to ensure stable and sustainable yields of pollination-dependent crops

USDA-ARS?s Scientific Manuscript database

Meeting the nutritional needs of our growing human population will be increasingly dependent on bees and other pollinators that provide the essential delivery of pollen to crop flowers during bloom. Honey bees have experienced population declines in some regions, and similar changes are evident for ...

Remote sensing based crop type mapping and evapotranspiration estimates at the farm level in arid regions of the globe

NASA Astrophysics Data System (ADS)

Ozdogan, M.; Serrat-Capdevila, A.; Anderson, M. C.

2017-12-01

Despite increasing scarcity of freshwater resources, there is dearth of spatially explicit information on irrigation water consumption through evapotranspiration, particularly in semi-arid and arid geographies. Remote sensing, either alone or in combination with ground surveys, is increasingly being used for irrigation water management by quantifying evaporative losses at the farm level. Increased availability of observations, sophisticated algorithms, and access to cloud-based computing is also helping this effort. This presentation will focus on crop-specific evapotranspiration estimates at the farm level derived from remote sensing in a number of water-scarce regions of the world. The work is part of a larger effort to quantify irrigation water use and improve use efficiencies associated with several World Bank projects. Examples will be drawn from India, where groundwater based irrigation withdrawals are monitored with the help of crop type mapping and evapotranspiration estimates from remote sensing. Another example will be provided from a northern irrigation district in Mexico, where remote sensing is used for detailed water accounting at the farm level. These locations exemplify the success stories in irrigation water management with the help of remote sensing with the hope that spatially disaggregated information on evapotranspiration can be used as inputs for various water management decisions as well as for better water allocation strategies in many other water scarce regions.

Determination of actual crop evapotranspiration (ETc) and dual crop coefficients (Kc) for cotton, wheat and maize in Fergana Valley: integration of the FAO-56 approach and BUDGET

NASA Astrophysics Data System (ADS)

Kenjabaev, Shavkat; Dernedde, Yvonne; Frede, Hans-Georg; Stulina, Galina

2014-05-01

Determination of the actual crop evapotranspiration (ETc) during the growing period is important for accurate irrigation scheduling in arid and semi-arid regions. Development of a crop coefficient (Kc) can enhance ETc estimations in relation to specific crop phenological development. This research was conducted to determine daily and growth-stage-specific Kc and ETc values for cotton (Gossypium hirsutum L.), winter wheat (Triticum aestivum L.) and maize (Zea mays L.) for silage at fields in Fergana Valley (Uzbekistan). The soil water balance model - Budget with integration of the dual crop procedure of the FAO-56 was used to estimate the ETc and separate it into evaporation (Ec) and transpiration (Tc) components. An empirical equation was developed to determine the daily Kc values based on the estimated Ec and Tc. The ETc, Kc determination and comparison to existing FAO Kc values were performed based on 10, 5 and 6 study cases for cotton, wheat and maize, respectively. Mean seasonal amounts of crop water consumption in terms of ETc were 560±50, 509±27 and 243±39 mm for cotton, wheat and maize, respectively. The growth-stage-specific Kc for cotton, wheat and maize was 0.15, 0.27 and 0.11 at initial; 1.15, 1.03 and 0.56 at mid; and 0.45, 0.89 and 0.53 at late season stages. These values correspond to those reported by the FAO-56. Development of site specific Kc helps tremendously in irrigation management and furthermore provides precise water applications in the region. The developed simple approach to estimate daily Kc for the three main crops grown in the Fergana region was a first attempt to meet this issue. Keywords: Actual crop evapotranspiration, evaporation and transpiration, crop coefficient, model BUDGET, Fergana Valley.

Climate Change Impacts on Crop Production in Nigeria

NASA Astrophysics Data System (ADS)

Mereu, V.; Gallo, A.; Carboni, G.; Spano, D.

2011-12-01

The agricultural sector in Nigeria is particularly important for the country's food security, natural resources, and growth agenda. The cultivable areas comprise more than 70% of the total area; however, the cultivated area is about the 35% of the total area. The most important components in the food basket of the nation are cereals and tubers, which include rice, maize, corn, millet, sorghum, yam, and cassava. These crops represent about 80% of the total agricultural product in Nigeria (from NPAFS). The major crops grown in the country can be divided into food crops (produced for consumption) and export products. Despite the importance of the export crops, the primary policy of agriculture is to make Nigeria self-sufficient in its food and fiber requirements. The projected impacts of future climate change on agriculture and water resources are expected to be adverse and extensive in these area. This implies the need for actions and measures to adapt to climate change impacts, and especially as they affect agriculture, the primary sector for Nigerian economy. In the framework of the Project Climate Risk Analysis in Nigeria (founded by World Bank Contract n.7157826), a study was made to assess the potential impact of climate change on the main crops that characterize Nigerian agriculture. The DSSAT-CSM (Decision Support System for Agrotechnology Transfer - Cropping System Model) software, version 4.5 was used for the analysis. Crop simulation models included in DSSAT are tools that simulate physiological processes of crop growth, development and production by combining genetic crop characteristics and environmental (soil and weather) conditions. For each selected crop, the models were calibrated to evaluate climate change impacts on crop production. The climate data used for the analysis are derived by the Regional Circulation Model COSMO-CLM, from 1971 to 2065, at 8 km of spatial resolution. The RCM model output was "perturbed" with 10 Global Climate Models to have

Characterisation of caecum and crop microbiota of Indian indigenous chicken targeting multiple hypervariable regions within 16S rRNA gene.

PubMed

Saxena, S; Saxena, V K; Tomar, S; Sapcota, D; Gonmei, G

2016-06-01

A comparative analysis of caecum and crop microbiota of chick, grower and adult stages of Indian indigenous chickens was conducted to investigate the role of the microbiota of the gastrointestinal tract, which play an important role in host performance, health and immunity. High-throughput Illumina sequencing was performed for V3, V4 and V4-V6 hypervariable regions of the 16S rRNA gene. M5RNA and M5NR databases under MG-RAST were used for metagenomic datasets annotation. In the crop, Firmicutes (~78%) and Proteobacteria (~16%) were the predominant phyla whereas in the caecum, Firmicutes (~50%), Bacteroidetes (~29%) and Actinobacteria (~10%) were predominant. The Shannon-Wiener diversity index suggested that sample richness and diversity increased as the chicken aged. For the first time, the presence of Lactobacillus species such as L. frumenti, L. antri, L. mucosae in the chicken crop along with Kineococcus radiotolerans, Desulfohalobium retbaense and L. jensenii in the caecum are reported. Many of these bacterial species have been found to be involved in immune response modulation and disease prevention in pigs and humans. The gut microbiome of the indigenous chicken was enriched with microbes having probiotic potential which might be essential for their adaptability.

Soil and water quality implications of production of herbaceous and woody energy crops

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

Tolbert, V.R.; Lindberg, J.E.; Green, T.H.

1997-10-01

Field-scale studies in three physiographic regions of the Tennessee Valley in the Southeastern US are being used to address the environmental effects of producing biomass energy crops on former agricultural lands. Comparison of erosion, surface water quality and quantity, and subsurface movement of water and nutrients from woody crops, switchgrass and agricultural crops began with crop establishment in 1994. Nutrient cycling, soil physical changes, and productivity of the different crops are also being monitored at the three sites.

Energy balances of bioenergy crops (Miscanthus, maize, rapeseed) and their CO2-mitigation potential on a regional farm scale

NASA Astrophysics Data System (ADS)

Felten, D.; Emmerling, C.

2012-04-01

Increasing cultivation of energy crops in agriculture reveals the progressive substitution of fossil fuels, such as crude oil or brown coal. For the future development of renewable resources, the efficiency of different cropping systems will be crucial, as energy crops differ in terms of the energy needed for crop cultivation and refinement and the respective energy yield, e.g. per area. Here, balancing is certainly the most suitable method for the assessment of cropping system efficiency, contrasting energy inputs with energy outputs and the related CO2 emissions with potential CO2 credits due to substitution of fossil fuels, respectively. The aim of the present study was to calculate both energy and CO2 balances for rapeseed and maize, representing the recently most often cultivated energy crops in Germany, on a regional farm scale. Furthermore, special emphasis was made on perennial Miscanthus x giganteus, which is commonly used as a solid fuel for combustion. This C4-grass is of increasing interest due to its high yield potential accompanied by low requirements for soil tillage, weed control, and fertilization as well as long cultivation periods up to 25 years. In contrast to more general approaches, balances were calculated with local data from commercial farms. The site-specific consumption of diesel fuel was calculated using an online-based calculator, developed by the German Association for Technology and Structures in Agriculture (KTBL). By balancing each of the aforementioned cropping systems, our research focused on (i) the quantification of energy gains and CO2 savings due to fossil fuel substitution and (ii) the assessment of energy efficiency, expressed as the ratio of energy output to input. The energy input was highest for maize sites (33.8 GJ ha-1 yr-1), followed by rapeseed (18.2 GJ ha-1 yr-1), and Miscanthus (1.1 GJ ha-1 yr-1); corresponding energy yields were 129.5 GJ ha-1 yr-1 (maize), 83.6 GJ ha-1 yr-1 (rapeseed), and 259.7 GJ ha-1 yr-1

Enhancing Adoption of Irrigation Scheduling to Sustain the Viability of Fruit and Nut Crops in California

NASA Astrophysics Data System (ADS)

Fulton, A.; Snyder, R.; Hillyer, C.; English, M.; Sanden, B.; Munk, D.

2012-04-01

Enhancing Adoption of Irrigation Scheduling to Sustain the Viability of Fruit and Nut Crops in California Allan Fulton, Richard Snyder, Charles Hillyer, Marshall English, Blake Sanden, and Dan Munk Adoption of scientific methods to decide when to irrigate and how much water to apply to a crop has increased over the last three decades in California. In 1988, less than 4.3 percent of US farmers employed some type of science-based technique to assist in making irrigation scheduling decisions (USDA, 1995). An ongoing survey in California, representing an industry irrigating nearly 0.4 million planted almond hectares, indicates adoption rates ranging from 38 to 55 percent of either crop evapotranspiration (ETc), soil moisture monitoring, plant water status, or some combination of these irrigation scheduling techniques to assist with making irrigation management decisions (California Almond Board, 2011). High capital investment to establish fruit and nut crops, sensitivity to over and under-irrigation on crop performance and longevity, and increasing costs and competition for water have all contributed to increased adoption of scientific irrigation scheduling methods. These trends in adoption are encouraging and more opportunities exist to develop improved irrigation scheduling tools, especially computer decision-making models. In 2009 and 2010, an "On-line Irrigation Scheduling Advisory Service" (OISO, 2012), also referred to as Online Irrigation Management (IMO), was used and evaluated in commercial walnut, almond, and French prune orchards in the northern Sacramento Valley of California. This specific model has many features described as the "Next Generation of Irrigation Schedulers" (Hillyer, 2010). While conventional irrigation management involves simply irrigating as needed to avoid crop stress, this IMO is designed to control crop stress, which requires: (i) precise control of crop water availability (rather than controlling applied water); (ii) quantifying crop

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

NASA Astrophysics Data System (ADS)

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

2012-12-01

. For the case of 280 DOY, Crop yield estimation showed better accuracy for soybean at county level. Though the case of 200 DOY resulted in less accuracy (i.e. 20% mean bias), it provides a useful tool for early forecasting of crop yield. We improved the spatial accuracy of estimated crop yield at county level by developing county-specific crop conversion coefficient. Our results indicate that the aboveground crop biomass can be estimated successfully with the simple LUE and respiration models combined with MODIS data and then, county-specific conversion coefficient can be different with each other across different counties. Hence, applying region-specific conversion coefficient is necessary to estimate crop yield with better accuracy.

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

Assessing wild bees in perennial bioenergy landscapes: effects of bioenergy crop composition, landscape configuration, and bioenergy crop area

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

Graham, John B.; Nassauer, Joan I.; Currie, William S.

Wild bee populations are currently under threat, which has led to recent efforts to increase pollinator habitat in North America. Simultaneously, U.S. federal energy policies are beginning to encourage perennial bioenergy cropping (PBC) systems, which have the potential to support native bees. Our objective was to explore the potentially interactive effects of crop composition, total PBC area, and PBC patches in different landscape configurations. Using a spatially-explicit modeling approach, the Lonsdorf model, we simulated the impacts of three perennial bioenergy crops (PBC: willow, switchgrass, and prairie), three scenarios with different total PBC area (11.7%, 23.5% and 28.8% of agricultural landmore » converted to PBC) and two types of landscape configurations (PBC in clustered landscape patterns that represent realistic future configurations or in dispersed neutral landscape models) on a nest abundance index in an Illinois landscape. Our modeling results suggest that crop composition and PBC area are particularly important for bee nest abundance, whereas landscape configuration is associated with bee nest abundance at the local scale but less so at the regional scale. Moreover, strategies to enhance wild bee habitat should therefore emphasize the crop composition and amount of PBC.« less

Assessing wild bees in perennial bioenergy landscapes: effects of bioenergy crop composition, landscape configuration, and bioenergy crop area

DOE PAGES

Graham, John B.; Nassauer, Joan I.; Currie, William S.; ...

2017-03-25

Wild bee populations are currently under threat, which has led to recent efforts to increase pollinator habitat in North America. Simultaneously, U.S. federal energy policies are beginning to encourage perennial bioenergy cropping (PBC) systems, which have the potential to support native bees. Our objective was to explore the potentially interactive effects of crop composition, total PBC area, and PBC patches in different landscape configurations. Using a spatially-explicit modeling approach, the Lonsdorf model, we simulated the impacts of three perennial bioenergy crops (PBC: willow, switchgrass, and prairie), three scenarios with different total PBC area (11.7%, 23.5% and 28.8% of agricultural landmore » converted to PBC) and two types of landscape configurations (PBC in clustered landscape patterns that represent realistic future configurations or in dispersed neutral landscape models) on a nest abundance index in an Illinois landscape. Our modeling results suggest that crop composition and PBC area are particularly important for bee nest abundance, whereas landscape configuration is associated with bee nest abundance at the local scale but less so at the regional scale. Moreover, strategies to enhance wild bee habitat should therefore emphasize the crop composition and amount of PBC.« less

Methods to estimate irrigated reference crop evapotranspiration - a review.

PubMed

Kumar, R; Jat, M K; Shankar, V

2012-01-01

Efficient water management of crops requires accurate irrigation scheduling which, in turn, requires the accurate measurement of crop water requirement. Irrigation is applied to replenish depleted moisture for optimum plant growth. Reference evapotranspiration plays an important role for the determination of water requirements for crops and irrigation scheduling. Various models/approaches varying from empirical to physically base distributed are available for the estimation of reference evapotranspiration. Mathematical models are useful tools to estimate the evapotranspiration and water requirement of crops, which is essential information required to design or choose best water management practices. In this paper the most commonly used models/approaches, which are suitable for the estimation of daily water requirement for agricultural crops grown in different agro-climatic regions, are reviewed. Further, an effort has been made to compare the accuracy of various widely used methods under different climatic conditions.

Estimating the Impact and Spillover Effect of Climate Change on Crop Yield in Northern Ghana.

NASA Astrophysics Data System (ADS)

Botchway, E.

2016-12-01

In tropical regions of the world human-induced climate change is likely to impact negatively on crop yields. To investigate the impact of climate change and its spillover effect on mean and variance of crop yields in northern Ghana, the Just and Pope stochastic production function and the Spatial Durbin model were adopted. Surprisingly, the results suggest that both precipitation and average temperature have positive effects on mean crop yield during the wet season. Wet season average temperature has a significant spillover effect in the region, whereas precipitation during the wet season has only one significant spillover effect on maize yield. Wet season precipitation does not have a strong significant effect on crop yield despite the rainfed nature of agriculture in the region. Thus, even if there are losers and winners as a result of future climate change at the regional level, future crop yield would largely depend on future technological development in agriculture, which may improve yields over time despite the changing climate. We argue, therefore, that technical improvement in farm management such as improved seeds and fertilizers, conservation tillage and better pest control, may have a more significant role in increasing observed crop productivity levels over time. So investigating the relative importance of non-climatic factors on crop yield may shed more light on where appropriate interventions can help in improving crop yields. Climate change, also, needs to be urgently assessed at the level of the household, so that poor and vulnerable people dependent on agriculture can be appropriately targeted in research and development activities whose object is poverty alleviation.

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.

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

Closed Loop Short Rotation Woody Biomass Energy Crops

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

Brower, Michael

CRC Development LLC is pursuing commercialization of shrub willow crops to evaluate and confirm estimates of yield, harvesting, transportation and renewable energy conversion costs and to provide a diverse resource in its supply portfolio.The goal of Closed Loop Short Rotation Woody Biomass Energy Crops is supply expansion in Central New York to facilitate the commercialization of willow biomass crops as part of the mix of woody biomass feedstocks for bioenergy and bioproducts. CRC Development LLC established the first commercial willow biomass plantation acreage in North America was established on the Tug Hill in the spring of 2006 and expanded inmore » 2007. This was the first 230- acres toward the goal of 10,000 regional acres. This project replaces some 2007-drought damaged acreage and installs a total of 630-acre new planting acres in order to demonstrate to regional agricultural producers and rural land-owners the economic vitality of closed loop short rotation woody biomass energy crops when deployed commercially in order to motivate new grower entry into the market-place. The willow biomass will directly help stabilize the fuel supply for the Lyonsdale Biomass facility, which produces 19 MWe of power and exports 15,000 pph of process steam to Burrows Paper. This project will also provide feedstock to The Biorefinery in New York for the manufacture of renewable, CO2-neutral liquid transportation fuels, chemicals and polymers. This project helps end dependency on imported fossil fuels, adds to region economic and environmental vitality and contributes to national security through improved energy independence.« less

Using cover crops and cropping systems for nitrogen management

USDA-ARS?s Scientific Manuscript database

The reasons for using cover crops and optimized cropping sequences to manage nitrogen (N) are to maximize economic returns, improve soil quality and productivity, and minimize losses of N that might adversely impact environmental quality. Cover crops and cropping systems’ effects on N management are...

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

NASA Astrophysics Data System (ADS)

Johnson, D. M.

2010-12-01

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

Crop modeling applications in agricultural water management

USGS Publications Warehouse

Kisekka, Isaya; DeJonge, Kendall C.; Ma, Liwang; Paz, Joel; Douglas-Mankin, Kyle R.

2017-01-01

This article introduces the fourteen articles that comprise the “Crop Modeling and Decision Support for Optimizing Use of Limited Water” collection. This collection was developed from a special session on crop modeling applications in agricultural water management held at the 2016 ASABE Annual International Meeting (AIM) in Orlando, Florida. In addition, other authors who were not able to attend the 2016 ASABE AIM were also invited to submit papers. The articles summarized in this introductory article demonstrate a wide array of applications in which crop models can be used to optimize agricultural water management. The following section titles indicate the topics covered in this collection: (1) evapotranspiration modeling (one article), (2) model development and parameterization (two articles), (3) application of crop models for irrigation scheduling (five articles), (4) coordinated water and nutrient management (one article), (5) soil water management (two articles), (6) risk assessment of water-limited irrigation management (one article), and (7) regional assessments of climate impact (two articles). Changing weather and climate, increasing population, and groundwater depletion will continue to stimulate innovations in agricultural water management, and crop models will play an important role in helping to optimize water use in agriculture.

Beyond Marbles: Percent Change and Social Justice

ERIC Educational Resources Information Center

Denny, Flannery

2013-01-01

In the author's eighth year of teaching, she hit a wall teaching percent change. Percent change is one of the few calculations taught in math classes that shows up regularly in the media, and one that she often does in her head to make sense of the world around her. Despite this, she had been teaching percent change using textbook problems about…

Chemistry and microbial functional diversity differences in biofuel crop and grassland soils in multiple geographies

EPA Science Inventory

As crop and non-crop lands are increasingly converted to biofuel feedstock production, it is of interest to identify potential impacts of annual and perennial feedstocks on soil ecosystem services. Soil samples were obtained from diverse regionally distributed biofuel cropping si...

Soybean crop-water production functions in a humid region across years and soils determined with APEX model

Treesearch

Bangbang Zhang; Gary Feng; Lajpat R. Ahuja; Xiangbin Kong; Ying Ouyang; Ardeshir Adeli; Johnie N. Jenkins

2018-01-01

Crop production as a function of water use or water applied, called the crop water production function (CWPF), is a useful tool for irrigation planning, design and management. However, these functions are not only crop and variety specific they also vary with soil types and climatic conditions (locations). Derivation of multi-year average CWPFs through field...

Impacts of Near-Term Climate Change on Irrigation Demands and Crop Yields in the Columbia River Basin

NASA Astrophysics Data System (ADS)

Rajagopalan, K.; Chinnayakanahalli, K. J.; Stockle, C. O.; Nelson, R. L.; Kruger, C. E.; Brady, M. P.; Malek, K.; Dinesh, S. T.; Barber, M. E.; Hamlet, A. F.; Yorgey, G. G.; Adam, J. C.

2018-03-01

Adaptation to a changing climate is critical to address future global food and water security challenges. While these challenges are global, successful adaptation strategies are often generated at regional scales; therefore, regional-scale studies are critical to inform adaptation decision making. While climate change affects both water supply and demand, water demand is relatively understudied, especially at regional scales. The goal of this work is to address this gap, and characterize the direct impacts of near-term (for the 2030s) climate change and elevated CO2 levels on regional-scale crop yields and irrigation demands for the Columbia River basin (CRB). This question is addressed through a coupled crop-hydrology model that accounts for site-specific and crop-specific characteristics that control regional-scale response to climate change. The overall near-term outlook for agricultural production in the CRB is largely positive, with yield increases for most crops and small overall increases in irrigation demand. However, there are crop-specific and location-specific negative impacts as well, and the aggregate regional response of irrigation demands to climate change is highly sensitive to the spatial crop mix. Low-value pasture/hay varieties of crops—typically not considered in climate change assessments—play a significant role in determining the regional response of irrigation demands to climate change, and thus cannot be overlooked. While, the overall near-term outlook for agriculture in the region is largely positive, there may be potential for a negative outlook further into the future, and it is important to consider this in long-term planning.

Regionalizing land use impacts on farmland birds.

PubMed

Glemnitz, Michael; Zander, Peter; Stachow, Ulrich

2015-06-01

The environmental impacts of land use vary regionally. Differences in geomorphology, climate, landscape structure, and biotope inventories are regarded as the main causes of this variation. We present a methodological approach for identifying regional responses in land use type to large-scale changes and the implications for the provision of habitat for farmland birds. The methodological innovations of this approach are (i) the coupling of impact assessments with economic models, (ii) the linking of cropping techniques at the plot scale with the regional distribution of land use, and (iii) the integration of statistical or monitoring data on recent states. This approach allows for the regional differentiation of farmers' responses to changing external conditions and for matching the ecological impacts of land use changes with regional environmental sensitivities. An exemplary scenario analysis was applied for a case study of an area in Germany, assessing the impacts of increased irrigation and the promotion of energy cropping on farmland birds, evaluated as a core indicator for farmland biodiversity. The potential effects on farmland birds were analyzed based on the intrinsic habitat values of the crops and cropping techniques. The results revealed that the strongest decrease in habitat availability for farmland birds occurred in regions with medium-to-low agricultural yields. As a result of the limited cropping alternatives, the increase in maize production was highest in marginal regions for both examined scenarios. Maize production replaced many crops with good-to-medium habitat suitability for birds. The declines in habitat quality were strongest in regions that are not in focus for conservation efforts for farmland birds.

Area estimation of crops by digital analysis of Landsat data

NASA Technical Reports Server (NTRS)

Bauer, M. E.; Hixson, M. M.; Davis, B. J.

1978-01-01

The study for which the results are presented had these objectives: (1) to use Landsat data and computer-implemented pattern recognition to classify the major crops from regions encompassing different climates, soils, and crops; (2) to estimate crop areas for counties and states by using crop identification data obtained from the Landsat identifications; and (3) to evaluate the accuracy, precision, and timeliness of crop area estimates obtained from Landsat data. The paper describes the method of developing the training statistics and evaluating the classification accuracy. Landsat MSS data were adequate to accurately identify wheat in Kansas; corn and soybean estimates for Indiana were less accurate. Systematic sampling of entire counties made possible by computer classification methods resulted in very precise area estimates at county, district, and state levels.

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.

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

PubMed Central

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

2017-01-01

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

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

PubMed

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

2017-01-01

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

The AgMIP GRIDded Crop Modeling Initiative (AgGRID) and the Global Gridded Crop Model Intercomparison (GGCMI)

NASA Technical Reports Server (NTRS)

Elliott, Joshua; Muller, Christoff

2015-01-01

Climate change is a significant risk for agricultural production. Even under optimistic scenarios for climate mitigation action, present-day agricultural areas are likely to face significant increases in temperatures in the coming decades, in addition to changes in precipitation, cloud cover, and the frequency and duration of extreme heat, drought, and flood events (IPCC, 2013). These factors will affect the agricultural system at the global scale by impacting cultivation regimes, prices, trade, and food security (Nelson et al., 2014a). Global-scale evaluation of crop productivity is a major challenge for climate impact and adaptation assessment. Rigorous global assessments that are able to inform planning and policy will benefit from consistent use of models, input data, and assumptions across regions and time that use mutually agreed protocols designed by the modeling community. To ensure this consistency, large-scale assessments are typically performed on uniform spatial grids, with spatial resolution of typically 10 to 50 km, over specified time-periods. Many distinct crop models and model types have been applied on the global scale to assess productivity and climate impacts, often with very different results (Rosenzweig et al., 2014). These models are based to a large extent on field-scale crop process or ecosystems models and they typically require resolved data on weather, environmental, and farm management conditions that are lacking in many regions (Bondeau et al., 2007; Drewniak et al., 2013; Elliott et al., 2014b; Gueneau et al., 2012; Jones et al., 2003; Liu et al., 2007; M¨uller and Robertson, 2014; Van den Hoof et al., 2011;Waha et al., 2012; Xiong et al., 2014). Due to data limitations, the requirements of consistency, and the computational and practical limitations of running models on a large scale, a variety of simplifying assumptions must generally be made regarding prevailing management strategies on the grid scale in both the baseline and

Hyperspectral remote sensing of paddy crop using insitu measurement and clustering technique

NASA Astrophysics Data System (ADS)

Moharana, S.; Dutta, S.

2014-11-01

Rice Agriculture, mainly cultivated in South Asia regions, is being monitored for extracting crop parameter, crop area, crop growth profile, crop yield using both optical and microwave remote sensing. Hyperspectral data provide more detailed information of rice agriculture. The present study was carried out at the experimental station of the Regional Rainfed Low land Rice Research Station, Assam, India (26.1400° N, 91.7700° E) and the overall climate of the study area comes under Lower Brahmaputra Valley (LBV) Agro Climatic Zones. The hyperspectral measurements were made in the year 2009 from 72 plots that include eight rice varieties along with three different level of nitrogen treatments (50, 100, 150 kg/ha) covering rice transplanting to the crop harvesting period. With an emphasis to varieties, hyperspectral measurements were taken in the year 2014 from 24 plots having 24 rice genotypes with different crop developmental ages. All the measurements were performed using a spectroradiometer with a spectral range of 350-1050 nm under direct sunlight of a cloud free sky and stable condition of the atmosphere covering more than 95 % canopy. In this study, reflectance collected from canopy of rice were expressed in terms of waveforms. Furthermore, generated waveforms were analysed for all combinations of nitrogen applications and varieties. A hierarchical clustering technique was employed to classify these waveforms into different groups. By help of agglomerative clustering algorithm a few number of clusters were finalized for different rice varieties along with nitrogen treatments. By this clustering approach, observational error in spectroradiometer reflectance was also nullified. From this hierarchical clustering, appropriate spectral signature for rice canopy were identified and will help to create rice crop classification accurately and therefore have a prospect to make improved information on rice agriculture at both local and regional scales. From this

Effects of Crop Canopies on Rain Splash Detachment

PubMed Central

Ma, Bo; Yu, Xiaoling; Ma, Fan; Li, Zhanbin; Wu, Faqi

2014-01-01

Crops are one of the main factors affecting soil erosion in sloping fields. To determine the characteristics of splash erosion under crop canopies, corn, soybean, millet, and winter wheat were collected, and the relationship among splash erosion, rainfall intensity, and throughfall intensity under different crop canopies was analyzed through artificial rainfall experiments. The results showed that, the mean splash detachment rate on the ground surface was 390.12 g/m2·h, which was lower by 67.81% than that on bare land. The inhibiting effects of crops on splash erosion increased as the crops grew, and the ability of the four crops to inhibit splash erosion was in the order of winter wheat>corn>soybeans>millet. An increase in rainfall intensity could significantly enhance the occurrence of splash erosion, but the ability of crops to inhibit splash erosion was 13% greater in cases of higher rainfall intensity. The throughfall intensity under crop canopies was positively related to the splash detachment rate, and this relationship was more significant when the rainfall intensity was 40 mm/h. Splash erosion tended to occur intensively in the central row of croplands as the crop grew, and the non-uniformity of splash erosion was substantial, with splash erosion occurring mainly between the rows and in the region directly under the leaf margin. This study has provided a theoretical basis for describing the erosion mechanisms of cropland and for assisting soil erosion prediction as well as irrigation and fertilizer management in cultivated fields. PMID:24992386

Effects of crop canopies on rain splash detachment.

PubMed

Ma, Bo; Yu, Xiaoling; Ma, Fan; Li, Zhanbin; Wu, Faqi

2014-01-01

Crops are one of the main factors affecting soil erosion in sloping fields. To determine the characteristics of splash erosion under crop canopies, corn, soybean, millet, and winter wheat were collected, and the relationship among splash erosion, rainfall intensity, and throughfall intensity under different crop canopies was analyzed through artificial rainfall experiments. The results showed that, the mean splash detachment rate on the ground surface was 390.12 g/m2 · h, which was lower by 67.81% than that on bare land. The inhibiting effects of crops on splash erosion increased as the crops grew, and the ability of the four crops to inhibit splash erosion was in the order of winter wheat>corn>soybeans>millet. An increase in rainfall intensity could significantly enhance the occurrence of splash erosion, but the ability of crops to inhibit splash erosion was 13% greater in cases of higher rainfall intensity. The throughfall intensity under crop canopies was positively related to the splash detachment rate, and this relationship was more significant when the rainfall intensity was 40 mm/h. Splash erosion tended to occur intensively in the central row of croplands as the crop grew, and the non-uniformity of splash erosion was substantial, with splash erosion occurring mainly between the rows and in the region directly under the leaf margin. This study has provided a theoretical basis for describing the erosion mechanisms of cropland and for assisting soil erosion prediction as well as irrigation and fertilizer management in cultivated fields.

Determining Regional Sensitivity to Energy-Related Water Withdrawals in Minnesota

NASA Astrophysics Data System (ADS)

McCulloch, A.; Brauman, K. A.

2015-12-01

Minnesota has abundant freshwater resources, yet concerns about water-impacts of energy and mining development are increasing. Statewide, total annual water withdrawals have increased, and, in some watersheds, withdrawals make up a large fraction of available water. The energy and mining sectors play a critical role in determining water availability, as water is used to irrigate biofuel feedstock crops, cool thermoelectric plants, and process and transport fuels and iron ore. We evaluated the Minnesota Department of Natural Resources (DNR) Water and Reporting System (MPARS) dataset (1988-2014) to identify regions where energy and mining-related water withdrawals are high or where they are increasing. The energy and mining sectors account for over 65 percent of total water extractions in Minnesota, but this percentage is greater in some regions. In certain southern and northeastern Minnesota watersheds, these extractions account for 90 percent of total water demand. Sensitivity to these demands is not dependent on total water demand alone, and is also not uniform among watersheds. We identified and evaluated factors influencing sensitivity, including population, extraction type (surface water or groundwater), percentage of increased demand, and whether withdrawals are consumptive or not. We determined that southern Minnesota is particularly sensitive to increased water demands, because of growing biofuel and sand extraction industries (the products of which are used in hydraulic fracturing). In the last ten years, ethanol production in Minnesota has increased by 440 percent, and over fifteen refineries (each with a capacity over 1.1 billion gallons), have been built. These users primarily extract from surface water bodies within a few watersheds, compromising local supplies. As these energy-related industries continue to grow, so will the demand for freshwater resources. Determining regional sensitivity to increased demands will allow policy-makers to manage the

Modelling regional cropping patterns under scenarios of climate and socio-economic change in Hungary.

PubMed

Li, Sen; Juhász-Horváth, Linda; Pintér, László; Rounsevell, Mark D A; Harrison, Paula A

2018-05-01

Impacts of socio-economic, political and climatic change on agricultural land systems are inherently uncertain. The role of regional and local-level actors is critical in developing effective policy responses that accommodate such uncertainty in a flexible and informed way across governance levels. This study identified potential regional challenges in arable land use systems, which may arise from climate and socio-economic change for two counties in western Hungary: Veszprém and Tolna. An empirically-grounded, agent-based model was developed from an extensive farmer household survey about local land use practices. The model was used to project future patterns of arable land use under four localised, stakeholder-driven scenarios of plausible future socio-economic and climate change. The results show strong differences in farmers' behaviour and current agricultural land use patterns between the two regions, highlighting the need to implement focused policy at the regional level. For instance, policy that encourages local food security may need to support improvements in the capacity of farmers to adapt to physical constraints in Veszprém and farmer access to social capital and environmental awareness in Tolna. It is further suggested that the two regions will experience different challenges to adaptation under possible future conditions (up to 2100). For example, Veszprém was projected to have increased fallow land under a scenario with high inequality, ineffective institutions and higher-end climate change, implying risks of land abandonment. By contrast, Tolna was projected to have a considerable decline in major cereals under a scenario assuming a de-globalising future with moderate climate change, inferring challenges to local food self-sufficiency. The study provides insight into how socio-economic and physical factors influence the selection of crop rotation plans by farmers in western Hungary and how farmer behaviour may affect future risks to agricultural

Current and Future Greenhouse Gas Emissions from Global Crop Intensification and Expansion

NASA Astrophysics Data System (ADS)

Carlson, K. M.; Gerber, J. S.; Mueller, N. D.; O'Connell, C.; West, P. C.

2014-12-01

Food systems currently contribute up to one-third of total anthropogenic greenhouse gas emissions, and these emissions are expected to rise as demand for agricultural products increases. Thus, improving the greenhouse gas emissions efficiency of agriculture - the tons or kilocalories of production per ton of CO2 equivalent emissions - will be critical to support a resilient future global system. Here, we model and evaluate global, 2000-era, spatially explicit relationships between a suite of greenhouse gas emissions from various agronomic practices (i.e., fertilizer application, peatland draining, and rice cultivation) and crop yields. Then, we predict potential emissions from future crop production increases achieved through intensification and extensification, including CO2 emissions from croplands replacing non-urban land cover. We find that 2000-era yield-scaled agronomic emissions are highly heterogeneous across crops types, crop management practices, and regions. Rice agriculture produces more total CO2-equivalent emissions than any other crop. Moreover, inundated rice in just a few countries contributes the vast majority of these rice emissions. Crops such as sunflower and cotton have low efficiency on a caloric basis. Our results suggest that intensification tends to be a more efficient pathway to boost greenhouse gas emissions efficiency than expansion. We conclude by discussing potential crop- and region-specific agricultural development pathways that may boost the greenhouse gas emissions efficiency of agriculture.

The impacts of data constraints on the predictive performance of a general process-based crop model (PeakN-crop v1.0)

NASA Astrophysics Data System (ADS)

Caldararu, Silvia; Purves, Drew W.; Smith, Matthew J.

2017-04-01

Improving international food security under a changing climate and increasing human population will be greatly aided by improving our ability to modify, understand and predict crop growth. What we predominantly have at our disposal are either process-based models of crop physiology or statistical analyses of yield datasets, both of which suffer from various sources of error. In this paper, we present a generic process-based crop model (PeakN-crop v1.0) which we parametrise using a Bayesian model-fitting algorithm to three different sources: data-space-based vegetation indices, eddy covariance productivity measurements and regional crop yields. We show that the model parametrised without data, based on prior knowledge of the parameters, can largely capture the observed behaviour but the data-constrained model greatly improves both the model fit and reduces prediction uncertainty. We investigate the extent to which each dataset contributes to the model performance and show that while all data improve on the prior model fit, the satellite-based data and crop yield estimates are particularly important for reducing model error and uncertainty. Despite these improvements, we conclude that there are still significant knowledge gaps, in terms of available data for model parametrisation, but our study can help indicate the necessary data collection to improve our predictions of crop yields and crop responses to environmental changes.

Impact of GM crops on biodiversity.

PubMed

Carpenter, Janet E

2011-01-01

The potential impact of GM crops on biodiversity has been a topic of interest both in general as well as specifically in the context of the Convention on Biological Diversity. Agricultural biodiversity has been defined at levels from genes to ecosystems that are involved or impacted by agricultural production (www.cbd.int/agro/whatis.shtml). After fifteen years of commercial cultivation, a substantial body of literature now exists addressing the potential impacts of GM crops on the environment. This review takes a biodiversity lens to this literature, considering the impacts at three levels: the crop, farm and landscape scales. Within that framework, this review covers potential impacts of the introduction of genetically engineered crops on: crop diversity, biodiversity of wild relatives, non-target soil organisms, weeds, land use, non-target above-ground organisms, and area-wide pest suppression. The emphasis of the review is peer-reviewed literature that presents direct measures of impacts on biodiversity. In addition, possible impacts of changes in management practises such as tillage and pesticide use are also discussed to complement the literature on direct measures. The focus of the review is on technologies that have been commercialized somewhere in the world, while results may emanate from non-adopting countries and regions. Overall, the review finds that currently commercialized GM crops have reduced the impacts of agriculture on biodiversity, through enhanced adoption of conservation tillage practices, reduction of insecticide use and use of more environmentally benign herbicides and increasing yields to alleviate pressure to convert additional land into agricultural use.

Farmland Drought Evaluation Based on the Assimilation of Multi-Temporal Multi-Source Remote Sensing Data into AquaCrop Model

NASA Astrophysics Data System (ADS)

Yang, Guijun; Yang, Hao; Jin, Xiuliang; Pignatti, Stefano; Casa, Faffaele; Silverstro, Paolo Cosmo

2016-08-01

Drought is the most costly natural disasters in China and all over the world. It is very important to evaluate the drought-induced crop yield losses and further improve water use efficiency at regional scale. Firstly, crop biomass was estimated by the combined use of Synthetic Aperture Radar (SAR) and optical remote sensing data. Then the estimated biophysical variable was assimilated into crop growth model (FAO AquaCrop) by the Particle Swarm Optimization (PSO) method from farmland scale to regional scale.At farmland scale, the most important crop parameters of AquaCrop model were determined to reduce the used parameters in assimilation procedure. The Extended Fourier Amplitude Sensitivity Test (EFAST) method was used for assessing the contribution of different crop parameters to model output. Moreover, the AquaCrop model was calibrated using the experiment data in Xiaotangshan, Beijing.At regional scale, spatial application of our methods were carried out and validated in the rural area of Yangling, Shaanxi Province, in 2014. This study will provide guideline to make irrigation decision of balancing of water consumption and yield loss.

Crop to wild introgression in lettuce: following the fate of crop genome segments in backcross populations

PubMed Central

2012-01-01

Background After crop-wild hybridization, some of the crop genomic segments may become established in wild populations through selfing of the hybrids or through backcrosses to the wild parent. This constitutes a possible route through which crop (trans)genes could become established in natural populations. The likelihood of introgression of transgenes will not only be determined by fitness effects from the transgene itself but also by the crop genes linked to it. Although lettuce is generally regarded as self-pollinating, outbreeding does occur at a low frequency. Backcrossing to wild lettuce is a likely pathway to introgression along with selfing, due to the high frequency of wild individuals relative to the rarely occurring crop-wild hybrids. To test the effect of backcrossing on the vigour of inter-specific hybrids, Lactuca serriola, the closest wild relative of cultivated lettuce, was crossed with L. sativa and the F1 hybrid was backcrossed to L. serriola to generate BC1 and BC2 populations. Experiments were conducted on progeny from selfed plants of the backcrossing families (BC1S1 and BC2S1). Plant vigour of these two backcrossing populations was determined in the greenhouse under non-stress and abiotic stress conditions (salinity, drought, and nutrient deficiency). Results Despite the decreasing contribution of crop genomic blocks in the backcross populations, the BC1S1 and BC2S1 hybrids were characterized by a substantial genetic variation under both non-stress and stress conditions. Hybrids were identified that performed equally or better than the wild genotypes, indicating that two backcrossing events did not eliminate the effect of the crop genomic segments that contributed to the vigour of the BC1 and BC2 hybrids. QTLs for plant vigour under non-stress and the various stress conditions were detected in the two populations with positive as well as negative effects from the crop. Conclusion As it was shown that the crop contributed QTLs with either a

Crop to wild introgression in lettuce: following the fate of crop genome segments in backcross populations.

PubMed

Uwimana, Brigitte; Smulders, Marinus J M; Hooftman, Danny A P; Hartman, Yorike; van Tienderen, Peter H; Jansen, Johannes; McHale, Leah K; Michelmore, Richard W; Visser, Richard G F; van de Wiel, Clemens C M

2012-03-26

After crop-wild hybridization, some of the crop genomic segments may become established in wild populations through selfing of the hybrids or through backcrosses to the wild parent. This constitutes a possible route through which crop (trans)genes could become established in natural populations. The likelihood of introgression of transgenes will not only be determined by fitness effects from the transgene itself but also by the crop genes linked to it. Although lettuce is generally regarded as self-pollinating, outbreeding does occur at a low frequency. Backcrossing to wild lettuce is a likely pathway to introgression along with selfing, due to the high frequency of wild individuals relative to the rarely occurring crop-wild hybrids. To test the effect of backcrossing on the vigour of inter-specific hybrids, Lactuca serriola, the closest wild relative of cultivated lettuce, was crossed with L. sativa and the F(1) hybrid was backcrossed to L. serriola to generate BC(1) and BC(2) populations. Experiments were conducted on progeny from selfed plants of the backcrossing families (BC(1)S(1) and BC(2)S(1)). Plant vigour of these two backcrossing populations was determined in the greenhouse under non-stress and abiotic stress conditions (salinity, drought, and nutrient deficiency). Despite the decreasing contribution of crop genomic blocks in the backcross populations, the BC(1)S(1) and BC(2)S(1) hybrids were characterized by a substantial genetic variation under both non-stress and stress conditions. Hybrids were identified that performed equally or better than the wild genotypes, indicating that two backcrossing events did not eliminate the effect of the crop genomic segments that contributed to the vigour of the BC(1) and BC(2) hybrids. QTLs for plant vigour under non-stress and the various stress conditions were detected in the two populations with positive as well as negative effects from the crop. As it was shown that the crop contributed QTLs with either a positive

Investigating hydrometeorological impacts of perennial bioenergy crops under realistic scenario expansions

NASA Astrophysics Data System (ADS)

Wagner, M.; Wang, M.; Miguez-Macho, G.; Miller, J. N.; Bagley, J. E.; Bernacchi, C.; Georgescu, M.

2016-12-01

Perennial bioenergy crops, such as switchgrass and miscanthus, have been posed as a more sustainable energy pathway relative to annual bioenergy crops due to their reduced carbon footprint and ability to grow on abandoned and degraded land, thereby, avoiding competition with food crops. Previous studies that replaced annual bioenergy crops with perennial crops noted regional cooling associated with enhanced ET due to their deeper rooting systems extracting deeper soil moisture. This study provides a more realistic assessment by (1) analyzing perennial bioenergy expansion only in suitable abandoned and degraded farmlands, and (2) using field scale measurements of albedo in conjunction with known vegetation fraction and leaf area index (LAI) values. High-resolution (2 km grid spacing) simulations were performed using a state-of-the-art atmospheric model (Weather Research and Forecasting system) dynamically coupled to a land surface model system over the Southern Plains of the U.S., during a normal precipitation year (2007) and a drought year (2011). Our results show that perennial bioenergy crop expansion leads to regional cooling (1-2 oC), that is driven primarily by enhanced reflection of shortwave radiation, and secondarily, by enhanced ET. Perennial bioenergy crop expansion was also shown to mitigate drought impacts through moistening and cooling of the near-surface environment. These impacts, however, were reduced during the drought year as a result of differential environmental conditions, when compared to those of the normal cimate year. This study serves as a major step towards assessing the sustainability of perennial bioenergy crop expansion under diverse hydrometeorological conditions by highlighting the driving mechanisms and processes associated with this energy pathway.

Technology targeting for sustainable intensification of crop production in the Delta region of Bangladesh

NASA Astrophysics Data System (ADS)

Schulthess, U.; Krupnik, T. J.; Ahmed, Z. U.; McDonald, A. J.

2015-04-01

Remote sensing data are nowadays being acquired within short intervals and made available at a low cost or for free. This opens up opportunities for new remote sensing applications, such as the characterization of entire regions to identify most suitable areas for technology targeting. Increasing population growth and changing dietary habits in South Asia call for higher cereal production to ensure future food security. In the Delta area of Bangladesh, surface water is considered to be available in quantities large enough to support intensification by adding an irrigated dry season crop. Fuel-efficient, low lift axial flow pumps have shown to be suitable to carry water to fields that are within a buffer of four hundred meters of the rivers. However, information on how and where to target surface water irrigation efforts is currently lacking. We describe the opportunities and constraints encountered in developing a procedure to identify cropland for which axial flow pumps could be successfully deployed upon in a 43'000 km2 area. First, we isolated cropland and waterways using Landsat 5 and 7 scenes using image segmentation followed by classification with the random forest algorithm. Based on Landsat 7 and 8 scenes, we extracted maximum dry season enhanced vegetation index (EVI) values, which we classified into fallow, low-, and high-intensity cropland for the last three years. Last, we investigated the potential for surface water irrigation on fallow and low-intensity land by applying a cropping risk matrix to address the twin threats of soil and water salinity. Our analysis indicates that there are at least 20,000 ha of fallow land under the low-risk category, while more than 100,000 ha of low-intensity cropland can be brought into intensified production. This information will aid in technology targeting for the efficient deployment of surface water irrigation as a tool for intensification.

Crop and non-crop productivity in a traditional maize agroecosystem of the highland of Mexico

PubMed Central

2009-01-01

Background In Mexico, the traditional maize cultivation system has resisted intensification attempts for many decades in some areas, even in some well-connected regions of the temperate highlands. We suggest that this is due to economics. Methods The total useful biomass of several fields in Nanacamilpa, Tlaxcala, are evaluated for productivity and costs. Results Maize grain production is low (1.5 t ha-1) and does not cover costs. However, maize stover demands a relatively high price. If it included, a profit is possible (about 110 US $ ha-1). We show that non-crop production (weeds for food and forage) potentially has a higher value than the crop. It is only partially used, as there are constraints on animal husbandry, but it diversifies production and plays a role as a back-up system in case of crop failure. Conclusion The diversified system described is economically rational under current conditions and labor costs. It is also stable, low-input and ecologically benign, and should be recognized as an important example of integrated agriculture, though some improvements could be investigated. PMID:19943939

International Global Crop Condition Assessments in the framework of GEOGLAM

NASA Astrophysics Data System (ADS)

Becker-Reshef, I.; Justice, C. O.; Vermote, E.; Whitcraft, A. K.; Claverie, M.

2013-12-01

The Group on Earth Observations (partnership of governments and international organizations) developed the Global Agricultural Monitoring (GEOGLAM) initiative in response to the growing calls for improved agricultural information. The goal of GEOGLAM is to strengthen the international community's capacity to produce and disseminate relevant, timely and accurate forecasts of agricultural production at national, regional and global scales through the use of Earth observations. This initiative is designed to build on existing agricultural monitoring initiatives at national, regional and global levels and to enhance and strengthen them through international networking, operationally focused research, and data/method sharing. GEOGLAM was adopted by the G20 as part of the action plan on food price volatility and agriculture and is being implemented through building on the extensive GEO Agricultural Community of Practice (CoP) that was initiated in 2007 and includes key national and international agencies, organizations, and universities involved in agricultural monitoring. One of the early GEOGLAM activities is to provide harmonized global crop outlooks that offer timely qualitative consensus information on crop status and prospects. This activity is being developed in response to a request from the G-20 Agricultural Market Information System (AMIS) and is implemented within the global monitoring systems component of GEOGLAM. The goal is to develop a transparent, international, multi-source, consensus assessment of crop growing conditions, status, and agro-climatic conditions, likely to impact global production. These assessments are focused on the four primary crop types (corn, wheat, soy and rice) within the main agricultural producing regions of the world. The GEOGLAM approach is to bring together international experts from global, regional and national monitoring systems that can share and discuss information from a variety of independent complementary sources in

Genome editing for crop improvement: Challenges and opportunities

PubMed Central

Abdallah, Naglaa A; Prakash, Channapatna S; McHughen, Alan G

2015-01-01

ABSTRACT Genome or gene editing includes several new techniques to help scientists precisely modify genome sequences. The techniques also enables us to alter the regulation of gene expression patterns in a pre-determined region and facilitates novel insights into the functional genomics of an organism. Emergence of genome editing has brought considerable excitement especially among agricultural scientists because of its simplicity, precision and power as it offers new opportunities to develop improved crop varieties with clear-cut addition of valuable traits or removal of undesirable traits. Research is underway to improve crop varieties with higher yields, strengthen stress tolerance, disease and pest resistance, decrease input costs, and increase nutritional value. Genome editing encompasses a wide variety of tools using either a site-specific recombinase (SSR) or a site-specific nuclease (SSN) system. Both systems require recognition of a known sequence. The SSN system generates single or double strand DNA breaks and activates endogenous DNA repair pathways. SSR technology, such as Cre/loxP and Flp/FRT mediated systems, are able to knockdown or knock-in genes in the genome of eukaryotes, depending on the orientation of the specific sites (loxP, FLP, etc.) flanking the target site. There are 4 main classes of SSN developed to cleave genomic sequences, mega-nucleases (homing endonuclease), zinc finger nucleases (ZFNs), transcriptional activator-like effector nucleases (TALENs), and the CRISPR/Cas nuclease system (clustered regularly interspaced short palindromic repeat/CRISPR-associated protein). The recombinase mediated genome engineering depends on recombinase (sub-) family and target-site and induces high frequencies of homologous recombination. Improving crops with gene editing provides a range of options: by altering only a few nucleotides from billions found in the genomes of living cells, altering the full allele or by inserting a new gene in a targeted

Identification of a novel percent mammographic density locus at 12q24.

PubMed

Stevens, Kristen N; Lindstrom, Sara; Scott, Christopher G; Thompson, Deborah; Sellers, Thomas A; Wang, Xianshu; Wang, Alice; Atkinson, Elizabeth; Rider, David N; Eckel-Passow, Jeanette E; Varghese, Jajini S; Audley, Tina; Brown, Judith; Leyland, Jean; Luben, Robert N; Warren, Ruth M L; Loos, Ruth J F; Wareham, Nicholas J; Li, Jingmei; Hall, Per; Liu, Jianjun; Eriksson, Louise; Czene, Kamila; Olson, Janet E; Pankratz, V Shane; Fredericksen, Zachary; Diasio, Robert B; Lee, Adam M; Heit, John A; DeAndrade, Mariza; Goode, Ellen L; Vierkant, Robert A; Cunningham, Julie M; Armasu, Sebastian M; Weinshilboum, Richard; Fridley, Brooke L; Batzler, Anthony; Ingle, James N; Boyd, Norman F; Paterson, Andrew D; Rommens, Johanna; Martin, Lisa J; Hopper, John L; Southey, Melissa C; Stone, Jennifer; Apicella, Carmel; Kraft, Peter; Hankinson, Susan E; Hazra, Aditi; Hunter, David J; Easton, Douglas F; Couch, Fergus J; Tamimi, Rulla M; Vachon, Celine M

2012-07-15

Percent mammographic density adjusted for age and body mass index (BMI) is one of the strongest risk factors for breast cancer and has a heritable component that remains largely unidentified. We performed a three-stage genome-wide association study (GWAS) of percent mammographic density to identify novel genetic loci associated with this trait. In stage 1, we combined three GWASs of percent density comprised of 1241 women from studies at the Mayo Clinic and identified the top 48 loci (99 single nucleotide polymorphisms). We attempted replication of these loci in 7018 women from seven additional studies (stage 2). The meta-analysis of stage 1 and 2 data identified a novel locus, rs1265507 on 12q24, associated with percent density, adjusting for age and BMI (P = 4.43 × 10(-8)). We refined the 12q24 locus with 459 additional variants (stage 3) in a combined analysis of all three stages (n = 10 377) and confirmed that rs1265507 has the strongest association in the 12q24 region (P = 1.03 × 10(-8)). Rs1265507 is located between the genes TBX5 and TBX3, which are members of the phylogenetically conserved T-box gene family and encode transcription factors involved in developmental regulation. Understanding the mechanism underlying this association will provide insight into the genetics of breast tissue composition.

Identification of a novel percent mammographic density locus at 12q24

PubMed Central

Stevens, Kristen N.; Lindstrom, Sara; Scott, Christopher G.; Thompson, Deborah; Sellers, Thomas A.; Wang, Xianshu; Wang, Alice; Atkinson, Elizabeth; Rider, David N.; Eckel-Passow, Jeanette E.; Varghese, Jajini S.; Audley, Tina; Brown, Judith; Leyland, Jean; Luben, Robert N.; Warren, Ruth M.L.; Loos, Ruth J.F.; Wareham, Nicholas J.; Li, Jingmei; Hall, Per; Liu, Jianjun; Eriksson, Louise; Czene, Kamila; Olson, Janet E.; Shane Pankratz, V.; Fredericksen, Zachary; Diasio, Robert B.; Lee, Adam M.; Heit, John A.; deAndrade, Mariza; Goode, Ellen L.; Vierkant, Robert A.; Cunningham, Julie M.; Armasu, Sebastian M.; Weinshilboum, Richard; Fridley, Brooke L.; Batzler, Anthony; Ingle, James N.; Boyd, Norman F.; Paterson, Andrew D.; Rommens, Johanna; Martin, Lisa J.; Hopper, John L.; Southey, Melissa C.; Stone, Jennifer; Apicella, Carmel; Kraft, Peter; Hankinson, Susan E.; Hazra, Aditi; Hunter, David J.; Easton, Douglas F.; Couch, Fergus J.; Tamimi, Rulla M.; Vachon, Celine M.

2012-01-01

Percent mammographic density adjusted for age and body mass index (BMI) is one of the strongest risk factors for breast cancer and has a heritable component that remains largely unidentified. We performed a three-stage genome-wide association study (GWAS) of percent mammographic density to identify novel genetic loci associated with this trait. In stage 1, we combined three GWASs of percent density comprised of 1241 women from studies at the Mayo Clinic and identified the top 48 loci (99 single nucleotide polymorphisms). We attempted replication of these loci in 7018 women from seven additional studies (stage 2). The meta-analysis of stage 1 and 2 data identified a novel locus, rs1265507 on 12q24, associated with percent density, adjusting for age and BMI (P = 4.43 × 10−8). We refined the 12q24 locus with 459 additional variants (stage 3) in a combined analysis of all three stages (n = 10 377) and confirmed that rs1265507 has the strongest association in the 12q24 region (P = 1.03 × 10−8). Rs1265507 is located between the genes TBX5 and TBX3, which are members of the phylogenetically conserved T-box gene family and encode transcription factors involved in developmental regulation. Understanding the mechanism underlying this association will provide insight into the genetics of breast tissue composition. PMID:22532574

Pollinator communities in strawberry crops - variation at multiple spatial scales.

PubMed

Ahrenfeldt, E J; Klatt, B K; Arildsen, J; Trandem, N; Andersson, G K S; Tscharntke, T; Smith, H G; Sigsgaard, L

2015-08-01

Predicting potential pollination services of wild bees in crops requires knowledge of their spatial distribution within fields. Field margins can serve as nesting and foraging habitats for wild bees and can be a source of pollinators. Regional differences in pollinator community composition may affect this spill-over of bees. We studied how regional and local differences affect the spatial distribution of wild bee species richness, activity-density and body size in crop fields. We sampled bees both from the field centre and at two different types of semi-natural field margins, grass strips and hedges, in 12 strawberry fields. The fields were distributed over four regions in Northern Europe, representing an almost 1100 km long north-south gradient. Even over this gradient, daytime temperatures during sampling did not differ significantly between regions and did therefore probably not impact bee activity. Bee species richness was higher in field margins compared with field centres independent of field size. However, there was no difference between centre and margin in body-size or activity-density. In contrast, bee activity-density increased towards the southern regions, whereas the mean body size increased towards the north. In conclusion, our study revealed a general pattern across European regions of bee diversity, but not activity-density, declining towards the field interior which suggests that the benefits of functional diversity of pollinators may be difficult to achieve through spill-over effects from margins to crop. We also identified dissimilar regional patterns in bee diversity and activity-density, which should be taken into account in conservation management.

Impacts of Watershed Characteristics and Crop Rotations on Winter Cover Crop Nitrate-Nitrogen Uptake Capacity within Agricultural Watersheds in the Chesapeake Bay Region.

PubMed

Lee, Sangchul; Yeo, In-Young; Sadeghi, Ali M; McCarty, Gregory W; Hively, W Dean; Lang, Megan W

2016-01-01

The adoption rate of winter cover crops (WCCs) as an effective conservation management practice to help reduce agricultural nutrient loads in the Chesapeake Bay (CB) is increasing. However, the WCC potential for water quality improvement has not been fully realized at the watershed scale. This study was conducted to evaluate the long-term impact of WCCs on hydrology and NO3-N loads in two adjacent watersheds and to identify key management factors that affect the effectiveness of WCCs using the Soil and Water Assessment Tool (SWAT) and statistical methods. Simulation results indicated that WCCs are effective for reducing NO3-N loads and their performance varied based on planting date, species, soil characteristics, and crop rotations. Early-planted WCCs outperformed late-planted WCCs on the reduction of NO3-N loads and early-planted rye (RE) reduced NO3-N loads by ~49.3% compared to the baseline (no WCC). The WCCs were more effective in a watershed dominated by well-drained soils with increased reductions in NO3-N fluxes of ~2.5 kg N·ha-1 delivered to streams and ~10.1 kg N·ha-1 leached into groundwater compared to poorly-drained soils. Well-drained agricultural lands had higher transport of NO3-N in the soil profile and groundwater due to increased N leaching. Poorly-drained agricultural lands had lower NO3-N due to extensive drainage ditches and anaerobic soil conditions promoting denitrification. The performance of WCCs varied by crop rotations (i.e., continuous corn and corn-soybean), with increased N uptake following soybean crops due to the increased soil mineral N availability by mineralization of soybean residue compared to corn residue. The WCCs can reduce N leaching where baseline NO3-N loads are high in well-drained soils and/or when residual and mineralized N availability is high due to the cropping practices. The findings suggested that WCC implementation plans should be established in watersheds according to local edaphic and agronomic

Impacts of Watershed Characteristics and Crop Rotations on Winter Cover Crop Nitrate-Nitrogen Uptake Capacity within Agricultural Watersheds in the Chesapeake Bay Region

PubMed Central

Lee, Sangchul; Yeo, In-Young; Sadeghi, Ali M.; McCarty, Gregory W.; Hively, W. Dean; Lang, Megan W.

2016-01-01

The adoption rate of winter cover crops (WCCs) as an effective conservation management practice to help reduce agricultural nutrient loads in the Chesapeake Bay (CB) is increasing. However, the WCC potential for water quality improvement has not been fully realized at the watershed scale. This study was conducted to evaluate the long-term impact of WCCs on hydrology and NO3-N loads in two adjacent watersheds and to identify key management factors that affect the effectiveness of WCCs using the Soil and Water Assessment Tool (SWAT) and statistical methods. Simulation results indicated that WCCs are effective for reducing NO3-N loads and their performance varied based on planting date, species, soil characteristics, and crop rotations. Early-planted WCCs outperformed late-planted WCCs on the reduction of NO3-N loads and early-planted rye (RE) reduced NO3-N loads by ~49.3% compared to the baseline (no WCC). The WCCs were more effective in a watershed dominated by well-drained soils with increased reductions in NO3-N fluxes of ~2.5 kg N·ha-1 delivered to streams and ~10.1 kg N·ha-1 leached into groundwater compared to poorly-drained soils. Well-drained agricultural lands had higher transport of NO3-N in the soil profile and groundwater due to increased N leaching. Poorly-drained agricultural lands had lower NO3-N due to extensive drainage ditches and anaerobic soil conditions promoting denitrification. The performance of WCCs varied by crop rotations (i.e., continuous corn and corn-soybean), with increased N uptake following soybean crops due to the increased soil mineral N availability by mineralization of soybean residue compared to corn residue. The WCCs can reduce N leaching where baseline NO3-N loads are high in well-drained soils and/or when residual and mineralized N availability is high due to the cropping practices. The findings suggested that WCC implementation plans should be established in watersheds according to local edaphic and agronomic

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

Research achievements and adoption of no-till, dryland cropping in the semi-arid US Great Plains

USDA-ARS?s Scientific Manuscript database

The Great Plains region of the United States and Canada is an area of widespread dryland crop production, with wheat being the dominant crop. Precipitation in the region ranges from 300 to 500 mm annually, with the majority of precipitatioCPRLn falling during hot summer months. The prevailing croppi...

Cover crop biomass harvest for bioenergy: implications for crop productivity

USDA-ARS?s Scientific Manuscript database

Winter cover crops, such as rye (Secale cereale), are usually used in conservation agriculture systems in the Southeast. Typically, the cover crop is terminated two to three weeks before planting the summer crop, with the cover biomass left on the soil surface as a mulch. However, these cover crops ...

Rice crop risk map in Babahoyo canton (Ecuador)

NASA Astrophysics Data System (ADS)

Valverde Arias, Omar; Tarquis, Ana; Garrido, Alberto

2016-04-01

It is widely known that extreme climatic phenomena occur with more intensity and frequency. This fact has put more pressure over farming, making agricultural and livestock production riskier. In order to reduce hazards and economic loses that could jeopardize farmer's incomes and even its business continuity, it is very important to implement agriculture risk management plans by governments and institutions. One of the main strategies is transfer risk by agriculture insurance. Agriculture insurance based in indexes has a significant growth in the last decade. And consist in a comparison between measured index values with a defined threshold that triggers damage losses. However, based index insurance could not be based on an isolated measurement. It is necessary to be integrated in a complete monitoring system that uses many sources of information and tools. For example, index influence areas, crop production risk maps, crop yields, claim statistics, and so on. Crop production risk is related with yield variation of crops and livestock, due to weather, pests, diseases, and other factors that affect both the quantity and quality of commodities produced. This is the risk which farmers invest more time managing, and it is completely under their control. The aim of this study is generate a crop risk map of rice that can provide risk manager important information about the status of crop facing production risks. Then, based on this information, it will be possible to make best decisions to deal with production risk. The rice crop risk map was generated qualifying a 1:25000 scale soil and climatic map of Babahoyo canton, which is located in coast region of Ecuador, where rice is one of the main crops. The methodology to obtain crop risk map starts by establishing rice crop requirements and indentifying the risks associated with this crop. A second step is to evaluate soil and climatic conditions of the study area related to optimal crop requirements. Based on it, we can

An evaluation of 10 percent and 20 percent benzocaine gels in patients with acute toothaches: efficacy, tolerability and compliance with label dose administration directions.

PubMed

Hersh, Elliot V; Ciancio, Sebastian G; Kuperstein, Arthur S; Stoopler, Eric T; Moore, Paul A; Boynes, Sean G; Levine, Steven C; Casamassimo, Paul; Leyva, Rina; Mathew, Tanya; Shibly, Othman; Creighton, Paul; Jeffers, Gary E; Corby, Patricia M A; Turetzky, Stanley N; Papas, Athena; Wallen, Jillian; Idzik-Starr, Cynthia; Gordon, Sharon M

2013-05-01

The authors evaluated the efficacy and tolerability of 10 percent and 20 percent benzocaine gels compared with those of a vehicle (placebo) gel for the temporary relief of toothache pain. They also assessed the compliance with the label dose administration directions on the part of participants with toothache pain. Under double-masked conditions, 576 participants self-applied study gel to an open tooth cavity and surrounding oral tissues. Participants evaluated their pain intensity and pain relief for 120 minutes. The authors determined the amount of gel the participants applied. The responders' rates (the primary efficacy parameter), defined as the percentage of participants who had an improvement in pain intensity as exhibited by a pain score reduction of at least one unit on the dental pain scale from baseline for two consecutive assessments any time between the five- and 20-minute points, were 87.3 percent, 80.7 percent and 70.4 percent, respectively, for 20 percent benzocaine gel, 10 percent benzocaine gel and vehicle gel. Both benzocaine gels were significantly (P ≤ .05) better than vehicle gel; the 20 percent benzocaine gel also was significantly (P ≤ .05) better than the 10 percent benzocaine gel. The mean amount of gel applied was 235.6 milligrams, with 88.2 percent of participants applying 400 mg or less. Both 10 percent and 20 percent benzocaine gels were more efficacious than the vehicle gel, and the 20 percent benzocaine gel was more efficacious than the 10 percent benzocaine gel. All treatments were well tolerated by participants. Practical Implications. Patients can use 10 percent and 20 percent benzocaine gels to temporarily treat toothache pain safely.

Connecting Biochemical Photosynthesis Models with Crop Models to Support Crop Improvement

PubMed Central

Wu, Alex; Song, Youhong; van Oosterom, Erik J.; Hammer, Graeme L.

2016-01-01

The next advance in field crop productivity will likely need to come from improving crop use efficiency of resources (e.g., light, water, and nitrogen), aspects of which are closely linked with overall crop photosynthetic efficiency. Progress in genetic manipulation of photosynthesis is confounded by uncertainties of consequences at crop level because of difficulties connecting across scales. Crop growth and development simulation models that integrate across biological levels of organization and use a gene-to-phenotype modeling approach may present a way forward. There has been a long history of development of crop models capable of simulating dynamics of crop physiological attributes. Many crop models incorporate canopy photosynthesis (source) as a key driver for crop growth, while others derive crop growth from the balance between source- and sink-limitations. Modeling leaf photosynthesis has progressed from empirical modeling via light response curves to a more mechanistic basis, having clearer links to the underlying biochemical processes of photosynthesis. Cross-scale modeling that connects models at the biochemical and crop levels and utilizes developments in upscaling leaf-level models to canopy models has the potential to bridge the gap between photosynthetic manipulation at the biochemical level and its consequences on crop productivity. Here we review approaches to this emerging cross-scale modeling framework and reinforce the need for connections across levels of modeling. Further, we propose strategies for connecting biochemical models of photosynthesis into the cross-scale modeling framework to support crop improvement through photosynthetic manipulation. PMID:27790232

Connecting Biochemical Photosynthesis Models with Crop Models to Support Crop Improvement.

PubMed

Wu, Alex; Song, Youhong; van Oosterom, Erik J; Hammer, Graeme L

2016-01-01

The next advance in field crop productivity will likely need to come from improving crop use efficiency of resources (e.g., light, water, and nitrogen), aspects of which are closely linked with overall crop photosynthetic efficiency. Progress in genetic manipulation of photosynthesis is confounded by uncertainties of consequences at crop level because of difficulties connecting across scales. Crop growth and development simulation models that integrate across biological levels of organization and use a gene-to-phenotype modeling approach may present a way forward. There has been a long history of development of crop models capable of simulating dynamics of crop physiological attributes. Many crop models incorporate canopy photosynthesis (source) as a key driver for crop growth, while others derive crop growth from the balance between source- and sink-limitations. Modeling leaf photosynthesis has progressed from empirical modeling via light response curves to a more mechanistic basis, having clearer links to the underlying biochemical processes of photosynthesis. Cross-scale modeling that connects models at the biochemical and crop levels and utilizes developments in upscaling leaf-level models to canopy models has the potential to bridge the gap between photosynthetic manipulation at the biochemical level and its consequences on crop productivity. Here we review approaches to this emerging cross-scale modeling framework and reinforce the need for connections across levels of modeling. Further, we propose strategies for connecting biochemical models of photosynthesis into the cross-scale modeling framework to support crop improvement through photosynthetic manipulation.

Biofuel as an Integrated Farm Drainage Management crop: A bioeconomic analysis

NASA Astrophysics Data System (ADS)

Levers, L. R.; Schwabe, K. A.

2017-04-01

Irrigated agricultural lands in arid regions often suffer from soil salinization and lack of drainage, which affect environmental quality and productivity. Integrated Farm Drainage Management (IFDM) systems, where drainage water generated from higher-valued crops grown on high quality soils are used to irrigate salt-tolerant crops grown on marginal soils, is one possible strategy for managing salinity and drainage problems. If the IFDM crop were a biofuel crop, both environmental and private benefits may be generated; however, little is known about this possibility. As such, we develop a bioeconomic programming model of irrigated agricultural production to examine the role salt-tolerant biofuel crops might play within an IFDM system. Our results, generated by optimizing profits over land, water, and crop choice decisions subject to resource constraints, suggest that based on the private profits alone, biofuel crops can be a competitive alternative to the common practices of land retirement and nonbiofuel crop production under both low to high drainage water salinity. Yet IFDM biofuel crop production generates 30-35% fewer GHG emissions than the other strategies. The private market competitiveness coupled with the public good benefits may justify policy changes encouraging the growth of IFDM biofuel crops in arid agricultural areas globally.

Could Crop Height Impact the Wind Resource at Agriculturally Productive Wind Farm Sites?

NASA Astrophysics Data System (ADS)

Vanderwende, B. J.; Lundquist, J. K.

2013-12-01

The agriculture-intensive United States Midwest and Great Plains regions feature some of the best wind resources in the nation. Collocation of cropland and wind turbines introduces complex meteorological interactions that could affect both agriculture and wind power production. Crop management practices may modify the wind resource through alterations of land-surface properties. In this study, we used 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. We parameterized a hypothetical array of 121 1.8 MW turbines at the site of the 2011 Crop/Wind-energy Experiment field campaign using the WRF wind farm parameterization. We estimated the impact of crop choices on power production by altering the aerodynamic roughness length in a region approximately 65 times larger than that occupied by the turbine array. Roughness lengths of 10 cm and 25 cm represent a mature soy crop and a mature corn crop respectively. Results suggest that the presence of the mature corn crop reduces hub-height wind speeds and increases rotor-layer wind shear, even in the presence of a large wind farm which itself modifies the flow. During the night, the influence of the surface was dependent on the boundary layer stability, with strong stability inhibiting the surface drag from modifying the wind resource aloft. 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.

Multiscale analysis of deforestation risk due to commodity crop expansion in sub-Saharan Africa and the role of non-industrial producers

NASA Astrophysics Data System (ADS)

Ordway, E.; Asner, G. P.; Naylor, R. L.; Nkongho, R.; Lambin, E.

2017-12-01

Rapid integration of global agricultural markets and subsequent cropland displacement in recent decades increased large-scale tropical deforestation in South America and Southeast Asia. Growing land scarcity and more stringent land use regulations in these regions could incentivize the offshoring of export-oriented commodity crop production to sub-Saharan Africa (SSA). We assess the effects of domestic- and export-oriented agricultural expansion on deforestation in SSA in recent decades at the global, regional and local scales. Using Cameroon as a case-study, we explore the influence of emerging oil palm expansion on deforestation in greater depth. We found that commodity crops are expanding in SSA, increasing pressure on tropical forests. Four Congo Basin countries, Sierra Leone, Liberia, and Cote d'Ivoire were most at risk in terms of exposure, vulnerability and pressures from agricultural expansion. These countries averaged the highest percent forest cover (58% ±17.9) and lowest proportions of potentially available cropland outside forest areas (1% ±0.9). Foreign investment in these countries was concentrated in oil palm production (81%), with a median investment area of 41,582 thousand ha. Based on remote sensing and field survey results, however, medium- and large-scale non-industrial producers are driving a substantial fraction of the oil palm expansion leading to deforestation in Cameroon. Additionally, unlike Southeast Asia, oil palm expansion in sub-Saharan Africa is associated primarily with domestic market demands. In contrast, cocoa, the fastest expanding export-oriented crop across SSA, accounted for 57% of global expansion in 2000-2013 at a rate of 132 thousand ha yr-1, yet only amounted to 0.9% of foreign land investment. Commodity crop expansion in SSA appears largely driven by small- and medium-scale farmers rather than industrial plantations. Findings highlight that, although most agricultural expansion was associated with domestic demand, there

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

Micronutrients in Soils, Crops, and Livestock

NASA Astrophysics Data System (ADS)

Gupta, Umesh C.; Wu, Kening; Liang, Siyuan

Micronutrient concentrations are generally higher in the surface soil and decrease with soil depth. In spite of the high concentration of most micronutrients in soils, only a small fraction is available to plants. Micronutrients, also known as trace elements, are required in microquantities but their lack can cause serious crop production and animal health problems. Crops vary considerably in their response to various micronutrients. Brassicas and legumes are highly responsive to molybdenum (Mo) and boron (B), whereas corn and other cereals are more responsive to zinc (Zn) and copper (Cu). Micronutrient deficiencies are more common in humid temperate regions, as well as in humid tropical regions, because of intense leaching associated with high precipitation. Soil pH is one of the most important factors affecting the availability of micronutrients to plants. With increasing pH, the availability of these nutrients is reduced with the exception of Mo whose availability increases as soil pH increases. In most plant species, leaves contain higher amounts of nutrients than other plant parts. Therefore, whenever possible, leaves should be sampled to characterize the micronutrient status of crops. Deficiency symptoms for most micronutrients appear on the younger leaves at the top of the plant, whereas toxicity symptoms generally appear on the older leaves of plants. As summarized by Deckers and Steinnes, micronutrient deficiencies are widespread in developing countries, which have much poorer soil resources than the fertile soils of Europe and North America. Many of these areas lie in the humid tropics with extremely infertile, highly weathered, and/or highly leached soils, which are intensely deficient in nutrients. The rest of such soils are in the semiarid and areas adjacent to the latter, where alkaline and calcareous soil conditions severely limit the availability of micronutrients to plants. Frequently, the Cu, iron (Fe), manganese (Mn), Zn, and selenium (Se) levels

Global Estimates of Trace Gas Fluxes Affected by Land Use Change and Irrigation of Major Crops

NASA Astrophysics Data System (ADS)

Ojima, D. S.; del Grosso, S.; Parton, W. J.; Keough, C.

2005-12-01

Cropland conversions have altered many fertile regions of the earth and have modified the biogeochemical and hydrological cycling in these regions. These croplands are significant sources of N trace gas emissions however, the extent of changing trace gas emission due to land management changes and irrigation need further analysis. We use the DAYCENT biogeochemical model which is a daily time step version of the CENTURY model. DAYCENT simulates fluxes of N2O between croplands and the atmosphere for major crop types, and allows for a dynamic representation of GHG fluxes that accounts for environmental conditions, soil characteristics, climate, specific crop qualities, and fertilizer and irrigation management practices. DAYCENT is applied to all world cropland regions. Global datasets of weather, soils, native vegetation and cropping fractions were mapped to an approximate 2° x 2° resolution. Non-spatial data (such as planting date and fertilizer application rates) were assigned as point values for each region (i.e. country), and were assumed to be similar within crop types across the region. Three major crops were simulated (corn, wheat and soybeans) under both irrigated and non-irrigated conditions. Results indicate that N2O emission for maize and soy bean increase between 3 to 10%, where as wheat emission decline by about 1% when irrigated systems are compared to non-irrigated systems.

A Conceptual Model for Solving Percent Problems.

ERIC Educational Resources Information Center

Bennett, Albert B., Jr.; Nelson, L. Ted

1994-01-01

Presents an alternative method to teaching percent problems which uses a 10x10 grid to help students visualize percents. Offers a means of representing information and suggests different approaches for finding solutions. Includes reproducible student worksheet. (MKR)

Effects of Tree-crop Farming on Land-cover Transitions in a Mosaic Landscape in the Eastern Region of Ghana.

PubMed

Asubonteng, Kwabena; Pfeffer, Karin; Ros-Tonen, Mirjam; Verbesselt, Jan; Baud, Isa

2018-05-11

Tree crops such as cocoa and oil palm are important to smallholders' livelihoods and national economies of tropical producer countries. Governments seek to expand tree-crop acreages and improve yields. Existing literature has analyzed socioeconomic and environmental effects of tree-crop expansion, but its spatial effects on the landscape are yet to be explored. This study aims to assess the effects of tree-crop farming on the composition and the extent of land-cover transitions in a mixed cocoa/oil palm landscape in Ghana. Land-cover maps of 1986 and 2015 produced through ISODATA, and maximum likelihood classification were validated with field reference, Google Earth data, and key respondent interviews. Post-classification change detection was conducted and the transition matrix analyzed using intensity analysis. Cocoa and oil palm areas have increased in extent by 8.9% and 11.2%, respectively, mainly at the expense of food-crop land and forest. The intensity of forest loss to both tree crops is at a lower intensity than the loss of food-crop land. There were transitions between cocoa and oil palm, but the gains in oil palm outweigh those of cocoa. Cocoa and oil palm have increased in area and dominance. The main cover types converted to tree-crop areas are food-crop land and off-reserve forest. This is beginning to have serious implications for food security and livelihood options that depend on ecosystem services provided by the mosaic landscape. Tree-crop policies should take account of the geographical distribution of tree-commodity production at landscape level and its implications for food production and ecosystems services.

Large Area Crop Inventory Experiment (LACIE). Phase 1: Evaluation report

NASA Technical Reports Server (NTRS)

1976-01-01

It appears that the Large Area Crop Inventory Experiment over the Great Plains, can with a reasonable expectation, be a satisfactory component of a 90/90 production estimator. The area estimator produced more accurate area estimates for the total winter wheat region than for the mixed spring and winter wheat region of the northern Great Plains. The accuracy does appear to degrade somewhat in regions of marginal agriculture where there are small fields and abundant confusion crops. However, it would appear that these regions tend also to be marginal with respect to wheat production and thus increased area estimation errors do not greatly influence the overall production estimation accuracy in the United States. The loss of segments resulting from cloud cover appears to be a random phenomenon that introduces no significant bias into the estimates. This loss does increase the variance of the estimates.

75 FR 65995 - Biomass Crop Assistance Program

Federal Register 2010, 2011, 2012, 2013, 2014

2010-10-27

... practices approved through conservation planning would be periodically monitored by USDA to determine the... negative impacts, through reduced purchases of inputs for traditional farming, within a region ranging from... changes in land management associated with the adoption of dedicated biomass energy cropping practices and...

Cranes and Crops: Investigating Farmer Tolerances toward Crop Damage by Threatened Blue Cranes (Anthropoides paradiseus) in the Western Cape, South Africa.

PubMed

van Velden, Julia L; Smith, Tanya; Ryan, Peter G

2016-12-01

The Western Cape population of Blue Cranes (Anthropoides paradiseus) in South Africa is of great importance as the largest population throughout its range. However, Blue Cranes are strongly associated with agricultural lands in the Western Cape, and therefore may come into conflict with farmers who perceive them as damaging to crops. We investigated the viability of this population by exploring farmer attitudes toward crane damage in two regions of the Western Cape, the Swartland and Overberg, using semi-structured interviews. Perceptions of cranes differed widely between regions: farmers in the Swartland perceived crane flocks to be particularly damaging to the feed crop sweet lupin (65 % of farmers reported some level of damage by cranes), and 40 % of these farmers perceived cranes as more problematic than other common bird pests. Farmers in the Overberg did not perceive cranes as highly damaging, although there was concern about cranes eating feed at sheep troughs. Farmers who had experienced large flocks on their farms and farmers who ranked cranes as more problematic than other bird pests more often perceived cranes to be damaging to their livelihoods. Biographical variables and crop profiles could not be related to the perception of damage, indicating the complexity of this human-wildlife conflict. Farmers' need for management alternatives was related to the perceived severity of damage. These results highlight the need for location-specific management solutions to crop damage by cranes, and contribute to the management of this vulnerable species.

Cranes and Crops: Investigating Farmer Tolerances toward Crop Damage by Threatened Blue Cranes ( Anthropoides paradiseus) in the Western Cape, South Africa

NASA Astrophysics Data System (ADS)

van Velden, Julia L.; Smith, Tanya; Ryan, Peter G.

2016-12-01

The Western Cape population of Blue Cranes ( Anthropoides paradiseus) in South Africa is of great importance as the largest population throughout its range. However, Blue Cranes are strongly associated with agricultural lands in the Western Cape, and therefore may come into conflict with farmers who perceive them as damaging to crops. We investigated the viability of this population by exploring farmer attitudes toward crane damage in two regions of the Western Cape, the Swartland and Overberg, using semi-structured interviews. Perceptions of cranes differed widely between regions: farmers in the Swartland perceived crane flocks to be particularly damaging to the feed crop sweet lupin (65 % of farmers reported some level of damage by cranes), and 40 % of these farmers perceived cranes as more problematic than other common bird pests. Farmers in the Overberg did not perceive cranes as highly damaging, although there was concern about cranes eating feed at sheep troughs. Farmers who had experienced large flocks on their farms and farmers who ranked cranes as more problematic than other bird pests more often perceived cranes to be damaging to their livelihoods. Biographical variables and crop profiles could not be related to the perception of damage, indicating the complexity of this human-wildlife conflict. Farmers' need for management alternatives was related to the perceived severity of damage. These results highlight the need for location-specific management solutions to crop damage by cranes, and contribute to the management of this vulnerable species.

Simulated Near-term Climate Change Impacts on Major Crops across Latin America and the Caribbean

NASA Astrophysics Data System (ADS)

Gourdji, S.; Mesa-Diez, J.; Obando-Bonilla, D.; Navarro-Racines, C.; Moreno, P.; Fisher, M.; Prager, S.; Ramirez-Villegas, J.

2016-12-01

Robust estimates of climate change impacts on agricultural production can help to direct investments in adaptation in the coming decades. In this study commissioned by the Inter-American Development Bank, near-term climate change impacts (2020-2049) are simulated relative to a historical baseline period (1971-2000) for five major crops (maize, rice, wheat, soybean and dry bean) across Latin America and the Caribbean (LAC) using the DSSAT crop model. No adaptation or technological change is assumed, thereby providing an analysis of existing climatic stresses on yields in the region and a worst-case scenario in the coming decades. DSSAT is run across irrigated and rain-fed growing areas in the region at a 0.5° spatial resolution for each crop. Crop model inputs for soils, planting dates, crop varieties and fertilizer applications are taken from previously-published datasets, and also optimized for this study. Results show that maize and dry bean are the crops most affected by climate change, followed by wheat, with only minimal changes for rice and soybean. Generally, rain-fed production sees more severe yield declines than irrigated production, although large increases in irrigation water are needed to maintain yields, reducing the yield-irrigation productivity in most areas and potentially exacerbating existing supply limitations in watersheds. This is especially true for rice and soybean, the two crops showing the most neutral yield changes. Rain-fed yields for maize and bean are projected to decline most severely in the sub-tropical Caribbean, Central America and northern South America, where climate models show a consistent drying trend. Crop failures are also projected to increase in these areas, necessitating switches to other crops or investment in adaptation measures. Generally, investment in agricultural adaptation to climate change (such as improved seed and irrigation infrastructure) will be needed throughout the LAC region in the 21st century.

A blended approach to analyze staple and high-value crops using remote sensing with radiative transfer and crop models.

NASA Astrophysics Data System (ADS)

Davitt, A. W. D.; Winter, J.; McDonald, K. C.; Escobar, V. M.; Steiner, N.

2017-12-01

The monitoring of staple and high-value crops is important for maintaining food security. The recent launch of numerous remote sensing satellites has created the ability to monitor vast amounts of crop lands, continuously and in a timely manner. This monitoring provides users with a wealth of information on various crop types over different regions of the world. However, a challenge still remains on how to best quantify and interpret the crop and surface characteristics that are measured by visible, near-infrared, and active and passive microwave radar. Currently, two NASA funded projects are examining the ability to monitor different types of crops in California with different remote sensing platforms. The goal of both projects is to develop a cost-effective monitoring tool for use by vineyard and crop managers. The first project is designed to examine the capability to monitor vineyard water management and soil moisture in Sonoma County using Soil Moisture Active Passive (SMAP), Sentinel-1A and -2, and Landsat-8. The combined mission products create thorough and robust measurements of surface and vineyard characteristics that can potentially improve the ability to monitor vineyard health. Incorporating the Michigan Microwave Canopy Scattering (MIMICS), a radiative transfer model, enables us to better understand surface and vineyard features that influence radar measurements from Sentinel-1A. The second project is a blended approach to analyze corn, rice, and wheat growth using Sentinel-1A products with Decision Support System for Agrotechnology Transfer (DSSAT) and MIMICS models. This project aims to characterize the crop structures that influence Sentinel-1A radar measurements. Preliminary results have revealed the corn, rice, and wheat structures that influence radar measurements during a growing season. The potential of this monitoring tool can be used for maintaining food security. This includes supporting sustainable irrigation practices, identifying crop

Simulating crop growth with Expert-N-GECROS under different site conditions in Southwest Germany

NASA Astrophysics Data System (ADS)

Poyda, Arne; Ingwersen, Joachim; Demyan, Scott; Gayler, Sebastian; Streck, Thilo

2016-04-01

When feedbacks between the land surface and the atmosphere are investigated by Atmosphere-Land surface-Crop-Models (ALCM) it is fundamental to accurately simulate crop growth dynamics as plants directly influence the energy partitioning at the plant-atmosphere interface. To study both the response and the effect of intensive agricultural crop production systems on regional climate change in Southwest Germany, the crop growth model GECROS (YIN & VAN LAAR, 2005) was calibrated based on multi-year field data from typical crop rotations in the Kraichgau and Swabian Alb regions. Additionally, the SOC (soil organic carbon) model DAISY (MÜLLER et al., 1998) was implemented in the Expert-N model tool (ENGEL & PRIESACK, 1993) and combined with GECROS. The model was calibrated based on a set of plant (BBCH, LAI, plant height, aboveground biomass, N content of biomass) and weather data for the years 2010 - 2013 and validated with the data of 2014. As GECROS adjusts the root-shoot partitioning in response to external conditions (water, nitrogen, CO2), it is suitable to simulate crop growth dynamics under changing climate conditions and potentially more frequent stress situations. As C and N pools and turnover rates in soil as well as preceding crop effects were expected to considerably influence crop growth, the model was run in a multi-year, dynamic way. Crop residues and soil mineral N (nitrate, ammonium) available for the subsequent crop were accounted for. The model simulates growth dynamics of winter wheat, winter rape, silage maize and summer barley at the Kraichgau and Swabian Alb sites well. The Expert-N-GECROS model is currently parameterized for crops with potentially increasing shares in future crop rotations. First results will be shown.

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

Crop biomass and evapotranspiration estimation using SPOT and Formosat-2 Data

NASA Astrophysics Data System (ADS)

Veloso, Amanda; Demarez, Valérie; Ceschia, Eric; Claverie, Martin

2013-04-01

The use of crop models allows simulating plant development, growth and yield under different environmental and management conditions. When combined with high spatial and temporal resolution remote sensing data, these models provide new perspectives for crop monitoring at regional scale. We propose here an approach to estimate time courses of dry aboveground biomass, yield and evapotranspiration (ETR) for summer (maize, sunflower) and winter crops (wheat) by assimilating Green Area Index (GAI) data, obtained from satellite observations, into a simple crop model. Only high spatial resolution and gap-free satellite time series can provide enough information for efficient crop monitoring applications. The potential of remote sensing data is often limited by cloud cover and/or gaps in observation. Data from different sensor systems need then to be combined. For this work, we employed a unique set of Formosat-2 and SPOT images (164 images) and in-situ measurements, acquired from 2006 to 2010 in southwest France. Among the several land surface biophysical variables accessible from satellite observations, the GAI is the one that has a key role in soil-plant-atmosphere interactions and in biomass accumulation process. Many methods have been developed to relate GAI to optical remote sensing signal. Here, seasonal dynamics of remotely sensed GAI were estimated by applying a method based on the inversion of a radiative transfer model using artificial neural networks. The modelling approach is based on the Simple Algorithm for Yield and Evapotranspiration estimate (SAFYE) model, which couples the FAO-56 model with an agro-meteorological model, based on Monteith's light-use efficiency theory. The SAFYE model is a daily time step crop model that simulates time series of GAI, dry aboveground biomass, grain yield and ETR. Crop and soil model parameters were determined using both in-situ measurements and values found in the literature. Phenological parameters were calibrated by the

Insecticide use and crop selection in regions with high GM adoption rates

USDA-ARS?s Scientific Manuscript database

South Dakota has recently experienced a significant increase in the proportion of acres treated with insecticide. Unfortunately, data on insecticide usage by crop at the county level is not available. The following case study seeks to uncover the reasons for this increase by analyzing county-leve...

Cover crop biomass production and water use in the central great plains under varying water availability

USDA-ARS?s Scientific Manuscript database

The water-limited environment of the semi-arid central Great Plains may not have potential to produce enough cover crop biomass to generate benefits associated with cover crop use in more humid regions. There have been reports that cover crops grown in mixtures produce more biomass with greater wate...

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.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Measuring the economic impact of climate change on major South African field crops: a Ricardian approach

NASA Astrophysics Data System (ADS)

Gbetibouo, G. A.; Hassan, R. M.

2005-07-01

This study employed a Ricardian model to measure the impact of climate change on South Africa's field crops and analysed potential future impacts of further changes in the climate. A regression of farm net revenue on climate, soil and other socio-economic variables was conducted to capture farmer-adapted responses to climate variations. The analysis was based on agricultural data for seven field crops (maize, wheat, sorghum, sugarcane, groundnut, sunflower and soybean), climate and edaphic data across 300 districts in South Africa. Results indicate that production of field crops was sensitive to marginal changes in temperature as compared to changes in precipitation. Temperature rise positively affects net revenue whereas the effect of reduction in rainfall is negative. The study also highlights the importance of season and location in dealing with climate change showing that the spatial distribution of climate change impact and consequently needed adaptations will not be uniform across the different agro-ecological regions of South Africa. Results of simulations of climate change scenarios indicate many impacts that would induce (or require) very distinct shifts in farming practices and patterns in different regions. Those include major shifts in crop calendars and growing seasons, switching between crops to the possibility of complete disappearance of some field crops from some region.

A double-hurdle model estimation of cocoa farmers' willingness to pay for crop insurance in Ghana.

PubMed

Okoffo, Elvis Dartey; Denkyirah, Elisha Kwaku; Adu, Derick Taylor; Fosu-Mensah, Benedicta Yayra

2016-01-01

Agriculture is an important sector in Ghana's economy, however, with high risk due to natural factors like climate change, pests and diseases and bush fires among others. Farmers in the Brong-Ahafo region of Ghana which is known as one of the major cocoa producing regions, face these risks which sometimes results in crop failure. The need for farmers to therefore insure their farms against crop loss is crucial. Insurance has been a measure to guard against risk. The aim of this study was to assess cocoa farmers' willingness to access crop insurance, the factors affecting willingness to pay (WTP) for crop insurance scheme and insurance companies' willingness to provide crop insurance to cocoa farmers. Multi-stage sampling technique was used to sample 240 farmers from four communities in the Dormaa West District in Brong-Ahafo Region. The double-hurdle model shows that age, marital status and education significantly and positively influenced cocoa farmer's willingness to insure their farms whiles household size and cropped area negatively influenced farmers' willingness to insure their farms. Similarly, age, household size and cropped area significantly and positively influenced the premium cocoa farmers were willing to pay whiles marital status and cocoa income negatively influenced the premium farmers were willing to pay. The contingent valuation method shows that the maximum, minimum and average amounts cocoa farmers are willing to pay for crop insurance per production cost per acre was GH¢128.40, GH¢32.10 and GH¢49.32 respectively. Insurance companies do not have crop insurance policy but willing to provide crop insurance policy to cocoa farmers on a condition that farmers adopt modern cultivation practices to reduce the level of risk. The study recommends that cocoa farmers should be well educated on crop insurance and should be involved in planning the crop insurance scheme in order to conclude on the premium to be paid by them.

Guidance on Compatibility of UST Systems with Ethanol Blends Greater Than 10 Percent and Biodiesel Blends Greater Than 20 Percent

EPA Pesticide Factsheets

EPA guidance on complying with the federal compatibility requirement for underground storage tank (UST) systems storing gasoline containing greater than 10 percent ethanol or diesel containing greater than 20 percent biodiesel.

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

Matching Crew Diet and Crop Food Production in BIO-Plex

NASA Technical Reports Server (NTRS)

Jones, Harry; Kwauk, Xianmin; Mead, Susan C. (Technical Monitor)

2000-01-01

This paper matches the BIO-Plex crop food production to the crew diet requirements. The expected average calorie requirement for BIO-Plex is 2,975 Calories per crewmember per day, for a randomly selected crew with a typical level of physical activity. The range of 2,550 to 3,400 Calories will cover about two-thirds of all crews. The exact calorie requirement will depend on the gender composition, individual weights, exercise, and work effort of the selected crew. The expected average crewmember calorie requirement can be met by 430 grams of carbohydrate, 100 grams of fat, and 90 grams of protein per crewmember per day, for a total of 620 grams. Some fat can replaced by carbohydrate. Each crewmember requires only 2 grams of vitamins and minerals per day. Only unusually restricted diets may lack essential nutrients. The Advanced Life Support (ALS) consensus is that BIO-Plex should grow wheat, potato, and soybean, and maybe sweet potato or peanut, and maybe lettuce and tomato. The BIO-Plex Biomass Production System food production and the external food supply must be matched to the crew diet requirement for calories and nutritional balance. The crop production and external supply specifications can each be varied as long as their sum matches the required diet specification. We have wide flexibility in choosing the crops and resupply. We can easily grow one-half the crew calories in one BIO-Plex Biomass Production Chamber (BPC) if we grow only the most productive crops (wheat, potato, and sweet potato) and it we achieve nominal crop productivity. If we assume higher productivity we can grow a wider variety of crops. If we grow one-half of the crew calories, externally supplied foods can easily provide the other half of the calories and balance the diet. We can not grow 95 percent of the crew calories in two BPCs at nominal productivity while growing a balanced diet. We produce maximum calories by growing wheat, potato, and peanut.

Functional Genomics of Drought Tolerance in Bioenergy Crops

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

Yin, Hengfu; Chen, Rick; Yang, Jun

2014-01-01

With the predicted trends in climate change, drought will increasingly impose a grand challenge to biomass production. Most of the bioenergy crops have some degree of drought susceptibility with low water-use efficiency (WUE). It is imperative to improve drought tolerance and WUE in bioenergy crops for sustainable biomass production in arid and semi-arid regions with minimal water input. Genetics and functional genomics can play a critical role in generating knowledge to inform and aid genetic improvement of drought tolerance in bioenergy crops. The molecular aspect of drought response has been extensively investigated in model plants like Arabidopsis, yet our understandingmore » of the molecular mechanisms underlying drought tolerance in bioenergy crops are limited. Crops exhibit various responses to drought stress depending on species and genotype. A rational strategy for studying drought tolerance in bioenergy crops is to translate the knowledge from model plants and pinpoint the unique features associated with individual species and genotypes. In this review, we summarize the general knowledge about drought responsive pathways in plants, with a focus on the identification of commonality and specialty in drought responsive mechanisms among different species and/or genotypes. We describe the genomic resources developed for bioenergy crops and discuss genetic and epigenetic regulation of drought responses. We also examine comparative and evolutionary genomics to leverage the ever-increasing genomics resources and provide new insights beyond what has been known from studies on individual species. Finally, we outline future exploration of drought tolerance using the emerging new technologies.« less

AgMIP Training in Multiple Crop Models and Tools

NASA Technical Reports Server (NTRS)

Boote, Kenneth J.; Porter, Cheryl H.; Hargreaves, John; Hoogenboom, Gerrit; Thornburn, Peter; Mutter, Carolyn

2015-01-01

The Agricultural Model Intercomparison and Improvement Project (AgMIP) has the goal of using multiple crop models to evaluate climate impacts on agricultural production and food security in developed and developing countries. There are several major limitations that must be overcome to achieve this goal, including the need to train AgMIP regional research team (RRT) crop modelers to use models other than the ones they are currently familiar with, plus the need to harmonize and interconvert the disparate input file formats used for the various models. Two activities were followed to address these shortcomings among AgMIP RRTs to enable them to use multiple models to evaluate climate impacts on crop production and food security. We designed and conducted courses in which participants trained on two different sets of crop models, with emphasis on the model of least experience. In a second activity, the AgMIP IT group created templates for inputting data on soils, management, weather, and crops into AgMIP harmonized databases, and developed translation tools for converting the harmonized data into files that are ready for multiple crop model simulations. The strategies for creating and conducting the multi-model course and developing entry and translation tools are reviewed in this chapter.

Global accumulation of tree-crops and its competition with forest loss and food security in Southeast Asia

NASA Astrophysics Data System (ADS)

Shigematsu, A.; Mizoue, N.; Yoshida, S.

2011-12-01

Tree-crops, which are the plants holding trunks for several decades and supply products in a form of fruits or resin, such as oil palm and natural rubber, comprises 5% of crop land of the world in 2008. While the expansion has been a major driver of forest loss and food security, a research on the process and proportion of tree-crops on global scale has been lacking. We examined the regional and temporal difference on the expansion process of the top five abundant tree-crops of the world while linking the trend of crop areas (for food production) and forest areas between 1960s and 2000s. We adopted FAOSTAT database and focused on globally abundant top-five tree crops (oil palm, rubber, coconuts, coffee, cocoa). Globally, notable proportional change of these five tree-crops on total crop lands was observed in Asia from 1.8% in 1961 to 5.2% in 2008. Regionally, it was Southeast Asia that exhibited the growth in the ratio of these five tree-crops on overall crop lands for the last half a century; from only one-tenth in 1961 to as much as one-fourth in 2008. While oil palm plantations are established in southern part of Southeast Asia, rubber plantations are being established in expense of traditional agricultural fields in northern Southeast Asia. We identified the tree-crops expansion has been increased in expense of agricultural areas (production for food) in Thailand from 1961 to 2008 (r = -0.828, P < 0.0001) and Myanmar from 1961 to 1989 (r = -0.741, P < 0.0001). The impacts of ongoing tree-crops expansion on food and wood security of the region need to be carefully monitored in terms of biodiversity, carbon storage, the local climate and the hydrological cycle. We proposed the suggestion the necessity of a new framework of protecting agricultural land from the expansion of tree-crops, especially oil palm and rubber.

Selection of the Argentine indicator region

NASA Technical Reports Server (NTRS)

Ramirez, C. J.; Reed, C. R. (Principal Investigator)

1982-01-01

Determined from available Argentine crop statistics, selection of the Indicator Region was based on the highest wheat, corn, and soybean producing provinces, which were: Buenos Aires, Cordoba, Entre Rios, and Santa Fe. Each province in Argentina was examined for the availability of LANDSAT data; area, yield and production statistics; crop calendars; and other ancillary data. The Argentine Indicator Region is described.

Crop-specific seasonal estimates of irrigation-water demand in South Asia

NASA Astrophysics Data System (ADS)

Biemans, Hester; Siderius, Christian; Mishra, Ashok; Ahmad, Bashir

2016-05-01

Especially in the Himalayan headwaters of the main rivers in South Asia, shifts in runoff are expected as a result of a rapidly changing climate. In recent years, our insight into these shifts and their impact on water availability has increased. However, a similar detailed understanding of the seasonal pattern in water demand is surprisingly absent. This hampers a proper assessment of water stress and ways to cope and adapt. In this study, the seasonal pattern of irrigation-water demand resulting from the typical practice of multiple cropping in South Asia was accounted for by introducing double cropping with monsoon-dependent planting dates in a hydrology and vegetation model. Crop yields were calibrated to the latest state-level statistics of India, Pakistan, Bangladesh and Nepal. The improvements in seasonal land use and cropping periods lead to lower estimates of irrigation-water demand compared to previous model-based studies, despite the net irrigated area being higher. Crop irrigation-water demand differs sharply between seasons and regions; in Pakistan, winter (rabi) and monsoon summer (kharif) irrigation demands are almost equal, whereas in Bangladesh the rabi demand is ~ 100 times higher. Moreover, the relative importance of irrigation supply versus rain decreases sharply from west to east. Given the size and importance of South Asia improved regional estimates of food production and its irrigation-water demand will also affect global estimates. In models used for global water resources and food-security assessments, processes like multiple cropping and monsoon-dependent planting dates should not be ignored.

The best alternative for estimating reference crop evapotranspiration in different sub-regions of mainland China.

PubMed

Peng, Lingling; Li, Yi; Feng, Hao

2017-07-14

Reference crop evapotranspiration (ET o ) is a critically important parameter for climatological, hydrological and agricultural management. The FAO56 Penman-Monteith (PM) equation has been recommended as the standardized ET o (ET o,s ) equation, but it has a high requirements of climatic data. There is a practical need for finding a best alternative method to estimate ET o in the regions where full climatic data are lacking. A comprehensive comparison for the spatiotemporal variations, relative errors, standard deviations and Nash-Sutcliffe efficacy coefficients of monthly or annual ET o,s and ET o,i (i = 1, 2, …, 10) values estimated by 10 selected methods (i.e., Irmak et al., Makkink, Priestley-Taylor, Hargreaves-Samani, Droogers-Allen, Berti et al., Doorenbos-Pruitt, Wright and Valiantzas, respectively) using data at 552 sites over 1961-2013 in mainland China. The method proposed by Berti et al. (2014) was selected as the best alternative of FAO56-PM because it was simple in computation process, only utilized temperature data, had generally good accuracy in describing spatiotemporal characteristics of ET o,s in different sub-regions and mainland China, and correlated linearly to the FAO56-PM method very well. The parameters of the linear correlations between ET o of the two methods are calibrated for each site with the smallest determination of coefficient being 0.87.

Opportunities and challenges for harvest weed seed control in global cropping systems.

PubMed

Walsh, Michael J; Broster, John C; Schwartz-Lazaro, Lauren M; Norsworthy, Jason K; Davis, Adam S; Tidemann, Breanne D; Beckie, Hugh J; Lyon, Drew J; Soni, Neeta; Neve, Paul; Bagavathiannan, Muthukumar V

2017-11-28

The opportunity to target weed seeds during grain harvest was established many decades ago following the introduction of mechanical harvesting and the recognition of high weed-seed retention levels at crop maturity; however, this opportunity remained largely neglected until more recently. The introduction and adoption of harvest weed seed control (HWSC) systems in Australia has been in response to widespread occurrence of herbicide-resistant weed populations. With diminishing herbicide resources and the need to maintain highly productive reduced tillage and stubble-retention practices, growers began to develop systems that targeted weed seeds during crop harvest. Research and development efforts over the past two decades have established the efficacy of HWSC systems in Australian cropping systems, where widespread adoption is now occurring. With similarly dramatic herbicide resistance issues now present across many of the world's cropping regions, it is timely for HWSC systems to be considered for inclusion in weed-management programs in these areas. This review describes HWSC systems and establishing the potential for this approach to weed control in several cropping regions. As observed in Australia, the inclusion of HWSC systems can reduce weed populations substantially reducing the potential for weed adaptation and resistance evolution. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

Measuring short-crop reference evapotranspiration in a humid region using electronic atmometers

USDA-ARS?s Scientific Manuscript database

The Crop Water Use phone app is a weather-based program developed by the Missouri Extension Service to help farmers with irrigation scheduling. A limitation of the program is that it only works on Missouri fields. The app is linked to the state agricultural weather station network, which supplies da...

Nurse crop

Treesearch

Wayne D. Shepperd; John R. Jones

1985-01-01

In forestry, a nurse crop generally is a crop of trees or shrubs that fosters the development of another tree species, usually by protecting the second species, during its youth, from frost, insolation, or wind (Ford-Robertson 1971). Aspen may be a nurse crop for shade-tolerant tree species that do not become established in full sunlight (e.g., Engelmann spruce)....

Relay cropping as a sustainable approach: problems and opportunities for sustainable crop production.

PubMed

Tanveer, Mohsin; Anjum, Shakeel Ahmad; Hussain, Saddam; Cerdà, Artemi; Ashraf, Umair

2017-03-01

Climate change, soil degradation, and depletion of natural resources are becoming the most prominent challenges for crop productivity and environmental sustainability in modern agriculture. In the scenario of conventional farming system, limited chances are available to cope with these issues. Relay cropping is a method of multiple cropping where one crop is seeded into standing second crop well before harvesting of second crop. Relay cropping may solve a number of conflicts such as inefficient use of available resources, controversies in sowing time, fertilizer application, and soil degradation. Relay cropping is a complex suite of different resource-efficient technologies, which possesses the capability to improve soil quality, to increase net return, to increase land equivalent ratio, and to control the weeds and pest infestation. The current review emphasized relay cropping as a tool for crop diversification and environmental sustainability with special focus on soil. Briefly, benefits, constraints, and opportunities of relay cropping keeping the goals of higher crop productivity and sustainability have also been discussed in this review. The research and knowledge gap in relay cropping was also highlighted in order to guide the further studies in future.

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.

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

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

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

Vanderwende, Brian; Lundquist, Julie K.

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

Effects of climate change on suitable rice cropping areas, cropping systems and crop water requirements in southern China

DOE PAGES

Ye, Qing; Yang, Xiaoguang; Dai, Shuwei; ...

2015-06-05

Here, we discuss that rice is one of the main crops grown in southern China. Global climate change has significantly altered the local water availability and temperature regime for rice production. In this study, we explored the influence of climate change on suitable rice cropping areas, rice cropping systems and crop water requirements (CWRs) during the growing season for historical (from 1951 to 2010) and future (from 2011 to 2100) time periods. The results indicated that the land areas suitable for rice cropping systems shifted northward and westward from 1951 to 2100 but with different amplitudes.

Simulating changes in cropping practices in conventional and glyphosate-resistant maize. II. Weed impacts on crop production and biodiversity.

PubMed

Colbach, Nathalie; Darmency, Henri; Fernier, Alice; Granger, Sylvie; Le Corre, Valérie; Messéan, Antoine

2017-05-01

Overreliance on the same herbicide mode of action leads to the spread of resistant weeds, which cancels the advantages of herbicide-tolerant (HT) crops. Here, the objective was to quantify, with simulations, the impact of glyphosate-resistant (GR) weeds on crop production and weed-related wild biodiversity in HT maize-based cropping systems differing in terms of management practices. We (1) simulated current conventional and probable HT cropping systems in two European regions, Aquitaine and Catalonia, with the weed dynamics model FLORSYS; (2) quantified how much the presence of GR weeds contributed to weed impacts on crop production and biodiversity; (3) determined the effect of cultural practices on the impact of GR weeds and (4) identified which species traits most influence weed-impact indicators. The simulation study showed that during the analysed 28 years, the advent of glyphosate resistance had little effect on plant biodiversity. Glyphosate-susceptible populations and species were replaced by GR ones. Including GR weeds only affected functional biodiversity (food offer for birds, bees and carabids) and weed harmfulness when weed effect was initially low; when weed effect was initially high, including GR weeds had little effect. The GR effect also depended on cultural practices, e.g. GR weeds were most detrimental for species equitability when maize was sown late. Species traits most harmful for crop production and most beneficial for biodiversity were identified, using RLQ analyses. None of the species presenting these traits belonged to a family for which glyphosate resistance was reported. An advice table was built; the effects of cultural practices on crop production and biodiversity were synthesized, explained, quantified and ranked, and the optimal choices for each management technique were identified.

Organochlorine pesticide exposure among agricultural workers in Colombian regions with illegal crops: an exploration in a hidden and dangerous world.

PubMed

Varona, Marcela Eugenia; Díaz-Criollo, Sonia M; Lancheros-Bernal, Angélica R; Murcia-Orjuela, Alix M; Henao-Londoño, Gloria L; Idrovo, Alvaro Javier

2010-12-01

A previous study suggested that banned organochlorine pesticides were being used to protect illegal crops from pests. The study herein explored the exposure of individuals living in a region with such crops. Samples from 99 individuals were collected during 2005 and 2006 and organochlorine pesticides were quantified using chromatography in serum samples. We detected heptachlor (72.73%), 4,4-DDE (19.19%), aldrin (15.15%), γ-chlordane (12.12%), dieldrin (11.11%), α-chlordane (10,10%), α-endosulfan (8.08%), endosulfan (6.06%), β-endosulfan (5.05%), oxychlordane (3.03%), 4,4-DDT (3.03%), and 2,4-DDT (2.02%). Heptachlor had a skewed and negative distribution (median: 8.69 ng/l and maximum: 43.8 ng/l). A two-dimensional biplot suggested that mixtures present were endosulfan/4,4-DDT, aldrin/γ-chlordane, and oxychlordane/β-endosulfan/dieldrin. We did not identify variables associated with exposure levels. These data suggest that banned organochlorine pesticides are used. This is an example of research in a war context, where the problems related with pesticides are complex, and their implications go beyond a toxicological or epidemiological viewpoint.

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.

Predicting optimum crop designs using crop models and seasonal climate forecasts.

PubMed

Rodriguez, D; de Voil, P; Hudson, D; Brown, J N; Hayman, P; Marrou, H; Meinke, H

2018-02-02

Expected increases in food demand and the need to limit the incorporation of new lands into agriculture to curtail emissions, highlight the urgency to bridge productivity gaps, increase farmers profits and manage risks in dryland cropping. A way to bridge those gaps is to identify optimum combination of genetics (G), and agronomic managements (M) i.e. crop designs (GxM), for the prevailing and expected growing environment (E). Our understanding of crop stress physiology indicates that in hindsight, those optimum crop designs should be known, while the main problem is to predict relevant attributes of the E, at the time of sowing, so that optimum GxM combinations could be informed. Here we test our capacity to inform that "hindsight", by linking a tested crop model (APSIM) with a skillful seasonal climate forecasting system, to answer "What is the value of the skill in seasonal climate forecasting, to inform crop designs?" Results showed that the GCM POAMA-2 was reliable and skillful, and that when linked with APSIM, optimum crop designs could be informed. We conclude that reliable and skillful GCMs that are easily interfaced with crop simulation models, can be used to inform optimum crop designs, increase farmers profits and reduce risks.

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

PubMed

Dubey, Swatantra Kumar; Sharma, Devesh

2018-09-01

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

Improving the monitoring of crop productivity using spaceborne solar-induced fluorescence.

PubMed

Guan, Kaiyu; Berry, Joseph A; Zhang, Yongguang; Joiner, Joanna; Guanter, Luis; Badgley, Grayson; Lobell, David B

2016-02-01

Large-scale monitoring of crop growth and yield has important value for forecasting food production and prices and ensuring regional food security. A newly emerging satellite retrieval, solar-induced fluorescence (SIF) of chlorophyll, provides for the first time a direct measurement related to plant photosynthetic activity (i.e. electron transport rate). Here, we provide a framework to link SIF retrievals and crop yield, accounting for stoichiometry, photosynthetic pathways, and respiration losses. We apply this framework to estimate United States crop productivity for 2007-2012, where we use the spaceborne SIF retrievals from the Global Ozone Monitoring Experiment-2 satellite, benchmarked with county-level crop yield statistics, and compare it with various traditional crop monitoring approaches. We find that a SIF-based approach accounting for photosynthetic pathways (i.e. C3 and C4 crops) provides the best measure of crop productivity among these approaches, despite the fact that SIF sensors are not yet optimized for terrestrial applications. We further show that SIF provides the ability to infer the impacts of environmental stresses on autotrophic respiration and carbon-use-efficiency, with a substantial sensitivity of both to high temperatures. These results indicate new opportunities for improved mechanistic understanding of crop yield responses to climate variability and change. © 2015 John Wiley & Sons Ltd.

Improving the Monitoring of Crop Productivity Using Spaceborne Solar-Induced Fluorescence

NASA Technical Reports Server (NTRS)

Guan, Kaiyu; Berry, Joseph A.; Zhang, Yongguang; Joiner, Joanna; Guanter, Luis; Badgley, Grayson; Lobell, David B.

2015-01-01

Large-scale monitoring of crop growth and yield has important value for forecasting food production and prices and ensuring regional food security. A newly emerging satellite retrieval, solar-induced fluorescence (SIF) of chlorophyll, provides for the first time a direct measurement related to plant photosynthetic activity (i.e. electron transport rate). Here, we provide a framework to link SIF retrievals and crop yield, accounting for stoichiometry, photosynthetic pathways, and respiration losses. We apply this framework to estimate United States crop productivity for 2007-2012, where we use the spaceborne SIF retrievals from the Global Ozone Monitoring Experiment-2 satellite, benchmarked with county-level crop yield statistics, and compare it with various traditional crop monitoring approaches. We find that a SIF-based approach accounting for photosynthetic pathways (i.e. C3 and C4 crops) provides the best measure of crop productivity among these approaches, despite the fact that SIF sensors are not yet optimized for terrestrial applications. We further show that SIF provides the ability to infer the impacts of environmental stresses on autotrophic respiration and carbon-use-efficiency, with a substantial sensitivity of both to high temperatures. These results indicate new opportunities for improved mechanistic understanding of crop yield responses to climate variability and change.

Effects of geoengineering on crop yields

NASA Astrophysics Data System (ADS)

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

2011-12-01

The potential of "solar radiation management" (SRM) to reduce future climate change and associated risks has been receiving significant attention in scientific and policy circles. SRM schemes aim to reduce global warming despite increasing atmospheric CO2 concentrations by diminishing the amount of solar insolation absorbed by the Earth, for example, by injecting scattering aerosols into the atmosphere. Climate models predict that SRM could fully compensate warming at the global mean in a high-CO2 world. While reduction of global warming may offset a part of the predicted negative effects of future climate change on crop yields, SRM schemes are expected to alter regional climate and to have substantial effects on climate variables other than temperature, such as precipitation. It has therefore been warned that, overall, SRM may pose a risk to food security. Assessments of benefits and risks of geoengineering are imperative, yet such assessments are only beginning to emerge; in particular, effects on global food security have not previously been assessed. Here, for the first time, we combine climate model simulations with models of crop yield responses to climate to assess large-scale changes in yields and food production under SRM. In most crop-growing regions, we find that yield losses caused by climate changes are substantially reduced under SRM as compared with a non-geoengineered doubling of atmospheric CO2. Substantial yield losses with SRM are only found for rice in high latitudes, where the limits of low temperatures are no longer alleviated. At the same time, the beneficial effect of CO2-fertilization on plant productivity remains active. Overall therefore, SRM in our models causes global crop yields to increase. We estimate the direct effects of climate and CO2 changes on crop production, and do not quantify effects of market dynamics and management changes. We note, however, that an SRM deployment would be unlikely to maintain the economic status quo, as

Effect of crop rotation on soil nutrient balance and weediness in soddy podzolic organic farming fields

NASA Astrophysics Data System (ADS)

Zarina, Livija; Zarina, Liga

2017-04-01

The nutrient balance in different crop rotations under organic cropping system has been investigated in Latvia at the Institute of Agricultural Resources and Economics since 2006. Latvia is located in a humid and moderate climatic region where the rainfall exceeds evaporation (soil moisture coefficient > 1) and the soil moisture regime is characteristic with percolation. The average annual precipitation is 670-850 mm. The average temperature varies from -6.7° C in January to 16.5 °C in July. The growing season is 175 - 185 days. The most widespread are podzolic soils and mainly they are present in agricultural fields in all regions of Latvia. In a wider sense the goal of the soil management in organic farming is a creation of the biologically active flora and fauna in the soil by maintaining a high level of soil organic matter which is good for crops nutrient balance. Crop rotation is a central component of organic farming systems and has many benefits, including growth of soil microbial activity, which may increase nutrient availability. The aim of the present study was to calculate nutrient balance for each crop in the rotations and average in each rotation. Taking into account that crop rotations can limit build-up of weeds, additionally within the ERA-net CORE Organic Plus transnational programs supported project PRODIVA the information required for a better utilization of crop diversification for weed management in North European organic arable cropping systems was summarized. It was found that the nutrient balance was influenced by nutrients uptake by biomass of growing crops in crop rotation. The number of weeds in the organic farming fields with crop rotation is dependent on the cultivated crops and the succession of crops in the crop rotation.

75 FR 70850 - Common Crop Insurance Regulations; Extra Long Staple Cotton Crop Provisions

Federal Register 2010, 2011, 2012, 2013, 2014

2010-11-19

... Crop Insurance Regulations; Extra Long Staple Cotton Crop Provisions AGENCY: Federal Crop Insurance... Corporation (FCIC) proposes to amend the Common Crop Insurance Regulations, Extra Long Staple Cotton Crop Insurance Provisions to remove all references to the Daily Spot Cotton Quotation and replace the reference...

78 FR 47214 - Common Crop Insurance Regulations; Extra Long Staple Cotton Crop Provisions

Federal Register 2010, 2011, 2012, 2013, 2014

2013-08-05

... Long Staple Cotton Crop Provisions AGENCY: Federal Crop Insurance Corporation, USDA. ACTION: Proposed... Insurance Regulations, Extra Long Staple (ELS) Cotton Crop Insurance Provisions to make the ELS Cotton Crop Insurance Provisions consistent with the Upland Cotton Crop Insurance Provisions and to allow a late...

Envisioning a metropolitan foodshed: potential environmental consequences of increasing food-crop production around Chicago

NASA Astrophysics Data System (ADS)

Bowen, E. E.; Martin, P. A.; Schuble, T. J.

2009-12-01

Nationwide, cities are increasingly developing policies aimed at greater sustainability, particularly focusing on reducing environmental impact. Such policies commonly emphasize more efficiently using energy to decrease the greenhouse gas (GHG) footprint of the city. However, most plans ignore the food system as a factor in regional energy use and GHG emissions. Yet, the food system in the United States accounts for ~20% of per capita greenhouse gas emissions. Local, sustainable food production is cited as one strategy for mitigating GHG emissions of large metropolitan areas. “Sustainable” for regional agriculture is often identified as small-scale, diversified food crop production using best practices management. Localized food production (termed “foodshed”) using sustainable agriculture could mitigate climate change in multiple ways: (1) energy and therefore CO2-intensive portions of the conventional food system might be replaced by local, lower-input food production resulting in carbon offsets; (2) increased regional carbon storage might result from well-managed food crop production vs. commodity crop production; and (3) averted N2O emissions might result from closing nutrient cycles on agricultural lands following changes in management practices. The broader implications for environmental impact of widespread conversion to sustainable food crop agriculture, however, remain largely unknown. We examine the Chicago metropolitan region to quantify the impact of increased local food production on regional energy efficiency and GHG emissions. Geospatial analysis is used to quantify the resource potential for establishing a Chicago metropolitan foodshed. A regional foodshed is defined by minimizing cost through transportation mode (road, rail, or water) and maximizing the production potential of different soil types. Simple biogeochemical modeling is used to predict changes in N2O emissions and nutrient flows following changes in land management practices

78 FR 70485 - Common Crop Insurance Regulations; Extra Long Staple Cotton Crop Provisions

Federal Register 2010, 2011, 2012, 2013, 2014

2013-11-26

...-0002] RIN 0563-AC41 Common Crop Insurance Regulations; Extra Long Staple Cotton Crop Provisions AGENCY... Cotton Crop Insurance Provisions to make the Extra Long Staple (ELS) Cotton Crop Insurance Provisions consistent with the Upland Cotton Crop Insurance Provisions and to allow a late planting period. The intended...

Detection of meteorological extreme effect on historical crop yield anomaly

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Measurement of the fluorescence of crop residues: A tool for controlling soil erosion

NASA Technical Reports Server (NTRS)

Daughtry, C. S. T.; Mcmurtrey, J. E., III; Chappelle, E. W.; Hunter, W. J.

1994-01-01

Management of crop residues, the portion of a crop left in the field after harvest, is an important conservation practice for minimizing soil erosion and for improving water quality. Quantification of crop residue cover is required to evaluate the effectiveness of conservation tillage practices. Methods are needed to quantify residue cover that are rapid, accurate, and objective. The fluorescence of crop residue was found to be a broadband phenomenon with emission maxima at 420 to 495 nm for excitations of 350 to 420 nm. Soils had low intensity broadband emissions over the 400 to 690 nm region for excitations of 300 to 600 nm. The range of relative fluorescence intensities for the crop residues was much greater than the fluorescence observed of the soils. As the crop residues decompose their blue fluorescence values approach the fluorescence of the soil. Fluorescence techniques are concluded to be less ambiguous and better suited for discriminating crop residues and soils than reflectance methods. If properly implemented, fluorescence techniques can be used to quantify, not only crop residue cover, but also photosynthetic efficiency in the field.

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

NASA Astrophysics Data System (ADS)

Gao, F.; Anderson, M. C.

2017-12-01

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

Orphan legume crops enter the genomics era!

PubMed

Varshney, Rajeev K; Close, Timothy J; Singh, Nagendra K; Hoisington, David A; Cook, Douglas R

2009-04-01

Many of the world's most important food legumes are grown in arid and semi-arid regions of Africa and Asia, where crop productivity is hampered by biotic and abiotic stresses. Until recently, these crops have also suffered from a dearth of genomic and molecular-genetic resources and thus were 'orphans' of the genome revolution. However, the community of legume researchers has begun a concerted effort to change this situation. The driving force is a series of international collaborations that benefit from recent advances in genome sequencing and genotyping technologies. The focus of these activities is the development of genome-scale data sets that can be used in high-throughput approaches to facilitate genomics-assisted breeding in these legumes.

Large Area Crop Inventory Experiment (LACIE). An overview of the Large Area Crop Inventory Experiment and the outlook for a satellite crop inventory. [Great Plains Corridor (North America), Canada, U.S.S.R., Brazil, China, India, and Australia

NASA Technical Reports Server (NTRS)

Erb, R. B. (Principal Investigator)

1979-01-01

The author has identified the following significant results. The most important LACIE finding was that the technology worked very well in estimating wheat production in important geographic locations. Based on working through the many successes and shortcomings of LACIE, it can be stated with confidence that: (1) the current technology can successfully monitor what production in regions having similar characteristics to those of the U.S.S.R. wheat areas and the U.S. hard red winter wheat areas; (2) with additional applied research, significant improvements in capabilities to monitor wheat in these and other important production regions can be expected in the near future; (3) the remote sensing and weather effects modeling technology approached used by LACIE is generally applicable to other major crops and crop-producing regions of the world; and (4) with suitable effort, this technology can now advance rapidly and could be widespread use in the late 1980's.

Impact of the Gulf of California SST on simulating precipitation and crop productivity in the Southwestern United States

NASA Astrophysics Data System (ADS)

Kim, S.; Kim, J.; Prasad, A. K.; Stack, D. H.; El-Askary, H. M.; Kafatos, M.

2012-12-01

Like other ecosystems, agricultural productivity is substantially affected by climate factors. Therefore, accurate climatic data (i.e. precipitation, temperature, and radiation) is crucial to simulating crop yields. In order to understand and anticipate climate change and its impacts on agricultural productivity in the Southwestern United States, the WRF regional climate model (RCM) and the Agricultural Production Systems sIMulator (APSIM) were employed for simulating crop production. 19 years of WRF RCM output show that there is a strong dry bias during the warm season, especially in Arizona. Consequently, the APSIM crop model indicates very low crop yields in this region. We suspect that the coarse resolution of reanalysis data could not resolve the relatively warm Sea Surface Temperature (SST) in the Gulf of California (GC), causing the SST to be up to 10 degrees lower than the climatology. In the Southwestern United States, a significant amount of precipitation is associated with North American Monsoon (NAM). During the monsoon season, the low-level moisture is advected to the Southwestern United States via the GC, which is known to be the dominant moisture source. Thus, high-resolution SST data in the GC is required for RCM simulations to accurately represent a reasonable amount of precipitation in the region, allowing reliable evaluation of the impacts on regional ecosystems.and evaluate impacts on regional ecosystems. To evaluate the influence of SST on agriculture in the Southwestern U.S., two sets of numerical simulations were constructed: a control, using unresolved SST of GC, and daily updated SST data from the MODIS satellite sensor. The meteorological drivers from each of the 6 year RCM runs were provided as input to the APSIM model to determine the crop yield. Analyses of the simulated crop production, and the interannual variation of the meteorological drivers, demonstrate the influence of SST on crop yields in the Southwestern United States.

Fourteen Years of Diverse Annual No-Till Cropping in Washington’s Winter Wheat – Summer Fallow Region

USDA-ARS?s Scientific Manuscript database

We have completed the 14th year of a cropping systems experiment to evaluate diverse annual (i.e., no summer fallow) cropping systems using no-till as an alternative to tillage-intensive winter wheat (Triticum aestivum L.) – summer fallow (WW-SF). Soft white and hard white classes of winter and spri...

The Effect of Crop Insurance on Technical Efficiency of Wheat Farmers in Kermanshah Province: A Corrected Ordinary Least Square Approach

NASA Astrophysics Data System (ADS)

Agahi, Hossein; Zarafshani, Kiumars; Behjat, Amir-Mohsen

The purpose of this study was to describe the effect of crop insurance on agricultural production among dry wheat farmers in Kermanshah province. The population of this study consisted of dry wheat farmers. Data used in this study was collected using stratified multi-stage cluster sampling method and face to face interview with 251 farmers in three different climate regions: tropical, temperate and cold during 2003-2004 crop years. The procedures used for determining farmers' technical efficiency was Corrected Ordinary Least Square (COLS). Findings revealed that crop insurance has positive effect on temperate and tropical regions. However, the production difference between insured and uninsured farmers in cold region was non-significant. It is therefore concluded that technical efficiency of agricultural production in Kermanshah province is a function of crop insurance as well as other variables such as crop management practices, personal characteristics and fair distribution of agricultural inputs.

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

NASA Astrophysics Data System (ADS)

Li, X.; Troy, T. J.

2018-06-01

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

Actively learning human gaze shifting paths for semantics-aware photo cropping.

PubMed

Zhang, Luming; Gao, Yue; Ji, Rongrong; Xia, Yingjie; Dai, Qionghai; Li, Xuelong

2014-05-01

Photo cropping is a widely used tool in printing industry, photography, and cinematography. Conventional cropping models suffer from the following three challenges. First, the deemphasized role of semantic contents that are many times more important than low-level features in photo aesthetics. Second, the absence of a sequential ordering in the existing models. In contrast, humans look at semantically important regions sequentially when viewing a photo. Third, the difficulty of leveraging inputs from multiple users. Experience from multiple users is particularly critical in cropping as photo assessment is quite a subjective task. To address these challenges, this paper proposes semantics-aware photo cropping, which crops a photo by simulating the process of humans sequentially perceiving semantically important regions of a photo. We first project the local features (graphlets in this paper) onto the semantic space, which is constructed based on the category information of the training photos. An efficient learning algorithm is then derived to sequentially select semantically representative graphlets of a photo, and the selecting process can be interpreted by a path, which simulates humans actively perceiving semantics in a photo. Furthermore, we learn a prior distribution of such active graphlet paths from training photos that are marked as aesthetically pleasing by multiple users. The learned priors enforce the corresponding active graphlet path of a test photo to be maximally similar to those from the training photos. Experimental results show that: 1) the active graphlet path accurately predicts human gaze shifting, and thus is more indicative for photo aesthetics than conventional saliency maps and 2) the cropped photos produced by our approach outperform its competitors in both qualitative and quantitative comparisons.

Crop and cattle production responses to tillage and cover crop management in an integrated crop-livestock system in the southeastern USA

USDA-ARS?s Scientific Manuscript database

Integrated crop-livestock systems can help achieve greater environmental quality from disparate crop and livestock systems by recycling nutrients and taking advantage of synergies between systems. We investigated crop and animal production responses in integrated crop-livestock systems with two typ...

Changing Pattern of Crop Fraction in Late Blight Induced Potato Crops in Potato Bowl of West Bengal by using Multi-temporal Time Series AWiFs Data

NASA Astrophysics Data System (ADS)

Chakrabarty, Abhisek

2016-07-01

after late blight disease affected in potato crops. Therefore, it can be concluded that based on the result of this study the improved Pixel Dichotomy Model is the most convenient method for crop fraction estimation for this region with satisfactory accuracy.

Large Area Crop Inventory Experiment (LACIE). Phase 2 evaluation report

NASA Technical Reports Server (NTRS)

1977-01-01

Documentation of the activities of the Large Area Crop Inventory Experiment during the 1976 Northern Hemisphere crop year is presented. A brief overview of the experiment is included as well as phase two area, yield, and production estimates for the United States Great Plains, Canada, and the Union of Soviet Socialist Republics spring winter wheat regions. The accuracies of these estimates are compared with independent government estimates. Accuracy assessment of the United States Great Plains yardstick region based on a through blind sight analysis is given, and reasons for variations in estimating performance are discussed. Other phase two technical activities including operations, exploratory analysis, reporting, methods of assessment, phase three and advanced system design, technical issues, and developmental activities are also included.

Developing a global crop model for maize, wheat, and soybean production

NASA Astrophysics Data System (ADS)

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

2008-12-01

Recently, the world food supply has faced a crisis due to increasing food prices driven by rising food demand, increasing fuel prices, poor harvests due to climate factors, and the use of crops such as maize and soybean to produce biofuel. In order to assess the future of global food availability, there is a need for understanding the factors underlying food production. Farmer management practices along with climatic conditions are the main elements directly influencing crop yield. As a consequence, estimations of future world food production require the use of a global crop model that simulates reasonably the effect of both climate and management practices on yield. Only a few global crop models have been developed to date, and currently none of them represent management factors adequately, principally due to the lack of spatially explicit datasets at the global scale. In this study, we present a global crop model designed for maize, wheat, and soybean production that incorporates planting and harvest decisions, along with irrigation options based on newly available data. The crop model is built on a simple water-balance algorithm based on the Penman- Monteith equation combined with a light use efficiency approach that calculates biomass production under non-nutrient-limiting conditions. We used a world crop calendar dataset to develop statistical relationships between climate variables and planting dates for different regions of the world. Development stages are defined based on total growing degree days required to reach the beginning of each phase. Irrigation options are considered in regions where water stress occurs and irrigation infrastructures exist. We use a global dataset on irrigated areas for each crop type. The quantity of water applied is then calculated in order to avoid water stress but with an upper threshold derived from total irrigation withdrawal quantity estimated by the global water use model WaterGAP 2. Our analysis will present the model

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

NASA Astrophysics Data System (ADS)

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

2013-11-01

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

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.

Climate change and farmers’ cropping patterns in Cemoro watershed area, Central Java, Indonesia

NASA Astrophysics Data System (ADS)

Sugihardjo; Sutrisno, J.; Setyono, P.; Suntoro

2018-03-01

Cropping pattern applied by farmers is usually based on the availability of water. Farmers cultivate rice when water is available. If it is unavailable, farmers will choose to plant crops that need less water. Climate change greatly affects to farmers in determining the cropping pattern as it alters the rainfall pattern and distribution in the region. This condition requires farmers to adjust the cropping pattern so that they can do the farming successfully. This study aims to examine the application of cropping patterns applied by the farmers in the Cemoro Watershed, Central Java, Indonesia. Descriptive analysis approach is employed in this research. The results showed that farmers’ cropping pattern is not based on the availability of water. However, it adopts a habit that has been practiced since long time ago or just adopt others farmer's habit. The cropping pattern applied by irrigated paddy farmers in Cemoro watershed area consists of two types: rice-rice-rice and rice-rice-secondary crops. Among those two types, most farmers apply the rice-rice-rice pattern. Meanwhile, there are three cropping patterns applied in the rain-land, namely rice-rice-rice, rice-rice-secondary crop, and rice-rice-fallow. The majority of farmers apply the second pattern (rice-rice-secondary crops). It was also found that farmers’ cropping pattern was not in accordance with the recommendation of the local government.

History - National Site for the Regional IPM Centers

Science.gov Websites

History of the Regional IPM Centers 2014 - Crop Protection and Pest Management Program (CPPM) Funding for eventually cut short to two years when the Crop and Pest Management Program replaced existing funding the word "Integrated" was inserted in the titles. Regional Integrated Pest Management

48 CFR 1852.219-76 - NASA 8 percent goal.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 48 Federal Acquisition Regulations System 6 2010-10-01 2010-10-01 true NASA 8 percent goal. 1852... 1852.219-76 NASA 8 percent goal. As prescribed in 1819.7003 insert the following clause: NASA 8 Percent... and daily business operations are controlled by one or more women. (b) The NASA Administrator is...

48 CFR 1852.219-76 - NASA 8 percent goal.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 48 Federal Acquisition Regulations System 6 2013-10-01 2013-10-01 false NASA 8 percent goal. 1852... 1852.219-76 NASA 8 percent goal. As prescribed in 1819.7003 insert the following clause: NASA 8 Percent... and daily business operations are controlled by one or more women. (b) The NASA Administrator is...

48 CFR 1852.219-76 - NASA 8 percent goal.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 48 Federal Acquisition Regulations System 6 2014-10-01 2014-10-01 false NASA 8 percent goal. 1852... 1852.219-76 NASA 8 percent goal. As prescribed in 1819.7003 insert the following clause: NASA 8 Percent... and daily business operations are controlled by one or more women. (b) The NASA Administrator is...

48 CFR 1852.219-76 - NASA 8 percent goal.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 48 Federal Acquisition Regulations System 6 2012-10-01 2012-10-01 false NASA 8 percent goal. 1852... 1852.219-76 NASA 8 percent goal. As prescribed in 1819.7003 insert the following clause: NASA 8 Percent... and daily business operations are controlled by one or more women. (b) The NASA Administrator is...

48 CFR 1852.219-76 - NASA 8 percent goal.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 48 Federal Acquisition Regulations System 6 2011-10-01 2011-10-01 false NASA 8 percent goal. 1852... 1852.219-76 NASA 8 percent goal. As prescribed in 1819.7003 insert the following clause: NASA 8 Percent... and daily business operations are controlled by one or more women. (b) The NASA Administrator is...

Using NASA UAVSAR Datasets to Link Soil Moisture to Crop Conditions

NASA Astrophysics Data System (ADS)

Davitt, A. W. D.; McDonald, K. C.; Azarderakhsh, M.; Winter, J.

2015-12-01

California and The Central Valley are experiencing one of that region's worst, persistent droughts, which represents the continuation of a prolonged drought that started in the early 2000's. Due to the continued drought, many agricultural regions in The Central Valley have been experiencing water shortages, negatively impacting agricultural production and the socio-economics of the region. Due to these impacts, there has been an increased incentive to find new ways to conserve water for use in irrigation. Recent advances in remote sensing techniques provide the ability for end users to better understand field conditions so they may make more informed decisions on irrigation timing and amounts. However, a good understanding of soil moisture and its role in crop health and yield is lacking to support informed water management decisions. Though known to be important, a robust understanding of the role of the spatio-temporal patterns in soil moisture linked to crop health is lacking. Remote sensing platforms such as NASA's Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) provide the capacity to obtain within-field measurements to estimate within-field and field-to-field variability in soil moisture. UAVSAR radar images acquired from 2010 to 2014 for Yolo County, California are being examined to determine the suitability of high resolution (field scale) multi-temporal L-band radar backscatter imagery for soil moisture assessment and crop conditions through the growing season. By using such data and linking to in-situ meteorology measurements, modeling (MIMICS), and other remote sensing derived datasets (Sentinel, Landsat, MODIS, and TOPS-SIMS), an integrated monitoring system can potentially support the assessment of agricultural field conditions. This allows growers to optimize the use of limited water supplies through informed water management practices, potentially improving crop conditions and yield in a water stressed region.