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Sample records for agricultural crop yields

  1. Hyperspectral imagery for mapping crop yield for precision agriculture

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    PubMed

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

    2016-01-01

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

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

    PubMed Central

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

    2013-01-01

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

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

    PubMed Central

    Savage, Steven D.; Jabbour, Randa

    2016-01-01

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

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

    PubMed

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

    2016-01-01

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

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

    PubMed

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

    2015-12-01

    The carbon (C) balance of agricultural soils may be largely affected by climate change. Increasing temperatures are discussed to cause a loss of soil organic carbon (SOC) due to enhanced decomposition of soil organic matter, which has a high intrinsic temperature sensitivity. On the other hand, several modeling studies assumed that potential SOC losses would be compensated or even outperformed by an increased C input by crop residues into agricultural soils. This assumption was based on a predicted general increase of net primary productivity (NPP) as a result of the CO2 fertilization effect and prolonged growing seasons. However, it is questionable if the crop C input into agricultural soils can be derived from NPP predictions of vegetation models. The C input in European croplands is largely controlled by the agricultural management and was strongly related to the development of crop yields in the last decades. Thus, a glance at past yield development will probably be more instructive for future estimations of the C input than previous modeling approaches based on NPP predictions. An analysis of European yield statistics indicated that yields of wheat, barley and maize are stagnating in Central and Northern Europe since the 1990s. The stagnation of crop yields can probably be related to a fundamental change of the agricultural management and to climate change effects. It is assumed that the soil C input is concurrently stagnating which would necessarily lead to a decrease of agricultural SOC stocks in the long-term given a constant temperature increase. Remarkably, for almost all European countries that are faced with yield stagnation indications for agricultural SOC decreases were already found. Potentially adverse effects of yield stagnation on the C balance of croplands call for an interdisciplinary investigation of its causes and a comprehensive monitoring of SOC stocks in agricultural soils of Europe. PMID:26235605

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

    NASA Astrophysics Data System (ADS)

    Azzari, G.; Lobell, D. B.

    2015-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

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

    NASA Astrophysics Data System (ADS)

    Vico, Giulia; Porporato, Amilcare

    2011-02-01

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

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

    NASA Astrophysics Data System (ADS)

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

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

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

    NASA Astrophysics Data System (ADS)

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

    2011-06-01

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

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

    PubMed Central

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

    2010-01-01

    Expanding croplands to meet the needs of a growing population, changing diets, and biofuel production comes at the cost of reduced carbon stocks in natural vegetation and soils. Here, we present a spatially explicit global analysis of tradeoffs between carbon stocks and current crop yields. The difference among regions is striking. For example, for each unit of land cleared, the tropics lose nearly two times as much carbon (∼120 tons·ha−1 vs. ∼63 tons·ha−1) and produce less than one-half the annual crop yield compared with temperate regions (1.71 tons·ha−1·y−1 vs. 3.84 tons·ha−1·y−1). Therefore, newly cleared land in the tropics releases nearly 3 tons of carbon for every 1 ton of annual crop yield compared with a similar area cleared in the temperate zone. By factoring crop yield into the analysis, we specify the tradeoff between carbon stocks and crops for all areas where crops are currently grown and thereby, substantially enhance the spatial resolution relative to previous regional estimates. Particularly in the tropics, emphasis should be placed on increasing yields on existing croplands rather than clearing new lands. Our high-resolution approach can be used to determine the net effect of local land use decisions. PMID:21041633

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

  16. Assimilation of Downscaled SMOS Soil Moisture for Quantifying Drought Impacts on Crop Yield in Agricultural Regions in Brazil

    NASA Astrophysics Data System (ADS)

    Chakrabarti, S.; Bongiovanni, T. E.; Judge, J.; Principe, J. C.; Fraisse, C.

    2013-12-01

    Reliable soil moisture (SM) information in the root zone (RZSM) is critical for quantification of agricultural drought impacts on crop yields and for recommending management and adaptation strategies for crop management, commodity trading and food security.The recently launched European Space Agency-Soil Moisture and Ocean Salinity (ESA-SMOS) and the near-future National Aeronautics and Space Administration-Soil Moisture Active Passive (NASA-SMAP) missions provide SM at unprecedented spatial resolutions of 10-25 km, but these resolutions are still too coarse for agricultural applications in heterogeneous landscapes, making downscaling a necessity. This downscaled near-surface SM can be merged with crop growth models in a data assimilation framework to provide optimal estimates of RZSM and crop yield. The objectives of the study include: 1) to implement a novel downscalingalgorithm based on the Information theoretical learning principlesto downscale SMOS soil moisture at 25 km to 1km in the Brazilian La Plata Basin region and2) to assimilate the 1km-soil moisture in the crop model for a normal and a drought year to understand the impact on crop yield. In this study, a novel downscaling algorithm based on the Principle of Relevant Information (PRI) was applied to in-situ and remotely sensed precipitation, SM, land surface temperature and leaf area index in the Brazilian Lower La Plata region in South America. An Ensemble Kalman Filter (EnKF) based assimilation algorithm was used to assimilate the downscaled soil moisture to update both states and parameters. The downscaled soil moisture for two growing seasons in2010-2011 and 2011-2012 was assimilated into the Decision Support System for Agrotechnology Transfer (DSSAT) Cropping System Model over 161 km2 rain-fed region in the Brazilian LPB regionto improve the estimates of soybean yield. The first season experienced normal precipitation, while the second season was impacted by drought. Assimilation improved yield

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed

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

    2016-01-01

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  1. Decomposing global crop yield variability

    NASA Astrophysics Data System (ADS)

    Ben-Ari, Tamara; Makowski, David

    2014-11-01

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

  2. Linking Drought Information to Crop Yield

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

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

    NASA Astrophysics Data System (ADS)

    Marshall, M.; Tu, K. P.

    2015-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2006-12-01

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

  6. Precision agriculture in dry land: spatial variability of crop yield and roles of soil surveys, aerial photos, and digital elevation models

    NASA Astrophysics Data System (ADS)

    Nachabe, Mahmood; Ahuja, Laj; Shaffer, Mary Lou; Ascough, J.; Flynn, Brian; Cipra, J.

    1998-12-01

    In dryland, yield of crop varies substantially in space, often changing by an order of magnitude within few meters. Precision agriculture aims at exploiting this variability by changing agriculture management practices in space according to site specific conditions. Thus instead of managing a field (typical area 50 to 100 hectares) as a single unit using average conditions, the field is partitioned into small pieces of land known as management units. The size of management units can be in the order of 100 to 1,000 m2 to capture the patterns of variation of yield in the field. Agricultural practices like seeding rate, type of crop, and tillage and fertilizers are applied at the scale of the management unit to suit local agronomic conditions in unit. If successfully practiced, precision agriculture has the potential of increasing income and minimizing environmental impacts by reducing over application of crop production inputs. In the 90s, the implementation of precision agriculture was facilitated tremendously due to the wide availability and use of three technologies: (1) the Global Positioning System (GPS), (2) the Geographic Information System (GIS), and (3) remote sensing. The introduction of the GPS allowed the farmer to determine his coordinate location as equipments are moved in the field. Thus, any piece of equipment can be easily programmed to vary agricultural practices according to coordinate location over the field. The GIS allowed the storage and manipulation of large sets of data and the production of yield maps. Yield maps can be correlated with soil attributes from soil survey, and/or topographical attributes from a Digital Elevation Model (DEM). This helps predicting variation of potential yield over the landscape based on the spatial distribution of soil and topographical attributes. Soil attributes may include soil PH, Organic Matter, porosity, and hydraulic conductivity, whereas topographical attributes involve the estimations of elevation, slope

  7. Ecoinformatics Reveals Effects of Crop Rotational Histories on Cotton Yield

    PubMed Central

    Meisner, Matthew H.; Rosenheim, Jay A.

    2014-01-01

    Crop rotation has been practiced for centuries in an effort to improve agricultural yield. However, the directions, magnitudes, and mechanisms of the yield effects of various crop rotations remain poorly understood in many systems. In order to better understand how crop rotation influences cotton yield, we used hierarchical Bayesian models to analyze a large ecoinformatics database consisting of records of commercial cotton crops grown in California's San Joaquin Valley. We identified several crops that, when grown in a field the year before a cotton crop, were associated with increased or decreased cotton yield. Furthermore, there was a negative association between the effect of the prior year's crop on June densities of the pest Lygus hesperus and the effect of the prior year's crop on cotton yield. This suggested that some crops may enhance L. hesperus densities in the surrounding agricultural landscape, because residual L. hesperus populations from the previous year cannot continuously inhabit a focal field and attack a subsequent cotton crop. In addition, we found that cotton yield declined approximately 2.4% for each additional year in which cotton was grown consecutively in a field prior to the focal cotton crop. Because L. hesperus is quite mobile, the effects of crop rotation on L. hesperus would likely not be revealed by small plot experimentation. These results provide an example of how ecoinformatics datasets, which capture the true spatial scale of commercial agriculture, can be used to enhance agricultural productivity. PMID:24465657

  8. Why we need GMO crops in agriculture

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  9. Possible future directions in crop yield forecasting

    NASA Technical Reports Server (NTRS)

    Colwell, J. E.

    1979-01-01

    This paper examines present and future possible applications of remote sensing to crop yield forecasting. It is concluded that there are ways in which Landsat data could be used to assist in crop yield forecasting using present technology. A framework for global crop yield forecasting which uses remote sensing, meteorological, field and ancillary data, as available, is proposed for the future.

  10. Effects of geoengineering on crop yields

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

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

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

    PubMed Central

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

    2015-01-01

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

  12. 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

  13. Field spectroscopy of agricultural crops

    NASA Technical Reports Server (NTRS)

    Bauer, M. E.; Daughtry, C. S. T.; Biehl, L. L.; Kanemasu, E. T.; Hall, F. G.

    1986-01-01

    The development of the full potential of multispectral data acquired from satellites, requires quantitative knowledge, and physical models of the spectral properties of specific earth surface features. Knowledge of the relationships between spectral-radiometric characteristics and important biophysical parameters of agricultural crops and soils can best be obtained by carefully controlled studies of fields or plots. It is important to select plots where data describing the agronomic-biophysical properties of the crop canopies and soil background are attainable, taking into account also the feasibility of frequent timely calibrated spectral measurements. The term 'field spectroscopy' is employed for this research. The present paper is concerned with field research which was sponsored by NASA as part of the AgRISTARS Supporting Research Project. Attention is given to field research objectives, field research instrumentation, measurement procedures, spectral-temporal profile modeling, and the effects of cultural and environmental factors on crop reflectance.

  14. Global crop yield losses from recent warming

    SciTech Connect

    Lobell, D; Field, C

    2006-06-02

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

  15. Mapping Crop Yield and Sow Date Using High Resolution Imagery

    NASA Astrophysics Data System (ADS)

    Royal, K.

    2015-12-01

    Keitasha Royal, Meha Jain, Ph.D., David Lobell, Ph.D Mapping Crop Yield and Sow Date Using High Resolution ImageryThe use of satellite imagery in agriculture is becoming increasingly more significant and valuable. Due to the emergence of new satellites, such as Skybox, these satellites provide higher resolution imagery (e.g 1m) therefore improving the ability to map smallholder agriculture. For the smallholder farm dominated area of northern India, Skybox high-resolution satellite imagery can aid in understanding how to improve farm yields. In particular, we are interested in mapping winter wheat in India, as this region produces approximately 80% of the country's wheat crop, which is important given that wheat is a staple crop that provides approximately 20% of household calories. In northeast India, the combination of increased heat stress, limited irrigation access, and the difficulty for farmers to access advanced farming technologies results in farmers only producing about 50% of their potential crop yield. The use of satellite imagery can aid in understanding wheat yields through time and help identify ways to increase crop yields in the wheat belt of India. To translate Skybox satellite data into meaningful information about wheat fields, we examine vegetation indices, such as the normalized difference vegetation index (NDVI), to measure the "greenness" of plants to help determine the health of the crops. We test our ability to predict crop characteristics, like sow date and yield, using vegetation indices of 59 fields for which we have field data in Bihar, India.

  16. Global Agriculture Yields and Conflict under Future Climate

    NASA Astrophysics Data System (ADS)

    Rising, J.; Cane, M. A.

    2013-12-01

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

  17. Random Forests for Global and Regional Crop Yield Predictions

    PubMed Central

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

    2016-01-01

    Accurate predictions of crop yield are critical for developing effective agricultural and food policies at the regional and global scales. We evaluated a machine-learning method, Random Forests (RF), for its ability to predict crop yield responses to climate and biophysical variables at global and regional scales in wheat, maize, and potato in comparison with multiple linear regressions (MLR) serving as a benchmark. We used crop yield data from various sources and regions for model training and testing: 1) gridded global wheat grain yield, 2) maize grain yield from US counties over thirty years, and 3) potato tuber and maize silage yield from the northeastern seaboard region. RF was found highly capable of predicting crop yields and outperformed MLR benchmarks in all performance statistics that were compared. For example, the root mean square errors (RMSE) ranged between 6 and 14% of the average observed yield with RF models in all test cases whereas these values ranged from 14% to 49% for MLR models. Our results show that RF is an effective and versatile machine-learning method for crop yield predictions at regional and global scales for its high accuracy and precision, ease of use, and utility in data analysis. RF may result in a loss of accuracy when predicting the extreme ends or responses beyond the boundaries of the training data. PMID:27257967

  18. Are the yields of major cereal crops stagnating? Results from the newly developed high spatial resolution crop yield time series

    NASA Astrophysics Data System (ADS)

    Ray, D. K.; Ramankutty, N.; Foley, J. A.

    2011-12-01

    A variety of global scale studies that use crop yield time series for the last 50 years have remained constrained to using national level information due to the lack of high spatial resolution crop yield time series data. In this presentation we will unveil a new global crop yield data set for the 1961-2008 time period, at 5 min spatial resolution, and covering 174 crops. We developed this data by collecting national and sub-national harvested area and production information for individual crops. This new dataset can be used to answer questions related to global agriculture at a resolution and over a time period not previously possible. We have used this new dataset to address the question of whether the yields of the three important cereal crops -- maize, rice and wheat -- are stagnating as widely reported. Our results show that while in the older crop belts of the world yield improvements have slowed, a green revolution type of major yield increases in maize, rice and wheat are continuing in newly cultivated areas of the world.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  20. Crop status evaluations and yield predictions

    NASA Technical Reports Server (NTRS)

    Haun, J. R.

    1976-01-01

    One phase of the large area crop inventory project is presented. Wheat yield models based on the input of environmental variables potentially obtainable through the use of space remote sensing were developed and demonstrated. By the use of a unique method for visually qualifying daily plant development and subsequent multifactor computer analyses, it was possible to develop practical models for predicting crop development and yield. Development of wheat yield prediction models was based on the discovery that morphological changes in plants are detected and quantified on a daily basis, and that this change during a portion of the season was proportional to yield.

  1. 7 CFR 1412.31 - Direct payment yields for covered commodities, except pulse crops.

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ... commodities, except pulse crops. (a) The direct payment yield for each covered commodity, except pulse crops... for covered commodities at part 1412 of this chapter in effect on January 1, 2008 (see 7 CFR part 1412... pulse crops. 1412.31 Section 1412.31 Agriculture Regulations of the Department of Agriculture...

  2. 7 CFR 1412.31 - Direct payment yields for covered commodities, except pulse crops.

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ... commodities, except pulse crops. (a) The direct payment yield for each covered commodity, except pulse crops... for covered commodities at part 1412 of this chapter in effect on January 1, 2008 (see 7 CFR part 1412... pulse crops. 1412.31 Section 1412.31 Agriculture Regulations of the Department of Agriculture...

  3. 7 CFR 1412.31 - Direct payment yields for covered commodities, except pulse crops.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... commodities, except pulse crops. (a) The direct payment yield for each covered commodity, except pulse crops... for covered commodities at part 1412 of this chapter in effect on January 1, 2008 (see 7 CFR part 1412... pulse crops. 1412.31 Section 1412.31 Agriculture Regulations of the Department of Agriculture...

  4. 7 CFR 1412.32 - Direct payment yield for designated oilseed and pulse crops.

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ... oilseed and pulse crops. (a) The direct payment yield for designated oilseeds for which a yield was not... designated oilseed for which a yield was not established by September 30, 2007, and for pulse crops on the... 7 Agriculture 10 2013-01-01 2013-01-01 false Direct payment yield for designated oilseed and...

  5. 7 CFR 1412.32 - Direct payment yield for designated oilseed and pulse crops.

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ... oilseed and pulse crops. (a) The direct payment yield for designated oilseeds for which a yield was not... designated oilseed for which a yield was not established by September 30, 2007, and for pulse crops on the... 7 Agriculture 10 2012-01-01 2012-01-01 false Direct payment yield for designated oilseed and...

  6. 7 CFR 1412.32 - Direct payment yield for designated oilseed and pulse crops.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... oilseed and pulse crops. (a) The direct payment yield for designated oilseeds for which a yield was not... designated oilseed for which a yield was not established by September 30, 2007, and for pulse crops on the... 7 Agriculture 10 2014-01-01 2014-01-01 false Direct payment yield for designated oilseed and...

  7. YIELD EDITOR: SOFTWARE FOR REMOVING ERRORS FROM CROP YIELD MAPS

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Yield maps are a key component of precision agriculture, due to their usefulness in both development and evaluation of precision management strategies. The value of these yield maps can be compromised by the fact that raw yield maps contain a variety of inherent errors. Researchers have reported t...

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

    NASA Astrophysics Data System (ADS)

    Kancheva, Rumiana; Borisova, Denitsa; Georgiev, Georgy

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

  9. Agricultural impacts: Mapping future crop geographies

    NASA Astrophysics Data System (ADS)

    Travis, William R.

    2016-06-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

  11. County-Level Crop Yield Prediction Using Remote Sensing Data

    NASA Astrophysics Data System (ADS)

    Wagstaff, K. L.; Roper, A.; Lane, T.

    2007-12-01

    Early estimates of crop yield, particularly at a fine scale, can inform precision agriculture efforts. The USDA National Agricultural Statistics Service (NASS) currently provides estimates of yield on a monthly basis for each state. These estimates are based on phone interviews with farmers and in-situ examination of randomly selected plots. We seek to provide predictions at a much higher spatial resolution, on a more frequent basis, using remote sensing observations. We use publicly available data from the MODIS (Moderate Resolution Imaging Spectroradiometer) instruments on the Aqua and Terra spacecraft. These observations have a spatial resolution of 250 m and consist of two spectral bands (red and infra-red) with a repeat period of 8 days. As part of the HARVIST (Heterogeneous Agricultural Research Via Interactive, Scalable Technology) project, we have created statistical crop yield models using historical MODIS data combined with the per-county yield reported by the USDA at the end of the growing season. In our approach, we analyze 100 randomly selected historical pixels from each county to generate a yield prediction for the county as a whole. We construct a time series for each pixel that consists of its NDVI (Normalized Difference Vegetation Index) value observed during each 8-day time period to date. We then cluster all pixels together to identify groups of distinct elements (different crops, bodies of water, urban areas, desert, etc.) and create a regression model for each one. For each crop of interest, the model that best predicts that crop's historical yield is selected. These models can then be applied to data from subsequent years to generate predictions for the future. We applied this approach to data from California and Kansas for corn and wheat. We found that, in general, the yield prediction error decreased as the harvest time approached. In California, distinctly different models were selected to predict corn and wheat, permitting specialization

  12. Possible changes to arable crop yields by 2050.

    PubMed

    Jaggard, Keith W; Qi, Aiming; Ober, Eric S

    2010-09-27

    By 2050, the world population is likely to be 9.1 billion, the CO(2) concentration 550 ppm, the ozone concentration 60 ppb and the climate warmer by ca 2 degrees C. In these conditions, what contribution can increased crop yield make to feeding the world? CO(2) enrichment is likely to increase yields of most crops by approximately 13 per cent but leave yields of C4 crops unchanged. It will tend to reduce water consumption by all crops, but this effect will be approximately cancelled out by the effect of the increased temperature on evaporation rates. In many places increased temperature will provide opportunities to manipulate agronomy to improve crop performance. Ozone concentration increases will decrease yields by 5 per cent or more. Plant breeders will probably be able to increase yields considerably in the CO(2)-enriched environment of the future, and most weeds and airborne pests and diseases should remain controllable, so long as policy changes do not remove too many types of crop-protection chemicals. However, soil-borne pathogens are likely to be an increasing problem when warmer weather will increase their multiplication rates; control is likely to need a transgenic approach to breeding for resistance. There is a large gap between achievable yields and those delivered by farmers, even in the most efficient agricultural systems. A gap is inevitable, but there are large differences between farmers, even between those who have used the same resources. If this gap is closed and accompanied by improvements in potential yields then there is a good prospect that crop production will increase by approximately 50 per cent or more by 2050 without extra land. However, the demands for land to produce bio-energy have not been factored into these calculations. PMID:20713388

  13. Possible changes to arable crop yields by 2050

    PubMed Central

    Jaggard, Keith W.; Qi, Aiming; Ober, Eric S.

    2010-01-01

    By 2050, the world population is likely to be 9.1 billion, the CO2 concentration 550 ppm, the ozone concentration 60 ppb and the climate warmer by ca 2°C. In these conditions, what contribution can increased crop yield make to feeding the world? CO2 enrichment is likely to increase yields of most crops by approximately 13 per cent but leave yields of C4 crops unchanged. It will tend to reduce water consumption by all crops, but this effect will be approximately cancelled out by the effect of the increased temperature on evaporation rates. In many places increased temperature will provide opportunities to manipulate agronomy to improve crop performance. Ozone concentration increases will decrease yields by 5 per cent or more. Plant breeders will probably be able to increase yields considerably in the CO2-enriched environment of the future, and most weeds and airborne pests and diseases should remain controllable, so long as policy changes do not remove too many types of crop-protection chemicals. However, soil-borne pathogens are likely to be an increasing problem when warmer weather will increase their multiplication rates; control is likely to need a transgenic approach to breeding for resistance. There is a large gap between achievable yields and those delivered by farmers, even in the most efficient agricultural systems. A gap is inevitable, but there are large differences between farmers, even between those who have used the same resources. If this gap is closed and accompanied by improvements in potential yields then there is a good prospect that crop production will increase by approximately 50 per cent or more by 2050 without extra land. However, the demands for land to produce bio-energy have not been factored into these calculations. PMID:20713388

  14. 7 CFR 1412.32 - Direct payment yield for designated oilseed and pulse crops.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 7 Agriculture 10 2010-01-01 2010-01-01 false Direct payment yield for designated oilseed and pulse... oilseed and pulse crops. (a) The direct payment yield for designated oilseeds for which a yield was not established by September 30, 2007, and pulse crops for the farm will be determined by multiplying the...

  15. Preventing pesticide contamination of groundwater while maximizing irrigated crop yield

    NASA Astrophysics Data System (ADS)

    Peralta, R. C.; Hegazy, M. A.; Musharrafieh, G. R.

    1994-11-01

    A simulation/optimization model is developed for maximizing irrigated crop yield while avoiding unacceptable pesticide leaching. The optimization model is designed to help managers prevent non-point source contamination of shallow groundwater aquifers. It computes optimal irrigation amounts for given soil, crop, chemical, and weather data and irrigation frequencies. It directly computes the minimum irrigated crop yield reduction needed to prevent groundwater contamination. Constraint equations used in the model maintain a layered soil moisture volume balance; describe percolation, downward unsaturated zone solute transport and pesticide degradation; and limit the amount of pesticide reaching groundwater. Constraints are linear, piecewise linear, nonlinear, and exponential. The problem is solved using nonlinear programming optimization. The model is tested for different scenarios of irrigating corn. The modeling approach is promising as a tool to aid in the development of environmentally sound agricultural production practices. It allows direct estimation of trade-offs between crop production and groundwater protection for different management approaches. More frequent irrigation tends to give better crop yield and reduce solute movement. Trade-offs decrease with increasing irrigation frequency. More frequent irrigation reduces yield loss due to moisture stress and requires less water to fill the root zone to field capacity. This prevents the solute from moving to deeper soil layers. Yield-environmental quality trade-offs are smaller for deeper groundwater tables because deeper groundwater allows more time for chemical degradation.

  16. Potential use of MODIS imagery for operational crop yield assessment

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Monitoring crop condition and yields at regional scales remains a challenge. Ground-based sampling for assessment of crop yields at regional and national scales require enormous resources. Crop yield simulation models have shown great success in predicting crop yields at field and small scales; how...

  17. Predicting Crop Yield from Biophysical and Spectral Variables

    NASA Astrophysics Data System (ADS)

    Kancheva, Rumiana; Borisova, Denitsa

    A strong stress is being put over the past years on the application and added-value of remotely sensed data. Agricultural monitoring is an important application field of remote sensing tech-nologies associated with plant growth assessment, stress detection and yield forecasting. In-terest is rapidly spreading in the use of hyperspectral data to precision farming. For precision agriculture running, regular and timely information is needed about plant growth in order to assess crop development and predict yield. Entering wider into their opperational stage, re-mote sensing technologies face higher requirements to the accuracy of the information they provide. Because of the raising need for reliability of the information products, ground-based observations are considered one of the pillars of remote sensing being used in land cover stud-ies for the development and validation of data analysis and retrieval algorithms. This paper presents the results of ground-level studies aimed at the empirical modelling of cereals yield using multispectral and multitemporal data. The objective of the study is to develop and test the performance of vegetation indices as predictors of crop production. The approach com-prises the development of yield forecasting models from single and multi-date spectral data and the verification of remote sensing predictions through comparison with estimations from yield relationships with crop agronomical parameters. Statistical relationships between crop spectral reflectance, growth variables and yield have been established. Grain yield has been related to spectral data acquired at different phenological stages of plant development and to spectral data accumulated during the entire growing season. Comparison has been made between the yield prediction results from crop biophysical, multispectral and multitemporal data in order to validate the predictive performance of the spectral models. The algorithm has been realized on winter wheat. In-situ high

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

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... 7 Agriculture 10 2011-01-01 2011-01-01 false Direct payment yield for designated oilseed and pulse... Establishment of Yields for Direct and Counter-Cyclical Payments § 1412.32 Direct payment yield for designated oilseed and pulse crops. (a) The direct payment yield for designated oilseeds for which a yield was...

  19. 7 CFR 1412.31 - Direct payment yields for covered commodities, except pulse crops.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... for covered commodities at part 1412 of this chapter in effect on January 1, 2008 (see 7 CFR part 1412... pulse crops. 1412.31 Section 1412.31 Agriculture Regulations of the Department of Agriculture (Continued... commodities, except pulse crops. (a) The direct payment yield for each covered commodity, except pulse...

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

    Annual crop yield depends on various factors such as soil properties, management decisions, and meteorological conditions. Unfavorable weather conditions, e.g. droughts, have the potential to drastically diminish crop yield in rain-fed agriculture. For example, the drought in 2003 caused direct losses of 1.5 billion EUR only in Germany. Predicting crop yields allows to mitigate negative effects of weather extremes which are assumed to occur more often in the future due to climate change. A standard approach in economics is to predict the impact of climate change on agriculture as a function of temperature and precipitation. This approach has been developed further using concepts like growing degree days. Other econometric models use nonlinear functions of heat or vapor pressure deficit. However, none of these approaches uses soil moisture to predict crop yield. We hypothesize that soil moisture is a better indicator to explain stress on plant growth than estimations based on precipitation and temperature. This is the case because the latter variables do not explicitly account for the available water content in the root zone, which is the primary source of water supply for plant growth. In this study, a reduced form panel approach is applied to estimate a multivariate econometric production function for the years 1999 to 2010. Annual crop yield data of various crops on the administrative district level serve as depending variables. The explanatory variable of major interest is the Soil Moisture Index (SMI), which quantifies anomalies in root zone soil moisture. The SMI is computed by the mesoscale Hydrological Model (mHM, www.ufz.de/mhm). The index represents the monthly soil water quantile at a 4 km2 grid resolution covering entire Germany. A reduced model approach is suitable because the SMI is the result of a stochastic weather process and therefore can be considered exogenous. For the ease of interpretation a linear functionality is preferred. Meteorological

  2. Lime effects on soil acidity, crop yield and aluminum chemistry in inland Pacific Northwest direct-seed cropping systems

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The pH of agricultural soils in the Inland Pacific Northwest (IPNW) has declined below established critical levels for cereal and grain legume crops. Our objective was to assess the effects of broadcast or subsurface banded lime treatments on soil acidity, crop yield, and aluminum (Al) chemistry in ...

  3. The fingerprint of climate trends on European crop yields

    PubMed Central

    Moore, Frances C.; Lobell, David B.

    2015-01-01

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

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

    ERIC Educational Resources Information Center

    Boyd, Chester; And Others

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

  5. Airborne hyperspectral imagery for mapping crop yield variability

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Information concerning the spatial variation in crop yield has become necessary for site-specific crop management. Traditional satellite imagery has long been used to monitor crop growing conditions and to estimate crop yields over large geographic areas. However, this type of imagery has limited us...

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  7. 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.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  9. Second Generation Crop Yield Models Review

    NASA Technical Reports Server (NTRS)

    Hodges, T. (Principal Investigator)

    1982-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

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

    NASA Technical Reports Server (NTRS)

    Bugbee, B.; Monje, O.

    1992-01-01

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

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

    PubMed

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

    2013-12-01

    Crop simulation models can be used to estimate impact of current and future climates on crop yields and food security, but require long-term historical daily weather data to obtain robust simulations. In many regions where crops are grown, daily weather data are not available. Alternatively, gridded weather databases (GWD) with complete terrestrial coverage are available, typically derived from: (i) global circulation computer models; (ii) interpolated weather station data; or (iii) remotely sensed surface data from satellites. The present study's objective is to evaluate capacity of GWDs to simulate crop yield potential (Yp) or water-limited yield potential (Yw), which can serve as benchmarks to assess impact of climate change scenarios on crop productivity and land use change. Three GWDs (CRU, NCEP/DOE, and NASA POWER data) were evaluated for their ability to simulate Yp and Yw of rice in China, USA maize, and wheat in Germany. Simulations of Yp and Yw based on recorded daily data from well-maintained weather stations were taken as the control weather data (CWD). Agreement between simulations of Yp or Yw based on CWD and those based on GWD was poor with the latter having strong bias and large root mean square errors (RMSEs) that were 26-72% of absolute mean yield across locations and years. In contrast, simulated Yp or Yw using observed daily weather data from stations in the NOAA database combined with solar radiation from the NASA-POWER database were in much better agreement with Yp and Yw simulated with CWD (i.e. little bias and an RMSE of 12-19% of the absolute mean). We conclude that results from studies that rely on GWD to simulate agricultural productivity in current and future climates are highly uncertain. An alternative approach would impose a climate scenario on location-specific observed daily weather databases combined with an appropriate upscaling method. PMID:23801639

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

    PubMed Central

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

    2013-01-01

    Crop simulation models can be used to estimate impact of current and future climates on crop yields and food security, but require long-term historical daily weather data to obtain robust simulations. In many regions where crops are grown, daily weather data are not available. Alternatively, gridded weather databases (GWD) with complete terrestrial coverage are available, typically derived from: (i) global circulation computer models; (ii) interpolated weather station data; or (iii) remotely sensed surface data from satellites. The present study's objective is to evaluate capacity of GWDs to simulate crop yield potential (Yp) or water-limited yield potential (Yw), which can serve as benchmarks to assess impact of climate change scenarios on crop productivity and land use change. Three GWDs (CRU, NCEP/DOE, and NASA POWER data) were evaluated for their ability to simulate Yp and Yw of rice in China, USA maize, and wheat in Germany. Simulations of Yp and Yw based on recorded daily data from well-maintained weather stations were taken as the control weather data (CWD). Agreement between simulations of Yp or Yw based on CWD and those based on GWD was poor with the latter having strong bias and large root mean square errors (RMSEs) that were 26–72% of absolute mean yield across locations and years. In contrast, simulated Yp or Yw using observed daily weather data from stations in the NOAA database combined with solar radiation from the NASA-POWER database were in much better agreement with Yp and Yw simulated with CWD (i.e. little bias and an RMSE of 12–19% of the absolute mean). We conclude that results from studies that rely on GWD to simulate agricultural productivity in current and future climates are highly uncertain. An alternative approach would impose a climate scenario on location-specific observed daily weather databases combined with an appropriate upscaling method. PMID:23801639

  14. Separability of agricultural crops with airborne scatterometry

    NASA Technical Reports Server (NTRS)

    Mehta, N. C.

    1983-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  16. 7 CFR 1412.34 - Submitting production evidence for establishing direct payment yields for oilseeds and pulse crops.

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ... oilseeds and pulse crops. (a)(1) Reports of production evidence must be submitted when the owner elects to... designated oilseeds for which a yield was not established by September 30, 2007, and for pulse crops must be... direct payment yields for oilseeds and pulse crops. 1412.34 Section 1412.34 Agriculture Regulations...

  17. 7 CFR 1412.34 - Submitting production evidence for establishing direct payment yields for oilseeds and pulse crops.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... oilseeds and pulse crops. (a)(1) Reports of production evidence must be submitted when the owner elects to... designated oilseeds for which a yield was not established by September 30, 2007, and for pulse crops must be... direct payment yields for oilseeds and pulse crops. 1412.34 Section 1412.34 Agriculture Regulations...

  18. 7 CFR 1412.34 - Submitting production evidence for establishing direct payment yields for oilseeds and pulse crops.

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ... oilseeds and pulse crops. (a)(1) Reports of production evidence must be submitted when the owner elects to... designated oilseeds for which a yield was not established by September 30, 2007, and for pulse crops must be... direct payment yields for oilseeds and pulse crops. 1412.34 Section 1412.34 Agriculture Regulations...

  19. Perun: The System For Seasonal Crop Yield Forecasting Based On The Crop Model and Weather Generator

    NASA Astrophysics Data System (ADS)

    Dubrovsky, M.; Zalud, Z.; Trnka, M.; Haberle, J.; Pesice, P.

    The main purpose of the computer system PERUN, which is now being developed, is the probabilistic seasonal crop yield forecasting. The crop yields (winter wheat and spring barley in the first step) are simulated by crop model WOFOST. The input daily weather series consist of observed data, which are available in the date of forecast issuance, and synthetic data, which follow up with the observed data till the end of the crop model simulation. The synthetic weather series are generated by stochastic generator Met&Roll conditionally on the seasonal weather forecast. The probabilis- tic forecast is based on multiple crop model runs. To provide the six daily weather characteristics required for crop model simulation (precipitation, solar radiation, max- imum and minimum temperatures, air humidity, wind speed), the previous WGEN- like four-variate version of Met&Roll generator was supplemented by a new module. This module adds wind speed and air humidity (necessary to calculate evapotranspi- ration) using the nearest neighbours resampling from the observed data. Because of the problems with availability and/or accuracy of wind and humidity data, the source code of the WOFOST model was modified and allows now to switch between Penman and Makkink methods of calculating the evapotranspiration (the daily values of wind speed and humidity are not required in the Makkink method). The contribution will address following items: 1) Structure of the PERUN system: components and their inputs and outputs. Modifications to WOFOST crop model and Met&Roll generator will be discussed. 2) Validation of the WOFOST crop model. The accuracy obtained using the Penman and Makkink methods will be compared. 3) Demonstration of the forecast accuracy in dependence on the date of issuance. Acknowledgement: The system PERUN is being developed within the frame of project QC1316 sponsored by the Czech National Agency for Agricultural Research (NAZV).

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

    NASA Astrophysics Data System (ADS)

    Jin, Z.; Zhuang, Q.

    2014-12-01

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    There is a growing demand for timely, spatially distributed information regarding crop condition and water use to inform agricultural decision making and yield forecasting efforts. Remote sensing of land-surface temperature has proven valuable for mapping evapotranspiration (ET) and crop stress from...

  2. Soil attributes, soybean mineral nutrition and yield in diverse crop rotations under no-till conditions

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Development of sustainable agricultural systems depends on understanding complex relationships between soil attributes, crop rotations, and crop yield. Objectives were to measure how soil chemical and physical attributes as well as soybean (Glycine max Merr.) stover dry weight and mineral concentra...

  3. Cover crops can improve potato tuber yield and quality

    Technology Transfer Automated Retrieval System (TEKTRAN)

    There is the need to develop sustainable systems with higher yields and crop quality. We conducted studies with cover crops grown under limited irrigation (< 200 mm) to assess the effects of certain types of cover crops on tuber yield and quality. On a commercial farm operation prior to the 2006 and...

  4. The Fingerprint of Climate Trends on European Crop Yields

    NASA Astrophysics Data System (ADS)

    Moore, F.; Lobell, D. B.

    2014-12-01

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

  5. Spectral Reflectance Features in Crop State and Yield Models Considering Soil and Anthropogenic Impacts

    NASA Astrophysics Data System (ADS)

    Kancheva, R.; Borisova, D.

    Agricultural models for estimating plant processes and growth require explicit information of soil, vegetation, climate, etc. Remote sensing is a tool that can be used to measure vegetation parameters for input into these models. Especially valuable are temporal data about crop state and crop development under different conditions. This paper is devoted to spectral-biophysical modeling of agricultural plants considering crop ontogenesis and dependency on soil properties (organic matter, pH-factor, nutrient accessibility) and anthropogenic impacts (fertilization, contamination). Ground-based VIS and NIR measurements have been performed to establish and statistically validate empirical relationships between crop reflectance and agronomic parameters taking into account the specific growing conditions. These relationships provide crop state assessment over the growing season. The estimated from spectral data bioparameters have been used in yield-predicting models linking crop production with plant agronomic variables. The results have been compared to the approach of using reflectance temporal behavior for yield assessment.

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  7. Tracing crop-specific sediment sources in agricultural catchments

    NASA Astrophysics Data System (ADS)

    Blake, William H.; Ficken, Katherine J.; Taylor, Philip; Russell, Mark A.; Walling, Desmond E.

    2012-02-01

    A Compound Specific Stable Isotope (CSSI) sediment tracing approach is evaluated for the first time in an agricultural catchment setting against established geochemical fingerprinting techniques. The work demonstrates that novel CSSI techniques have the potential to provide important support for soil resource management policies and inform sediment risk assessment for the protection of aquatic habitats and water resources. Analysis of soil material from a range of crop covers in a mixed land-use agricultural catchment shows that the carbon CSSI signatures of particle-reactive fatty acids label surface agricultural soil with distinct crop-specific signatures, thus permitting sediment eroded from each land-cover to be tracked downstream. High resolution sediment sampling during a storm event and analysis for CSSI and conventional geochemical fingerprints elucidated temporal patterns of sediment mobilisation under different crop regimes and the specific contribution that each crop type makes to downstream sediment load. Pasture sources (65% of the catchment area) dominated the sediment load but areal yield (0.13 ± 0.02 t ha - 1 ) was considerably less than that for winter wheat (0.44 ± 0.15 t ha - 1 ). While temporal patterns in crop response matched runoff and erosion response predictions based on plot-scale rainfall simulation experiments, comparison of biomarker and geochemical fingerprinting data indicated that the latter overestimated cultivated land inputs to catchment sediment yield due to inability to discriminate temporary pasture (in rotation) from cultivated land. This discrepancy, however, presents an opportunity since combination of the two datasets revealed the extremely localised nature of erosion from permanent pasture fields in this system (estimated at up to 0.5 t ha - 1 ). The novel use of CSSI and geochemical tracers in tandem provided unique insights into sediment source dynamics that could not have been derived from each method alone. Research

  8. Educational Software for Illustration of Drainage, Evapotranspiration, and Crop Yield.

    ERIC Educational Resources Information Center

    Khan, A. H.; And Others

    1996-01-01

    Describes a study that developed a software package for illustrating drainage, evapotranspiration, and crop yield as influenced by water conditions. The software is a tool for depicting water's influence on crop production in western Kansas. (DDR)

  9. Weather-based forecasts of California crop yields

    SciTech Connect

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

    2005-09-26

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

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

    NASA Astrophysics Data System (ADS)

    van der Velde, Marijn; Bareuth, Bettina

    2015-04-01

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

  11. Global growth and stability of agricultural yield decrease with pollinator dependence

    PubMed Central

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

    2011-01-01

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

  12. 7 CFR 1412.34 - Submitting production evidence for establishing direct payment yields for oilseeds and pulse crops.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... direct payment yields for oilseeds and pulse crops. 1412.34 Section 1412.34 Agriculture Regulations of... ELECTION PROGRAM FOR THE 2008 AND SUBSEQUENT CROP YEARS Establishment of Yields for Direct and Counter-Cyclical Payments § 1412.34 Submitting production evidence for establishing direct payment yields...

  13. Double-crop sunflowers for agricultural diesel fuel

    SciTech Connect

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

    1982-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

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

    NASA Astrophysics Data System (ADS)

    Li, X.; Troy, T.

    2014-12-01

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

  16. 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

  17. 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

  18. Increasing Crop Diversity Mitigates Weather Variations and Improves Yield Stability

    PubMed Central

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

    2015-01-01

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

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

    SciTech Connect

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

    2009-12-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2011-01-01

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

  1. 7 CFR 1412.34 - Submitting production evidence for establishing direct payment yields for oilseeds and pulse crops.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 7 Agriculture 10 2010-01-01 2010-01-01 false Submitting production evidence for establishing direct payment yields for oilseeds and pulse crops. 1412.34 Section 1412.34 Agriculture Regulations of the Department of Agriculture (Continued) COMMODITY CREDIT CORPORATION, DEPARTMENT OF AGRICULTURE LOANS, PURCHASES, AND OTHER OPERATIONS DIRECT...

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

    NASA Astrophysics Data System (ADS)

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

    2009-07-01

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

  3. 7 CFR 201.18 - Other agricultural seeds (crop seeds).

    Code of Federal Regulations, 2010 CFR

    2010-01-01

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

  4. 7 CFR 201.18 - Other agricultural seeds (crop seeds).

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... 7 Agriculture 3 2011-01-01 2011-01-01 false Other agricultural seeds (crop seeds). 201.18 Section... SERVICE (Standards, Inspections, Marketing Practices), DEPARTMENT OF AGRICULTURE (CONTINUED) FEDERAL SEED ACT FEDERAL SEED ACT REGULATIONS Labeling Agricultural Seeds § 201.18 Other agricultural seeds...

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

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... 7 Agriculture 3 2014-01-01 2014-01-01 false Other agricultural seeds (crop seeds). 201.18 Section... SERVICE (Standards, Inspections, Marketing Practices), DEPARTMENT OF AGRICULTURE (CONTINUED) FEDERAL SEED ACT FEDERAL SEED ACT REGULATIONS Labeling Agricultural Seeds § 201.18 Other agricultural seeds...

  6. 7 CFR 201.18 - Other agricultural seeds (crop seeds).

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ... 7 Agriculture 3 2012-01-01 2012-01-01 false Other agricultural seeds (crop seeds). 201.18 Section... SERVICE (Standards, Inspections, Marketing Practices), DEPARTMENT OF AGRICULTURE (CONTINUED) FEDERAL SEED ACT FEDERAL SEED ACT REGULATIONS Labeling Agricultural Seeds § 201.18 Other agricultural seeds...

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

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ... 7 Agriculture 3 2013-01-01 2013-01-01 false Other agricultural seeds (crop seeds). 201.18 Section... SERVICE (Standards, Inspections, Marketing Practices), DEPARTMENT OF AGRICULTURE (CONTINUED) FEDERAL SEED ACT FEDERAL SEED ACT REGULATIONS Labeling Agricultural Seeds § 201.18 Other agricultural seeds...

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

    NASA Astrophysics Data System (ADS)

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

    2013-09-01

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

  9. Precision agricultural techniques for identifying yield limiting factors in Louisiana sugarcane

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Precision Agriculture enables growers to efficiently manage inputs, identify yield limiting soil properties, mitigate detrimental environmental or crop conditions, and increase profits. Soil grid sampling and yield mapping were used to document the extent of yield loss resulting from two very differ...

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

    ERIC Educational Resources Information Center

    Poffenbarger, Hanna

    2010-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Kim, Nari; Lee, Yang-Won

    2014-10-01

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

  12. Unsupervised linear unmixing of hyperspectral image for crop yield estimation

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Multispectral and hyperspectral imagery are often used for estimating crop yield. This paper describes an unsupervised unmixing scheme of hyperspectral images to estimate crop yield. From the hyperspectral images, the endmembers and their abundance maps are computed by unsupervised unmixing. The abu...

  13. Random Forests for Global and Regional Crop Yield Predictions

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Traditional regression models have limitations when applied for predicting crop yield responses at multiple spatial scales. An alternative modeling method, Random Forest (RF) regression, was utilized to predict crop yield responses for wheat, maize, and potato at regional scales. This RF regressio...

  14. Climate impacts on agriculture: Implications for crop production

    SciTech Connect

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

    2011-04-19

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

  15. Incorporating remote sensing data in crop model to monitor crop growth and predict yield in regional area

    NASA Astrophysics Data System (ADS)

    Guo, Jianmao; Lu, Weisong; Zhang, Guoping; Qian, Yonglan; Yu, Qiang; Zhang, Jiahua

    2006-12-01

    Accurate crop growth monitoring and yield predicting is very important to food security and agricultural sustainable development. Crop models can be forceful tools for monitoring crop growth status and predicting yield over homogeneous areas, however, their application to a larger spatial domains is hampered by lack of sufficient spatial information about model inputs, such as the value of some of their parameters and initial conditions, which may have great difference between regions even fields. The use of remote sensing data helps to overcome this problem. By incorporating remote sensing data into the WOFOST crop model (through LAI), it is possible to incorporate remote sensing variables (vegetation index) for each point of the spatial domain, and it is possible for this point to re-estimate new values of the parameters or initial conditions, to which the model is particularly sensitive. This paper describes the use of such a method on a local scale, for winter wheat, focusing on the parameters describing emergence and early crop growth. These processes vary greatly depending on the soil, climate and seedbed preparation, and affect yield significantly. The WOFOST crop model is calibrated under standard conditions and then evaluated under test conditions to which the emergence and early growth parameters of the WOFOST model are adjusted by incorporating remote sensing data. The inversion of the combined model allows us to accurately monitoring crop growth status and predicting yield on a regional scale.

  16. Management controls on nitrous oxide emissions from row crop agriculture

    NASA Astrophysics Data System (ADS)

    Gelfand, I.; Shcherbak, I.; Millar, N.; Robertson, G. P.

    2011-12-01

    Agriculture is a significant source of the potent greenhouse gas (GHG) nitrous oxide (N2O), accounting for ~70% of total anthropic N2O emissions in the US primarily as a result of N fertilizer application. Emissions of N2O are the largest contributor to the global warming potential of row-crop agriculture. Management, including choice of crop type and rotation strongly impacts N2O emissions, but continuous emissions data from row-crops over multiple rotations are lacking. Empirical quantification of these long-term emissions and the development of crop- and rotation-specific N2O emission factors are vital for improving estimates of agricultural GHG emissions, important for informing management practices to reduce agriculture's GHG footprint, and developing mitigation protocols for environmental markets. Over 20 years we measured soil N2O emissions and calculated crop and management specific emission factors in four continuous rotations of corn (Zea mays) - soybean (Glycine max) - wheat (Triticum aestivum) under conventional tillage (CT), zero tillage (NT), low chemical input (LI), and biologically (Org) based management. Two of these systems (LI and Org) included winter cover crops, red clover (Trifolium pratense) or ray (Secale cereale). While average soil N2O fluxes in all systems where similar (2.9±0.2 to 3.8±0.5 g N2O-N ha-1 d-1), there was a significant interaction of total emissions with crop and phase. Surprisingly, the lowest total emissions from the corn period of the rotation were from CT, and the highest from LI, with 608±4 and 983±8 g N2O-N ha-1 crop year-1, respectively. Total emissions during the wheat period of the rotation showed the opposite trend, with total emissions of 942±7 and 524±38 g N2O-N ha-1 crop year-1, for CT ant LI, respectively. Total emissions from the soybean period of the rotation were highest under NT and lowest under CT management (526±5 and 296±2 g N2O-N ha-1 crop year-1, respectively). Emission efficiency, N2O emitted

  17. Modeling regional crop yield and irrigation demand using SMAP type of soil moisture data

    NASA Astrophysics Data System (ADS)

    El Sharif, H. A.; Wang, J.; Georgakakos, A. P.; Bras, R. L.

    2013-12-01

    Agricultural models, such as Decision Support System for Agrotechnology Transfer - Cropping Systems Model (DSSAT-CSM) (Tsuji, et al., 1994), have been developed to predict the yield of various crops at field and regional scales. The model simulations of crop yields provide essential information for water resources management. One key input of the agricultural models is soil moisture. So far there are no observed soil moisture data covering the entire US with adequate time (daily) and space (1 km or less) resolutions preferred for model simulation of crop yields. Spatially and temporally downscaled data from the upcoming Soil Moisture Active Passive (SMAP) mission can fill this data gap through the generation of fine resolution soil moisture maps that can be incorporated into DSSAT-CSM model. This study will explore the impact downscaled remotely-sensed soil moisture data can have on agricultural model forecasts of agricultural yield and irrigation demand using synthetically generated data sets exhibiting statistical characteristics (uncertainty) similar to the upcoming SMAP products. It is expected that incorporating this data into agricultural model will prove especially useful for cases in which soil water conductivity characteristics and/or precipitation amount at a specific site of interest are not fully known; furthermore, a proposed Bayesian analysis is expected to generate a soil moisture sequence that reduces the uncertainty in modeled yield and irrigation demand compared to using downscaled remotely-sensed soil moisture or precipitation data alone. References Tsuji, G., Uehara, G., and Balas, S. (1994). DSSAT V3, University of Hawaii, Honolulu.

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

    NASA Astrophysics Data System (ADS)

    Amikuzuno, J.

    2012-12-01

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

  19. An assessment of irrigation needs and crop yield for the United States under potential climate changes

    NASA Astrophysics Data System (ADS)

    Brumbelow, Kelly; Georgakakos, Aris

    2001-11-01

    Past assessments of climate change on U.S. agriculture have mostly focused on changes in crop yield. Few studies have included the entire conterminous United States, and few studies have assessed changing irrigation requirements. None have included the effects of changing soil moisture characteristics as determined by changing climatic forcing. This study assesses changes in irrigation requirements and crop yields for five crops in the areas of the United States where they have traditionally been grown. Physiologically based crop models are used to incorporate inputs of climate, soils, agricultural management, and drought stress tolerance. Soil moisture values from a macroscale hydrologic model run under a future climate scenario are used to initialize soil moisture content at the beginning of each growing season. Historical crop yield data are used to calibrate model parameters and to determine locally acceptable drought stress as a management parameter. Changes in irrigation demand and crop yield are assessed for both means and extremes by comparing results for atmospheric forcing close to the present climate with those for a future climate scenario. Assessments using the Canadian Center for Climate Modeling and Analysis General Circulation Model (CGCM1) indicate greater irrigation demands in the southern United States and decreased irrigation demands in the northern and western United States. Crop yields typically increase, except for winter wheat in the southern United States and corn. Variability in both irrigation demands and crop yields increases in most cases. Assessment results for the CGCM1 climate scenario are compared to those for the Hadley Centre for Climate Prediction and Research GCM (HadCM2) scenario for southwestern Georgia. The comparison shows significant differences in irrigation and yield trends, both in magnitude and in direction. The differences reflect the high forecast uncertainty of current GCMs. Nonetheless, both GCMs indicate higher

  20. An assessment of irrigation needs and crop yield for the United States under potential climate changes

    USGS Publications Warehouse

    Brumbelow, Kelly; Georgakakos, Aris P.

    2000-01-01

    Past assessments of climate change on U.S. agriculture have mostly focused on changes in crop yield. Few studies have included the entire conterminous U.S., and few studies have assessed changing irrigation requirements. None have included the effects of changing soil moisture characteristics as determined by changing climatic forcing. This study assesses changes in irrigation requirements and crop yields for five crops in the areas of the U.S. where they have traditionally been grown. Physiologically-based crop models are used to incorporate inputs of climate, soils, agricultural management, and drought stress tolerance. Soil moisture values from a macroscale hydrologic model run under a future climate scenario are used to initialize soil moisture content at the beginning of each growing season. Historical crop yield data is used to calibrate model parameters and determine locally acceptable drought stress as a management parameter. Changes in irrigation demand and crop yield are assessed for both means and extremes by comparing results for atmospheric forcing close to the present climate with those for a future climate scenario. Assessments using the Canadian Center for Climate Modeling and Analysis General Circulation Model (CGCM1) indicate greater irrigation demands in the southern U.S. and decreased irrigation demands in the northern and western U.S. Crop yields typically increase except for winter wheat in the southern U.S. and corn. Variability in both irrigation demands and crop yields increases in most cases. Assessment results for the CGCM1 climate scenario are compared to those for the Hadley Centre for Climate Prediction and Research GCM (HadCM2) scenario for southwestern Georgia. The comparison shows significant differences in irrigation and yield trends, both in magnitude and direction. The differences reflect the high forecast uncertainty of current GCMs. Nonetheless, both GCMs indicate higher variability in future climatic forcing and, consequently

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

    PubMed

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

    2013-01-01

    Several studies have shown that global crop production needs to double by 2050 to meet the projected demands from rising population, diet shifts, and increasing biofuels consumption. Boosting crop yields to meet these rising demands, rather than clearing more land for agriculture has been highlighted as a preferred solution to meet this goal. However, we first need to understand how crop yields are changing globally, and whether we are on track to double production by 2050. Using ∼2.5 million agricultural statistics, collected for ∼13,500 political units across the world, we track four key global crops-maize, rice, wheat, and soybean-that currently produce nearly two-thirds of global agricultural calories. We find that yields in these top four crops are increasing at 1.6%, 1.0%, 0.9%, and 1.3% per year, non-compounding rates, respectively, which is less than the 2.4% per year rate required to double global production by 2050. At these rates global production in these crops would increase by ∼67%, ∼42%, ∼38%, and ∼55%, respectively, which is far below what is needed to meet projected demands in 2050. We present detailed maps to identify where rates must be increased to boost crop production and meet rising demands. PMID:23840465

  2. Synthetic Aperture Radar (sar) and Optical Imagery Data Fusion: Crop Yield Analysis in Southeast Asia

    NASA Astrophysics Data System (ADS)

    Parks, S. M.

    2012-08-01

    With the expanding energy crisis and rising food prices, crop yield analysis in Southeast Asia is an increasingly important topic in this region. Rice is the most important food crop in Southeast Asia and the ability to accurately predict crop yields during a growing season is useful for decision-makers, aid providers, and commercial trade organizations. The use of optical satellite image data by itself is difficult due to the almost constant cloud in many parts of Southeast Asia. However, Synthetic Aperture Radar (SAR), or SAR data, which can image the Earth's surface through cloud cover, is suitable for many agricultural purposes, such as the detection of rice fields, and the identification of different crop species. Crop yield analysis is difficult in this region due to many factors. Rice cropping systems are often characterized by the type of rice planted, the size of rice field, the sowing dates for different fields, different types of rice cropping systems from one area to another, as well as cultural practices such as sowing and transplanting. This paper will discuss the use of SAR data fused with optical imagery to improve the ability to perform crop yield analysis on rice crops in Southeast Asia.

  3. What aspects of future rainfall changes matter for crop yields in West Africa?

    NASA Astrophysics Data System (ADS)

    Guan, Kaiyu; Sultan, Benjamin; Biasutti, Michela; Baron, Christian; Lobell, David B.

    2015-10-01

    How rainfall arrives, in terms of its frequency, intensity, the timing and duration of rainy season, may have a large influence on rainfed agriculture. However, a thorough assessment of these effects is largely missing. This study combines a new synthetic rainfall model and two independently validated crop models (APSIM and SARRA-H) to assess sorghum yield response to possible shifts in seasonal rainfall characteristics in West Africa. We find that shifts in total rainfall amount primarily drive the rainfall-related crop yield change, with less relevance to intraseasonal rainfall features. However, dry regions (total annual rainfall below 500 mm/yr) have a high sensitivity to rainfall frequency and intensity, and more intense rainfall events have greater benefits for crop yield than more frequent rainfall. Delayed monsoon onset may negatively impact yields. Our study implies that future changes in seasonal rainfall characteristics should be considered in designing specific crop adaptations in West Africa.

  4. Projecting crop yield in northern high latitude area.

    PubMed

    Matsumura, Kanichiro

    2014-01-01

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

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

    ERIC Educational Resources Information Center

    Leonard, David; And Others

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

  6. 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…

  7. Climate impacts on agriculture: Implications for crop production

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Changes in temperature, CO2, and precipitation under the scenarios of climate change for the next 50 years present a challenge to crop production. Understanding these implications for agricultural crops is critical to being able to develop cropping systems which are resilient to stresses induced by ...

  8. Tropical Rotation Crops Influence Nematode Densities and Vegetable Yields

    PubMed Central

    McSorley, R.; Dickson, D. W.; de Brito, J. A.; Hochmuth, R. C.

    1994-01-01

    The effects of eight summer rotation crops on nematode densities and yields of subsequent spring vegetable crops were determined in field studies conducted in north Florida from 1991 to 1993. The crop sequence was as follows: (i) rotation crops during summer 1991; (ii) cover crop of rye (Secale cereale) during winter 1991-92; (iii) 'Lemondrop L' squash (Cucurbita pepo) during spring 1992; (iv) rotation crops during summer 1992; (v) rye during winter 1992-93; (vi) 'Classic' eggplant (Solanum melongena) during spring 1993. The eight summer crop rotation treatments were as follows: 'Hale' castor (Ricinus communis), velvetbean (Mucuna deeringiana), sesame (Sesamum indicum), American jointvetch (Aeschynomene americana), weed fallow, 'SX- 17' sorghum-sudangrass (Sorghum bicolor x S. sudanense), 'Kirby' soybean (Glycine max), and 'Clemson Spineless' okra (Hibiscus esculentus) as a control. Rotations with castor, velvetbean, American jointvetch, and sorghum-sudangrass were most effective in maintaining the lowest population densities of Meloidogyne spp. (a mixture of M. incognita race 1 and M. arenaria race 1), but Paratrichodorus minor built up in the sorghum-sudangrass rotation. Yield of squash was lower (P ≤ 0.05) following sorghum-sudangrass than after any of the other treatments except fallow. Yield of eggplant was greater (P ≤ 0.05) following castor, sesame, or American jointvetch than following okra or fallow. Several of the rotation crops evaluated here may be useful for managing nematodes in the field and for improving yields of subsequent vegetable crops. PMID:19279897

  9. Tropical rotation crops influence nematode densities and vegetable yields.

    PubMed

    McSorley, R; Dickson, D W; de Brito, J A; Hochmuth, R C

    1994-09-01

    The effects of eight summer rotation crops on nematode densities and yields of subsequent spring vegetable crops were determined in field studies conducted in north Florida from 1991 to 1993. The crop sequence was as follows: (i) rotation crops during summer 1991; (ii) cover crop of rye (Secale cereale) during winter 1991-92; (iii) 'Lemondrop L' squash (Cucurbita pepo) during spring 1992; (iv) rotation crops during summer 1992; (v) rye during winter 1992-93; (vi) 'Classic' eggplant (Solanum melongena) during spring 1993. The eight summer crop rotation treatments were as follows: 'Hale' castor (Ricinus communis), velvetbean (Mucuna deeringiana), sesame (Sesamum indicum), American jointvetch (Aeschynomene americana), weed fallow, 'SX- 17' sorghum-sudangrass (Sorghum bicolor x S. sudanense), 'Kirby' soybean (Glycine max), and 'Clemson Spineless' okra (Hibiscus esculentus) as a control. Rotations with castor, velvetbean, American jointvetch, and sorghum-sudangrass were most effective in maintaining the lowest population densities of Meloidogyne spp. (a mixture of M. incognita race 1 and M. arenaria race 1), but Paratrichodorus minor built up in the sorghum-sudangrass rotation. Yield of squash was lower (P Yield of eggplant was greater (P crops evaluated here may be useful for managing nematodes in the field and for improving yields of subsequent vegetable crops. PMID:19279897

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  11. Scheduling for deficit irrigation, Crop Yield Predictor

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  12. Growth and yield of winter wheat as affected by preceding crop and crop management

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Producers in eastern South Dakota are interested in adding winter wheat (Triticum aestivum L.) to the corn (Zea mays L.)-soybean (Glycine max Merrill) rotation to improve crop yield and pest management. Our study quantified winter wheat response to preceding crop and crop management. Preceding cro...

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

    NASA Astrophysics Data System (ADS)

    Yokozawa, M.

    2013-12-01

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

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

    PubMed Central

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

    2013-01-01

    Several studies have shown that global crop production needs to double by 2050 to meet the projected demands from rising population, diet shifts, and increasing biofuels consumption. Boosting crop yields to meet these rising demands, rather than clearing more land for agriculture has been highlighted as a preferred solution to meet this goal. However, we first need to understand how crop yields are changing globally, and whether we are on track to double production by 2050. Using ∼2.5 million agricultural statistics, collected for ∼13,500 political units across the world, we track four key global crops—maize, rice, wheat, and soybean—that currently produce nearly two-thirds of global agricultural calories. We find that yields in these top four crops are increasing at 1.6%, 1.0%, 0.9%, and 1.3% per year, non-compounding rates, respectively, which is less than the 2.4% per year rate required to double global production by 2050. At these rates global production in these crops would increase by ∼67%, ∼42%, ∼38%, and ∼55%, respectively, which is far below what is needed to meet projected demands in 2050. We present detailed maps to identify where rates must be increased to boost crop production and meet rising demands. PMID:23840465

  15. The impact of climate extremes and irrigation on US crop yields

    NASA Astrophysics Data System (ADS)

    Troy, T. J.; Kipgen, C.; Pal, I.

    2015-05-01

    Climate variability and extremes are expected to increase due to climate change; this may have significant negative impacts for agricultural production. Previous work has primarily focused on the impact of mean growing season temperature and precipitation on rainfed crop yields with little work on irrigated crop yields or climate extremes and their timing. County-level crop yields and daily precipitation and temperature data are pooled to quantify the impact of climate variability and extremes on four major staple crops in the United States. Conditional density plots are used to graphically explore the relationship between climate extremes and crop yields, thereby avoiding assumptions about linearity or underlying probability distributions. Non-linear and threshold-type relationships exist between yields and both precipitation and temperature climate indices; irrigation significantly reduces the impact of all climate indices. In some cases, this occurs by shifting the threshold, such that a more extreme weather event is necessary to negatively impact yields. In other cases, irrigation essentially decouples the crop yields from climate. This work demonstrates that irrigation may be a beneficial adaptation mechanism to changes in climate extremes in coming decades.

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

    PubMed Central

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

    2010-01-01

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

  17. Direct effects of rising atmospheric carbon dioxide on crop yields

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Rising atmospheric carbon dioxide concentration (CO2) in this century will alter crop yield quantity and quality. It is important to understand the magnitude of the expected changes and the mechanisms involved in crop responses to elevated CO2 in order to adapt our food systems to the committed chan...

  18. Quantifying and mapping China's crop yield gains from sustainable and unsustainable irrigation water use

    NASA Astrophysics Data System (ADS)

    Grogan, D. S.; Zhang, F.; Glidden, S.; Wisser, D.; Proussevitch, A. A.; Li, C.; Lammers, R. B.; Frolking, S.

    2012-12-01

    About 40 - 50% of China's cropland is irrigated. We used the DNDC model to predict crop yield for ~17 crop types involved in ~28 cropping systems across China, under zero and full irrigation for each county for 1981-2000. We estimate that yield increases due to irrigation range from 0 - 100%, depending on water deficits arising from local climate and weather conditions and crop types. We used gridded water balance simulations with the UNH WBM driven by MERRA weather reconstructions for 1981-2000 to compute demand for irrigation water, and the capacity of various sources to supply that demand in each grid cell. We estimate that approximately 15% - 20% of the water needed to fulfill the country's irrigation water demand must come from unsustainable sources such as fossil groundwater. Yields using only the sustainable irrigation water capacity are calculated by weighing the DNDC zero and full irrigation yields based on the water availability results of WBM for each grid cell. Restricting irrigation water use to only sustainable sources results in a national crop yield decrease of ~20%. Irrigation water demand, unsustainable water use, and crop yield gains due to irrigation all have significant spatial variation across China. These spatial variations show that irrigation water use - sustainable and unsustainable - results in significant crop yield gains in some regions, and little to no crop yield gains in other regions. Unsustainable water use for irrigation is concentrated in the highly populated and agriculturally valuable North China Plain region, particularly Hebei, Shandong and Henan Provinces. While current plans for the South-North Water Transfer could mitigate some of the water deficit we do not expect the projected transfers to adequately supply this region with sufficient water resources to supply both the people and crops sustainably.

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  20. Assessment of Impacts of Climate Variability on Crop Yield over the Terai Region of Nepal

    NASA Astrophysics Data System (ADS)

    Subedi, S.; Acharya, A.

    2015-12-01

    Agricultural sector in Nepal which alone contributes about 42 % of the total GDP have a huge influence on national economy. This sector is very much susceptible to climate change. This study is emphasized on Terai region (situated at an altitude of 60m to 300m) of Nepal which investigates the impacts of climate variability on various stages of cropping (paddy) periods such as transplant, maturity and harvest. The climate variables namely temperature and rainfall are used to explore the relationship between climate and paddy yields based on 30 years of historical observed data. Observed monthly rainfall and temperature data are collected from the department of hydrology and meteorology, and paddy yield data are collected from the Ministry of Agricultural Development. A correlation analysis will be carried out between the backward difference filtered climate parameters and the backward difference filtered rice yield. This study will also analyze average monthly and annual rainfall, and, min, max and mean temperature during the period of 1981-2010 based on 15 synoptic stations of Nepal. This study will visualize rainfall and temperature distribution over Nepal, and also evaluate the effect of change in rainfall and temperature in the paddy yield. While evaluating the impacts of climate on crop yield, this study will not consider the impact of irrigation in crop yield. The major results, climate distribution and its local/regional impacts on agriculture, could be utilized by planners, decision makers, and climate and agricultural scientists as a basis in formulating/implementing future plans, policies and projects.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  2. 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.

  3. Spatial modeling of contemporary crop yields in China under sustainable and unsustainable water use scenarios

    NASA Astrophysics Data System (ADS)

    Grogan, D. S.; Zhang, F.; Li, C.; Frolking, S.

    2011-12-01

    Irrigated agriculture is an important part of China's population and economic growth. Currently, water needed to irrigate crops can be drawn from surface runoff, streams, reservoirs, renewable groundwater, or fossil groundwater. Fossil groundwater is not sustainable over long time periods, and therefore regions that rely on this source for irrigation water could face water shortages in the future, and may already be experiencing water stress today. This study uses two models, one to calculate water balance and the other to simulate crop yields, to address the question: how much unsustainable water is currently used for irrigation in China, and by how much would the use of only sustainable water reduce crop yields? The amount of sustainable water available for irrigation is determined using the WBMplus model. This model uses precipitation and temperature drivers, along with gridded data of soils, cropping, and irrigation, to simulate soil moisture, potential evapotranspiration, surface runoff, stream flow, and reservoir storage, in 30 min grid cells. The model also computes demand for irrigation water, and the capacity of various sources to supply that demand in each grid cell. The DNDC model, which has been evaluated against crop yield in a number of studies in China, is used to predict crop yield for ~50 crop types involved in ~100 cropping systems across China, under zero and full irrigation for each grid cell. Yields using only the sustainable irrigation water capacity will be calculated by weighing the zero and full irrigation yields based on the water availability results of WBMplus for each grid cell. With this methodology, we estimate how national-scale food production would be changed by limiting agricultural water use.

  4. 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.

  5. Enhancing crop yield by optimizing plant developmental features.

    PubMed

    Mathan, Jyotirmaya; Bhattacharya, Juhi; Ranjan, Aashish

    2016-09-15

    A number of plant features and traits, such as overall plant architecture, leaf structure and morphological features, vascular architecture and flowering time are important determinants of photosynthetic efficiency and hence the overall performance of crop plants. The optimization of such developmental traits thus has great potential to increase biomass and crop yield. Here, we provide a comprehensive review of these developmental traits in crop plants, summarizing their genetic regulation and highlighting the potential of manipulating these traits for crop improvement. We also briefly review the effects of domestication on the developmental features of crop plants. Finally, we discuss the potential of functional genomics-based approaches to optimize plant developmental traits to increase yield. PMID:27624833

  6. Climate change impacts on crop yield: evidence from China.

    PubMed

    Wei, Taoyuan; Cherry, Todd L; Glomrød, Solveig; Zhang, Tianyi

    2014-11-15

    When estimating climate change impact on crop yield, a typical assumption is constant elasticity of yield with respect to a climate variable even though the elasticity may be inconstant. After estimating both constant and inconstant elasticities with respect to temperature and precipitation based on provincial panel data in China 1980-2008, our results show that during that period, the temperature change contributes positively to total yield growth by 1.3% and 0.4% for wheat and rice, respectively, but negatively by 12% for maize. The impacts of precipitation change are marginal. We also compare our estimates with other studies and highlight the implications of the inconstant elasticities for crop yield, harvest and food security. We conclude that climate change impact on crop yield would not be an issue in China if positive impacts of other socio-economic factors continue in the future. PMID:25181045

  7. North–South divide: contrasting impacts of climate change on crop yields in Scotland and England

    PubMed Central

    Butterworth, Michael H.; Semenov, Mikhail A.; Barnes, Andrew; Moran, Dominic; West, Jonathan S.; Fitt, Bruce D. L.

    2010-01-01

    Effects of climate change on productivity of agricultural crops in relation to diseases that attack them are difficult to predict because they are complex and nonlinear. To investigate these crop–disease–climate interactions, UKCIP02 scenarios predicting UK temperature and rainfall under high- and low-CO2 emission scenarios for the 2020s and 2050s were combined with a crop-simulation model predicting yield of fungicide-treated winter oilseed rape and with a weather-based regression model predicting severity of phoma stem canker epidemics. The combination of climate scenarios and crop model predicted that climate change will increase yield of fungicide-treated oilseed rape crops in Scotland by up to 0.5 t ha−1 (15%). In contrast, in southern England the combination of climate scenarios, crop, disease and yield loss models predicted that climate change will increase yield losses from phoma stem canker epidemics to up to 50 per cent (1.5 t ha−1) and greatly decrease yield of untreated winter oilseed rape. The size of losses is predicted to be greater for winter oilseed rape cultivars that are susceptible than for those that are resistant to the phoma stem canker pathogen Leptosphaeria maculans. Such predictions illustrate the unexpected, contrasting impacts of aspects of climate change on crop–disease interactions in agricultural systems in different regions. PMID:19447817

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

    SciTech Connect

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

    2006-01-10

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

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

    NASA Astrophysics Data System (ADS)

    Kancheva, Rumiana

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

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

    NASA Technical Reports Server (NTRS)

    1978-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Lee, Scott; Cruse, Richard

    2015-04-01

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

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

    PubMed

    Kumar, Manoj

    2016-08-01

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

  13. Monitoring interannual variation in global crop yield using long-term AVHRR and MODIS observations

    NASA Astrophysics Data System (ADS)

    Zhang, Xiaoyang; Zhang, Qingyuan

    2016-04-01

    Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) data have been extensively applied for crop yield prediction because of their daily temporal resolution and a global coverage. This study investigated global crop yield using daily two band Enhanced Vegetation Index (EVI2) derived from AVHRR (1981-1999) and MODIS (2000-2013) observations at a spatial resolution of 0.05° (∼5 km). Specifically, EVI2 temporal trajectory of crop growth was simulated using a hybrid piecewise logistic model (HPLM) for individual pixels, which was used to detect crop phenological metrics. The derived crop phenology was then applied to calculate crop greenness defined as EVI2 amplitude and EVI2 integration during annual crop growing seasons, which was further aggregated for croplands in each country, respectively. The interannual variations in EVI2 amplitude and EVI2 integration were combined to correlate to the variation in cereal yield from 1982-2012 for individual countries using a stepwise regression model, respectively. The results show that the confidence level of the established regression models was higher than 90% (P value < 0.1) in most countries in the northern hemisphere although it was relatively poor in the southern hemisphere (mainly in Africa). The error in the yield predication was relatively smaller in America, Europe and East Asia than that in Africa. In the 10 countries with largest cereal production across the world, the prediction error was less than 9% during past three decades. This suggests that crop phenology-controlled greenness from coarse resolution satellite data has the capability of predicting national crop yield across the world, which could provide timely and reliable crop information for global agricultural trade and policymakers.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  15. Evaluating SPOT 5 Multispectral Imagery for Crop Yield Estimation

    Technology Transfer Automated Retrieval System (TEKTRAN)

    High resolution satellite imagery has the potential for mapping within-field variability in crop growth and yield. This study examined SPOT 5 multispectral imagery for estimating grain sorghum yield. A SPOT 5 image with 10-m spatial resolution and four spectral bands (green, red, near-infrared and m...

  16. Surprising yields with no-till cropping systems

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  17. Surprising yields with no-till cropping systems

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

  19. Genetic mechanisms of abiotic stress tolerance that translate to crop yield stability.

    PubMed

    Mickelbart, Michael V; Hasegawa, Paul M; Bailey-Serres, Julia

    2015-04-01

    Crop yield reduction as a consequence of increasingly severe climatic events threatens global food security. Genetic loci that ensure productivity in challenging environments exist within the germplasm of crops, their wild relatives and species that are adapted to extreme environments. Selective breeding for the combination of beneficial loci in germplasm has improved yields in diverse environments throughout the history of agriculture. An effective new paradigm is the targeted identification of specific genetic determinants of stress adaptation that have evolved in nature and their precise introgression into elite varieties. These loci are often associated with distinct regulation or function, duplication and/or neofunctionalization of genes that maintain plant homeostasis. PMID:25752530

  20. Fuel production potential of several agricultural crops

    SciTech Connect

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

    1984-11-01

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

  1. Heterogeneous global crop yield response to biochar: a meta-regression analysis

    NASA Astrophysics Data System (ADS)

    Crane-Droesch, Andrew; Abiven, Samuel; Jeffery, Simon; Torn, Margaret S.

    2013-12-01

    Biochar may contribute to climate change mitigation at negative cost by sequestering photosynthetically fixed carbon in soil while increasing crop yields. The magnitude of biochar’s potential in this regard will depend on crop yield benefits, which have not been well-characterized across different soils and biochars. Using data from 84 studies, we employ meta-analytical, missing data, and semiparametric statistical methods to explain heterogeneity in crop yield responses across different soils, biochars, and agricultural management factors, and then estimate potential changes in yield across different soil environments globally. We find that soil cation exchange capacity and organic carbon were strong predictors of yield response, with low cation exchange and low carbon associated with positive response. We also find that yield response increases over time since initial application, compared to non-biochar controls. High reported soil clay content and low soil pH were weaker predictors of higher yield response. No biochar parameters in our dataset—biochar pH, percentage carbon content, or temperature of pyrolysis—were significant predictors of yield impacts. Projecting our fitted model onto a global soil database, we find the largest potential increases in areas with highly weathered soils, such as those characterizing much of the humid tropics. Richer soils characterizing much of the world’s important agricultural areas appear to be less likely to benefit from biochar.

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  3. Biofuels, Bioenergy, and bioproducts from sustainable agricultural and forest crops

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Most conferences about short rotation crops have primarily focused on either agricultural or forest crops, resulting in less integration and slower advancement of common underlying science and application. The goal of this conference was to initiate and provide opportunities for an international for...

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  5. Operational prediction of crop yields using MODIS data and products

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Official crop progress, condition and production estimates for the United States are responsibilities of the U.S. Department of Agriculture’s, National Agricultural Statistics Service (NASS). In addition to weekly and monthly survey-based data, biweekly composite maps of the normalized difference v...

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

    NASA Astrophysics Data System (ADS)

    Shin, Y.; Lee, E.

    2015-12-01

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

  7. 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.

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

    PubMed

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

    2016-01-01

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

  9. 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

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

    NASA Astrophysics Data System (ADS)

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

    2009-05-01

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

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

    NASA Astrophysics Data System (ADS)

    Yonekura, T.

    2010-12-01

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

  12. 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

    National agencies such as USDA Foreign Agricultural Service (FAS), Production Estimation and Crop Assessment Division (PECAD) work specifically to analyze and generate timely crop yield estimates that help define national as well as global food policies. The USDA/FAS/PECAD utilizes a Decision Support System (DSS) called CADRE (Crop Condition and Data Retrieval Evaluation) mainly through an automated database management system that integrates various meteorological datasets, crop and soil models, and remote sensing data; providing significant contribution to the national and international crop production estimates. The "Sinclair" soybean growth model has been used inside CADRE DSS as one of the crop models. This project uses Sinclair model (a semi-mechanistic crop growth model) for its potential to be effectively used in a geo-processing environment with remote-sensing-based inputs. The main objective of this proposed work is to verify, validate and benchmark current and future NASA earth science research results for the benefit in the operational decision making process of the PECAD/CADRE DSS. For this purpose, the NASA South American Land Data Assimilation System (SALDAS) meteorological dataset is tested for its applicability as a surrogate meteorological input in the Sinclair model meteorological input requirements. Similarly, NASA sensor MODIS products is tested for its applicability in the improvement of the crop yield prediction through improving precision of planting date estimation, plant vigor and growth monitoring. The project also analyzes simulated Visible/Infrared Imager/Radiometer Suite (VIIRS, a future NASA sensor) vegetation product for its applicability in crop growth prediction to accelerate the process of transition of VIIRS research results for the operational use of USDA/FAS/PECAD DSS. The research results will help in providing improved decision making capacity to the USDA/FAS/PECAD DSS through improved vegetation growth monitoring from high

  13. 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.

  14. Remote sensing of agricultural crops and soils

    NASA Technical Reports Server (NTRS)

    Bauer, M. E. (Principal Investigator)

    1983-01-01

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

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

    SciTech Connect

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

    1997-12-31

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

  16. Impacts of biofuel cultivation on mortality and crop yields

    NASA Astrophysics Data System (ADS)

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

    2013-05-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2008-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-08-01

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

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

    PubMed

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

    2015-01-01

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

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

    PubMed Central

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

    2015-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Yokozawa, M.

    2014-12-01

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

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

    PubMed Central

    McLennan, Matthew R.; Hockings, Kimberley J.

    2014-01-01

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

  3. Soil Moisture Anomaly as Predictor of Crop Yield Deviation in Germany

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

    Natural hazards, such as droughts, have the potential to drastically diminish crop yield in rain-fed agriculture. For example, the drought in 2003 caused direct losses of 1.5 billion EUR only in Germany (COPA-COGECA 2003). Predicting crop yields allows to economize the mitigation of risks of weather extremes. Economic approaches for quantifying agricultural impacts of natural hazards mainly rely on temperature and related concepts. For instance extreme heat over the growing season is considered as best predictor of corn yield (Auffhammer and Schlenker 2014). However, those measures are only able to provide a proxy for the available water content in the root zone that ultimately determines plant growth and eventually crop yield. The aim of this paper is to analyse whether soil moisture has a causal effect on crop yield that can be exploited in improving adaptation measures. For this purpose, reduced form fixed effect panel models are developed with yield as dependent variable for both winter wheat and silo maize crops. The explanatory variables used are soil moisture anomalies, precipitation and temperature. The latter two are included to estimate the current state of the water balance. On the contrary, soil moisture provides an integrated signal over several months. It is also the primary source of water supply for plant growth. For each crop a single model is estimated for every month within the growing period to study the variation of the effects over time. Yield data is available for Germany as a whole on the level of administrative districts from 1990 to 2010. Station data by the German Weather Service are obtained for precipitation and temperature and are aggregated to the same spatial units. Simulated soil moisture computed by the mesoscale Hydrologic Model (mHM, www.ufz.de/mhm) is transformed into Soil Moisture Index (SMI), which represents the monthly soil water quantile and hence accounts directly for the water content available to plants. The results

  4. Remote Sensing and Modeling Methods for Crop Grain Yield Assessment

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Monitoring crop condition and yields at regional scales using satellite imagery from operational satellites remains a challenge for the developed and developing countries. Imagery from the MODIS sensor onboard NASA’s TERRA and ACQUA satellites offer an excellent opportunity for daily coverage at 25...

  5. Tillage and Cover Crops Effects on Potato Yield and Quality

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Delayed tillage and the inclusion of cover crops can substantially reduce erosion in intensively tilled potato systems. Both of these practices can potentially impact potato yield and quality via changes in soil temperature and soil water status. Research was conducted over seven rotation cycles a...

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

    USGS Publications Warehouse

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

    2006-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Lawrence, P.

    2015-12-01

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

  8. A meta-analysis of crop yield under climate change and adaptation

    NASA Astrophysics Data System (ADS)

    Challinor, A. J.; Watson, J.; Lobell, D. B.; Howden, S. M.; Smith, D. R.; Chhetri, N.

    2014-04-01

    Feeding a growing global population in a changing climate presents a significant challenge to society. The projected yields of crops under a range of agricultural and climatic scenarios are needed to assess food security prospects. Previous meta-analyses have summarized climate change impacts and adaptive potential as a function of temperature, but have not examined uncertainty, the timing of impacts, or the quantitative effectiveness of adaptation. Here we develop a new data set of more than 1,700 published simulations to evaluate yield impacts of climate change and adaptation. Without adaptation, losses in aggregate production are expected for wheat, rice and maize in both temperate and tropical regions by 2 °C of local warming. Crop-level adaptations increase simulated yields by an average of 7-15%, with adaptations more effective for wheat and rice than maize. Yield losses are greater in magnitude for the second half of the century than for the first. Consensus on yield decreases in the second half of the century is stronger in tropical than temperate regions, yet even moderate warming may reduce temperate crop yields in many locations. Although less is known about interannual variability than mean yields, the available data indicate that increases in yield variability are likely.

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

    USGS Publications Warehouse

    Senay, G.B.; Verdin, J.

    2003-01-01

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

  10. Estimation of winter wheat yield by using remote sensing data and crop model

    NASA Astrophysics Data System (ADS)

    Guo, Jianmao; Zheng, Tengfei; Wang, Qi; Yang, Jia; Shi, Junyi; Zhu, Jinhui

    2012-10-01

    Remote sensing data combined with crop model is an important application and development trend of current agricultural information technology, it can solve the problem that remote sensing or crop model cannot solve alone. In order to simulate crop growth and yield prediction in large scale, this paper using field test data to calibrate and validation the model parameters before apply to the winter wheat WOFOST model, than according to the actual environment of Xinxiang, simulate the growth in 3 different condition in the 2002-2003 growing season. Contrast the simulation value WOFOST model, using the Landsat-7 ETM retrieving leaf area index, define winter wheat's growth condition in each pixel, the remote sensing information combined with crop model is accomplished at pixel scale. Based on the actual production of Xinxiang winter wheat in 2003,compare the simulate results with the corresponding parameter, results shows that the method of this study method is feasible.

  11. Dynamics of mean-variance-skewness of cumulative crop yield impact temporal yield variance

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Production risk associated with cropping systems influences farmers’ decisions to adopt a new management practice or a production system. Cumulative yield (CY), temporal yield variance (TYV) and coefficient of variation (CV) were used to assess the risk associated with adopting combinations of new m...

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

    NASA Astrophysics Data System (ADS)

    Doria, R.; Byrne, J. M.

    2013-12-01

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

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

    NASA Astrophysics Data System (ADS)

    Fishman, Ram

    2016-02-01

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

  14. Modelling Changes to Crop Yield Under Climate Change Scenarios

    NASA Astrophysics Data System (ADS)

    Gerber, J. S.; Deryng, D.; Ray, D. K.; Mueller, N. D.; Foley, J. A.; Ramankutty, N.

    2010-12-01

    This paper presents two sets of quantitative predictions for global soy and maize yields under changes to temperature and precipitation. The climatic changes considered are based on IPCC scenarios A1B and B1 as calculated with a variety of GCMs. One set of crop yield predictions is calculated with the process-based PEGASUS model, the other is based on an empirical climate-analog approach. The core of PEGASUS is a simple global surface energy, water, and carbon balance model. In addition, PEGASUS simulates planting dates and optimum cultivars at different locations of the world, allocates carbon to a grain pool, and uses an empirical relationship to estimate the influence of fertilizer application. In the empirical climate analog approach, recently published global data sets are used to empirically determine maximum attainable (potential) crop yields for a given set of climatic and soil conditions. Farmers are then quantified by their abilities to reach potential yields and as new climatically-limited potential yields obtain under climate change scenarios, farmers’ yields are assumed to evolve proportionally. Preliminary results indicate that global average yields in the future are sensitive to the climate model used to generate the future climate. However, all models indicate a decrease in yields under climate scenarios A1B and B1.

  15. PRECISION AGRICULTURE MASTERS PROGRAM - EDUCATING MISSOURI CROP PRODUCERS ABOUT THE BENEFITS OF PRECISION AGRICULTURE MANAGEMENT THROUGH ON-FARM RESEARCH

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The Precision Agriculture Masters (PAM) Program was initiated to enhance the transfer of technology related to precision agriculture to Missouri's crop producers. The PAM program consists of three parts: the precision agriculture knowledge network available through the Missouri Precision Agricultur...

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

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

    PubMed

    Maas, Bea; Clough, Yann; Tscharntke, Teja

    2013-12-01

    Human welfare is significantly linked to ecosystem services such as the suppression of pest insects by birds and bats. However, effects of biocontrol services on tropical cash crop yield are still largely unknown. For the first time, we manipulated the access of birds and bats in an exclosure experiment (day, night and full exclosures compared to open controls in Indonesian cacao agroforestry) and quantified the arthropod communities, the fruit development and the final yield over a long time period (15 months). We found that bat and bird exclusion increased insect herbivore abundance, despite the concurrent release of mesopredators such as ants and spiders, and negatively affected fruit development, with final crop yield decreasing by 31% across local (shade cover) and landscape (distance to primary forest) gradients. Our results highlight the tremendous economic impact of common insectivorous birds and bats, which need to become an essential part of sustainable landscape management. PMID:24131776

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

    ERIC Educational Resources Information Center

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

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

  20. Control of Vertebrate Pests of Agricultural Crops.

    ERIC Educational Resources Information Center

    Wingard, Robert G.; Studholme, Clinton R.

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

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

    NASA Astrophysics Data System (ADS)

    Kamali, Bahareh; Yang, Hong; abbaspour, karim

    2014-05-01

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

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

    NASA Astrophysics Data System (ADS)

    Gopalakrishnan, G.; Negri, C. M.

    2010-12-01

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

  4. 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.

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

    PubMed

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

    2013-11-01

    Government priorities on provincial Nutrient Management Planning (NMP) programs include improving the program effectiveness for environmental quality protection, and promoting more widespread adoption. Understanding the effect of NMP on both crop yield and key water-quality parameters in agricultural watersheds requires a comprehensive evaluation that takes into consideration important NMP attributes and location-specific farming conditions. This study applied the Soil and Water Assessment Tool (SWAT) to investigate the effects of crop and rotation sequence, tillage type, and nutrient N application rate on crop yield and the associated groundwater [Formula: see text] leaching and sediment loss. The SWAT model was applied to the Thomas Brook Watershed, located in the most intensively managed agricultural region of Nova Scotia, Canada. Cropping systems evaluated included seven fertilizer application rates and two tillage systems (i.e., conventional tillage and no-till). The analysis reflected cropping systems commonly managed by farmers in the Annapolis Valley region, including grain corn-based and potato-based cropping systems, and a vegetable-horticulture system. ANOVA models were developed and used to assess the effects of crop management choices on crop yield and two water-quality parameters (i.e., [Formula: see text] leaching and sediment loading). Results suggest that existing recommended N-fertilizer rate can be reduced by 10-25 %, for grain crop production, to significantly lower [Formula: see text] leaching (P > 0.05) while optimizing the crop yield. The analysis identified the nutrient N rates in combination with specific crops and rotation systems that can be used to manage [Formula: see text] leaching while balancing impacts on crop yields within the watershed. PMID:23943075

  6. Optical Remote Sensing For Prediction Of Crop Yields

    NASA Astrophysics Data System (ADS)

    Steven, M. D.

    1982-02-01

    Recent studies have determined the efficiency of crop production by relating the rate of increase of dry matter in healthy growing crops to the interception of sunlight. In addition to knowledge of the incident light, such studies require measurement of light transmission in the crop, or timely information about leaf area for light interception to be estimated. Transmission measurements are necessarily confined to small areas while traditional methods of determining leaf area are laborious and often require destructive sampling of part of the crop. Remote sensing techniques offer a cheap, non-destructive system for sampling large areas. An airborne sensor is used to detect solar radiation reflected from crops in two spectral bands: the near infra-red band (780 - 940 nm) is strongly reflected by leaves due to the porous structure of the mesophyll; the red band (600 - 660 nm) is strongly absorbed by chlorophyll in the leaves. The ratio of red/infra-red reflected fluxes decreases with the percentage cover of healthy green leaf and is largely independent of the effects of varying solar irradiance. Measurements made over sugar beet showed that during the main period of growth, spectral ratios were linearly related to leaf cover and light interception. There was some evidence of hysteresis later in the season when the spectral ratios tended to increase in spite of constant leaf cover, and this may indicate senescence of the leaves and loss of chlorophyll. These relationships are consistent for a wide variety of crops and allow the light interception by the crop to be estimated by a single spectral measurement from above. This information may be used to predict future rates of growth and ultimately, crop yields.

  7. Assimilation of remote sensing data into crop growth model to improve the estimation of regional winter wheat yield

    NASA Astrophysics Data System (ADS)

    Liu, Chaoshun; Gao, Wei; Liu, Pudong; Sun, Zhibin

    2014-10-01

    Accurate regional crop growth monitoring and yield prediction is very critical for the national food security assessment and sustainable development of agriculture, especially for China, which has the largest population in the world. Remote sensing data and crop growth model have been successfully used in the crop production prediction. However, both of them have inherent limitation and uncertainty. The data assimilation method which combines crop growth model and remotely sensed data has been proven to be the most effective method in regional yield estimation. The aim of this paper is to improve the estimation of regional winter wheat yield of crop growth model by using data assimilation schemes with Ensemble Kalman Filter (EnKF) algorithm. WOrld FOod STudies (WOFOST) crop growth model was chosen as the crop growth model which was calibrated and validated by the field measured data. MODIS Leaf Area Index (LAI) values were used as remote sensing observations to adjust the LAI simulated by the WOFOST model based on EnKF. The results illustrate that the EnKF algorithm has significantly improved the regional winter wheat yield estimates over the WOFOST simulation without assimilation in both potential and water-limited modes. Although this study clearly implies that the assimilation of the remotely sensed data into crop growth model with EnKF algorithm has the potential to improve the prediction of regional crop yield and has great potential in agricultural applications, high resolution meteorological data and detailed crop field management are necessary to reach a high accuracy of regional crop yield estimation.

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

    NASA Astrophysics Data System (ADS)

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

    2009-04-01

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

  9. Modeling temporal and spatial variability of crop yield

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  10. 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.

  11. Simulating yield response of rice to salinity stress with the AquaCrop model.

    PubMed

    Mondal, M Shahjahan; Saleh, Abul Fazal M; Razzaque Akanda, Md Abdur; Biswas, Sujit K; Md Moslehuddin, Abu Zofar; Zaman, Sinora; Lazar, Attila N; Clarke, Derek

    2015-06-01

    The FAO AquaCrop model has been widely applied throughout the world to simulate crop responses to deficit water applications. However, its application to saline conditions is not yet reported, though saline soils are common in coastal areas. In this study, we parameterized and tested AquaCrop to simulate rice yield under different salinity regimes. The data and information required in the model were collected through a field experiment at the Bangladesh Agricultural Research Institute, Gazipur. The experiment was conducted with the BRRI Dhan28, a popular boro rice variety in Bangladesh, with five levels of saline water irrigation, three replicates for each level. In addition, field monitoring was carried out at Satkhira in the southwest coastal region of Bangladesh to collect data and information based on farmers' practices and to further validate the model. The results indicated that the AquaCrop model with most of its default parameters could replicate the variation of rice yield with the variation of salinity reasonably well. The root mean square error and mean absolute error of the model yield were only 0.12 t per ha and 0.03 t per ha, respectively. The crop response versus soil salinity stress curve was found to be convex in shape with a lower threshold of 2 dS m(-1), an upper threshold of 10 dS m(-1) and a shape factor of 2.4. As the crop production system in the coastal belt of Bangladesh has become vulnerable to climate induced sea-level rise and the consequent increase in water and soil salinity, the AquaCrop would be a useful tool in assessing the potential impact of these future changes as well as other climatic parameters on rice yield in the coastal region. PMID:25865338

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

    PubMed Central

    Chen, Hungyen; Yamagishi, Junko; Kishino, Hirohisa

    2014-01-01

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

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

    PubMed

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

    2016-02-01

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

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed Central

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

    2014-01-01

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

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

    PubMed

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

    2014-01-01

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

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

    SciTech Connect

    Gregg, Jay S.; Izaurralde, Roberto C.

    2010-08-26

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

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

    NASA Astrophysics Data System (ADS)

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

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

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

    ERIC Educational Resources Information Center

    Hexem, Roger; Krupa, Kenneth S.

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

  20. Nutrient Losses from Row Crop Agriculture in Indiana

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Topic: USDA CEAP: Research Results and Recommendations Nutrient losses from row crop agriculture are known to contribute to water quality problems such as eutrophication and the zone of hypoxia in the Gulf of Mexico. Fields and catchments in the Cedar Creek sub-watershed of the St. Joseph River ba...

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

    NASA Astrophysics Data System (ADS)

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

    2003-04-01

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

  2. The Importance of Juvenile Root Traits for Crop Yields

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  4. Hyperspectral mapping of crop and soils for precision agriculture

    NASA Astrophysics Data System (ADS)

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

    2006-08-01

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

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

    PubMed

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

    2015-06-01

    The Kashmir Himalayan region of India is expected to be highly prone to the change in agricultural land use because of its geo-ecological fragility, strategic location vis-à-vis the Himalayan landscape, its trans-boundary river basins, and inherent socio-economic instabilities. Food security and sustainability of the region are thus greatly challenged by these impacts. The effect of future climate change, increased competition for land and water, labor from non-agricultural sectors, and increasing population adds to this complex problem. In current study, paddy rice yield at regional level was estimated using GIS-based environment policy integrated climate (GEPIC) model. The general approach of current study involved combining regional level crop database, regional soil data base, farm management data, and climatic data outputs with GEPIC model. The simulated yield showed that estimated production to be 4305.55 kg/ha (43.05 q h(-1)). The crop varieties like Jhelum, K-39, Chenab, China 1039, China-1007, and Shalimar rice-1 grown in plains recorded average yield of 4783.3 kg/ha (47.83 q ha(-1)). Meanwhile, high altitude areas with varieties like Kohsaar, K-78 (Barkat), and K-332 recorded yield of 4102.2 kg/ha (41.02 q ha(-1)). The observed and simulated yield showed a good match with R (2) = 0.95, RMSE = 132.24 kg/ha, respectively. PMID:25937498

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

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

    NASA Astrophysics Data System (ADS)

    Johnson, David M.

    2016-10-01

    An exploratory assessment was undertaken to determine the correlation strength and optimal timing of several commonly used Moderate Resolution Imaging Spectroradiometer (MODIS) composited imagery products against crop yields for 10 globally significant agricultural commodities. The crops analyzed included barley, canola, corn, cotton, potatoes, rice, sorghum, soybeans, sugarbeets, and wheat. The MODIS data investigated included the Normalized Difference Vegetation Index (NDVI), Fraction of Photosynthetically Active Radiation (FPAR), Leaf Area Index (LAI), and Gross Primary Production (GPP), in addition to daytime Land Surface Temperature (DLST) and nighttime LST (NLST). The imagery utilized all had 8-day time intervals, but NDVI had a 250 m spatial resolution while the other products were 1000 m. These MODIS datasets were also assessed from both the Terra and Aqua satellites, with their differing overpass times, to document any differences. A follow-on analysis, using the Terra 250 m NDVI data as a benchmark, looked at the yield prediction utility of NDVI at two spatial scales (250 m vs. 1000 m), two time precisions (8-day vs. 16-day), and also assessed the Enhanced Vegetation Index (EVI, at 250 m, 16-day). The analyses spanned the major farming areas of the United States (US) from the summers of 2008-2013 and used annual county-level average crop yield data from the US Department of Agriculture as a basis. All crops, except rice, showed at least some positive correlations to each of the vegetation related indices in the middle of the growing season, with NDVI performing slightly better than FPAR. LAI was somewhat less strongly correlated and GPP weak overall. Conversely, some of the crops, particularly canola, corn, and soybeans, also showed negative correlations to DLST mid-summer. NLST, however, was never correlated to crop yield, regardless of the crop or seasonal timing. Differences between the Terra and Aqua results were found to be minimal. The 1000 m

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

    SciTech Connect

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

    2006-10-17

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    PubMed

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

    2015-01-01

    Information on the effect of long-term management on soil nutrients and chemical properties is scanty. We examined the 30-year effect of tillage frequency and cropping sequence combination on dryland soil Olsen-P, K, Ca, Mg, Na, SO4-S, and Zn concentrations, pH, electrical conductivity (EC), and cation exchange capacity (CEC) at the 0-120 cm depth and annualized crop yield in the northern Great Plains, USA. Treatments were no-till continuous spring wheat (Triticum aestivum L.) (NTCW), spring till continuous spring wheat (STCW), fall and spring till continuous spring wheat (FSTCW), fall and spring till spring wheat-barley (Hordeum vulgare L., 1984-1999) followed by spring wheat-pea (Pisum sativum L., 2000-2013) (FSTW-B/P), and spring till spring wheat-fallow (STW-F, traditional system). At 0-7.5 cm, P, K, Zn, Na, and CEC were 23-60% were greater, but pH, buffer pH, and Ca were 6-31% lower in NTCW, STCW, and FSTW-B/P than STW-F. At 7.5-15 cm, K was 23-52% greater, but pH, buffer pH, and Mg were 3-21% lower in NTCW, STCW, FSTCW, FSTW-B/P than STW-F. At 60-120 cm, soil chemical properties varied with treatments. Annualized crop yield was 23-30% lower in STW-F than the other treatments. Continuous N fertilization probably reduced soil pH, Ca, and Mg, but greater crop residue returned to the soil increased P, K, Na, Zn, and CEC in NTCW and STCW compared to STW-F. Reduced tillage with continuous cropping may be adopted for maintaining long-term soil fertility and crop yields compared with the traditional system. PMID:26171303

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed

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

    2016-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2001-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2011-01-01

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

  15. Spatial Variation in Carbon and Nitrogen in Cultivated Soils in Henan Province, China: Potential Effect on Crop Yield

    PubMed Central

    Zhang, Xuelin; Wang, Qun; Gilliam, Frank S.; Wang, Yilun; Cha, Feina; Li, Chaohai

    2014-01-01

    Improved management of soil carbon (C) and nitrogen (N) storage in agro-ecosystems represents an important strategy for ensuring food security and sustainable agricultural development in China. Accurate estimates of the distribution of soil C and N stores and their relationship to crop yield are crucial to developing appropriate cropland management policies. The current study examined the spatial variation of soil organic C (SOC), total soil N (TSN), and associated variables in the surface layer (0–40 cm) of soils from intensive agricultural systems in 19 counties within Henan Province, China, and compared these patterns with crop yield. Mean soil C and N concentrations were 14.9 g kg−1 and 1.37 g kg−1, respectively, whereas soil C and N stores were 4.1 kg m−2 and 0.4 kg m−2, respectively. Total crop production of each county was significantly, positively related to SOC, TSN, soil C and N store, and soil C and N stock. Soil C and N were positively correlated with soil bulk density but negatively correlated with soil porosity. These results indicate that variations in soil C could regulate crop yield in intensive agricultural systems, and that spatial patterns of C and N levels in soils may be regulated by both climatic factors and agro-ecosystem management. When developing suitable management programs, the importance of soil C and N stores and their effects on crop yield should be considered. PMID:25289703

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    EPA Science Inventory

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

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

    NASA Astrophysics Data System (ADS)

    Panagopoulos, Y.

    2009-04-01

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

  19. Comparing the simulation of climate impacts on crop yields with observed and synthetic weather data

    NASA Astrophysics Data System (ADS)

    Qian, B.; de Jong, R.; Yang, J.; Wang, H.; Gameda, S.

    2010-12-01

    Stochastic weather generators have been used extensively in the development of climate scenarios, especially at the daily or shorter time scales, for the use as climate input to agricultural simulation models that evaluate the climate impacts on crop yields. Because generated synthetic weather data mimic the observed weather data, discrepancies between the two datasets often exist. For example, interannual variability in the synthetic data is often found to be weaker than in the observed data, i.e., the well-known overdispersion problem. Therefore, it is important to evaluate if the climate impact models are sensitive to such discrepancies between synthetic weather data and observed ones. In this study, we used a stochastic weather generator (AAFC-WG) to generate 300-yr long synthetic weather data for two Canadian sites (Swift Current on the Canadian Prairies and London in southern Ontario), based on the observed weather data for the baseline period of 1961-1990. The Decision Support System for Agrotechnology Transfer (DSSAT) v4.0 was employed to simulate crop growth and yield. Spring wheat at Swift Current and grain corn at London were simulated by the DSSAT cropping system model with three major soil types at each location, using the 30-yr observed weather data and 300-yr synthetic data, respectively. Statistical tests were performed to investigate whether differences (both mean and variance) of the simulated crop yields between the simulations with observed and synthetic weather data are statistically significant or not. Results demonstrated that the differences in simulated crop yields are often not statistically significant when synthetic weather data are used to substitute the observed data.

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

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

    SciTech Connect

    Vanderwende, Brian; Lundquist, Julie K.

    2015-11-07

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

  2. 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.

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

    NASA Astrophysics Data System (ADS)

    Kuwata, K.

    2013-12-01

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

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

    SciTech Connect

    Mearns, L.O.

    1995-12-31

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

  6. Combining explanatory crop models with geospatial data for regional analyses of crop yield using field-scale modeling units

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Crop models are computational tools used for predicting crop yield and natural resource requirements and are frequently used to evaluate different climate or management scenarios at a specific site. However, problems involving land use or climate change would benefit from conducting crop simulation...

  7. Modeling with Limited Data: The Influence of Crop Rotation and Management on Weed Communities and Crop Yield Loss

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Theory and models of crop yield loss from weed competition have lead to decision models to help growers with cost-effective tactical weed management. Weed management decision models are available for multiple-species populations in a single season of several crops. Growers also rely on crop rotation...

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

    PubMed Central

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

    2012-01-01

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

  9. Crop suitability monitoring for improved yield estimations with 100m PROBA-V data

    NASA Astrophysics Data System (ADS)

    Özüm Durgun, Yetkin; Gilliams, Sven; Gobin, Anne; Duveiller, Grégory; Djaby, Bakary; Tychon, Bernard

    2015-04-01

    This study has been realised within the framework of a PhD targeting to advance agricultural monitoring with improved yield estimations using SPOT VEGETATION remotely sensed data. For the first research question, the aim was to improve dry matter productivity (DMP) for C3 and C4 plants by adding a water stress factor. Additionally, the relation between the actual crop yield and DMP was studied. One of the limitations was the lack of crop specific maps which leads to the second research question on 'crop suitability monitoring'. The objective of this work is to create a methodological approach based on the spectral and temporal characteristics of PROBA-V images and ancillary data such as meteorology, soil and topographic data to improve the estimation of annual crop yields. The PROBA-V satellite was launched on 6th May 2013, and was designed to bridge the gap in space-borne vegetation measurements between SPOT-VGT (March 1998 - May 2014) and the upcoming Sentinel-3 satellites scheduled for launch in 2015/2016. PROBA -V has products in four spectral bands: BLUE (centred at 0.463 µm), RED (0.655 µm), NIR (0.845 µm), and SWIR (1.600 µm) with a spatial resolution ranging from 1km to 300m. Due to the construction of the sensor, the central camera can provide a 100m data product with a 5 to 8 days revisiting time. Although the 100m data product is still in test phase a methodology for crop suitability monitoring was developed. The multi-spectral composites, NDVI (Normalised Difference Vegetation Index) (NIR_RED/NIR+RED) and NDII (Normalised Difference Infrared Index) (NIR-SWIR/NIR+SWIR) profiles are used in addition to secondary data such as digital elevation data, precipitation, temperature, soil types and administrative boundaries to improve the accuracy of crop yield estimations. The methodology is evaluated on several FP7 SIGMA test sites for the 2014 - 2015 period. Reference data in the form of vector GIS with boundaries and cover type of agricultural fields are

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

    SciTech Connect

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

    2010-01-01

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

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

    PubMed

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

    2014-01-01

    The appearance of agriculture in the Fertile Crescent propelled the development of Western civilization. Here we investigate the evolution of agronomic conditions in this region by reconstructing cereal kernel weight and using stable carbon and nitrogen isotope signatures of kernels and charcoal from a set of 11 Upper Mesopotamia archaeological sites, with chronologies spanning from the onset of agriculture to the turn of the era. We show that water availability for crops, inferred from carbon isotope discrimination (Δ(13)C), was two- to fourfold higher in the past than at present, with a maximum between 10,000 and 8,000 cal BP. Nitrogen isotope composition (δ(15)N) decreased over time, which suggests cultivation occurring under gradually less-fertile soil conditions. Domesticated cereals showed a progressive increase in kernel weight over several millennia following domestication. Our results provide a first comprehensive view of agricultural evolution in the Near East inferred directly from archaeobotanical remains. PMID:24853475

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

    PubMed Central

    Aguilera, Mònica; Buxó, Ramón

    2014-01-01

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

  13. Detecting Climate Change and Its Impacts on Crop Yield in the Continental United States

    NASA Astrophysics Data System (ADS)

    Ge, Y.; Cai, X.

    2012-12-01

    Climatic variables, temperature and precipitation in particular, play critical roles in crop growth. Changes in climate, i.e., the change of mean and/or variance in climatic time series have brought up concerns for agriculture. Detecting past climate change and its impact is essential to understand the causes on what have already occurred. This study uses a novel change point detection method, which is based on Bayesian local posterior density and Pettitt test to detect multiple change points in a given time series, and to classify change patterns (graduate and step change) based on the final posterior probability density. The detection method is then applied to the United States Historical Climate Network (USHCN) covering thousands of sites; the change patterns of precipitation, and maximum, average and minimum temperature in crop growing periods and growing years are examined in details. The impacts of the identified climate changes on the yield of grain corn in the US are assessed. A regression model with climate variables is developed to model crop yield responses to the climate since 1970. Through various testing scenarios, it is found that the impacts of climate change on corn yield vary by region (Figure 1), temperature component (minimum, maximum or average), time periods for the assessment (crop growing period or year), and irrigated and rainfed crops. The change in minimum temperature has the largest impact on the gross corn yield over the Continental U.S among those climate variables; warming of maximum temperature boosts the gross corn yield, while warming of average temperature and minimum temperature slows it. In the Midwest, precipitation change has much larger impact on rainfed than on irrigated corn, which shows an evidence of irrigation adaptation to climate change in the region. Figure 1 shows the estimated impact of minimum temperature change (mean monthly minimum daily temperature in the growing season) in the growing season during 1970-2010 on

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

    NASA Astrophysics Data System (ADS)

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

    2015-02-01

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

  15. Towards probabilistic projections of climate change impacts on global crop yields

    NASA Astrophysics Data System (ADS)

    Tebaldi, C.; Lobell, D. B.

    2008-04-01

    There is a widely recognized need in the scientific and policy communities for probabilistic estimates of climate change impacts, beyond simple scenario analysis. Here we propose a methodology to evaluate one major climate change impact - changes in global average yields of wheat, maize, and barley by 2030 - by a probabilistic approach that integrates uncertainties in climate change and crop yield responses to temperature, precipitation, and carbon dioxide. The resulting probability distributions, which are conditional on assuming the SRES A1B emission scenario and no agricultural adaptation, indicate expected changes of +1.6%, -14.1%, -1.8% for wheat, maize, and barley, with 95% probability intervals of (-4.1, +6.7), (-28.0, -4.3), (-11.0, 6.2) in percent of current yields, respectively. This fully probabilistic analysis aims at quantifying the range of plausible outcomes and allows us to gauge the relative importance of different sources of uncertainty.

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

    PubMed Central

    2011-01-01

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Novel management practices are needed to improve the declining dryland crop yields and soil organic matter using conventional farming practices in the northern Great Plains. We evaluated the 21-yr effect of tillage and cropping sequence on dryland grain and biomass (stems + leaves) yields of spring ...

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  19. Effects of Potato-Cotton Cropping Systems and Nematicides on Plant-Parasitic Nematodes and Crop Yields

    PubMed Central

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

    2000-01-01

    Belonolaimus longicaudatus has been reported as damaging both potato (Solanum tuberosum) and cotton (Gossypium hirsutum). These crops are not normally grown in cropping systems together in areas where the soil is infested with B. longicaudatus. During the 1990s cotton was grown in a potato production region that was a suitable habitat for B. longicaudatus. It was not known how integrating the production of these two crops by rotation or double-cropping would affect the population densities of B. longicaudatus, other plant-parasitic nematodes common in the region, or crop yields. A 3-year field study evaluated the viability of both crops in monocropping, rotation, and double-cropping systems. Viability was evaluated using effects on population densities of plant-parasitic nematodes and yields. Rotation of cotton with potato was found to decrease population densities of B. longicaudatus and Meloidogyne incognita in comparison with continuous potato. Population densities of B. longicaudatus following double-cropping were greater than following continuous cotton. Yields of both potato and cotton in rotation were equivalent to either crop in monocropping. Yields of both crops were lower following double-cropping when nematicides were not used. PMID:19270980

  20. USING MULTISPECTRAL IMAGERY AND LINEAR SPECTRAL UNMIXING TECHNIQUES FOR ESTIMATING CROP YIELD VARIABILITY

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Vegetation indices derived from multispectral imagery are commonly used to extract crop growth and yield information. Spectral unmixing techniques provide an alternative approach to quantifying crop canopy abundance within each image pixel and have the potential for mapping crop yield variability. T...

  1. Airborne hyperspectral imagery and linear spectral unmixing for mapping variation in crop yield

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Vegetation indices derived from remotely sensed imagery are commonly used to estimate crop yields. Spectral unmixing techniques provide an alternative approach to quantifying crop canopy abundance within each pixel of an image and have the potential for mapping crop yield variability. The objective ...

  2. The Role of Nutrient Efficient Plants in Improving Crop Yields in the Twenty First Century

    Technology Transfer Automated Retrieval System (TEKTRAN)

    In the 21st century, nutrient efficient plants will play a major role in increasing crop yields compared to the 20th century, mainly due to limited land and water resources available for crop production, higher cost of inorganic fertilizer inputs, and declining trends in crop yields globally. Furthe...

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

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

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

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

    SciTech Connect

    2010-01-01

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

  5. The Impact of Changing Snowmelt Timing on Non-Irrigated Crop Yield: A Parametric and Non-Parametric Approach

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

    As climate changes, the final date of spring snowmelt is projected to occur earlier in the year within the western United States. This earlier snowmelt timing may impact crop yield in snow-dominated watersheds by changing the timing of water delivery to agricultural fields. There is considerable uncertainty about how agricultural impacts of snowmelt timing may 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. A better understanding of the influence of changes in snowmelt on non-irrigated crop yield may additionally be extrapolated to better understand how climate change may alter biomass production in non-managed ecosystems. We utilized parametric regression techniques to isolate the magnitude of impact snowmelt timing has had on historical crop yield independently of climate and spatial variables that also impact yield. To do this, we examined the historical relationship between snowmelt timing and non-irrigated wheat and barley yield using a multiple linear regression model to predict yield in several Idaho counties as a function of snowmelt date, climate variables (precipitation and growing degree-days), and spatial differences between counties. We utilized non-parametric techniques to determine where snowmelt timing has positively versus negatively impacted yield. To do this, we developed classification and regression trees to identify spatial controls (e.g. latitude, elevation) on the relationship between snowmelt timing and yield. Most trends suggest a decrease in crop yield with earlier snowmelt, but a significant opposite relationship is observed in some regions of Idaho. An earlier snowmelt date occurring at high latitudes corresponds with higher than average wheat yield. Therefore, Northern Idaho may

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  7. Soil Carbon and Nitrogen Fractions and Crop Yields Affected by Residue Placement and Crop Types

    PubMed Central

    Wang, Jun; Sainju, Upendra M.

    2014-01-01

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

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

    PubMed

    Wang, Jun; Sainju, Upendra M

    2014-01-01

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

  9. Crop insurance: a tool to stabilize Spanish agricultural income

    NASA Astrophysics Data System (ADS)

    Calatayud Piñero, E.; Escribano Pintor, S.

    2009-04-01

    Agricultural insurance was born as a need for farmers, opposite to the erratic behavior of the climatology, natural disaster, which strangles the farmer during the cycle of his crops and harvest, reverberating negatively in the economy of the farmer. Before this situation, it became necessary to determine, inside the agricultural policies, a specific regulation of the agricultural insurance across a participation of the State by means of contributions to the agricultural insurance which result was, in Spain, the current Law 87/1978, of December 28 of Agricultural Insurance. The benefits of the existence of a good system of agricultural insurance not only are to level of the farmer but also to regional level and top areas, since to the regional production turns diminished, it reverberates in the economic productivity and in the rest of economic sectors, with the consequent tensions and imbalances, and the probability of being translated in a decrease of the quality of life of the rural way. But the analysis of the importance of his situation, not only must be carried out from a theoretical perspective, where already there exist numerous studies that treat the relation and importance of the agricultural insurance with regard to the traditional agriculture characterized by his limited capacity of innovation. For it, in this paper, we will proceed to realize an empirical analysis, inside our country, across the principal agrarian information statistics, as faithful reflection of the economic dimension of the sector, for across his evolution as well as that of the indemnifications paid for the agricultural insurance, to be able to show the importance of the same one in his contribution to the maintenance and improvement of the agriculture, avoiding the uncertainty of the farmer By means of the utilization of mobile averages, which eliminate the erratic behavior in the annual series, first we will realize a national analysis for the set of the lines of agricultural

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

    PubMed Central

    Rosenheim, Jay A.; Meisner, Matthew H.

    2013-01-01

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

  11. Global patterns of the trends in satellite-derived crop yield proxy, temperature and soil moisture

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

    Crop productivity (yield) is sensitive to climate variability and change. To inform stakeholders, including food agencies in food-importing countries, about future variations in food supply associated with climate variability and change, understanding major climatic drivers of the spatiotemporal variations in crop yield over global cropland during the last few decades is crucial. Although remote sensing has difficulty distinguishing individual crops and misses entire cropping cycles in areas where extensive cloud cover during the monsoon limits satellite observations, it is still useful in deriving a proxy of crop yield over large spatial domain and estimating the impacts on crop yield proxy due to climate, including land-surface temperature and surface-layer soil moisture. This study presents an attempt to globally depict the impact of climate change on crop yield proxy by applying a time series analysis to MODIS and AMSR-E satellite images. The crop yield proxy used was the annual maximum or integrated MODIS-derived NDVI during the growing period predefined on the basis of the global crop calendar. The trends in the crop yield proxy in the interval 2001-2013 appeared positive in higher latitudes and negative in lower latitudes. In higher latitudes (and thus colder regions), the increased land-surface temperature led to an increase in crop yield in part due to the enhanced photosynthesis rate. In contrast, the crop yield proxy showed negative correlation with land-surface temperature in lower latitudes. The increased temperature might decrease crop yield by increasing evapotranspiration rate, plant respiration and/or heat stress. The crop yield proxy was also correlated with the AMSR-E-derived soil moisture, although the geographical distribution of soil moisture was highly heterogeneous.

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

    PubMed

    Singh, Jay Shankar; Pandey, Vimal Chandra

    2013-03-01

    There are reports that the application of fly ash, compost and press mud or a combination thereof, improves plant growth, soil microbial communities etc. Also, fly ash in combination with farmyard manure or other organic amendments improves soil physico-chemical characteristics, rice yield and microbial processes in paddy fields. However, the knowledge about the impact of fly ash inputs alone or in combination with other organic amendments on soil methanotrophs number in paddy soils is almost lacking. We hypothesized that fly ash application at lower doses in paddy agriculture soil could be a potential amendment to elevate the paddy yields and methanotrophs number. Here we demonstrate the impact of fly ash and press mud inputs on number of methanotrophs, antioxidants, antioxidative enzymatic activities and paddy yields at agriculture farm. The impact of amendments was significant for methanotrophs number, heavy metal concentration, antioxidant contents, antioxidant enzymatic activities and paddy yields. A negative correlation was existed between higher doses of fly ash-treatments and methanotrophs number (R(2)=0.833). The content of antioxidants and enzymatic activities in leaves of higher doses fly ash-treated rice plants increased in response to stresses due to heavy metal toxicity, which was negatively correlated with rice grain yield (R(2)=0.944) and paddy straw yield (R(2)=0.934). A positive correlation was noted between heavy metals concentrations and different antioxidant and enzymatic activities across different fly ash treated plots.The data of this study indicate that heavy metal toxicity of fly ash may cause oxidative stress in the paddy crop and the antioxidants and related enzymes could play a defensive role against phytotoxic damages. We concluded that fly ash at lower doses with press mud seems to offer the potential amendments to improving soil methanotrophs population and paddy crop yields for the nutrient poor agriculture soils. PMID:23260239

  13. Agricultural Policy Environmental eXtender simulation of three adjacent row-crop watersheds in the claypan region

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The Agricultural Policy Environmental Extender (APEX) model can simulate crop yields, and pollutant loadings in whole farms or small watersheds with variety of management practices. The study objectives were to identify sensitive parameters and parameterize, calibrate and validate the APEX model fo...

  14. 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

  15. MODELING THE POTENTIAL CHANGE IN YIELD AND DISTRIBUTION OF THE EARTH'S CROPS UNDER A WARMED CLIMATE

    EPA Science Inventory

    The large scale distribution of crops is largely determined by climate. e present the results of a climate-crop prediction model based on the U.S. Food & Agriculture Organization crop-suitability approach, implemented in a geographic information system(GIS) environment using seve...

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

    NASA Astrophysics Data System (ADS)

    Kuwata, K.

    2014-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-06-01

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

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

    SciTech Connect

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

    1997-07-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  20. A Crop Simulation System for Integrating Remote Sensing and Climate Information to Reduce Model Uncertainty in Crop Yield Assessments

    NASA Astrophysics Data System (ADS)

    Ines, A. M.; Honda, K.; Yui, A.

    2012-12-01

    Uncertainties in crop yield assessments are caused by many factors, including an imperfect model, model parameters and modeling assumptions, as well as errors in data inputs, e.g. climate. Here, we present a crop simulation system that aims to reduce uncertainty in crop yield assessment due to model and data uncertainties. The system uses DSSAT-CSM as the core crop simulation model. The simulation strategy is two-folds: i) crop model parameter estimation and ii) simulation and prediction mode. In i) a noisy Monte Carlo genetic algorithm (NMCGA) is used to estimate crop, soil and management parameters and their uncertainties, where field and remote sensing data can be used in the process. In ii) simulations can be done in an incremental way, where climate data until the current day is used as inputs to the crop model while the climate inputs for rest of the simulation period are generated by a stochastic weather generator based on climatological or climate forecasts information. Also, in the prediction mode, an ensemble Kalman filter (EnKF) can be used to update crop model state variables, e.g., leaf area index (LAI) and soil moisture from remote sensing and field sensors, this can be used in tandem with the climate merging mechanism within the crop simulation system. A case study on wheat modeling in Hokkaido, Japan will be presented. Model uncertainty assessment and implications of the crop simulation system for crop assessment will be discussed.

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

    PubMed

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

    2008-01-01

    One approach to apply precision agriculture to optimize crop production and environmental quality is identifying management zones. In this paper, the variables of soil electrical conductivity (EC) data, cotton yield data and normalized difference vegetation index (NDVI) data in an about 15 ha field in a coastal saline land were selected as data resources, and their spatial variabilities were firstly analyzed and spatial distribution maps constructed with geostatistics technique. Then fuzzy c-means clustering algorithm was used to define management zones, fuzzy performance index (FPI) and normalized classification entropy (NCE) were used to determine the optimal cluster numbers. Finally one-way variance analysis was performed on 224 georeferenced soil and yield sampling points to assess how well the defined management zones reflected the soil properties and productivity level. The results reveal that the optimal number of management zones for the present study area was 3 and the defined management zones provided a better description of soil properties and yield variation. Statistical analyses indicate significant differences between the chemical properties of soil samples and crop yield in each management zone, and management zone 3 presented the highest nutrient level and potential crop productivity, whereas management zone 1 the lowest. Based on these findings, we conclude that fuzzy c-means clustering approach can be used to delineate management zones by using the given three variables in the coastal saline soils, and the defined management zones form an objective basis for targeting soil samples for nutrient analysis and development of site-specific application strategies. PMID:18196615

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    SciTech Connect

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

    1998-10-04

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

  4. Potential for improved crop yield prediction through assimilation of satellite-derived soil moisture data

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Official U.S. Department of Agriculture (USDA) yield estimates are summarized in the monthly World Agricultural Supply and Demand Estimates (WASDE) report released by the World Agricultural Outlook Board (WAOB). WAOB analyses contributing to the yield estimates are done using the Global Agricultural...

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

    PubMed Central

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

    2011-01-01

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  7. Long-term tillage and cropping sequence influence on dryland soil carbon, nitrogen, physical properties, and crop yields

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Novel management practices are needed to improve dryland soil C and N sequestration, N mineralization, soil physical properties, and crop yields in the northern Great Plains. We evaluated the 21-yr effect of tillage and cropping sequence on dryland soil aggregation, C and N storage, N mineralization...

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

    PubMed

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

    2015-03-01

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

  9. Global crop yield reductions due to surface ozone exposure: 2. Year 2030 potential crop production losses and economic damage under two scenarios of O 3 pollution

    NASA Astrophysics Data System (ADS)

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

    2011-04-01

    We examine the potential global risk of increasing surface ozone (O 3) exposure to three key staple crops (soybean, maize, and wheat) in the near future (year 2030) according to two trajectories of O 3 pollution: the Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios (IPCC SRES) A2 and B1 storylines, which represent upper- and lower-boundary projections, respectively, of most O 3 precursor emissions in 2030. We use simulated hourly O 3 concentrations from the Model for Ozone and Related Chemical Tracers version 2.4 (MOZART-2), satellite-derived datasets of agricultural production, and field-based concentration:response relationships to calculate crop yield reductions resulting from O 3 exposure. We then calculate the associated crop production losses and their economic value. We compare our results to the estimated impact of O 3 on global agriculture in the year 2000, which we assessed in our companion paper [Avnery et al., 2011]. In the A2 scenario we find global year 2030 yield loss of wheat due to O 3 exposure ranges from 5.4 to 26% (a further reduction in yield of +1.5-10% from year 2000 values), 15-19% for soybean (reduction of +0.9-11%), and 4.4-8.7% for maize (reduction of +2.1-3.2%) depending on the metric used, with total global agricultural losses worth 17-35 billion USD 2000 annually (an increase of +6-17 billion in losses from 2000). Under the B1 scenario, we project less severe but still substantial reductions in yields in 2030: 4.0-17% for wheat (a further decrease in yield of +0.1-1.8% from 2000), 9.5-15% for soybean (decrease of +0.7-1.0%), and 2.5-6.0% for maize (decrease of + 0.3-0.5%), with total losses worth 12-21 billion annually (an increase of +1-3 billion in losses from 2000). Because our analysis uses crop data from the year 2000, which likely underestimates agricultural production in 2030 due to the need to feed a population increasing from approximately 6 to 8 billion people between 2000 and 2030, our

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

    SciTech Connect

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

    1993-11-01

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

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

    SciTech Connect

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

    1997-10-01

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

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

    NASA Astrophysics Data System (ADS)

    Bhushan, R.; Ng, T. L.

    2015-12-01

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

  13. SOIL WATER USE AND GRAIN YIELD OF THREE DRYLAND CROPS UNDER DIFFERING TILLAGE SYSTEMS

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Combining the use of drought-adapted and early maturing crops with reduced tillage practices in dryland cropping systems can increase soil water storage, water-use efficiency and crop yields. The objective of this study was to evaluate soil water use by cowpeas (Vigna unguiculata), grain sorghum [So...

  14. Statistical modeling of yield and variance instability in conventional and organic cropping systems

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Cropping systems research was undertaken to address declining crop diversity and verify competitiveness of alternatives to the predominant conventional cropping system in the northern Corn Belt. To understand and capitalize on temporal yield variability within corn and soybean fields, we quantified ...

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

    DOE PAGESBeta

    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

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

    NASA Astrophysics Data System (ADS)

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

    2005-12-01

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

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

    NASA Astrophysics Data System (ADS)

    Nagy, Attila; Tamás, János; Fehér, János

    2015-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

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

    PubMed

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

    2016-10-01

    Mass-flowering crops (MFCs) are increasingly cultivated and might influence pollinator communities in MFC fields and nearby semi-natural habitats (SNHs). Across six European regions and 2 years, we assessed how landscape-scale cover of MFCs affected pollinator densities in 408 MFC fields and adjacent SNHs. In MFC fields, densities of bumblebees, solitary bees, managed honeybees and hoverflies were negatively related to the cover of MFCs in the landscape. In SNHs, densities of bumblebees declined with increasing cover of MFCs but densities of honeybees increased. The densities of all pollinators were generally unrelated to the cover of SNHs in the landscape. Although MFC fields apparently attracted pollinators from SNHs, in landscapes with large areas of MFCs they became diluted. The resulting lower densities might negatively affect yields of pollinator-dependent crops and the reproductive success of wild plants. An expansion of MFCs needs to be accompanied by pollinator-supporting practices in agricultural landscapes. PMID:27531385

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

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

    PubMed

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

    2013-01-01

    In the Laurentian Great Lakes Basin (GLB), corn acreage has been expanding since 2005 in response to high demand for corn as an ethanol feedstock. This study integrated remote sensing-derived products and the Soil and Water Assessment Tool (SWAT) within a geographic information system (GIS) modeling environment to assess the impacts of cropland change on sediment yield within four selected watersheds in the GLB. The SWAT models were calibrated during a 6 year period (2000-2005), and predicted stream flows were validated. The R(2) values were 0.76, 0.80, 0.72, and 0.81 for the St. Joseph River, the St. Mary River, the Peshtigo River, and the Cattaraugus Creek watersheds, respectively. The corresponding E (Nash and Sutcliffe model efficiency coefficient) values ranged from 0.24 to 0.79. The average annual sediment yields (tons/ha/year) ranged from 0.12 to 4.44 for the baseline (2000 to 2008) condition. Sediment yields were predicted to increase for possible future cropland change scenarios. The first scenario was to convert all "other" agricultural row crop types (i.e., sorghum) to corn fields and switch the current/baseline crop rotation into continuous corn. The average annual sediment yields increased 7-42 % for different watersheds. The second scenario was to further expand the corn planting to hay/pasture fields. The average annual sediment yields increased 33-127 % compared with baseline conditions. PMID:22791140

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

    NASA Astrophysics Data System (ADS)

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

    2013-01-01

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

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

    NASA Astrophysics Data System (ADS)

    LeBauer, D.

    2015-12-01

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

  4. Methodology for Developing a Crop Yield Stability Map for a Field

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This abstract will summarize the methodology used to develop a yield stability map for a field. We proposed that there exist yield stability patters for commercial field crop production which growers can use to optimize crop production while minimizing inputs. The methodology uses multiple years o...

  5. Impact of corn residue on yield of cool-season crops

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Synergy between dry pea and corn can reduce the density of corn needed for optimum yield. Lower crop density may accrue an additional benefit, as after-harvest residues of corn lying on the soil surface can reduce yield of crops planted the next year. This study evaluated impact of corn residue lev...

  6. Relating Crop Yield Patterns to Terrain Attributes Under Water-Limited and Waterlogged Conditions

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Terrain attributes derived from high-resolution digital elevation models (DEMs) can be useful for explaining spatial patterns of soil moisture and crop yields. Assuming landscape topographic controls on soil moisture variability, we correlated soil moisture and crop yield with a suite of terrain at...

  7. Correlation Between Precipitation and Crop Yield for Corn and Cotton Produced in Alabama

    NASA Technical Reports Server (NTRS)

    Hayes, Carol E.; Perkey, Donald J.

    1998-01-01

    In this study, variations in precipitation during the time of corn silking are compared to Alabama corn yields. Also, this study compares precipitation variations during bloom to Alabama cotton yield. The goal is to obtain mathematical correlations between rainfall during the crop's critical period and the crop amount harvested per acre.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  9. Book Review of the PHYSIOLOGY OF CROP YIELD by R. Hay and J. Porter

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The Physiology of Crop Yield by R. Hay and J. Porter (2006; Blackwell Publishing) represents a complete rewrite of An Introduction to the Physiology of Crop Yield, by R. Hay and A.J. Walker (1989). The new text emphasizes quantitative description of plant development and growth, working from a simpl...

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

    PubMed

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

    2016-02-01

    Throughout the history of agriculture, many new crop species (polyploids or artificial hybrids) have been introduced to diversify products or to increase yield. However, little is known about how these new crops influence the evolution of new pathogens and diseases. Triticale is an artificial hybrid of wheat and rye, and it was resistant to the fungal pathogen powdery mildew (Blumeria graminis) until 2001 (refs. 1,2,3). We sequenced and compared the genomes of 46 powdery mildew isolates covering several formae speciales. We found that B. graminis f. sp. triticale, which grows on triticale and wheat, is a hybrid between wheat powdery mildew (B. graminis f. sp. tritici) and mildew specialized on rye (B. graminis f. sp. secalis). Our data show that the hybrid of the two mildews specialized on two different hosts can infect the hybrid plant species originating from those two hosts. We conclude that hybridization between mildews specialized on different species is a mechanism of adaptation to new crops introduced by agriculture. PMID:26752267

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

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

    ERIC Educational Resources Information Center

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

    2007-01-01

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

  13. Estimation rice yield based on integration remote sensing information and crop model

    NASA Astrophysics Data System (ADS)

    Guo, Jianmao; Wang, Qi; Zheng, Tengfei; Li, Xujie; Shi, Junyi; Zhu, Jinhui

    2012-10-01

    Crop model is a powerful tool in crop growth monitoring and yield forecasting, however crop model is developed based on single point scale, due to regional differentiation、field variation and other reasons lead to input parameters and initial conditions which required by crop model simulation are hard to obtain, the application of crop model has been greatly limited in the regional scale, the introduction of remote sensing will solve this problem, remote sensing is combined with the crop model WOFOST, using the state variable retrieved by remote sensing to optimize crop model simulation, revaluing the sensitive parameters and initial conditions which needed in crop model on the region scale, in order to take the advantage of crop model in the area.This study is on the basis of adaptive adjustment and amendment of crop model WOFOST, build a winter wheat growth simulation model which is suitable for Yucheng, Shandong; Using the field experiment data calibration and validation the WOFOST model, discussed the method which combined crop simulation model and remote sensing under water stress level, using remote sensing calibrated some key processes of crop simulation or reinitialize、parameterize the crop simulation model in order to achieve the optimization model; Explored some reasonable and practical method of remote sensing information application in crop simulation at regional scale, with more research, make it possible to monitor regional crop growth and forecast the output.

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

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

  18. Airborne monitoring of crop canopy temperatures for irrigation scheduling and yield prediction

    NASA Technical Reports Server (NTRS)

    Millard, J. P.; Jackson, R. D.; Reginato, R. J.; Idso, S. B.; Goettelman, R. C.; Lapado, R. L.

    1977-01-01

    The aim of the program discussed was to develop techniques for remotely measuring crop irrigation needs and predicting crop yields, with emphasis on wheat. Airborne measurements, using an IR line scanner and color IR photography, were made to evaluate the feasibility of measuring minimum and maximum (dawn and afternoon) crop temperatures to compute a parameter, termed 'stress degree day' (SDD) - a valuable indicator of crop water needs, which can be related to irrigation scheduling and yield. Crop canopy temperature measurements by airborne IR techniques revealed the superiority of thermal IR data over color IR photography. Water stress undetected in the latter technique was clearly detected in thermal imagery. Color IR photography, however, is valuable in discerning vegetation. The pseudo-colored temperature-difference images (and pseudo-colored images, reading directly in daily SDD increments) are shown to be well suited for assessing plant water status and, thus, for determining the irrigation needs and crop yield potentials.

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

    NASA Astrophysics Data System (ADS)

    Wahbi, Ammar; Miwak, Hisham; Singh, Raphy

    2014-05-01

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

  20. Estimating soil moisture and the relationship with crop yield using surface temperature and vegetation index

    NASA Astrophysics Data System (ADS)

    Holzman, M. E.; Rivas, R.; Piccolo, M. C.

    2014-05-01

    Soil moisture availability affects rainfed crop yield. Therefore, the development of methods for pre-harvest yield prediction is essential for the food security. A study was carried out to estimate regional crop yield using the Temperature Vegetation Dryness Index (TVDI). Triangular scatters from land surface temperature (LST) and enhanced vegetation index (EVI) space from MODIS (Moderate Resolution Imaging Spectroradiometer) were utilized to obtain TVDI and to estimate soil moisture availability. Then soybean and wheat crops yield was estimated on four agro-climatic zones of Argentine Pampas. TVDI showed a strong correlation with soil moisture measurements, with R2 values ranged from 0.61 to 0.83 and also it was in agreement with spatial pattern of soil moisture. Moreover, results showed that TVDI data can be used effectively to predict crop yield on the Argentine Pampas. Depending on the agro-climatic zone, R2 values ranged from 0.68 to 0.79 for soybean crop and 0.76 to 0.81 for wheat. The RMSE values were 366 and 380 kg ha-1 for soybean and they varied between 300 and 550 kg ha-1 in the case of wheat crop. When expressed as percentages of actual yield, the RMSE values ranged from 12% to 13% for soybean and 14% to 22% for wheat. The bias values indicated that the obtained models underestimated soybean and wheat yield. Accurate crop grain yield forecast using the developed regression models was achieved one to three months before harvest. In many cases the results were better than others obtained using only a vegetation index, showing the aptitude of surface temperature and vegetation index combination to reflect the crop water condition. Finally, the analysis of a wide range of soil moisture availability allowed us to develop a generalized model of crop yield and dryness index relationship which could be applicable in other regions and crops at regional scale.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  2. ALTERNATIVE OZONE DOSE METRICS TO CHARACTERIZE OZONE IMPACT ON CROP YIELD LOSS (JOURNAL VERSION)

    EPA Science Inventory

    Previous studies of the National Crop Loss Assessment Network (NCLAN) relating the impact of ozone (O3) on agricultural crops have used the seasonal arithmetic average of O3 for either a 7- or 12-h daily period as the measure of dose in the dose response relationships. The study ...

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

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

    PubMed

    Sun, Junyan; Liu, Yu

    2014-09-01

    In this paper, we analyze the relationships among the tree-ring chronology, meteorological drought (precipitation), agricultural drought (Palmer Drought Severity Index PDSI), hydrological drought (runoff), and agricultural data in the Shanxi province of North China. Correlation analyses indicate that the tree-ring chronology is significantly correlated with all of the drought indices during the main growing season from March to July. Sign test analyses further indicate that the tree-ring chronology shows variation similar to that of the drought indices in both high and low frequencies. Comparisons of the years with narrow tree rings to the severe droughts reflected in all three indices from 1957 to 2008 reveal that the radial growth of the trees in the study region can accurately record the severe drought for which all three indices were in agreement (1972, 1999, 2000, and 2001). Comparisons with the dryness/wetness index indicate that tree-ring growth can properly record the severe droughts in the history. Correlation analyses among agricultural data, tree-ring chronology, and drought indices indicate that the per-unit yield of summer crops is relatively well correlated with the agricultural drought, as indicated by the PDSI. The PDSI is the climatic factor that significantly influences both tree growth and per-unit yield of summer crops in the study region. These results indicate that the PDSI and tree-ring chronology have the potential to be used to monitor and predict the yield of summer crops. Tree-ring chronology is an important tool for drought research and for wider applications in agricultural and hydrological research. PMID:24162181

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

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

  7. Potential forcing of climate changes in crops yields: Brazil and Africa perspectives

    NASA Astrophysics Data System (ADS)

    Justino, F.; Stordal, F.

    2012-12-01

    This presentation will focus on the impact of human induced climate changes on crop yields in Brazil and sub-Saharan Africa. Crop modeling simulations have been run based on regional climate models (RegCM4 and PRECIS) to serve as initial conditions to DSSAT for both current and future climate conditions. The preliminary results indicate that substantial change may be expected in the interannual variability of crop yields in Brazil but not essentially in Africa. This is attributed to substantial changes in precipitation in Brazil which are not predicted to occur in Africa. It might be noted moreover that changes in future crop productivity exhibit for both regions high spatial heterogeneity.

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

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

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

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

    PubMed

    Karimi Alavijeh, Masih; Yaghmaei, Soheila

    2016-06-01

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

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

    SciTech Connect

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

    1991-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-07-01

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

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

    PubMed

    Sutter, Louis; Albrecht, Matthias

    2016-02-10

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

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

    PubMed Central

    Nonomura, A M; Benson, A A

    1992-01-01

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

  14. Comparison between historical yield and soybean crop EVI values using correlation map

    NASA Astrophysics Data System (ADS)

    Figueiredo, G. K.; Rocha, J. V.; Lamparelli, R. A.; Brunsell, N. A.

    2012-12-01

    Timely and accurate yield estimates using remote sensing represents an important advance towards objective crop forecasting in Brazil. Vegetation index values integrated over a period have been used to generate agronomic parameters such as crop yield. Several studies showed the strong relationship between accumulated vegetation index and historical yield, once it represents crop photosynthetic activity. The main goal of this study was to create correlation maps between Modis/TERRA EVI and historical yield during the soybean crop cycle in Paraná state, Brazil, from 2000 to 2010. The soybean cycle was separated in four variables corresponding to the crop stage: emergence to maturity, emergence to flowering, flowering to maturity, flowering to the grain filling. For each variable a correlation map was created between the accumulated EVI and soybean yield at pixel level. All variables showed a good correlation, but among all of them the best correlation was the period between flowering to maturity. This happened because of exclusion of months where EVI response was low, corresponding to period of crop emergence (October and November). A percentage map of soybean crop was confronted with the correlation map to check out whether the highest correlation was corresponding to soybean pixel. On the percentage map pixels showing above 70% of soybean were selected, then on the correlation map pixels with correlation coefficients above 0.7 were selected. Within the data set 43% of pixels from the correlation map had land cover greater than or equal to 70% of soybean crop.

  15. Nitrate leaching, yields and carbon sequestration after noninversion tillage, catch crops, and straw retention.

    PubMed

    Hansen, E M; Munkholm, L J; Olesen, J E; Melander, B

    2015-05-01

    Crop management factors, such as tillage, rotation, and straw retention, need to be long-term to allow conclusions on effects on crop yields, nitrate leaching, and carbon sequestration. In 2002, two field experiments, each including four cash crop rotations, were established on soils with 9 and 15% clay, under temperate, coastal climate conditions. Direct drilling and harrowing to two different depths were compared to plowing with respect to yield, nitrate N leaching, and carbon sequestration. For comparison of yields across rotations, grain and seed dry matter yields for each crop were converted to grain equivalents (GE). Leaching was compared to yields by calculating yield-scaled leaching (YSL, g N kg GE), and N balances were calculated as the N input in manure minus the N output in products removed from the fields. Direct drilling reduced yields, but no effect on leaching was found. Straw retention did not significantly increase yields, nor did it reduce leaching, while fodder radish ( L.) as a catch crop was capable of reducing nitrate leaching to a low level. Thus, YSL of winter wheat ( L.) was higher than for spring barley ( L.) grown after fodder radish due to the efficient catch crop. Soil organic carbon (SOC) did not increase significantly after 7 yr of straw incorporation or noninversion tillage. There was no correlation between N balances calculated for each growing season and N leaching measured in the following percolation period. PMID:26024267

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

    PubMed

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

    2015-10-01

    Ecological intensification has been promoted as a means to achieve environmentally sustainable increases in crop yields by enhancing ecosystem functions that regulate and support production. There is, however, little direct evidence of yield benefits from ecological intensification on commercial farms growing globally important foodstuffs (grains, oilseeds and pulses). We replicated two treatments removing 3 or 8% of land at the field edge from production to create wildlife habitat in 50-60 ha patches over a 900 ha commercial arable farm in central England, and compared these to a business as usual control (no land removed). In the control fields, crop yields were reduced by as much as 38% at the field edge. Habitat creation in these lower yielding areas led to increased yield in the cropped areas of the fields, and this positive effect became more pronounced over 6 years. As a consequence, yields at the field scale were maintained--and, indeed, enhanced for some crops--despite the loss of cropland for habitat creation. These results suggested that over a 5-year crop rotation, there would be no adverse impact on overall yield in terms of monetary value or nutritional energy. This study provides a clear demonstration that wildlife-friendly management which supports ecosystem services is compatible with, and can even increase, crop yields. PMID:26423846

  17. Sugarcane yield response to soybean double-cropping in Louisiana

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The interruption of continuous sugarcane plantings with a soybean (Glycine max) crop during the spring/summer fallow period between sugarcane plantings represents an economical opportunity for sugarcane growers in Louisiana. The objective of the experiment was to determine if soybeans grown in the u...

  18. Impact of corn residue quantity on yield of following crops

    Technology Transfer Automated Retrieval System (TEKTRAN)

    We have observed that crop growth can be suppressed in fields where high quantities of corn residue are present on the soil surface. To examine this perceived trend, we grew dry pea, spring wheat, and red clover in two levels of corn residues, achieved by growing corn at 21,000 and 30,000 plants/ac...

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  20. 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.

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

    PubMed

    Zhang, Tianyi; Lin, Xiaomao

    2016-04-15

    Evaluation of how historical irrigation reactions can adapt to future drought is indispensable to irrigation policy, however, such reactions are poorly quantified. In this paper, county-level irrigation data for maize, soybean, grain sorghum, and wheat crops in Kansas were compiled. Statistical models were developed to quantify changes of irrigation and yields in response to drought for each crop. These were then used to evaluate the ability of current irrigation to cope with future drought impacts on each crop based on an ensemble Palmer Drought Severity Index (PDSI) prediction under the Representative Concentration Pathways 4.5 scenario. Results indicate that irrigation in response to drought varies by crop; approximately 10 to 13% additional irrigation was applied when PDSI was reduced by one unit for maize, soybean, and grain sorghum. However, the irrigation reaction for wheat exhibits a large uncertainty, indicating a weaker irrigation reaction. Analysis of future climate conditions indicates that maize, soybean, and grain sorghum yields would decrease 2.2-12.4% at the state level despite additional irrigation application induced by drought (which was expected to increase 5.1-19.0%), suggesting that future drought will exceed the range that historical irrigation reactions can adapt to. In contrast, a lower reduction (-0.99 to -0.63%) was estimated for wheat yields because wetter climate was projected in the central section of the study area. Expanding wheat areas may be helpful in avoiding future drought risks for Kansas agriculture. PMID:26851757

  2. Using remote sensing and grid-based meteorological datasets for regional soybean crop yield prediction and crop monitoring

    NASA Astrophysics Data System (ADS)

    Mali, Preeti

    Regional crop yield estimations using crop models is a national priority due to its contributions to crop security assessment and food pricing policies. Many of these crop yield assessments are performed using time-consuming, intensive field surveys. This research was initiated to test the applicability of remote sensing and grid-based meteorological model data for providing improved and efficient predictive capabilities for crop bio-productivity. The soybean prediction model (Sinclair model) used in this research, requires daily data inputs to simulate yield which are temperature, precipitation, solar radiation, day length initialization of certain soil moisture parameters for each model run. The traditional meteorological datasets were compared with simulated South American Land Data Assimilation System (SALDAS) meteorological datasets for Sinclair model runs and for initializing soil moisture inputs. Considering the fact that grid-based meteorological data has the resolution of 1/8th of a degree, the estimations demonstrated a reasonable accuracy level and showed promise for increase in efficiency for regional level yield predictions. The research tested daily composited Normalized Difference Vegetation Index (NDVI) from Moderate Resolution Imaging Spectroradiometer (MODIS) sensor (both AQUA and TERRA platform) and simulated Visible/Infrared Imager Radiometer Suite (VIIRS) sensor product (a new sensor planned to be launched in the near future) for crop growth and development based on phenological events. The AQUA and TERRA fusion based daily MODIS NDVI was utilized to develop a planting date estimation method. The results have shown that daily MODIS composited NDVI values have the capability for enhanced monitoring of soybean crop growth and development. The method was able to predict planting date within +/-3.4 days. A geoprocessing framework for extracting data from the grid data sources was developed. Overall, this study was able to demonstrate the utility of

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

    PubMed

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

    2016-01-01

    Global food security requires increased crop productivity to meet escalating demand(1-3). Current food production systems are heavily dependent on synthetic inputs that threaten the environment and human well-being(2,4,5). Biodiversity, for instance, is key to the provision of ecosystem services such as pest control(6,7), but is eroded in conventional agricultural systems. Yet the conservation and reinstatement of biodiversity is challenging(5,8,9), and it remains unclear whether the promotion of biodiversity can reduce reliance on inputs without penalizing yields on a regional scale. Here we present results from multi-site field studies replicated in Thailand, China and Vietnam over a period of four years, in which we grew nectar-producing plants around rice fields, and monitored levels of pest infestation, insecticide use and yields. Compiling the data from all sites, we report that this inexpensive intervention significantly reduced populations of two key pests, reduced insecticide applications by 70%, increased grain yields by 5% and delivered an economic advantage of 7.5%. Additional field studies showed that predators and parasitoids of the main rice pests, together with detritivores, were more abundant in the presence of nectar-producing plants. We conclude that a simple diversification approach, in this case the growth of nectar-producing plants, can contribute to the ecological intensification of agricultural systems. PMID:27249349

  4. PREDICTING SPATIAL VARIATION OF CROP YIELD ACROSS A LANDSCAPE USING AGGREGATED ENVIRONMENTAL DATA

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Crop yield variability is an important attribute of agroecological systems. For decision-makers to make informed choices, it is necessary to understand spatial distribution of yield variability across landscapes. Spatial patterns of yield variability are associated with underlying environmental vari...

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

    The impact of soil nutrient depletion on crop production has been known for decades, but robust assessments of the impact of increasingly unbalanced nitrogen (N) and phosphorus (P) application rates on crop production are lacking. Here, we use crop response functions based on 741 FAO maize crop trials and EPIC crop modeling across Africa to examine maize yield deficits resulting from unbalanced N:P applications under low, medium, and high input scenarios, for past (1975), current, and future N:P mass ratios of respectively, 1:0.29, 1:0.15, and 1:0.05. At low N inputs (10 kg/ha), current yield deficits amount to 10% but will increase up to 27% under the assumed future N:P ratio, while at medium N inputs (50 kg N/ha), future yield losses could amount to over 40%. The EPIC crop model was then used to simulate maize yields across Africa. The model results showed relative median future yield reductions at low N inputs of 40%, and 50% at medium and high inputs, albeit with large spatial variability. Dominant low-quality soils such as Ferralsols, which are strongly adsorbing P, and Arenosols with a low nutrient retention capacity, are associated with a strong yield decline, although Arenosols show very variable crop yield losses at low inputs. Optimal N:P ratios, i.e. those where the lowest amount of applied P produces the highest yield (given N input) where calculated with EPIC to be as low as 1:0.5. Finally, we estimated the additional P required given current N inputs, and given N inputs that would allow Africa to close yield gaps (ca. 70%). At current N inputs, P consumption would have to increase 2.3-fold to be optimal, and to increase 11.7-fold to close yield gaps. The P demand to overcome these yield deficits would provide a significant additional pressure on current global extraction of P resources.

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

    PubMed

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

    2014-04-01

    The impact of soil nutrient depletion on crop production has been known for decades, but robust assessments of the impact of increasingly unbalanced nitrogen (N) and phosphorus (P) application rates on crop production are lacking. Here, we use crop response functions based on 741 FAO maize crop trials and EPIC crop modeling across Africa to examine maize yield deficits resulting from unbalanced N : P applications under low, medium, and high input scenarios, for past (1975), current, and future N : P mass ratios of respectively, 1 : 0.29, 1 : 0.15, and 1 : 0.05. At low N inputs (10 kg ha(-1)), current yield deficits amount to 10% but will increase up to 27% under the assumed future N : P ratio, while at medium N inputs (50 kg N ha(-1)), future yield losses could amount to over 40%. The EPIC crop model was then used to simulate maize yields across Africa. The model results showed relative median future yield reductions at low N inputs of 40%, and 50% at medium and high inputs, albeit with large spatial variability. Dominant low-quality soils such as Ferralsols, which are strongly adsorbing P, and Arenosols with a low nutrient retention capacity, are associated with a strong yield decline, although Arenosols show very variable crop yield losses at low inputs. Optimal N : P ratios, i.e. those where the lowest amount of applied P produces the highest yield (given N input) where calculated with EPIC to be as low as 1 : 0.5. Finally, we estimated the additional P required given current N inputs, and given N inputs that would allow Africa to close yield gaps (ca. 70%). At current N inputs, P consumption would have to increase 2.3-fold to be optimal, and to increase 11.7-fold to close yield gaps. The P demand to overcome these yield deficits would provide a significant additional pressure on current global extraction of P resources. PMID:24470387

  7. Assessing the Impact of Climate Change on Columbia River Basin Agriculture through Integrated Crop Systems, Hydrologic, and Water Management Modeling

    NASA Astrophysics Data System (ADS)

    Rajagopalan, K.; Chinnayakanahalli, K.; Adam, J. C.; Barber, M. E.; Yorgey, G.; Stockle, C.; Nelson, R.; Brady, M.; Dinesh, S.; Malek, K.; Kruger, C.; Yoder, J.; Marsh, T.

    2011-12-01

    rights data as well as instream flow requirements are incorporated to inform water allocation and curtailment decisions. This modeling framework is applied over the 1976-2006 period and compared to a future 30-year period centered on the 2030s. Impacts of climate change on irrigation water availability, crop irrigation demand, frequency of curtailment, and crop yields are quantified and presented. Development of this modeling framework is part of a larger effort to develop a regional-scale earth system model, "BioEarth". The goal of BioEarth is to understand the interactions between land use and water and nutrient cycling under decadal-scale climate variability to inform decisions related to agricultural and natural resources management.

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

    PubMed

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

    2003-01-01

    The genetic consequences of radioactive contamination by the fallout to agricultural crops after the accident at the Chernobyl NPP in 1986 have been studied. In the first, acute, period of this accident, when the absorbed dose was primarily due to external beta- and gamma-irradiation, the radiation injury of agricultural crops, according to the basic cytogenetic tests, resembled the effect produced by acute gamma-irradiation at comparable doses. The yield of cytogenetic damage in leaf meristem of plants grown in the 10-km zone of the ChNPP in 1987-1989 (the period of chronic, lower level radiation exposure) was shown to be enhanced and dependent on the level of radioactive contamination. The rate of decline with time in cytogenetic damage induced by chronic exposure lagged considerably behind that of the radiation exposure. Analysis of genetic variability in three sequential generations of rye and wheat revealed increased cytogenetic damage in plants exposed to chronic irradiation during the 2nd and 3rd years. PMID:12590075

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

    PubMed

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

    2016-01-01

    The covariability of temperature (T), precipitation (P) and radiation (R) is an important aspect in understanding the climate influence on crop yields. Here, we analyze county-level corn and soybean yields and observed climate for the period 1983-2012 to understand how growing-season (June, July and August) mean T, P and R influence crop yields jointly and in isolation across the CONterminous United States (CONUS). Results show that nationally averaged corn and soybean yields exhibit large interannual variability of 21% and 22%, of which 35% and 32% can be significantly explained by T and P, respectively. By including R, an additional of 5% in variability can be explained for both crops. Using partial regression analyses, we find that studies that ignore the covariability among T, P, and R can substantially overestimate the sensitivity of crop yields to a single climate factor at the county scale. Further analyses indicate large spatial variation in the relative contributions of different climate variables to the variability of historical corn and soybean yields. The structure of the dominant climate factors did not change substantially over 1983-2012, confirming the robustness of the findings, which have important implications for crop yield prediction and crop model validations. PMID:27616326

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  12. Impacts of humic product application on yields of potato and other field crops

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Commercial humic products are extracts from organic materials, including immature coals (lignite, leonardite) and composted plant residues. Their application to field crops has been claimed to promote increased crop growth and economic yield, although little published evidence exists. In two indepen...

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  16. Water and nutrient deficits, crop yields, and climate change

    SciTech Connect

    Reddy, K.R.; Reddy, A.R.; Hodges, H.F.; McKinion, J.M.

    1997-12-31

    Plant responses to rising CO{sub 2} environments have been largely determined in nearly optimum conditions for growth. In many studies, the nature of the experiment allowed only limited or no control of environmental factors other than [CO{sub 2}]. Here, we report the results from cotton plants grown in naturally-lit chambers in which temperature, [CO{sub 2}], water, and nutrients were controlled and varied systematically. Photosynthesis and transpiration of crop canopies were measured continuously.

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

    NASA Technical Reports Server (NTRS)

    Wagstaff, Kiri L.; Lane, Terran

    2010-01-01

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

  18. Relationship between grain crop yield potential and nitrogen response

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Cereal grain fertilizer nitrogen (N) recommendations should conform to accepted theory. The objective of this study was to evaluate the relationship between yield potential (yield level) and N responsiveness in long-term winter wheat (Triticum aestivum L.) and maize (Zea mays L.) field experiments ...

  19. Prediction of crop yield in Sweden based on mesoscale meteorological analysis

    NASA Astrophysics Data System (ADS)

    Foltescu, Valentin L.

    2000-12-01

    This paper presents a prediction system for regional crop growth in Sweden, recently set up at SMHI (Swedish Meteorological and Hydrological Institute). The system includes a state-of-the-art crop growth model, WOFOST (WOrld FOod STudies) and inputs from meteorological mesoscale analysis. The simulated crops are spring barley, spring rape, oats and winter wheat, and the period of investigation is 1985-98. The simulated water-limited grain yield is used as a predictor in the yield prediction procedure. The technological time trend describing the yearly increase of the production level is accounted for as well. Yield prediction based on crop growth modelling is justified since the ability to forecast the yield is higher compared to that using the technological time trend alone. The prediction errors are of the order of 8 to 16%, with the lowest errors for winter wheat and spring barley.

  20. Vegetation dynamics using AVHRR/NDVI: Regional climate, carbon dioxide fertilization and crop yield relations

    NASA Astrophysics Data System (ADS)

    Lim, Chai Kyung

    Vegetation Anomaly Index (VAI), which is not influenced by vegetation type and is almost perfectly correlated with spatially averaged NDVI over any eco-region. Finally, we examined a possibility of utilizing NDVI to forecast crop yield and crop market price. We found that National Agricultural Statistics Service (MASS) corn yield estimate for Iowa and August NDVI averaged over the selected counties of Iowa are fairly well correlated for the past two decades. The Iowa corn market price is better correlated with NASS yield estimate than the average August NDVI over the counties; however, the correlation is more stable with NDVI than the NASS estimates, which indicates a great possibility of utilizing NDVI to forecast crop related access by USDA.

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

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

  4. 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.

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

    PubMed

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

    2014-01-01

    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 Niño/Southern Oscillation (ENSO) often affects seasonal temperature and precipitation, and thus crop yields in many regions, the overall impacts of ENSO on global yields are uncertain. Here we present a global map of the impacts of ENSO on the yields of major crops and quantify its impacts on their global-mean yield anomalies. Results show that El Niño likely improves the global-mean soybean yield by 2.1-5.4% but appears to change the yields of maize, rice and wheat by -4.3 to +0.8%. The global-mean yields of all four crops during La Niña years tend to be below normal (-4.5 to 0.0%). Our findings highlight the importance of ENSO to global crop production. PMID:24827075

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

    PubMed Central

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

    2015-01-01

    Ecological intensification has been promoted as a means to achieve environmentally sustainable increases in crop yields by enhancing ecosystem functions that regulate and support production. There is, however, little direct evidence of yield benefits from ecological intensification on commercial farms growing globally important foodstuffs (grains, oilseeds and pulses). We replicated two treatments removing 3 or 8% of land at the field edge from production to create wildlife habitat in 50–60 ha patches over a 900 ha commercial arable farm in central England, and compared these to a business as usual control (no land removed). In the control fields, crop yields were reduced by as much as 38% at the field edge. Habitat creation in these lower yielding areas led to increased yield in the cropped areas of the fields, and this positive effect became more pronounced over 6 years. As a consequence, yields at the field scale were maintained—and, indeed, enhanced for some crops—despite the loss of cropland for habitat creation. These results suggested that over a 5-year crop rotation, there would be no adverse impact on overall yield in terms of monetary value or nutritional energy. This study provides a clear demonstration that wildlife-friendly management which supports ecosystem services is compatible with, and can even increase, crop yields. PMID:26423846

  7. Comparison of perimeter trap crop varieties: effects on herbivory, pollination, and yield in butternut squash.

    PubMed

    Adler, L S; Hazzard, R V

    2009-02-01

    Perimeter trap cropping (PTC) is a method of integrated pest management (IPM) in which the main crop is surrounded with a perimeter trap crop that is more attractive to pests. Blue Hubbard (Cucurbita maxima Duch.) is a highly effective trap crop for butternut squash (C. moschata Duch. ex Poir) attacked by striped cucumber beetles (Acalymma vittatum Fabricius), but its limited marketability may reduce adoption of PTC by growers. Research comparing border crop varieties is necessary to provide options for growers. Furthermore, pollinators are critical for cucurbit yield, and the effect of PTC on pollination to main crops is unknown. We examined the effect of five border treatments on herbivory, pollination, and yield in butternut squash and manipulated herbivory and pollination to compare their importance for main crop yield. Blue Hubbard, buttercup squash (C. maxima Duch.), and zucchini (C. pepo L.) were equally attractive to cucumber beetles. Border treatments did not affect butternut leaf damage, but butternut flowers had the fewest beetles when surrounded by Blue Hubbard or buttercup squash. Yield was highest in the Blue Hubbard and buttercup treatments, but this effect was not statistically significant. Native bees accounted for 87% of pollinator visits, and pollination did not limit yield. There was no evidence that border crops competed with the main crop for pollinators. Our results suggest that both buttercup squash and zucchini may be viable alternatives to Blue Hubbard as borders for the main crop of butternut squash. Thus, growers may have multiple border options that reduce pesticide use, effectively manage pests, and do not disturb mutualist interactions with pollinators. PMID:19791616

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

    DOE PAGESBeta

    Dalal, Jyoti; Lopez, Harry; Vasani, Naresh B.; Hu, Zhaohui; Swift, Jennifer E.; Yalamanchili, Roopa; Dvora, Mia; Lin, Xiuli; Xie, Deyu; Qu, Rongda; et al

    2015-10-29

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

  9. Dryland crop yields and soil organic matter as influenced by long-term tillage and cropping sequence

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Long-term management practices are needed to sustain dryland crop yields and maintain soil organic matter in the northern Great Plains. We evaluated the 21-yr effects of no-till continuous spring wheat (NTCW), spring till continuous spring wheat (STCW), fall and spring till continuous spring wheat (...

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

    PubMed

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

    2016-04-01

    The production of genetically modified (GM) crops is growing around the world, and with it possible opportunities to combat food insecurity and hunger, as well as solutions to current problems facing conventional agriculture. In this regard the use of GMOs in food and agricultural applications has increased greatly over the past decade. However, the development of GM crops has been a matter of considerable interest and worldwide public controversy. This, in addition to skepticism, has stifled the use of this practice on a large scale in many areas, including Iran. It stands to reason that a greater understanding of this practice could be formed after a review of the existing expert opinions surrounding GM crops. Therefore, the purpose of this study was to analyze the predictors that influence agricultural experts' attitudes toward the development of and policies related to GM crops. Using a descriptive correlational research method, questionnaire data was collected from 65 experts from the Agricultural Organization in the Gotvand district in Southwest Iran. Results indicated that agricultural experts were aware of the environmental benefits and possible risks associated with GM crops. The majority of participants agreed that GM crops could improve food security and accelerate rural development, and were proponents of labeling practices for GM crops. Finally, there was a positive correlation between the perception of benefits and attitudes towards GM crops. PMID:26045394

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

    PubMed

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

    2015-06-01

    Warming winters due to climate change may critically affect temperate tree species. Insufficiently cold winters are thought to result in fewer viable flower buds and the subsequent development of fewer fruits or nuts, decreasing the yield of an orchard or fecundity of a species. The best existing approximation for a threshold of sufficient cold accumulation, the "chilling requirement" of a species or variety, has been quantified by manipulating or modeling the conditions that result in dormant bud breaking. However, the physiological processes that affect budbreak are not the same as those that determine yield. This study sought to test whether budbreak-based chilling thresholds can reasonably approximate the thresholds that affect yield, particularly regarding the potential impacts of climate change on temperate tree crop yields. County-wide yield records for almond (Prunus dulcis), pistachio (Pistacia vera), and walnut (Juglans regia) in the Central Valley of California were compared with 50 years of weather records. Bayesian nonparametric function estimation was used to model yield potentials at varying amounts of chill accumulation. In almonds, average yields occurred when chill accumulation was close to the budbreak-based chilling requirement. However, in the other two crops, pistachios and walnuts, the best previous estimate of the budbreak-based chilling requirements was 19-32 % higher than the chilling accumulations associated with average or above average yields. This research indicates that physiological processes beyond requirements for budbreak should be considered when estimating chill accumulation thresholds of yield decline and potential impacts of climate change. PMID:25119825

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

    NASA Astrophysics Data System (ADS)

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

    2015-06-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

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

    SciTech Connect

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

    2007-10-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-05-01

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

  16. Crop Insurance Increases Water Withdrawals for Irrigation in Agriculture

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

  18. Soil properties, greenhouse gas emissions and crop yield under compost, biochar and co-composted biochar in two tropical agronomic systems.

    PubMed

    Bass, Adrian M; Bird, Michael I; Kay, Gavin; Muirhead, Brian

    2016-04-15

    The addition of organic amendments to agricultural soils has the potential to increase crop yields, reduce dependence on inorganic fertilizers and improve soil condition and resilience. We evaluated the effect of biochar (B), compost (C) and co-composted biochar (COMBI) on the soil properties, crop yield and greenhouse gas emissions from a banana and a papaya plantation in tropical Australia in the first harvest cycle. Biochar, compost and COMBI organic amendments improved soil properties, including significant increases in soil water content, CEC, K, Ca, NO3, NH4 and soil carbon content. However, increases in soil nutrient content and improvements in physical properties did not translate to improved fruit yield. Counter to our expectations, banana crop yield (weight per bunch) was reduced by 18%, 12% and 24% by B, C and COMBI additions respectively, and no significant effect was observed on the papaya crop yield. Soil efflux of CO2 was elevated by addition of C and COMBI amendments, likely due to an increase in labile carbon for microbial processing. Our data indicate a reduction in N2O flux in treatments containing biochar. The application of B, C and COMBI amendments had a generally positive effect on soil properties, but this did not translate into a crop productivity increase in this study. The benefits to soil nutrient content, soil carbon storage and N2O emission reduction need to be carefully weighed against potentially deleterious effects on crop yield, at least in the short-term. PMID:26845182

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

    NASA Astrophysics Data System (ADS)

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

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

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

    SciTech Connect

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

    1980-10-01

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

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

    PubMed

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

    2014-01-01

    Plant growth-promoting rhizobacteria (PGPR) are free-living bacteria which actively colonize plant roots, exerting beneficial effects on plant development. The PGPR may (i) promote the plant growth either by using their own metabolism (solubilizing phosphates, producing hormones or fixing nitrogen) or directly affecting the plant metabolism (increasing the uptake of water and minerals), enhancing root development, increasing the enzymatic activity of the plant or "helping" other beneficial microorganisms to enhance their action on the plants; (ii) or may promote the plant growth by suppressing plant pathogens. These abilities are of great agriculture importance in terms of improving soil fertility and crop yield, thus reducing the negative impact of chemical fertilizers on the environment. The progress in the last decade in using PGPR in a variety of plants (maize, rice, wheat, soybean and bean) along with their mechanism of action are summarized and discussed here. PMID:24144612

  2. Uncertainties in Predicting Rice Yield by Current Crop Models Under a Wide Range of Climatic Conditions

    NASA Technical Reports Server (NTRS)

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

    2014-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  5. Transgenic Crops and Sustainable Agriculture in the European Context

    ERIC Educational Resources Information Center

    Ponti, Luigi

    2005-01-01

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

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  7. Nematode Numbers and Crop Yield in a Fenamiphos-Treated Sweet Corn-Sweet Potato-Vetch Cropping System

    PubMed Central

    Johnson, A. W.; Dowler, C. C.; Glaze, N. C.; Chalfant, R. B.; Golden, A. M.

    1992-01-01

    Nematode population densities and yield of sweet corn and sweet potato as affected by the nematicide fenamiphos, in a sweet corn-sweet potato-vetch cropping system, were determined in a 5-year test (1981-85). Sweet potato was the best host of Meloidogyne incognita of these three crops. Fenamiphos 15G (6.7 kg a.i./ha) incorporated broadcast in the top 15 cm of the soil layer before planting of each crop increased (P ≤ 0.05) yields of sweet corn in 1981 and 1982 and sweet potato number 1 grade in 1982 and 1983. Yield of sweet corn and numbers of M. incognita second-stage juveniles (J2) in the soil each month were negatively correlated from planting (r = - 0.47) to harvest (r = -0.61) in 1982. Yield of number 1 sweet potato was inversely related to numbers of J2 in the soil in July-October 1982 and July-September 1983. Yield of cracked storage roots was positively related to the numbers of J2 in the soil on one or more sampling dates in all years except 1985. Some factor(s), such as microbial degradation, resistant M. incognita development, or environment, reduced the effect of fenamiphos. PMID:19283032

  8. Nematode numbers and crop yield in a fenamiphos-treated sweet corn-sweet potato-vetch cropping system.

    PubMed

    Johnson, A W; Dowler, C C; Glaze, N C; Chalfant, R B; Golden, A M

    1992-12-01

    Nematode population densities and yield of sweet corn and sweet potato as affected by the nematicide fenamiphos, in a sweet corn-sweet potato-vetch cropping system, were determined in a 5-year test (1981-85). Sweet potato was the best host of Meloidogyne incognita of these three crops. Fenamiphos 15G (6.7 kg a.i./ha) incorporated broadcast in the top 15 cm of the soil layer before planting of each crop increased (P yields of sweet corn in 1981 and 1982 and sweet potato number 1 grade in 1982 and 1983. Yield of sweet corn and numbers of M. incognita second-stage juveniles (J2) in the soil each month were negatively correlated from planting (r = - 0.47) to harvest (r = -0.61) in 1982. Yield of number 1 sweet potato was inversely related to numbers of J2 in the soil in July-October 1982 and July-September 1983. Yield of cracked storage roots was positively related to the numbers of J2 in the soil on one or more sampling dates in all years except 1985. Some factor(s), such as microbial degradation, resistant M. incognita development, or environment, reduced the effect of fenamiphos. PMID:19283032

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    EPA Science Inventory

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  12. Crop yield monitoring based on a photosynthetic sterility model using NDVI and daily meteorological data

    NASA Astrophysics Data System (ADS)

    Kaneko, Daijiro

    2007-10-01

    This research is intended to develop a model to monitor rice yields using the photosynthetic yield index, which integrates solar radiation and air temperature effects on photosynthesis and grain-filling from heading to ripening. Monitoring crop production using remotely sensed and daily meteorological data can provide an important early warning of poor crop production to Asian countries, with their still-growing populations, and also to Japan, which produces insufficient grain for its population. The author improved a photosynthesis-and-sterility-based crop production CPI index to crop yield index CYI, which estimates rice yields, in place of the crop situation index CSI. The CSI gives a percentage of rice yields compared to normal annual production. The model calculates photosynthesis rates including biomass effects, lowtemperature sterility, and high-temperature injury by incorporating: solar radiation, effective air temperature, normalized difference vegetation index NDVI, and the effect of temperature on photosynthesis by grain plant leaves. The method is based on routine observation data, enabling automated monitoring of crop production at arbitrary regions without special observations. The method aims to quantity grain production at an early stage to raise the alarm in Asian countries, which are facing climate fluctuation through this century of global warming.

  13. Seeing is believing I: The use of thermal sensing from satellite imagery to predict crop yield

    NASA Astrophysics Data System (ADS)

    B, Potgieter A.; D, Rodriguez; B, Power; J, Mclean; P, Davis

    2014-02-01

    Volatility in crop production has been part of the Australian environment since cropping began with the arrival of the first European settlers. Climate variability is the main factor affecting crop production at national, state and local scales. At field level spatial patterns on yield production are also determined by spatially changing soil properties in interaction with seasonal climate conditions and weather patterns at critical stages in the crop development. Here we used a combination of field level weather records, canopy characteristics, and satellite information to determine the spatial performance of a large field of wheat. The main objective of this research is to determine the ability of remote sensing technologies to capture yield losses due to water stress at the canopy level. The yield, canopy characteristics (i.e. canopy temperature and ground cover) and seasonal conditions of a field of wheat (~1400ha) (-29.402° South and 149.508°, New South Wales, Australia) were continuously monitored during the winter of 2011. Weather and crop variables were continuously monitored by installing three automatic weather stations in a transect covering different positions and soils in the landscape. Weather variables included rainfall, minimum and maximum temperatures and relative humidity, and crop characteristics included ground cover and canopy temperature. Satellite imagery Landsat TM 5 and 7 was collected at five different stages in the crop cycle. Weather variables and crop characteristics were used to calculate a crop stress index (CSI) at point and field scale (39 fields). Field data was used to validate a spatial satellite image derived index. Spatial yield data was downloaded from the harvester at the different locations in the field. We used the thermal band (land surface temperature, LST) and enhanced vegetation index (EVI) bands from the MODIS (250 m for visible bands and 1km for thermal band) and a derived EVI from Landsat TM 7 (25 m for visible and

  14. Scale-dependent effects of landscape composition and configuration on natural enemy diversity, crop herbivory, and yields.

    PubMed

    Martin, Emily A; Seo, Bumsuk; Park, Chan-Ryul; Reineking, Björn; Steffan-Dewenter, Ingolf

    2016-03-01

    (1) Land-use intensification in agricultural landscapes has led to changes in the way habitats and resources are distributed in space. Pests and their natural enemies are influenced by these changes, and by the farming intensity of crop fields. However, it is unknown whether the composition of landscapes (amount and diversity of land cover types) or their configuration (spatial arrangement of cover types) are more important for natural enemy diversity, and how they impact crop damage and yields. In addition, effects of interactions between local farming practices (organic vs. conventional) and landscape variables are unclear. (2) Here, we make use of a data set where landscape composition and configuration were uncorrelated across multiple spatial scales. Natural enemies, crop damage, and yields were sampled in 35 organic and conventional crop fields. Out of seven broad natural enemy taxa, five were positively affected by a complex landscape configuration. In contrast, only carabids were positively affected by the amount of seminatural habitat around fields. Increasing diversity of land cover types had positive effects on some, but negative effects on other taxa. Effect sizes varied among taxa but increased with increasing spatial scale, defined by circular areas of increasing radius around fields. (3) The diversity of aerial, but not of ground-dwelling enemies was higher in fields under organic than conventional management. Interactions of local and landscape variables were important for birds, but not other enemies. Bird richness was higher in organic fields in simple landscapes, but not in landscapes with complex configuration or high land cover diversity. (4) Crop damage decreased with landscape diversity, but increased in conventional fields with complex configuration. Yields increased with both parameters in conventional fields only, and were higher on average in organic compared to conventional fields. Enemy diversity was positively related to crop damage

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

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

    SciTech Connect

    Tolbert, V.R.; Schiller, A.

    1995-12-31

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

  17. Increased area of a highly suitable host crop increases herbivore pressure in intensified agricultural landscapes

    Technology Transfer Automated Retrieval System (TEKTRAN)

    tLandscape simplification associated with agricultural intensification has important effects on economi-cally important arthropods. The declining cover of natural and semi-natural habitats, in particular, hasbeen shown to reduce natural-enemy attack of crop pests, but also in some cases reduced crop...

  18. Biochar application to temperate soils - effects on soil fertility and crop yield

    NASA Astrophysics Data System (ADS)

    Kloss, S.; Zehetner, F.; Feichtmair, S.; Wimmer, B.; Zechmeister-Boltenstern, S.; Kitzler, B.; Watzinger, A.; Soja, G.

    2012-04-01

    Biochar (BC) application to soil as a potential soil amendment is currently intensively explored. Depending on feedstock and highest treatment temperature (HTT), BC application to soil may contribute to the soil nutrient status by directly adding nutrients to the soil as well as by increasing pH, cation exchange and water holding capacity. These parameters are known to play an important role in the soil nutrient status and nutrient availability. A positive effect on plant growth after BC application to tropical soils has been observed repeatedly; however, the effect of BC application to soils in temperate climate regions is much less explored. We investigated the effect of BC to temperate soils and crop yield using a randomized pot experiment in a greenhouse with three agricultural soils (Planosol, Cambisol, Chernozem) and four BC types (from straw, mixed woodchips and vineyard pruning, all pyrolyzed at 525°C). In order to analyze the effect of pyrolysis temperature, we additionally applied vineyard pruning BC pyrolyzed at 400°C. Selected treatments were planted with mustard (Sinapis alba L.), followed by barley (Hordeum vulgare). Soil sampling was carried out after barley harvest. Investigated soil parameters included pH, electrical conductivity (EC), C/N ratio, cation exchange capacity (CEC), CAL-extractable P and K, EDTA extractable Cu, Fe, Mn, Zn as well as nitrogen supplying potential (NSP). Biomass production of the two crops was determined as well as its elemental composition. Biochar application (3% wood-based BC) caused a considerable pH increase for the acidic Planosol. The effect of BC application on CEC was dependent on the original status of the soil, notably soil pH and texture. 3 % BC application (wood) decreased CEC by 3.5 % and 10 % for the Chernozem and Cambisol, respectively, but increased CEC by 35 % for the acidic, sandy Planosol, which may be due to the strong liming effect found for the Planosol. BC application significantly raised CAL

  19. Impact of bioenergy crops on pests, natural enemies and pollinators in agricultural and non-crop landscapes

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Sustainability of the nation's bioenergy feedstock production relies on selection and placement of energy crops that efficiently generate biomass or oilseed without compromising existing agricultural or natural systems. Pest and beneficial arthropods (e.g., pollinators, predators) will occur in thes...

  20. Impact of different cover crop residues and shank types on no-till tomato yield

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A three year experiment with no-till tomatoes was conducted in Cullman, AL (2006 to 2008) to determine the effect of plastic mulch (control), rye and crimson clover cover crops, and different subsoiler shanks on no–till tomato yield. In 2006 and 2008, plastic cover provided higher yield compared wit...

  1. Evaluating high resolution SPOT 5 satellite imagery for crop yield estimation

    Technology Transfer Automated Retrieval System (TEKTRAN)

    High resolution satellite imagery has the potential for mapping within-field variability in crop growth and yield. This study examined SPOT 5 multispectral imagery for estimating grain sorghum yield. A SPOT 5 image with 10-m spatial resolution and four spectral bands (green, red, near-infrared, and ...

  2. Dryland malt barley yield and quality affected by tillage, cropping sequence, and nitrogen fertilization

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Information is needed on the effects of management practices on dryland malt barley (Hordeum vulgaris L.) and pea (Pisum sativum L.) yields and quality. We evaluated the effects of tillage and cropping sequence combination and N fertilization on dryland malt barley and pea yields, grain characterist...

  3. MODELING THE IMPACT OF OZONE X DROUGHT INTERACTIONS ON REGIONAL CROP YIELDS (JOURNAL VERSION)

    EPA Science Inventory

    The influence of soil moisture stress on crop sensitivity to O3 was evaluated for corn, cotton, soybean, and wheat grown in the United States by using yield forecasting models to estimate the influence of soil moisture deficits on regional yield and a previously developed model t...

  4. Use of aggregated environment data to predict spatial variation of crop yields across a landscape

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Crop yield variability is effected by environmental heterogeneity at various scales. “Scaling-up” of locally-derived process-based models has not been universally successful in accurately modeling patterns of yield association with environmental characteristics at broader spatial scales. Use of re...

  5. Assessment of crop productivity over intensively managed agriculture regions in India and Australia using solar-induced fluorescence remote sensing data

    NASA Astrophysics Data System (ADS)

    Devadas, R.; Huete, A. R.; Patel, N. R.; Padalia, H.; Restrepo-Coupe, N.; Kuruvilla, A.

    2015-12-01

    Satellite based estimation of solar-induced terrestrial fluorescence (SIF) is considered to be a direct measure of photosynthetic functional status of the vegetation. Prior studies have shown SIF to more accurately retrieve the productivity of intensively managed croplands, as in the U.S. corn belt. In this study, we assessed and compared agricultural productivity over two intensive crop production regions in Australia and India using SIF data, traditional spectral measures, and crop yield data. Regional level wheat yield data were obtained for the Indo-Gangetic Plains (IGP) in India and the Murray Darling Basin (MDB) in Australia for analyses with GOME-2 SIF satellite and MODIS VI measurements, and gross primary productivity from flux towers. We investigated the importance of integrating traditional meteorological parameters and ground based data with time-series vegetation indices for scaling of SIF to obtain robust yield prediction models for application across years and continents. This study further explored the relationship of inter annual variations in crop phenology metrics through SIF retrievals and its relationship with crop yields. The IGP study region showed systematic cycles of double cropping. MDB region on the other hand showed cycles of pronounced winter cropping and a weaker and variable second cropping over the analysis period. For various winter wheat crop seasons in IGP, from 2007 to 2012, SIF explained and accounted between 48 to 74 per cent of the variations in regional wheat yields. Similar results were obtained in the case of MDB also, however, the relationship between SIF and yield estimates was weaker (R2 = 0.44). SIF measurements, as a surrogate of crop productivity, were considerably higher over the highly productive IGP region in almost all the years considered. The SIF data shows immense potential for modelling agricultural productivity, particularly as the resolution of SIF retrievals continues to improve.

  6. Estimated winter wheat yield from crop growth predicted by LANDSAT

    NASA Technical Reports Server (NTRS)

    Kanemasu, E. T.

    1977-01-01

    An evapotranspiration and growth model for winter wheat is reported. The inputs are daily solar radiation, maximum temperature, minimum temperature, precipitation/irrigation and leaf area index. The meteorological data were obtained from National Weather Service while LAI was obtained from LANDSAT multispectral scanner. The output provides daily estimates of potential evapotranspiration, transpiration, evaporation, soil moisture (50 cm depth), percentage depletion, net photosynthesis and dry matter production. Winter wheat yields are correlated with transpiration and dry matter accumulation.

  7. The Economic Impact of Climate, CO2, and Tropospheric Ozone Effects on Crop Yields in China, the US, and Europe

    NASA Astrophysics Data System (ADS)

    Reilly, J. M.; Felzer, B. S.; Paltsev, S.; Melillo, J. M.; Prinn, R. G.; Wang, C.; Sokolov, A. P.; Wang, X.

    2004-12-01

    Multiple environmental changes that may occur over the next century will affect crop productivity. Some of these effects are likely to be positive (CO2 fertilization), some negative (tropospheric ozone damage), and some may be either positive or negative (temperature and precipitation). Climate effects may operate in either direction because the direction of change may differ across regions (more precipitation in some areas and less in others) and warming may increase growing season lengths in cold-limited growing areas while acting as a detriment to productivity in areas with already high temperatures. Previous work has shown the effects of these combined environmental changes on carbon sequestration in natural and managed systems, and valued these effects in terms of avoided costs of fossil fuel carbon abatement. The more direct and obvious economic effect, however, is the changes in crop yields implied by these vegetation effects. Here we use the MIT Integrated Global Systems Model (IGSM) to analyze the potential economic impact of changes in crop yields. For this work we have augmented the Emissions Prediction and Policy Analysis (EPPA) model by further disaggregating the agricultural sector. This allows us to simulate economic effects of changes in yield (i.e. the productivity of cropland) on the regional economies of the world, including impacts on agricultural trade. The EPPA model includes multiple channels of market-based adaptation, including input substitution and trade. We are thus able to examine the extent to which market forces contribute toward adaptation and thus modify the initial yield effects. We examine multiple scenarios where tropospheric ozone precursors are controlled or not, and where greenhouse gas emissions are abated or not. This allows us to consider how these policies interact. We focus on China, the US, and Europe which are currently regions with high levels of tropospheric ozone damage. We find significant negative effects of

  8. Effects of Break Crops on Yield and Grain Protein Concentration of Barley in a Boreal Climate

    PubMed Central

    Zou, Ling; Yli-Halla, Markku; Stoddard, Frederick L.; Mäkelä, Pirjo S. A.

    2015-01-01

    Rotation with dicotyledonous crops to break cereal monoculture has proven to be beneficial to successive cereals. In two fields where the soil had been subjected to prolonged, continuous cereal production, two 3-year rotation trials were established. In the first year, faba bean, turnip rape and barley were grown, as first crops, in large blocks and their residues tilled into the soil after harvest. In the following year, barley, buckwheat, caraway, faba bean, hemp and white lupin were sown, as second crops, in each block and incorporated either at flowering stage (except barley) or after harvest. In the third year, barley was grown in all plots and its yield and grain protein concentration were determined. Mineral N in the plough layer was determined two months after incorporation of crops and again before sowing barley in the following year. The effect of faba bean and turnip rape on improving barley yields and grain protein concentration was still detectable two years after they were grown. The yield response of barley was not sensitive to the growth stage of second crops when they were incorporated, but was to different second crops, showing clear benefits averaging 6-7% after white lupin, faba bean and hemp but no benefit from caraway or buckwheat. The effect of increased N in the plough layer derived from rotation crops on barley yields was minor. Incorporation of plants at flowering stage slightly increased third-year barley grain protein concentration but posed a great potential for N loss compared with incorporation of crop residues after harvest, showing the value of either delayed incorporation or using catch crops. PMID:26076452

  9. Effects of Break Crops on Yield and Grain Protein Concentration of Barley in a Boreal Climate.

    PubMed

    Zou, Ling; Yli-Halla, Markku; Stoddard, Frederick L; Mäkelä, Pirjo S A

    2015-01-01

    Rotation with dicotyledonous crops to break cereal monoculture has proven to be beneficial to successive cereals. In two fields where the soil had been subjected to prolonged, continuous cereal production, two 3-year rotation trials were established. In the first year, faba bean, turnip rape and barley were grown, as first crops, in large blocks and their residues tilled into the soil after harvest. In the following year, barley, buckwheat, caraway, faba bean, hemp and white lupin were sown, as second crops, in each block and incorporated either at flowering stage (except barley) or after harvest. In the third year, barley was grown in all plots and its yield and grain protein concentration were determined. Mineral N in the plough layer was determined two months after incorporation of crops and again before sowing barley in the following year. The effect of faba bean and turnip rape on improving barley yields and grain protein concentration was still detectable two years after they were grown. The yield response of barley was not sensitive to the growth stage of second crops when they were incorporated, but was to different second crops, showing clear benefits averaging 6-7% after white lupin, faba bean and hemp but no benefit from caraway or buckwheat. The effect of increased N in the plough layer derived from rotation crops on barley yields was minor. Incorporation of plants at flowering stage slightly increased third-year barley grain protein concentration but posed a great potential for N loss compared with incorporation of crop residues after harvest, showing the value of either delayed incorporation or using catch crops. PMID:26076452

  10. Mutually beneficial pollinator diversity and crop yield outcomes in small and large farms.

    PubMed

    Garibaldi, Lucas A; Carvalheiro, Luísa G; Vaissière, Bernard E; Gemmill-Herren, Barbara; Hipólito, Juliana; Freitas, Breno M; Ngo, Hien T; Azzu, Nadine; Sáez, Agustín; Åström, Jens; An, Jiandong; Blochtein, Betina; Buchori, Damayanti; Chamorro García, Fermín J; Oliveira da Silva, Fabiana; Devkota, Kedar; Ribeiro, Márcia de Fátima; Freitas, Leandro; Gaglianone, Maria C; Goss, Maria; Irshad, Mohammad; Kasina, Muo; Pacheco Filho, Alípio J S; Kiill, Lucia H Piedade; Kwapong, Peter; Parra, Guiomar Nates; Pires, Carmen; Pires, Viviane; Rawal, Ranbeer S; Rizali, Akhmad; Saraiva, Antonio M; Veldtman, Ruan; Viana, Blandina F; Witter, Sidia; Zhang, Hong

    2016-01-22

    Ecological intensification, or the improvement of crop yield through enhancement of biodiversity, may be a sustainable pathway toward greater food supplies. Such sustainable increases may be especially important for the 2 billion people reliant on small farms, many of which are undernourished, yet we know little about the efficacy of this approach. Using a coordinated protocol across regions and crops, we quantify to what degree enhancing pollinator density and richness can improve yields on 344 fields from 33 pollinator-dependent crop systems in small and large farms from Africa, Asia, and Latin America. For fields less than 2 hectares, we found that yield gaps could be closed by a median of 24% through higher flower-visitor density. For larger fields, such benefits only occurred at high flower-visitor richness. Worldwide, our study demonstrates that ecological intensification can create synchronous biodiversity and yield outcomes. PMID:26798016

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

    NASA Astrophysics Data System (ADS)

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

    2010-12-01

    Toshichika Iizumi, Masayuki Yokozawa, Gen Sakurai, Motoki Nishimori Agro-Meteorology Division, National Institute for Agro-Environmental Sciences, Japan Abstract One of concerning issues of food security under changing climate is to predict the inter-annual variation of crop production induced by climate extremes and modulated climate. To secure food supply for growing world population, methodology that can accurately predict crop yield on a large scale is needed. However, for developing a process-based large-scale crop model with a scale of general circulation models (GCMs), 100 km in latitude and longitude, researchers encounter the difficulties in spatial heterogeneity of available information on crop production such as cultivated cultivars and management. This study proposed an ensemble-based simulation method that uses a process-based crop model and systematic parameter perturbation procedure, taking maize in U.S., China, and Brazil as examples. The crop model was developed modifying the fundamental structure of the Soil and Water Assessment Tool (SWAT) to incorporate the effect of heat stress on yield. We called the new model PRYSBI: the Process-based Regional-scale Yield Simulator with Bayesian Inference. The posterior probability density function (PDF) of 17 parameters, which represents the crop- and grid-specific features of the crop and its uncertainty under given data, was estimated by the Bayesian inversion analysis. We then take 1500 ensemble members of simulated yield values based on the parameter sets sampled from the posterior PDF to describe yearly changes of the yield, i.e. perturbed-parameter ensemble method. The ensemble median for 27 years (1980-2006) was compared with the data aggregated from the county yield. On a country scale, the ensemble median of the simulated yield showed a good correspondence with the reported yield: the Pearson’s correlation coefficient is over 0.6 for all countries. In contrast, on a grid scale, the correspondence

  12. 7 CFR 1412.31 - Direct payment yields for covered commodities, except pulse crops.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... for covered commodities at part 1412 of this chapter in effect on January 1, 2008 (see 7 CFR part 1412... 7 Agriculture 10 2011-01-01 2011-01-01 false Direct payment yields for covered commodities, except... Establishment of Yields for Direct and Counter-Cyclical Payments § 1412.31 Direct payment yields for...

  13. 50 year trends in nitrogen use efficiency of world cropping systems: the relationship between yield and nitrogen input to cropland

    NASA Astrophysics Data System (ADS)

    Lassaletta, Luis; Billen, Gilles; Grizzetti, Bruna; Anglade, Juliette; Garnier, Josette

    2014-10-01

    Nitrogen (N) is crucial for crop productivity. However, nowadays more than half of the N added to cropland is lost to the environment, wasting the resource, producing threats to air, water, soil and biodiversity, and generating greenhouse gas emissions. Based on FAO data, we have reconstructed the trajectory followed, in the past 50 years, by 124 countries in terms of crop yield and total nitrogen inputs to cropland (manure, synthetic fertilizer, symbiotic fixation and atmospheric deposition). During the last five decades, the response of agricultural systems to increased nitrogen fertilization has evolved differently in the different world countries. While some countries have improved their agro-environmental performances, in others the increased fertilization has produced low agronomical benefits and higher environmental losses. Our data also suggest that, in general, those countries using a higher proportion of N inputs from symbiotic N fixation rather than from synthetic fertilizer have a better N use efficiency.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Information on the effect of long-term management on soil nutrients and chemical properties is scanty. We examined the 30-yr effect of tillage frequency and cropping sequence combination on dryland soil Olsen-P, K, Ca, Mg, Na, SO4-S, and Zn concentrations, pH, electrical conductivity (EC), and catio...

  15. Changes in water budgets and sediment yields from a hypothetical agricultural field as a function of landscape and management characteristics--A unit field modeling approach

    USGS Publications Warehouse

    Roth, Jason L.; Capel, Paul D.

    2012-01-01

    Crop agriculture occupies 13 percent of the conterminous United States. Agricultural management practices, such as crop and tillage types, affect the hydrologic flow paths through the landscape. Some agricultural practices, such as drainage and irrigation, create entirely new hydrologic flow paths upon the landscapes where they are implemented. These hydrologic changes can affect the magnitude and partitioning of water budgets and sediment erosion. Given the wide degree of variability amongst agricultural settings, changes in the magnitudes of hydrologic flow paths and sediment erosion induced by agricultural management practices commonly are difficult to characterize, quantify, and compare using only field observations. The Water Erosion Prediction Project (WEPP) model was used to simulate two landscape characteristics (slope and soil texture) and three agricultural management practices (land cover/crop type, tillage type, and selected agricultural land management practices) to evaluate their effects on the water budgets of and sediment yield from agricultural lands. An array of sixty-eight 60-year simulations were run, each representing a distinct natural or agricultural scenario with various slopes, soil textures, crop or land cover types, tillage types, and select agricultural management practices on an isolated 16.2-hectare field. Simulations were made to represent two common agricultural climate regimes: arid with sprinkler irrigation and humid. These climate regimes were constructed with actual climate and irrigation data. The results of these simulations demonstrate the magnitudes of potential changes in water budgets and sediment yields from lands as a result of landscape characteristics and agricultural practices adopted on them. These simulations showed that variations in landscape characteristics, such as slope and soil type, had appreciable effects on water budgets and sediment yields. As slopes increased, sediment yields increased in both the arid and

  16. A synthesis of AOT40-based response functions and critical levels of ozone for agricultural and horticultural crops

    NASA Astrophysics Data System (ADS)

    Mills, G.; Buse, A.; Gimeno, B.; Bermejo, V.; Holland, M.; Emberson, L.; Pleijel, H.

    Crop-response data from over 700 published papers and conference proceedings have been analysed with the aim of establishing ozone dose-response functions for a wide range of European agricultural and horticultural crops. Data that met rigorous selection criteria (e.g. field-based, ozone concentrations within European range, full season exposure period) were used to derive AOT40-yield response functions for 19 crops by first converting the published ozone concentration data into AOT40 (AOT40 is the hourly mean ozone concentration accumulated over a threshold ozone concentration of 40 ppb during daylight hours, units ppm h). For any individual crop, there were no significant differences in the linear response functions derived for experiments conducted in the USA or Europe, or for individual cultivars. Three statistically independent groups were identified: ozone sensitive crops (wheat, water melon, pulses, cotton, turnip, tomato, onion, soybean and lettuce); moderately sensitive crops (sugar beet, potato, oilseed rape, tobacco, rice, maize, grape and broccoli) and ozone resistant (barley and fruit represented by plum and strawberry). Critical levels of a 3 month AOT40 of 3 ppm h and a 3.5 month AOT40 of 6 ppm h were derived from the functions for wheat and tomato, respectively.

  17. Predicting the Impacts of Climate Change on Agricultural Yields and Water Resources in the Maumee River Watershed

    NASA Astrophysics Data System (ADS)

    Nagelkirk, R. L.; Kendall, A. D.; Basso, B.; Hyndman, D. W.

    2012-12-01

    Climate change will likely have considerable effects on agriculture in the Midwestern United States. Under current climate projections, end-of-century temperatures rise by approximately 4 C, while precipitation stays relatively unchanged despite a potential increase in heavy rainfall events. These trends have already been observed over the last century: rising temperatures have extended the growing season two days per decade and heavy rainfall events have become twice as common. In an effort to understand the likely effects of climate change on agriculture, maize and soybean yields in the Maumee River Watershed were simulated using the Systems Approach to Land Use Sustainability (SALUS) crop model. SALUS calculates daily crop growth in response to changing climate, soil, and management conditions. We test the hypotheses that 1) despite any positive effects of CO2 fertilization and allowing for higher yielding varieties, longer and warmer growing seasons will lead to excessive water- and heat-stress, lowering yields under current management practices, and 2) that double-cropping maize and soybeans successively in the same season to offset these losses may become feasible if sufficient late-season soil moisture is made available. Outputs of daily Leaf Area Index (LAI) and root mass from a range of SALUS models are then distributed spatially to drive regional hydrologic simulations using the Integrated Landscape Hydrology Model (ILHM). These coupled simulations demonstrate the response of streamflow and groundwater levels to different management strategies.

  18. Impacts of Different Assimilation Methodologies on Crop Yield Estimates Using Active and Passive Microwave Dataset at L-Band

    NASA Astrophysics Data System (ADS)

    Liu, P.; Bongiovanni, T. E.; Monsivais-Huertero, A.; Bindlish, R.; Judge, J.

    2013-12-01

    Accurate estimates of crop yield are important for managing agricultural production and food security. Although the crop growth models, such as the Decision Support System Agrotechnology Transfer (DSSAT), have been used to simulate crop growth and development, the crop yield estimates still diverge from the reality due to different sources of errors in the models and computation. Auxiliary observations may be incorporated into such dynamic models to improve predictions using data assimilation. Active and passive (AP) microwave observations at L-band (1-2 GHz) are sensitive to dielectric and geometric properties of soil and vegetation, including soil moisture (SM), vegetation water content (VWC), surface roughness, and vegetation structure. Because SM and VWC are one of the governing factors in estimating crop yield, microwave observations may be used to improve crop yield estimates. Current studies have shown that active observations are more sensitive to the surface roughness of soil and vegetation structure during the growing season, while the passive observations are more sensitive to the SM. Backscatter and emission models linked with the DSSAT model (DSSAT-A-P) allow assimilation of microwave observations of backscattering coefficient (σ0) and brightness temperature (TB) may provide biophysically realistic estimates of model states and parameters. The present ESA Soil Moisture Ocean Salinity (SMOS) mission provides passive observations at 1.41 GHz at 25 km every 2-3 days, and the NASA/CNDAE Aquarius mission provides L-band AP observations at spatial resolution of 150 km with a repeat coverage of 7 days for global SM products. In 2014, the planned NASA Soil Moisture Active Passive mission will provide AP observations at 1.26 and 1.41 GHz at the spatial resolutions of 3 and 30 km, respectively, with a repeat coverage of 2-3 days. The goal of this study is to understand the impacts of assimilation of asynchronous and synchronous AP observations on crop yield

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  20. Role of native shrubs of the Sahel in mitigating water and nutrient stresses of agricultural crops

    NASA Astrophysics Data System (ADS)

    Bayala, R.; Ghezzehei, T. A.; Bogie, N. A.; Diedhiou, I.; Dick, R.

    2015-12-01

    In the semi arid zone of the Sahel native woody shrubs are present in many farmers' fields. The native density of these shrubs is fairly low at around 200 to 300 individuals per hectare. An ongoing study in the Peanut Basin, Senegal has shown a vast improvement in crop yields when annual food crops are planted with the shrub Guiera senegalensis, especially in years of low or irregular precipitation. Shrubs in field plots established in 2003 where a rotation of peanuts and millet are grown are planted at a much higher density of 1500-1830 individuals per hectare. In order to increase the density of shrubs on the landscape, the shrubs must be cultivated. We monitored soil moisture, soil temperature, and growth of recently transplanted individuals at a field station in Thies, Senegal.This study seeks to determine the growth characteristics and water use of young shrubs in order to inform possible future plantations of the shrubs in a more intensely managed agroecosystem. If this technique of intercropping is to be expanded we must not exceed the carrying capacity of the landscape. In vulnerable ecosystems where natural resources are scarce and farming inputs are low, we must work to determine ways of exploiting the adaptation of local agroecosystems to increase the sustainability of agriculture in the region.

  1. New oilseed crops for fuels and chemicals: ecological and agricultural considerations

    SciTech Connect

    Draper, H.M. III

    1982-01-01

    A new approach to agriculture involving oilseed crops for fuels and chemicals is proposed. Such an approach to biomass energy would be designed to benefit the limited-resource farmer in the United States and the Third World, while at the same time not aggravating global ecological problems such as deforestation and desertification. Since food versus fuel conflicts arise when plants are grown for industrial uses on good lands, productivity questions are examined, with the conclusion that fundamental biological constraints will limit yields on marginal lands. Conventional vegetable oil crops are limited in their climatic requirements or are not well adapted to limited-resource farming; therefore, new oilseeds more adaptable to small farming are proposed. Such plants would be for specialty chemicals or to meet local energy needs. Chemicals produced would be low-volume, labor-intensive, and possibly high-priced. A list of 281 potential new oilseeds is provided, and each is classified according to potential, multiple product potential, and vegetative characteristics. Using climatic data which are available for most areas, a method of making rough productivity estimates for unconventional wild plant oilseeds is proposed, and example resource estimates are provided for the southeastern United States.

  2. Activated Carbon Derived from Fast Pyrolysis Liquids Production of Agricultural Residues and Energy Crops

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Fast pyrolysis is a thermochemical method that can be used for processing energy crops such as switchgrass, alfalfa, soybean straw, corn stover as well as agricultural residuals (broiler litter) for bio-oil production. Researchers with the Agriculture Research Service (ARS) of the USDA developed a 2...

  3. Soil carbon management in large-scale Earth system modelling: implications for crop yields and nitrogen leaching

    NASA Astrophysics Data System (ADS)

    Olin, S.; Lindeskog, M.; Pugh, T. A. M.; Schurgers, G.; Wårlind, D.; Mishurov, M.; Zaehle, S.; Stocker, B. D.; Smith, B.; Arneth, A.

    2015-06-01

    We explore cropland management alternatives and the effect these can have on future C and N pools and fluxes using the land use-enabled dynamic vegetation model LPJ-GUESS. Simulated crop production, cropland carbon storage, carbon sequestration and nitrogen leaching from croplands are evaluated and discussed. Compared to the version of LPJ-GUESS that does not include land use dynamics, estimates of soil carbon stocks and nitrogen leaching from terrestrial to aquatic ecosystems were improved. We explore trade-offs between important ecosystem services that can be provided from agricultural fields such as crop yields, retention of nitrogen and carbon storage. These trade-offs are evaluated for current land use and climate and further explored for future conditions within the two future climate change scenarios, RCP 2.6 and 8.5. Our results show that the potential for carbon sequestration due to typical cropland management practices such as no-till and cover-crops proposed in literature is not realised, globally or over larger climatic regions. Our results highlight important considerations to be made when modelling C-N interactions in agricultural ecosystems under future environmental change, and the effects these have on terrestrial biogeochemical cycles.

  4. Seasonal changes in the performance of a catch crop for mitigating diffuse agricultural pollution.

    PubMed

    Kondo, K; Inoue, K; Fujiwara, T; Yamane, S; Yasutake, D; Maeda, M; Nagare, H; Akao, S; Ohtoshi, K

    2013-01-01

    An in situ technology for mitigating diffuse agricultural pollution using catch crops was developed for simultaneously preventing nitrate groundwater pollution, reducing nitrous oxide (N2O) gas emissions, and removing salts from the topsoil. Seasonal changes in the performance of a catch crop were investigated using lysimeters in a full-scale greenhouse experiment with 50 d cultivation of dent corn. Catch crop cultivation significantly reduced the leached mineral nitrogen by 89-91% in summer, 87-89% in spring, and 61-82% in winter, and it also significantly reduced the N2O emission by 68-84% in summer. The amounts of nitrogen uptake by the catch crop were remarkably higher than those of leached nitrogen and N2O emission in each season. Catch crop cultivation is a promising technology for mitigating diffuse agricultural pollution. PMID:23985506

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

    SciTech Connect

    Tolbert, V.R.; Schiller, A.

    1996-10-01

    Short-rotation woody crops and perennial grasses are grown as biomass feedstocks for energy and fiber. When replacing traditional row crops on similar lands, these alternative crops can provide multiple environmental benefits in addition to enhancing rural economies and providing valuable resources. The DOE is supporting research to address how these crops can provide environmental benefits to soil, water, and native wildlife species in addition to providing bioenergy feedstocks. Research is underway to address the potential for biomass crops to provide soils conservation and water quality improvements in crop settings. Replacement of traditional erosive row drops with biomass crops on marginal lands and establishment of biomass plantations as filter strips adjacent to streams and wetlands are being studied. The habitat value of different crops for wildlife species is also considered. Combining findings on wildlife use of individual plantations with information on the cumulative effects of multiple plantations on wildlife populations can provide guidance for establishing and managing biomass crops to enhance biodiversity while providing feedstocks. Data from site-specific environmental studies can provide input for evaluation of the effects of large-scale plantings at both landscape and regional levels of resolution.

  6. EFFECTS OF ULTRAVIOLET-B RADIATION ON THE GROWTH AND YIELD OF CROP PLANTS

    EPA Science Inventory

    The paper reviews growth chamber, greenhouse, and field studies on the effects of ultraviolet B (UV-B, between 280 and 320 nm) radiation on agricultural crop plants. The understanding of the physiological effects of UV-B radiation comes primarily from growth chamber studies where...

  7. Crop modelling as a tool to separate the influence of the soil and weather on crop yields

    NASA Astrophysics Data System (ADS)

    Mathe-Gaspar, Gabriella; Fodor, Nandor; Pokovai, Klara; Kovacs, Geza Janos

    The yield of traditional food and feed crops in a given habitat is controlled by the soil and weather conditions as the main environmental factors. In real world it is not possible to segregate the influences of the soil and the weather on the crop production. Using simulation models there are ways to analyse the effects of the changes of soil characteristics or weather elements separately. The role of different soil characteristics can be studied in a way that the first run is considered as a control, then one of the soil characteristics is changed within a realistic range while all the other soil factors and weather inputs are left original. This way all the soil characteristic and weather elements can be changed one by one or different combinations of them can be used as input series. A more practical approach is when the role of local soils and weather are compared by a series of runs applying observed weather data from different years and real soil profiles from different fields of the selected farm. The results of the simulation can be evaluated from many different aspects: biomass or yield production, vulnerability to nitrate leaching or denitrification and profitability. In this study real Hungarian soil and weather scenarios were used that are significantly different from one another. The two main crops of Hungary were used: maize and wheat plus field pea as an addition. Pea is known as a sensitive crop to weather. 4M-simulation package was used as a modelling tool. Our group at RISSAC based on CERES and CROPGRO models has developed it. The results showed that the weather differences caused more significant changes in yields then soil differences though soils could moderate the effects of the extreme weather scenarios. The measure of reactions is meaningfully different depending on the species and cultivars. Analysis of separated effects of soil and weather factors has not only theoretical and methodological importance, but useful for the practice, too

  8. Crop modelling as a tool to separate the influences of the soil and weather on crop yields

    NASA Astrophysics Data System (ADS)

    Mathe-Gaspar, G.; Fodor, N.; Pokovai, K.; Kovacs, G. J.

    2003-04-01

    The yield of traditional food and feed crops in a given habitat is controlled by the soil and weather conditions as the main environmental factors. In real world it is not possible to segregate the influences of the soil and the weather on the crop production. Using simulation models there are ways to analyse the effects of the changes of soil characteristics or weather elements separately. The role of different soil characteristics can be studied in a way that the first run is considered as a control, then one of the soil characteristics is changed within a realistic range while all the other soil factors and weather inputs are left original. This way all the soil characteristic and weather elements can be changed one by one or different combinations of them can be used as input series. A more practical approach is when the role of local soils and weather are compared by a series of runs applying observed weather data from different years and real soil profiles from different fields of the selected farm. The results of the simulation can be evaluated from many different aspects: biomass or yield production, vulnerability to nitrate leaching or denitrification and profitability. In this study real Hungarian soil and weather scenarios were used that are significantly different from one another. The two main crops of Hungary were used: maize and wheat plus field pea as an addition. Pea is known as a sensitive crop to weather. 4M-simulation package was used as a modelling tool. Our group at RISSAC based on CERES and CROPGRO models has developed it. The results showed that the weather differences caused more significant changes in yields then soil differences though soils could moderate the effects of the extreme weather scenarios. The measure of reactions is meaningfully different depending on the species and cultivars. Analysis of separated effects of soil and weather factors has not only theoretical and methodological importance, but useful for the practice, too

  9. Nitrogen and Water Stress Impact on Hard Red Spring Wheat Crop Reflectance, Yield and Grain Quality

    NASA Astrophysics Data System (ADS)

    Reese, C. L.; Clay, D. E.; Beck, D.; Clay, S. A.; Seielstad, G.

    2007-12-01

    Water and nitrogen stress impact hard red spring wheat (Triticum aestivum) crop reflectance, yield and grain quality. To minimize yield losses from nitrogen (N) and water stress, it is essential to apply appropriate N in relation to water stress. The objective of this experiment was to determine the influence of N and water stress on hard red spring wheat crop reflectance, yield, and grain quality. Complete randomized block experiments were conducted in 2003, 2004 and 2004 in dryland and irrigated fields at three locations in central South Dakota. Treatments consisted of N rates and N application at different growth stages. Nitrogen fertilizer rates ranged from 0 to 200 kg ha-1. Nitrogen fertilizer application times were (1) planting; (2) planting and tillering (Feekes 2 -3) or (3) tillering (Feekes 2 -3). Reflectance data was collected using a Cropscan and a CropCircle radiometer. Reflectance data was collected at bare soil, tillering (Feekes 2-3) and flag leaf (Feekes 9-10). Carbon 13 isotopic discrimination (Ä) was used to determine yield loss to nitrogen or water stress. Reflectance data was compared to yield and Ä values or grain quality and Ä values. Correlation of crop reflectance (measured at the different growth stages and by the different radiometers) with yield loss to nitrogen or water and grain quality will be presented. Information presented will be used to make corrective nitrogen treatments and improve marketing decisions as related to grain quality.

  10. Uncertainty in soil data can outweigh climate impact signals in global crop yield simulations

    PubMed Central

    Folberth, Christian; Skalský, Rastislav; Moltchanova, Elena; Balkovič, Juraj; Azevedo, Ligia B.; Obersteiner, Michael; van der Velde, Marijn

    2016-01-01

    Global gridded crop models (GGCMs) are increasingly used for agro-environmental assessments and estimates of climate change impacts on food production. Recently, the influence of climate data and weather variability on GGCM outcomes has come under detailed scrutiny, unlike the influence of soil data. Here we compare yield variability caused by the soil type selected for GGCM simulations to weather-induced yield variability. Without fertilizer application, soil-type-related yield variability generally outweighs the simulated inter-annual variability in yield due to weather. Increasing applications of fertilizer and irrigation reduce this variability until it is practically negligible. Importantly, estimated climate change effects on yield can be either negative or positive depending on the chosen soil type. Soils thus have the capacity to either buffer or amplify these impacts. Our findings call for improvements in soil data available for crop modelling and more explicit accounting for soil variability in GGCM simulations. PMID:27323866

  11. Uncertainty in soil data can outweigh climate impact signals in global crop yield simulations

    NASA Astrophysics Data System (ADS)

    Folberth, Christian; Skalský, Rastislav; Moltchanova, Elena; Balkovič, Juraj; Azevedo, Ligia B.; Obersteiner, Michael; van der Velde, Marijn

    2016-06-01

    Global gridded crop models (GGCMs) are increasingly used for agro-environmental assessments and estimates of climate change impacts on food production. Recently, the influence of climate data and weather variability on GGCM outcomes has come under detailed scrutiny, unlike the influence of soil data. Here we compare yield variability caused by the soil type selected for GGCM simulations to weather-induced yield variability. Without fertilizer application, soil-type-related yield variability generally outweighs the simulated inter-annual variability in yield due to weather. Increasing applications of fertilizer and irrigation reduce this variability until it is practically negligible. Importantly, estimated climate change effects on yield can be either negative or positive depending on the chosen soil type. Soils thus have the capacity to either buffer or amplify these impacts. Our findings call for improvements in soil data available for crop modelling and more explicit accounting for soil variability in GGCM simulations.

  12. Uncertainty in soil data can outweigh climate impact signals in global crop yield simulations.

    PubMed

    Folberth, Christian; Skalský, Rastislav; Moltchanova, Elena; Balkovič, Juraj; Azevedo, Ligia B; Obersteiner, Michael; van der Velde, Marijn

    2016-01-01

    Global gridded crop models (GGCMs) are increasingly used for agro-environmental assessments and estimates of climate change impacts on food production. Recently, the influence of climate data and weather variability on GGCM outcomes has come under detailed scrutiny, unlike the influence of soil data. Here we compare yield variability caused by the soil type selected for GGCM simulations to weather-induced yield variability. Without fertilizer application, soil-type-related yield variability generally outweighs the simulated inter-annual variability in yield due to weather. Increasing applications of fertilizer and irrigation reduce this variability until it is practically negligible. Importantly, estimated climate change effects on yield can be either negative or positive depending on the chosen soil type. Soils thus have the capacity to either buffer or amplify these impacts. Our findings call for improvements in soil data available for crop modelling and more explicit accounting for soil variability in GGCM simulations. PMID:27323866

  13. Identifying opportunities to reduce excess nitrogen in croplands while maintaining current crop yields

    NASA Astrophysics Data System (ADS)

    West, P. C.; Mueller, N. D.; Foley, J. A.

    2011-12-01

    Use of synthetic nitrogen fertilizer has greatly contributed to the increased crop yields brought about by the Green Revolution. Unfortunately, it also has also contributed to substantial excess nitrogen in the environment. Application of excess nitrogen not only is a waste of energy and other resources used to produce, transport and apply it, it also pollutes aquatic ecosystems and has led to the development of more than 200 hypoxic-or "dead"-zones in coastal areas around the world. How can we decrease use of excess nitrogen without compromising crop yields? To help address this challenge, our study (1) quantified hot spots of excess nitrogen, and (2) estimated how much nitrogen reduction is possible in these areas while still maintaining yields. We estimated excess nitrogen for major crops using a mass balance approach and global spatial data sets of crop area and yield, fertilizer application rates, and nitrogen deposition. Hot spots of excess nitrogen were identified by quantifying the smallest area within large river basins that contributed 25% and 50% of the total load within each basin. Nitrogen reduction scenarios were developed using a yield response model to estimate nitrogen application rates needed to maintain current yields. Our research indicated that excess nitrogen is concentrated in very small portions of croplands within river basins, with 25% of the total nitrogen load in each basin from ~10% of the cropland, and 50% of the total nitrogen load in each basin from ~25% of the cropland. Targeting reductions in application rates in these hot spots can allow us to maintain current crop yields while greatly reducing nitrogen loading to coastal areas and creating the opportunity to reallocate resources to boost yields on nitrogen-limited croplands elsewhere.

  14. Reduced nitrogen losses following conversion of row crop agriculture to perennial biofuel crops

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Current biofuel feedstock crops such as corn lead to large environmental losses of N through nitrate leaching and N2O emissions, and require large inputs of N fertilizer. Second generation cellulosic crops have the potential to reduce these N losses, and provide even greater biomass for conversion t...

  15. Multiyear high-resolution carbon exchange over European croplands from the integration of observed crop yields into CarbonTracker Europe

    NASA Astrophysics Data System (ADS)

    Combe, Marie; Vilà-Guerau de Arellano, Jordi; de Wit, Allard; Peters, Wouter

    2016-04-01

    Carbon exchange over croplands plays an important role in the European carbon cycle over daily-to-seasonal time scales. Not only do crops occupy one fourth of the European land area, but their photosynthesis and respiration are large and affect CO2 mole fractions at nearly every atmospheric CO2 monitoring site. A better description of this crop carbon exchange in our CarbonTracker Europe data assimilation system - which currently treats crops as unmanaged grasslands - could strongly improve its ability to constrain terrestrial carbon fluxes. Available long-term observations of crop yield, harvest, and cultivated area allow such improvements, when combined with the new crop-modeling framework we present. This framework can model the carbon fluxes of 10 major European crops at high spatial and temporal resolution, on a 12x12 km grid and 3-hourly time-step. The development of this framework is threefold: firstly, we optimize crop growth using the process-based WOrld FOod STudies (WOFOST) agricultural crop growth model. Simulated yields are downscaled to match regional crop yield observations from the Statistical Office of the European Union (EUROSTAT) by estimating a yearly regional parameter for each crop species: the yield gap factor. This step allows us to better represent crop phenology, to reproduce the observed multiannual European crop yields, and to construct realistic time series of the crop carbon fluxes (gross primary production, GPP, and autotrophic respiration, Raut) on a fine spatial and temporal resolution. Secondly, we combine these GPP and Raut fluxes with a simple soil respiration model to obtain the total ecosystem respiration (TER) and net ecosystem exchange (NEE). And thirdly, we represent the horizontal transport of carbon that follows crop harvest and its back-respiration into the atmosphere during harvest consumption. We distribute this carbon using observations of the density of human and ruminant populations from EUROSTAT. We assess the model

  16. Genetically Engineered Crops and Certified Organic Agriculture for Improving Nutrition Security in Africa and South Asia.

    PubMed

    Pray, Carl; Ledermann, Samuel

    2016-01-01

    In Africa and South Asia, where nutrition insecurity is severe, two of the most prominent production technologies are genetically modified (GM) crops and certified organic agriculture. We analyze the potential impact pathways from agricultural production to nutrition. Our review of data and the literature reveals increasing farm-level income from cash crop production as the main pathway by which organic agriculture and GM agriculture improve nutrition. Potential secondary pathways include reduced prices of important food crops like maize due to GM maize production and increased food production using organic technology. Potential tertiary pathways are improvements in health due to reduced insecticide use. Challenges to the technologies achieving their impact include the politics of GM agriculture and the certification costs of organic agriculture. Given the importance of agricultural production in addressing nutrition security, accentuated by the post-2015 sustainable development agenda, the chapter concludes by stressing the importance of private and public sector research in improving the productivity and adoption of both GM and organic crops. In addition, the chapter reminds readers that increased farm income and productivity require complementary investments in health, education, food access and women's empowerment to actually improve nutrition security. PMID:27197837

  17. MANAGING COVER CROPS IN CONSERVATION AGRICULTURE USING ROLLERS/CRIMPERS

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Rollers may provide a viable alternative to herbicides for terminating cover crops, however, excessive vibration generated by rollers and transferred to tractors hinders adoption of this technology in the US. To avoid excessive vibration, producers must limit their operational speed, which increases...

  18. Subsistence Agriculture versus Cash Cropping: The Social Repercussions.

    ERIC Educational Resources Information Center

    Rennie, Sandra Joy

    1991-01-01

    The introduction of cash cropping in the Solomon Islands and Tonga has had negative effects on women, leading to deterioration in their status, decreased leisure time, fewer opportunities to earn cash, increased birth rate (to help with the increased workload), and more sharply defined sex roles. (SV)

  19. Assessing agricultural risks of climate change in the 21st century in a global gridded crop model intercomparison.

    PubMed

    Rosenzweig, Cynthia; Elliott, Joshua; Deryng, Delphine; Ruane, Alex C; Müller, Christoph; Arneth, Almut; Boote, Kenneth J; Folberth, Christian; Glotter, Michael; Khabarov, Nikolay; Neumann, Kathleen; Piontek, Franziska; Pugh, Thomas A M; Schmid, Erwin; Stehfest, Elke; Yang, Hong; Jones, James W

    2014-03-01

    Here we present the results from an intercomparison of multiple global gridded crop models (GGCMs) within the framework of the Agricultural Model Intercomparison and Improvement Project and the Inter-Sectoral Impacts Model Intercomparison Project. Results indicate strong negative effects of climate change, especially at higher levels of warming and at low latitudes; models that include explicit nitrogen stress project more severe impacts. Across seven GGCMs, five global climate models, and four representative concentration pathways, model agreement on direction of yield changes is found in many major agricultural regions at both low and high latitudes; however, reducing uncertainty in sign of response in mid-latitude regions remains a challenge. Uncertainties related to the representation of carbon dioxide, nitrogen, and high temperature effects demonstrated here show that further research is urgently needed to better understand effects of climate change on agricultural production and to devise targeted adaptation strategies. PMID:24344314

  20. Assessing agricultural risks of climate change in the 21st century in a global gridded crop model intercomparison

    PubMed Central

    Rosenzweig, Cynthia; Elliott, Joshua; Deryng, Delphine; Ruane, Alex C.; Müller, Christoph; Arneth, Almut; Boote, Kenneth J.; Folberth, Christian; Glotter, Michael; Khabarov, Nikolay; Neumann, Kathleen; Piontek, Franziska; Pugh, Thomas A. M.; Schmid, Erwin; Stehfest, Elke; Yang, Hong; Jones, James W.

    2014-01-01

    Here we present the results from an intercomparison of multiple global gridded crop models (GGCMs) within the framework of the Agricultural Model Intercomparison and Improvement Project and the Inter-Sectoral Impacts Model Intercomparison Project. Results indicate strong negative effects of climate change, especially at higher levels of warming and at low latitudes; models that include explicit nitrogen stress project more severe impacts. Across seven GGCMs, five global climate models, and four representative concentration pathways, model agreement on direction of yield changes is found in many major agricultural regions at both low and high latitudes; however, reducing uncertainty in sign of response in mid-latitude regions remains a challenge. Uncertainties related to the representation of carbon dioxide, nitrogen, and high temperature effects demonstrated here show that further research is urgently needed to better understand effects of climate change on agricultural production and to devise targeted adaptation strategies. PMID:24344314

  1. Assessing Agricultural Risks of Climate Change in the 21st Century in a Global Gridded Crop Model Intercomparison

    NASA Technical Reports Server (NTRS)

    Rosenzweig, Cynthia E.; Elliott, Joshua; Deryng, Delphine; Ruane, Alex C.; Mueller, Christoph; Arneth, Almut; Boote, Kenneth J.; Folberth, Christian; Glotter, Michael; Khabarov, Nikolay

    2014-01-01

    Here we present the results from an intercomparison of multiple global gridded crop models (GGCMs) within the framework of the Agricultural Model Intercomparison and Improvement Project and the Inter-Sectoral Impacts Model Intercomparison Project. Results indicate strong negative effects of climate change, especially at higher levels of warming and at low latitudes; models that include explicit nitrogen stress project more severe impacts. Across seven GGCMs, five global climate models, and four representative concentration pathways, model agreement on direction of yield changes is found in many major agricultural regions at both low and high latitudes; however, reducing uncertainty in sign of response in mid-latitude regions remains a challenge. Uncertainties related to the representation of carbon dioxide, nitrogen, and high temperature effects demonstrated here show that further research is urgently needed to better understand effects of climate change on agricultural production and to devise targeted adaptation strategies.

  2. Modelling crop canopy and residue rainfall interception effects on soil hydrological components for semi-arid agriculture

    NASA Astrophysics Data System (ADS)

    Kozak, Joseph A.; Ahuja, Lajpat R.; Green, Timothy R.; Ma, Liwang

    2007-01-01

    Crop canopies and residues have been shown to intercept a significant amount of rainfall. However, rainfall or irrigation interception by crops and residues has often been overlooked in hydrologic modelling. Crop canopy interception is controlled by canopy density and rainfall intensity and duration. Crop residue interception is a function of crop residue type, residue density and cover, and rainfall intensity and duration. We account for these controlling factors and present a model for both interception components based on Merriam's approach. The modified Merriam model and the current modelling approaches were examined and compared with two field studies and one laboratory study. The Merriam model is shown to agree well with measurements and was implemented within the Agricultural Research Service's Root Zone Water Quality Model (RZWQM). Using this enhanced version of RZWQM, three simulation studies were performed to examine the quantitative effects of rainfall interception by corn and wheat canopies and residues on soil hydrological components. Study I consisted of 10 separate hypothetical growing seasons (1991-2000) for canopy effects and 10 separate non-growing seasons (1991-2000) for residue effects for eastern Colorado conditions. For actual management practices in a no-till wheat-corn-fallow cropping sequence at Akron, Colorado (study II), a continuous 10-year RZWQM simulation was performed to examine the cumulative changes on water balance components and crop growth caused by canopy and residue rainfall interception. Finally, to examine a higher precipitation environment, a hypothetical, no-till wheat-corn-fallow rotation scenario at Corvallis, Oregon, was simulated (study III). For all studies, interception was shown to decrease infiltration, runoff, evapotranspiration from soil, deep seepage of water and chemical transport, macropore flow, leaf area index, and crop/grain yield. Because interception decreased both infiltration and soil evapotranspiration

  3. Evaluation of the performance of SiBcrop model in predicting carbon fluxes and crop yields in the croplands of the US mid continental region

    NASA Astrophysics Data System (ADS)

    Lokupitiya, E.; Denning, S.; Paustian, K.; Corbin, K.; Baker, I.; Schaefer, K.

    2008-12-01

    The accurate representation of phenology, physiology, and major crop variables is important in the land- atmosphere carbon models being used to predict carbon and other exchanges of the man-made cropland ecosystems. We evaluated the performance of SiBcrop model (which is the Simple Biosphere model (SiB) with a new scheme for crop phenology and physiology) in predicting carbon exchanges of the US mid continental region which has several major crops. The use of the new phenology scheme within SiB remarkably improved the prediction of LAI and carbon fluxes for corn, soybean, and wheat crops as compared with the observed data at several Ameriflux eddy covariance flux tower sites with those crops. SiBcrop better predicted the onset and end of the growing season, harvest, interannual variability associated with crop rotation, day time carbon draw down, and day to day variability in the carbon exchanges. The model has been coupled with RAMS, the regional Atmospheric Modeling System (developed at Colorado State University), and the coupled SiBcrop-RAMS has predicted better carbon and other fluxes compared to the original SiB-RAMS. SiBcrop also predicted daily variation in biomass in different plant pools (i.e. roots, leaves, stems, and products). In this study, we further evaluated the performance of SiBcrop by comparing the yield estimates based on the grain/seed biomass at harvest predicted by SiBcrop for relevant major crops, against the county-level crop yields reported by the US National Agricultural Statistics Service (NASS). Initially, the model runs were based on crop maps scaled at 40 km resolution; the maps were used to derive the fraction of corn, soybean, and wheat at each grid cell across the US Mid Continental Intensive (MCI) region under the North American Carbon Program (NACP). The yield biomass carbon values (at harvest) predicted for each grid cell by SiBcrop were extrapolated to derive the county-level yield biomass carbon values, which were then

  4. [Effects of tobacco garlic crop rotation and intercropping on tobacco yield and rhizosphere soil phosphorus fractions].

    PubMed

    Tang, Biao; Zhang, Xi-zhou; Yang, Xian-bin

    2015-07-01

    A field plot experiment was conducted to investigate the tobacco yield and different forms of soil phosphorus under tobacco garlic crop rotation and intercropping patterns. The results showed that compared with tobacco monoculture, the tobacco yield and proportion of middle/high class of tobacco leaves to total leaves were significantly increased in tobacco garlic crop rotation and intercropping, and the rhizosphere soil available phosphorus contents were 1.3 and 1.7 times as high as that of tobacco monoculture at mature stage of lower leaf. For the inorganic phosphorus in rhizosphere and non-rhizosphere soil in different treatments, the contents of O-P and Fe-P were the highest, followed by Ca2-P and Al-P, and Ca8-P and Ca10-P were the lowest. Compared with tobacco monoculture and tobacco garlic crop intercropping, the Ca2-P concentration in rhizosphere soil under tobacco garlic crop rotation at mature stage of upper leaf, the Ca8-P concentration at mature stage of lower leaf, and the Ca10-P concentration at mature stage of middle leaf were lowest. The Al-P concentrations under tobacco garlic crop rotation and intercropping were 1.6 and 1.9 times, and 1.2 and 1.9 times as much as that under tobacco monoculture in rhizosphere soil at mature stages of lower leaf and middle leaf, respectively. The O-P concentrations in rhizosphere soil under tobacco garlic crop rotation and intercropping were significantly lower than that under tobacco monoculture. Compared with tobacco garlic crop intercropping, the tobacco garlic crop rotation could better improve tobacco yield and the proportion of high and middle class leaf by activating O-P, Ca10-P and resistant organic phosphorus in soil. PMID:26710622

  5. Potential alternative fuel sources for agricultural crops and plant components

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The changing landscape of agricultural production is placing unprecedented demands on farmers as they face increasing global competition and greater natural resource conservation challenges. However, shrinking profit margins due to increasing input costs, particularly of fuel and fertilizer, can res...

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

    NASA Astrophysics Data System (ADS)

    Setiyono, T. D.

    2014-12-01

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

  7. Quantifying the weather-signal in national crop-yield variability

    NASA Astrophysics Data System (ADS)

    Frieler, K.; Arneth, A.; Balkovic, J.; Chryssanthacopoulos, J.; Deryng, D.; Elliott, J. W.; Folberth, C.; Khabarov, N.; Mueller, C.; Olin, S.; Pugh, T.; Schaphoff, S.; Schewe, J.; Schmid, E.; Schauberger, B.; Warszawski, L.; Levermann, A.

    2015-12-01

    Year-to-year variations in crop yields can have major impacts on the livelihoods of subsistence farmers and may trigger significant global price fluctuations with particularly severe consequences for people in developing countries. The fluctuations can be induced by weather conditions but also by management decisions, diseases, and pests. To get a better understanding of future sensitivities to climate change it is important to quantify the degree to which historical crop yields are determined by weather fluctuations. This separation from other influences is usually done by highly simplified empirical models. In contrast, here we provide a conservative estimate of the fraction of the observed national yield variability that is caused by weather, using state-of-the-art process-based crop model simulations. As these models provide a detailed representation of our current understanding of the underlying processes they are also suitable to assess potential adaptation options. We provide an identification of the countries where the weather induced variability of crop yields is particularly high (explained variance > 50%). In addition, inhibiting water stress by simulating yields assuming full irrigation shows that water limitation is the main driver of the observed variations in most of these countries.

  8. Plant-Based Assessment of Inherent Soil Productivity and Contributions to China’s Cereal Crop Yield Increase since 1980

    PubMed Central

    Fan, Mingsheng; Lal, Rattan; Cao, Jian; Qiao, Lei; Su, Yansen; Jiang, Rongfeng; Zhang, Fusuo

    2013-01-01

    Objective China’s food production has increased 6-fold during the past half-century, thanks to increased yields resulting from the management intensification, accomplished through greater inputs of fertilizer, water, new crop strains, and other Green Revolution’s technologies. Yet, changes in underlying quality of soils and their effects on yield increase remain to be determined. Here, we provide a first attempt to quantify historical changes in inherent soil productivity and their contributions to the increase in yield. Methods The assessment was conducted based on data-set derived from 7410 on-farm trials, 8 long-term experiments and an inventory of soil organic matter concentrations of arable land. Results Results show that even without organic and inorganic fertilizer addition crop yield from on-farm trials conducted in the 2000s was significantly higher compared with those in the 1980s — the increase ranged from 0.73 to 1.76 Mg/ha for China’s major irrigated cereal-based cropping systems. The increase in on-farm yield in control plot since 1980s was due primarily to the enhancement of soil-related factors, and reflected inherent soil productivity improvement. The latter led to higher and stable yield with adoption of improved management practices, and contributed 43% to the increase in yield for wheat and 22% for maize in the north China, and, 31%, 35% and 22% for early and late rice in south China and for single rice crop in the Yangtze River Basin since 1980. Conclusions Thus, without an improvement in inherent soil productivity, the ‘Agricultural Miracle in China’ would not have happened. A comprehensive strategy of inherent soil productivity improvement in China, accomplished through combining engineering-based measures with biological-approaches, may be an important lesson for the developing world. We propose that advancing food security in 21st century for both China and other parts of world will depend on continuously improving inherent soil

  9. Ensiling of crops for biogas production: effects on methane yield and total solids determination

    PubMed Central

    2011-01-01

    Background Ensiling is a common method of preserving energy crops for anaerobic digestion, and many scientific studies report that ensiling increases the methane yield. In this study, the ensiling process and the methane yields before and after ensiling were studied for four crop materials. Results The changes in wet weight and total solids (TS) during ensiling were small and the loss of energy negligible. The methane yields related to wet weight and to volatile solids (VS) were not significantly different before and after ensiling when the VS were corrected for loss of volatile compounds during TS and VS determination. However, when the TS were measured according to standard methods and not corrected for losses of volatile compounds, the TS loss during ensiling was overestimated for maize and sugar beet. The same methodological error leads to overestimation of methane yields; when TS and VS were not corrected the methane yield appeared to be 51% higher for ensiled than fresh sugar beet. Conclusions Ensiling did not increase the methane yield of the studied crops. Published methane yields, as well as other information on silage related to uncorrected amounts of TS and VS, should be regarded with caution. PMID:22032645

  10. Proximity to Crops and Residential Exposure to Agricultural Herbicides in Iowa

    PubMed Central

    Ward, Mary H.; Lubin, Jay; Giglierano, James; Colt, Joanne S.; Wolter, Calvin; Bekiroglu, Nural; Camann, David; Hartge, Patricia; Nuckols, John R.

    2006-01-01

    Rural residents can be exposed to agricultural pesticides through the proximity of their homes to crop fields. Previously, we developed a method to create historical crop maps using a geographic information system. The aim of the present study was to determine whether crop maps are useful for predicting levels of crop herbicides in carpet dust samples from residences. From homes of participants in a case–control study of non-Hodgkin lymphoma in Iowa (1998–2000), we collected vacuum cleaner dust and measured 14 herbicides with high use on corn and soybeans in Iowa. Of 112 homes, 58% of residences had crops within 500 m of their home, an intermediate distance for primary drift from aerial and ground applications. Detection rates for herbicides ranged from 0% for metribuzin and cyanazine to 95% for 2,4-dichlorophenoxyacetic acid. Six herbicides used almost exclusively in agriculture were detected in 28% of homes. Detections and concentrations were highest in homes with an active farmer. Increasing acreage of corn and soybean fields within 750 m of homes was associated with significantly elevated odds of detecting agricultural herbicides compared with homes with no crops within 750 m (adjusted odds ratio per 10 acres = 1.06; 95% confidence interval, 1.02–1.11). Herbicide concentrations also increased significantly with increasing acreage within 750 m. We evaluated the distance of crop fields from the home at < 100, 101–250, 251–500, and 501–750 m. Including the crop buffer distance parameters in the model did not significantly improve the fit compared with a model with total acres within 750 m. Our results indicate that crop maps may be a useful method for estimating levels of herbicides in homes from nearby crop fields. PMID:16759991

  11. Agricultural Classification of Multi-Temporal MODIS Imagery in Northwest Argentina Using Kansas Crop Phenologies

    NASA Astrophysics Data System (ADS)

    Keifer, Jarrett Alexander

    Subtropical deforestation in Latin America is thought to be driven by demand for agricultural land, particularly to grow soybeans. However, existing remote sensing methods that can differentiate crop types to verify this hypothesis require high spatial or spectral resolution data, or extensive ground truth information to develop training sites, none of which are freely available for much of the world. I developed a new method of crop classification based on the phenological signatures of crops extracted from multi-temporal MODIS vegetation indices. I tested and refined this method using the USDA Cropland Data Layer from Kansas, USA as a reference. I then applied the method to classify crop types for a study site in Pellegrini, Santiago Del Estero, Argentina. The results show that this method is unable to effectively separate summer crops in Pellegrini, but can differentiate summer crops and non-summer crops. Unmet assumptions about agricultural practices are primarily responsible for the ineffective summer crop classification, underlining the need for researchers to have a complete understanding of ground conditions when designing a remote sensing analysis.

  12. Integrating remote sensing, geographic information system and modeling for estimating crop yield

    NASA Astrophysics Data System (ADS)

    Salazar, Luis Alonso

    This thesis explores various aspects of the use of remote sensing, geographic information system and digital signal processing technologies for broad-scale estimation of crop yield in Kansas. Recent dry and drought years in the Great Plains have emphasized the need for new sources of timely, objective and quantitative information on crop conditions. Crop growth monitoring and yield estimation can provide important information for government agencies, commodity traders and producers in planning harvest, storage, transportation and marketing activities. The sooner this information is available the lower the economic risk translating into greater efficiency and increased return on investments. Weather data is normally used when crop yield is forecasted. Such information, to provide adequate detail for effective predictions, is typically feasible only on small research sites due to expensive and time-consuming collections. In order for crop assessment systems to be economical, more efficient methods for data collection and analysis are necessary. The purpose of this research is to use satellite data which provides 50 times more spatial information about the environment than the weather station network in a short amount of time at a relatively low cost. Specifically, we are going to use Advanced Very High Resolution Radiometer (AVHRR) based vegetation health (VH) indices as proxies for characterization of weather conditions.

  13. Effects of No-Till on Yields as Influenced by Crop and Environmental Factors

    SciTech Connect

    Toliver, Dustin K.; Larson, James A.; Roberts, Roland K.; English, B.C.; De La Torre Ugarte, D. G.; West, Tristram O.

    2012-02-07

    Th is research evaluated diff erences in yields and associated downside risk from using no-till and tillage practices. Yields from 442 paired tillage experiments across the United States were evaluated with respect to six crops and environmental factors including geographic location, annual precipitation, soil texture, and time since conversion from tillage to no-till. Results indicated that mean yields for sorghum [Sorghum bicolor (L.) Moench] and wheat (Triticum aestivum L.) with no-till were greater than with tillage. In addition, no-till tended to produce similar or greater mean yields than tillage for crops grown on loamy soils in the Southern Seaboard and Mississippi Portal regions. A warmer and more humid climate and warmer soils in these regions relative to the Heartland, Basin and Range, and Fruitful Rim regions appear to favor no-till on loamy soils. With the exception of corn (Zea mays L.) and cotton (Gossypium hirsutum L.) in the Southern Seaboard region, no-till performed poorly on sandy soils. Crops grown in the Southern Seaboard were less likely to have lower no-till yields than tillage yields on loamy soils and thus had lower downside yield risk than other farm resource regions. Consistent with mean yield results, soybean [Glycine max (L.) Merr.] and wheat grown on sandy soils in the Southern Seaboard region using no-till had larger downside yield risks than when produced with no-till on loamy soils. Th e key fi ndings of this study support the hypothesis that soil and climate factors impact no-till yields relative to tillage yields and may be an important factor infl uencing risk and expected return and the adoption of the practice by farmers.

  14. Climatological sensitivity analysis of crop yield to changes in temperature and precipitation using particle filter

    NASA Astrophysics Data System (ADS)

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

    2010-12-01

    The climatological sensitivities of crop yields to changes in mean temperature and precipitation during a period of the growing season were statistically examined. The sensitivity is defined as the change of yield in response to the change of climatic condition in the growth period from sowing to harvesting. The objective crops are maize and soybean, which are being cultivated in United States, Brazil and China as the world major production countries. We collected the yield data of maize and soybean on county level of United States from USDA during a period of 1980-2006, on Município level of Brazil during a period of 1990-2006 and on Xiàn level of China during a period of 1980-2005. While the data on only four provinces in China are used (Heilongjiang, Henan, Liaoning, and Shandong), total production of the four provinces reaches about 40% (maize) and 51% (soybean) to the country total (USDA 1997). We used JRA-25 reanalysis climate data distributed from the Japanese Meteorological Agency during a period of 1980 through 2006 with a resolution of 1.125° in latitude and longitude. To coincide in resolution, the crop yield data were reallocated into the same grids as climate. To eliminate economical and technical effects on yield, we detrended the time series data of yield and climate. We applied a local regression model to conduct the detrend (cubic weighting and M estimator of Tukey's bi-weight function). The time series data on the deviation from the trend were examined with the changes in temperature and precipitation for each grid using the particle filter. The particle filter used here is based on self-organizing state-space model. As a result, in the northern hemisphere, positive sensitivity, i.e. increase in temperature shifts the crop yield positively, is generally found especially in higher latitude, while negative sensitivity is found in the lower latitude. The neutral sensitivity is found in the regions where the mean temperature during growing season

  15. Paradoxical EU agricultural policies on genetically engineered crops.

    PubMed

    Masip, Gemma; Sabalza, Maite; Pérez-Massot, Eduard; Banakar, Raviraj; Cebrian, David; Twyman, Richard M; Capell, Teresa; Albajes, Ramon; Christou, Paul

    2013-06-01

    European Union (EU) agricultural policy has been developed in the pursuit of laudable goals such as a competitive economy and regulatory harmony across the union. However, what has emerged is a fragmented, contradictory, and unworkable legislative framework that threatens economic disaster. In this review, we present case studies highlighting differences in the regulations applied to foods grown in EU countries and identical imported products, which show that the EU is undermining its own competitiveness in the agricultural sector, damaging both the EU and its humanitarian activities in the developing world. We recommend the adoption of rational, science-based principles for the harmonization of agricultural policies to prevent economic decline and lower standards of living across the continent. PMID:23623240

  16. Effects of ecological and conventional agricultural intensification practices on maize yields in sub-Saharan Africa under potential climate change

    NASA Astrophysics Data System (ADS)

    Folberth, Christian; Yang, Hong; Gaiser, Thomas; Liu, Junguo; Wang, Xiuying; Williams, Jimmy; Schulin, Rainer

    2014-04-01

    Much of Africa is among the world’s regions with lowest yields in staple food crops, and climate change is expected to make it more difficult to catch up in crop production in particular in the long run. Various agronomic measures have been proposed for lifting agricultural production in Africa and to adapt it to climate change. Here, we present a projection of potential climate change impacts on maize yields under different intensification options in Sub-Saharan Africa (SSA) using an agronomic model, GIS-based EPIC (GEPIC). Fallow and nutrient management options taken into account are (a) conventional intensification with high mineral N supply and a bare fallow, (b) moderate mineral N supply and cowpea rotation, and (c) moderate mineral N supply and rotation with a fast growing N fixing tree Sesbania sesban. The simulations suggest that until the 2040s rotation with Sesbania will lead to an increase in yields due to increasing N supply besides improving water infiltration and soils’ water holding capacity. Intensive cultivation with a bare fallow or an herbaceous crop like cowpea in the rotation is predicted to result in lower yields and increased soil erosion during the same time span. However, yields are projected to decrease in all management scenarios towards the end of the century, should temperature increase beyond critical thresholds. The results suggest that the effect of eco-intensification as a sole means of adapting agriculture to climate change is limited in Sub-Saharan Africa. Highly adverse temperatures would rather have to be faced by improved heat tolerant cultivars, while strongly adverse decreases in precipitation would have to be faced by expanding irrigation where feasible. While the evaluation of changes in agro-environmental variables like soil organic carbon, erosion, and soil humidity hints that these are major factors influencing climate change resilience of the field crop, no direct relationship between these factors, crop yields, and

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

    PubMed

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

    2016-01-15

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

  18. Impact of different cover crops and types of transplanter mounted subsoiler shanks on tomato yield

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A four year experiment with different tillage practices for tomatoes was conducted in Cullman, AL to determine the impact of plastic mulch (control), rye and crimson clover cover crops, and different subsoiler shanks (no shank, slim 13 mm thick, and wide 20 mm thick) on tomato yield. Overall, in 200...

  19. EPIC Simulations of Crop Yields and Soil Organic Carbon in Iowa

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Depending on management, soil organic carbon is source or sink of atmospheric carbon dioxide. The Environmental Policy Integrated Climate (EPIC) model is a useful tool for predicting impacts of soil management on crop yields and soil organic carbon. We used EPIC-Century to simulate changes in soil o...

  20. Global Food Insecurity? Lower Than Expected Crop Yield Stimulation with Rising Carbon Dioxide Concentrations

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Predictions of yield for the globe's major grain and legume arable crops suggest that, with a moderate temperature increase, production may increase in the temperate zone, but decline in the tropics. In total, global food supply may show little change. This security comes from inclusion of the dir...

  1. Changes in Soil Moisture with Cover Crops and Tillage: Impact on Cotton Yield and Quality

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The alluvial soils of the lower Mississippi River flood plain are highly productive, but low in organic matter. Use of irrigation in the area has increased in order to ensure adequate yield return. Use of cover crops has been used in other areas to increase soil organic matter and improve infiltrati...

  2. Crop yield estimation based on unsupervised linear unmixing of multidate hyperspectral imagery

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Hyperspectral imagery, which contains hundreds of spectral bands, has the potential to better describe the biological and chemical attributes on the plants than multispectral imagery and has been evaluated in this paper for the purpose of crop yield estimation. The spectrum of each pixel in a hypers...

  3. Variability of soil properties and crop yield in landscapes affected by long-term tillage

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Intensive tillage moves large quantities of soil, resulting in a pattern of soil redistribution where topsoil is depleted from convex slope positions and deposited in concave positions. In these experiments, the variation in erosion estimates, soil properties and crop yield were determined in a hill...

  4. Crop rotation affects corn, grain sorghum, and soybean yields and nitrogen recovery

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Long-term cropping system and fertilizer N studies are essential towards understanding production potential and yield stability of corn (Zea mays L.), grain sorghum [Sorghum bicolor (L.) Moench], and soybean [Glycine max (L.) Merr.] in rain-fed environments. A no-till experiment (2007-13) was conduc...

  5. Predicting the impact of changing CO2 on crop yields: Some thoughts on food

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Recent breakthroughs in CO2 fumigation methods using free-air CO2 enrichment (FACE) technology have prompted comparisons between FACE experiments and "enclosure studies" with respect to quantification of projected atmospheric CO2 concentrations on crop yields. Based on one such comparison, it was a...

  6. Applying linear spectral unmixing to airborne hyperspectral imagery for mapping crop yield variability.

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This study evaluated linear spectral unmixing techniques for mapping the variation in crop yield. Both unconstrained and constrained linear spectral unmixing models were applied to airborne hyperspectral imagery recorded from one grain sorghum field and a cotton field. A pair of plant and soil spect...

  7. Three years of crop yields using drainage water management at eight sites in Ohio

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Drainage water management (NRCS-Practice Code 554) is an important water management practice for dealing with nitrate-loading across the Midwest US. A multi-year study is being conducted in Ohio to evaluate the effects of drainage water management on crop yield and water quality. We have installed w...

  8. TILLAGE, COVER CROPS, AND NITROGEN FERTILIZATION EFFECTS ON SOIL NITROGEN AND COTTON AND SORGHUM YIELDS

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Sustainable soil and crop management practices that reduce soil erosion and nitrogen (N) leaching, conserve soil organic matter, and optimize cotton and sorghum yields still remain a challenge. We examined the influence of three tillage practices (no-till, strip till, and chisel till ), four cover c...

  9. Potential for Improved Crop Yield Prediction Through Assimilation of Satellite-Derived Soil Moisture Data

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Crop yield estimates have a strong impact on dealing with food shortages and on market demand and supply; these estimates are critical for decision-making processes by the U.S. Government, policy makers, stakeholders, etc. Most of the decision making is based on forecasts provided by the U.S. Depart...

  10. A GPS Backpack System for Mapping Soil and Crop Parameters in Agricultural Fields

    NASA Astrophysics Data System (ADS)

    Stafford, J. V.; Lebars, J. M.

    Farmers are having to gather increasing amounts of data on their soils and crops. Precision agriculture metre-by-metre is based on a knowledge of the spatial variation of soil and crop parameters across a field. The data has to be spatially located and GPS is an effective way of doing this. A backpack data logging system with GPS position tagging is described which has been designed to aid a fanner in the manual collection of data.

  11. Mind the Gap: How do climate and agricultural management explain the "yield gap" of croplands around the world?

    NASA Astrophysics Data System (ADS)

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

    2007-12-01

    At present, cultivated lands extend across approximately fifteen million square kilometers of the Earth's surface, making it one of the most dominant land cover types. The management practices used on these lands have become increasingly intensified, requiring large inputs of fertilizers and water, in addition to mechanization and biotechnology. These intensified practices have had implications for ecosystem goods and services ranging from water quality and availability to carbon sequestration. However, the billions of additional people that are projected to inhabit the planet in the twenty-first century will require further outputs from our global agricultural system. Given our food system's already expansive and intensive state, it is important to consider where the additional yields might come from and what additional management inputs this might require. In this study, we compare yields both within crop types and within regions of similar climate to determine where yield gaps exist. We do so using recently created, five-minute datasets of the area harvested and yield of 175 different crop types for the year 2000. We also explore the links of these yield gaps to global patterns of management. For example, we consider the ways in which management practices such as irrigation and fire are influencing yields around the world - analyses that can help critically evaluate the level of management currently employed and help imagine what management might be necessary to achieve higher yields in the future. These data will be needed in the next generation of Earth System models, in order to better represent the practices of agricultural land use in more realistic ways, thereby improving our understanding of land use / land cover change on the global carbon and water cycles, and the climate system.

  12. Agricultural water demand, water quality and crop suitability in Souk-Alkhamis Al-Khums, Libya

    NASA Astrophysics Data System (ADS)

    Abunnour, Mohamed Ali; Hashim, Noorazuan Bin Md.; Jaafar, Mokhtar Bin

    2016-06-01

    Water scarcity, unequal population distribution and agricultural activities increased in the coastal plains, and the probability of seawater intrusion with ground water. According to this, the quantitative and qualitative deterioration of underground water quality has become a potential for the occurrence, in addition to the decline in agricultural production in the study area. This paper aims to discover the use of ground water for irrigation in agriculture and their suitability and compatibility for agricultural. On the other hand, the quality is determines by the cultivated crops. 16 random samples of regular groundwater are collected and analyzed chemically. Questionnaires are also distributed randomly on regular basis to farmers.

  13. Research report on development of sweet sorghum as an energy crop. Volume I. Agricultural Task to US Department of Energy

    SciTech Connect

    Arthur, M.F.; Davis, M.; Kresovich, S.; Lawhon, W.T.; Lipinsky, E.S.; Price, M.; Rudolph, A

    1980-05-31

    An interregional experimental agricultural task was undertaken to evaluate biomass and sugar yields of sweet sorghum using similar cultural practices. Climatic conditions varied from North Dakota to southern Texas and Florida having respective frost-free days of 121 and 300. Maximum yields obtained in 1978 and 1979 at the various experimental locations ranged from 12.0 to 40.5 t/ha for dry biomass and from 2.9 to 13.2 t/ha for total sugars. Assuming 582 1 of ethanol can be produced per metric ton of sugars, equivalent ethanol yields range from 1688 to 7682 1/ha. In addition to sweet sorghum, new sorghum hybrids, male-sterile corn, and sugarcane were investigated as potential sugar-stalk crops for producing ethanol from fermentation.

  14. Agricultural Production and Business Management: Volume 1 (Crops).

    ERIC Educational Resources Information Center

    Mercer, R. J., Ed.

    The curriculum guide is the first part of a two-year program developed as part of revision of the total agricultural education curriculum in South Carolina. The project was designed to implement the following changes: (1) provide a more comprehensive vocational offering; (2) place a greater emphasis on behavioral objectives; (3) place a greater…

  15. Nutrient Losses from Row Crop Agriculture in Indiana

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Nutrient losses from agriculture in the Midwestern United States have been identified as contributing to water quality problems such as hypoxia in the Gulf of Mexico, and eutrophication in the great lakes. Fields and catchments in the Cedar Creek sub-watershed of the St. Joseph River basin were mon...

  16. Lady Beetles (Coleoptera: Coccinellidae: Coccinellini) Associated with Alaskan Agricultural Crops

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Coccinellid populations were monitored in agricultural areas of the Tanana and Matanuska-Susitna river valleys of Alaska from 2004 to 2005. Ten species were confirmed from the University of Alaska, Fairbanks, Museum of the North Insect Collection and 13 species were collected in association with Ala...

  17. Innovating Conservation Agriculture: The Case of No-Till Cropping

    ERIC Educational Resources Information Center

    Coughenour, C. Milton

    2003-01-01

    The extensive sociological studies of conservation agriculture have provided considerable understanding of farmers' use of conservation practices, but attempts to develop predictive models have failed. Reviews of research findings question the utility of the conceptual and methodological perspectives of prior research. The argument advanced here…

  18. Safeguarding fruit crops in the age of agricultural globalization

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The expansion of fruit production and markets into new geographic areas provides novel opportunities and challenges for the agricultural and marketing industries. In today’s competitive global market environment, growers need access to the best material available in terms of genetics and plant heal...

  19. [Effect of earthworm inoculation on soil carbon and nitrogen dynamics and on crop yield with application of corn residues].

    PubMed

    Li, Huixin; Hu, Feng; Shen, Qirong; Chen, Xiaoyun; Cang, Long; Wang, Xia

    2002-12-01

    This study was carried out in the Experimental Station of Nanjing Agricultural University, which is in a subtropical monsoon region characterized by a warm-wet spring and a hot-dry summer. The annual average temperature, precipitation and evaporation are 15.6 degrees C, 1010 mm and 1560 mm, respectively. In 1999, the experimental plots (2.8 m x 1.0 m x 0.6 m) were established by concrete frame. Soil in the plots was orthic aquisols collected from Rugao County, Jiangsu Province. Crop rotation was upland rice and winter wheat. At the beginning of the first crop (rice) season, earthworms (Pheretima sp.) were inoculated at a density of 10.m-2 and 20.m-2, respectively, in the plots with an application of corn residues at the rate of 1500 g.m-2(750 g.m-2 in the following seasons). The responses of soil carbon and nitrogen and crop yield to earthworm activity were investigated from 1999 to 2001. The results showed that earthworms had no significant influences on total soil carbon and nitrogen content, which implied that there was no depletion of soil carbon and nitrogen pools in the presence of earthworms. The maintenance of soil carbon might be explained by low assimilation efficiency of organic matter by earthworms, and by the compensation of carbon returning from plant production enhancement. Soil mineral nitrogen, soil microbial biomass carbon and microbial biomass nitrogen were increased, and nitrogen mineralization was strengthened by earthworm activities, which was more obvious at jointing/booting and heading stages. In comparison with no-worm treatments, the yield of rice wheat increased by 9.3% and 5.1%, respectively, in the treatments inoculated with earthworms. It was concluded that earthworm was very important in promoting nitrogen recycling of crop residues and plant productivity, and in keeping the balance of soil carbon pool as well. PMID:12682972

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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