Variation in canopy duration in the perennial biofuel crop Miscanthus reveals complex associations with yield.

PubMed

Robson, Paul R H; Farrar, Kerrie; Gay, Alan P; Jensen, Elaine F; Clifton-Brown, John C; Donnison, Iain S

2013-05-01

Energy crops can provide a sustainable source of power and fuels, and mitigate the negative effects of CO2 emissions associated with fossil fuel use. Miscanthus is a perennial C4 energy crop capable of producing large biomass yields whilst requiring low levels of input. Miscanthus is largely unimproved and therefore there could be significant opportunities to increase yield. Further increases in yield will improve the economics, energy balance, and carbon mitigation of the crop, as well as reducing land-take. One strategy to increase yield in Miscanthus is to maximize the light captured through an extension of canopy duration. In this study, canopy duration was compared among a diverse collection of 244 Miscanthus genotypes. Canopy duration was determined by calculating the number of days between canopy establishment and senescence. Yield was positively correlated with canopy duration. Earlier establishment and later senescence were also both separately correlated with higher yield. However, although genotypes with short canopy durations were low yielding, not all genotypes with long canopy durations were high yielding. Differences of yield between genotypes with long canopy durations were associated with variation in stem and leaf traits. Different methodologies to assess canopy duration traits were investigated, including visual assessment, image analysis, light interception, and different trait thresholds. The highest correlation coefficients were associated with later assessments of traits and the use of quantum sensors for canopy establishment. A model for trait optimization to enable yield improvement in Miscanthus and other bioenergy crops is discussed.

Variation in canopy duration in the perennial biofuel crop Miscanthus reveals complex associations with yield

PubMed Central

Robson, Paul R.H.; Farrar, Kerrie; Gay, Alan P.; Jensen, Elaine F.; Clifton-Brown, John C.; Donnison, Iain S.

2013-01-01

Energy crops can provide a sustainable source of power and fuels, and mitigate the negative effects of CO2 emissions associated with fossil fuel use. Miscanthus is a perennial C4 energy crop capable of producing large biomass yields whilst requiring low levels of input. Miscanthus is largely unimproved and therefore there could be significant opportunities to increase yield. Further increases in yield will improve the economics, energy balance, and carbon mitigation of the crop, as well as reducing land-take. One strategy to increase yield in Miscanthus is to maximize the light captured through an extension of canopy duration. In this study, canopy duration was compared among a diverse collection of 244 Miscanthus genotypes. Canopy duration was determined by calculating the number of days between canopy establishment and senescence. Yield was positively correlated with canopy duration. Earlier establishment and later senescence were also both separately correlated with higher yield. However, although genotypes with short canopy durations were low yielding, not all genotypes with long canopy durations were high yielding. Differences of yield between genotypes with long canopy durations were associated with variation in stem and leaf traits. Different methodologies to assess canopy duration traits were investigated, including visual assessment, image analysis, light interception, and different trait thresholds. The highest correlation coefficients were associated with later assessments of traits and the use of quantum sensors for canopy establishment. A model for trait optimization to enable yield improvement in Miscanthus and other bioenergy crops is discussed. PMID:23599277

Strategies for soil-based precision agriculture in cotton

NASA Astrophysics Data System (ADS)

Neely, Haly L.; Morgan, Cristine L. S.; Stanislav, Scott; Rouze, Gregory; Shi, Yeyin; Thomasson, J. Alex; Valasek, John; Olsenholler, Jeff

2016-05-01

The goal of precision agriculture is to increase crop yield while maximizing the use efficiency of farm resources. In this application, UAV-based systems are presenting agricultural researchers with an opportunity to study crop response to environmental and management factors in real-time without disturbing the crop. The spatial variability soil properties, which drive crop yield and quality, cannot be changed and thus keen agronomic choices with soil variability in mind have the potential to increase profits. Additionally, measuring crop stress over time and in response to management and environmental conditions may enable agronomists and plant breeders to make more informed decisions about variety selection than the traditional end-of-season yield and quality measurements. In a previous study, seed-cotton yield was measured over 4 years and compared with soil variability as mapped by a proximal soil sensor. It was found that soil properties had a significant effect on seed-cotton yield and the effect was not consistent across years due to different precipitation conditions. However, when seed-cotton yield was compared to the normalized difference vegetation index (NDVI), as measured using a multispectral camera from a UAV, predictions improved. Further improvement was seen when soil-only pixels were removed from the analysis. On-going studies are using UAV-based data to uncover the thresholds for stress and yield potential. Long-term goals of this research include detecting stress before yield is reduced and selecting better adapted varieties.

Soil Functional Zone Management: A Vehicle for Enhancing Production and Soil Ecosystem Services in Row-Crop Agroecosystems.

PubMed

Williams, Alwyn; Kane, Daniel A; Ewing, Patrick M; Atwood, Lesley W; Jilling, Andrea; Li, Meng; Lou, Yi; Davis, Adam S; Grandy, A Stuart; Huerd, Sheri C; Hunter, Mitchell C; Koide, Roger T; Mortensen, David A; Smith, Richard G; Snapp, Sieglinde S; Spokas, Kurt A; Yannarell, Anthony C; Jordan, Nicholas R

2016-01-01

There is increasing global demand for food, bioenergy feedstocks and a wide variety of bio-based products. In response, agriculture has advanced production, but is increasingly depleting soil regulating and supporting ecosystem services. New production systems have emerged, such as no-tillage, that can enhance soil services but may limit yields. Moving forward, agricultural systems must reduce trade-offs between production and soil services. Soil functional zone management (SFZM) is a novel strategy for developing sustainable production systems that attempts to integrate the benefits of conventional, intensive agriculture, and no-tillage. SFZM creates distinct functional zones within crop row and inter-row spaces. By incorporating decimeter-scale spatial and temporal heterogeneity, SFZM attempts to foster greater soil biodiversity and integrate complementary soil processes at the sub-field level. Such integration maximizes soil services by creating zones of 'active turnover', optimized for crop growth and yield (provisioning services); and adjacent zones of 'soil building', that promote soil structure development, carbon storage, and moisture regulation (regulating and supporting services). These zones allow SFZM to secure existing agricultural productivity while avoiding or minimizing trade-offs with soil ecosystem services. Moreover, the specific properties of SFZM may enable sustainable increases in provisioning services via temporal intensification (expanding the portion of the year during which harvestable crops are grown). We present a conceptual model of 'virtuous cycles', illustrating how increases in crop yields within SFZM systems could create self-reinforcing feedback processes with desirable effects, including mitigation of trade-offs between yield maximization and soil ecosystem services. Through the creation of functionally distinct but interacting zones, SFZM may provide a vehicle for optimizing the delivery of multiple goods and services in agricultural systems, allowing sustainable temporal intensification while protecting and enhancing soil functioning.

Soil Functional Zone Management: A Vehicle for Enhancing Production and Soil Ecosystem Services in Row-Crop Agroecosystems

PubMed Central

Williams, Alwyn; Kane, Daniel A.; Ewing, Patrick M.; Atwood, Lesley W.; Jilling, Andrea; Li, Meng; Lou, Yi; Davis, Adam S.; Grandy, A. Stuart; Huerd, Sheri C.; Hunter, Mitchell C.; Koide, Roger T.; Mortensen, David A.; Smith, Richard G.; Snapp, Sieglinde S.; Spokas, Kurt A.; Yannarell, Anthony C.; Jordan, Nicholas R.

2016-01-01

There is increasing global demand for food, bioenergy feedstocks and a wide variety of bio-based products. In response, agriculture has advanced production, but is increasingly depleting soil regulating and supporting ecosystem services. New production systems have emerged, such as no-tillage, that can enhance soil services but may limit yields. Moving forward, agricultural systems must reduce trade-offs between production and soil services. Soil functional zone management (SFZM) is a novel strategy for developing sustainable production systems that attempts to integrate the benefits of conventional, intensive agriculture, and no-tillage. SFZM creates distinct functional zones within crop row and inter-row spaces. By incorporating decimeter-scale spatial and temporal heterogeneity, SFZM attempts to foster greater soil biodiversity and integrate complementary soil processes at the sub-field level. Such integration maximizes soil services by creating zones of ‘active turnover’, optimized for crop growth and yield (provisioning services); and adjacent zones of ‘soil building’, that promote soil structure development, carbon storage, and moisture regulation (regulating and supporting services). These zones allow SFZM to secure existing agricultural productivity while avoiding or minimizing trade-offs with soil ecosystem services. Moreover, the specific properties of SFZM may enable sustainable increases in provisioning services via temporal intensification (expanding the portion of the year during which harvestable crops are grown). We present a conceptual model of ‘virtuous cycles’, illustrating how increases in crop yields within SFZM systems could create self-reinforcing feedback processes with desirable effects, including mitigation of trade-offs between yield maximization and soil ecosystem services. Through the creation of functionally distinct but interacting zones, SFZM may provide a vehicle for optimizing the delivery of multiple goods and services in agricultural systems, allowing sustainable temporal intensification while protecting and enhancing soil functioning. PMID:26904043

Drought tolerant (DT) and non-DT corn production under center pivot irrigation in the Texas High Plains

USDA-ARS?s Scientific Manuscript database

Corn (Zea mays L.) for feed is an important crop in the Texas High Plains region. However, it requires more water than the other major crops grown in the area to maximize grain yields. Pumping water for agriculture from the declining Ogallala Aquifer is of concern and improving irrigation water use ...

Leaf and canopy scale drivers of genotypic variation in soybean response to elevated carbon dioxide concentration

USDA-ARS?s Scientific Manuscript database

The atmospheric [CO2] in which crops grow today is greater than at any point in their domestication history, and represents an opportunity for positive effects on seed yield that can counteract the negative effects of greater heat and drought this century. In order to maximize yields under future at...

The genetic and molecular basis of crop height based on a rice model.

PubMed

Liu, Fang; Wang, Pandi; Zhang, Xiaobo; Li, Xiaofei; Yan, Xiaohong; Fu, Donghui; Wu, Gang

2018-01-01

This review presents genetic and molecular basis of crop height using a rice crop model. Height is controlled by multiple genes with potential to be manipulated through breeding strategies to improve productivity. Height is an important factor affecting crop architecture, apical dominance, biomass, resistance to lodging, tolerance to crowding and mechanical harvesting. The impressive increase in wheat and rice yield during the 'green revolution' benefited from a combination of breeding for high-yielding dwarf varieties together with advances in agricultural mechanization, irrigation and agrochemical/fertilizer use. To maximize yield under irrigation and high fertilizer use, semi-dwarfing is optimal, whereas extreme dwarfing leads to decreased yield. Rice plant height is controlled by genes that lie in a complex regulatory network, mainly involved in the biosynthesis or signal transduction of phytohormones such as gibberellins, brassinosteroids and strigolactones. Additional dwarfing genes have been discovered that are involved in other pathways, some of which are uncharacterized. This review discusses our current understanding of the regulation of plant height using rice as a well-characterized model and highlights some of the most promising research that could lead to the development of new, high-yielding varieties. This knowledge underpins future work towards the genetic improvement of plant height in rice and other crops.

Biodiversity management of organic farming enhances agricultural sustainability

PubMed Central

Liu, Haitao; Meng, Jie; Bo, Wenjing; Cheng, Da; Li, Yong; Guo, Liyue; Li, Caihong; Zheng, Yanhai; Liu, Meizhen; Ning, Tangyuan; Wu, Guanglei; Yu, Xiaofan; Feng, Sufei; Wuyun, Tana; Li, Jing; Li, Lijun; Zeng, Yan; Liu, Shi V.; Jiang, Gaoming

2016-01-01

Organic farming (OF) has been believed to be capable of curtailing some hazardous effects associated with chemical farming (CF). However, debates also exist on whether OF can feed a world with increasing human population. We hypothesized that some improvements on OF may produce adequate crops and reduce environmental pollutions from CF. This paper makes comparative analysis of crop yield, soil organic matter and economic benefits within the practice on Biodiversity Management of Organic Farming (BMOF) at Hongyi Organic Farm (HOF) over eight years and between BMOF and CF. Linking crop production with livestock to maximal uses of by-products from each production and avoid xenobiotic chemicals, we have achieved beneficial improvement in soil properties, effective pest and weed control, and increased crop yields. After eight years experiment, we have obtained a gradual but stable increase in crop yields with a 9.6-fold increase of net income. The net income of HOF was 258,827 dollars and 24,423 dollars in 2014 and 2007 respectively. Thus, BMOF can not only feed more population, but also increase adaptive capacity of agriculture ecosystems and gain much higher economic benefits. PMID:27032369

Biodiversity management of organic farming enhances agricultural sustainability

NASA Astrophysics Data System (ADS)

Liu, Haitao; Meng, Jie; Bo, Wenjing; Cheng, Da; Li, Yong; Guo, Liyue; Li, Caihong; Zheng, Yanhai; Liu, Meizhen; Ning, Tangyuan; Wu, Guanglei; Yu, Xiaofan; Feng, Sufei; Wuyun, Tana; Li, Jing; Li, Lijun; Zeng, Yan; Liu, Shi V.; Jiang, Gaoming

2016-04-01

Organic farming (OF) has been believed to be capable of curtailing some hazardous effects associated with chemical farming (CF). However, debates also exist on whether OF can feed a world with increasing human population. We hypothesized that some improvements on OF may produce adequate crops and reduce environmental pollutions from CF. This paper makes comparative analysis of crop yield, soil organic matter and economic benefits within the practice on Biodiversity Management of Organic Farming (BMOF) at Hongyi Organic Farm (HOF) over eight years and between BMOF and CF. Linking crop production with livestock to maximal uses of by-products from each production and avoid xenobiotic chemicals, we have achieved beneficial improvement in soil properties, effective pest and weed control, and increased crop yields. After eight years experiment, we have obtained a gradual but stable increase in crop yields with a 9.6-fold increase of net income. The net income of HOF was 258,827 dollars and 24,423 dollars in 2014 and 2007 respectively. Thus, BMOF can not only feed more population, but also increase adaptive capacity of agriculture ecosystems and gain much higher economic benefits.

Photoperiod shift effects on yield characteristics of rice

NASA Technical Reports Server (NTRS)

Volk, G. M.; Mitchell, C. A.

1995-01-01

Edible yield must be maximized for each crop species selected for inclusion in the Controlled Ecological Life-Support System (CELSS) proposed by NASA to support long-term manned space missions. In a greenhouse study aimed at increasing biomass partitioning to rice (Oryza sativa L.) grain, plants of the high yielding semi-dwarf rice cultivar Ai-Nan-Tsao were started in pots under 8-h photoperiods at a density of 212 plants m-2. After different periods of time under 8-h photoperiods, pots were switched to continuous light for the remainder of the cropping cycle. Continuous light did not delay time to first panicle emergence (60 d) or time to harvest (83 d). There was a positive correlation between the length of continuous light treatments and nongrain biomass. Grain yield (1.6 +/- 0.2 g plant-1) did not increase in continuous light. Yield-efficiency rate (grain weight per length of cropping cycle, canopy volume, and weight of nongrain shoot biomass) was used to compare treatments. Small Ai-Nan-Tsao rice canopies grown under 8-h photoperiods were more efficient producers of grain than canopies grown under continuous light for a portion of the rice cropping cycle.

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.

Fewer not more leaves - Key to obtaining the needed jump in crop yield potential and water use efficiency

NASA Astrophysics Data System (ADS)

Srinivasan, V.; Kumar, P.; Long, S.

2013-12-01

Word food and feed supply needs to increase by 75% by 2050 to meet the increasing demands of our growing population. Soybean which is the world`s fourth most important crop in terms of total production at 250 million Mt/yr is a key protein source, and together with rice and wheat, are experiencing declining global yield increases year on year. At present rates of improvement, 2050 targets cannot be reached without new innovations. In this study we demonstrate an innovative approach that could provide a yield jump. While, natural selection favors individual plants to maximize leaf production to maximize light interception and shade competitors, the presence of this trait in domestic crops could be disadvantageous. In addition, rising CO2 causes increased leaf production further exacerbating the problem. Here, we show by mathematical model and field experiment that, a modern cultivar growing at the center of US soy cultivation produces too many leaves and reduction to an optimal level would increase yield. Our model results indicate that an LAI of 3.5 and 3.8 produces maximal rates of net canopy assimilation under ambient and elevated CO2 conditions respectively. However, observed peak LAI values are 6.9 and 7.5 under ambient and elevated CO2 conditions respectively. This results in a NPP loss of 30% and 20% under ambient and elevated CO2 conditions respectively. Furthermore, the optimal LAI results in a decreased transpiration of up to 30% thus increasing water use efficiency. We show that as LAI increases, the tradeoffs between diminishing day time gains in NPP, and increasing losses in respiration is responsible for this effect. By designing a more optimum canopy, we can increase NPP and this potentially translates to increased seed yield. To test this model result, we perform canopy manipulation experiments on soybean plants, where we artificially decrease LAI by periodically removing young and emerging leaves throughout the growing season (after pod onset), and measure the seed yield under ambient and elevated CO2 conditions. Our experimental results show that an LAI reduction of 0.5 results in an increased seed yield of 8.1% validating our model results. We propose that, by achieving a stronger LAI reduction, we can improve seed yields by up to 24% providing the much needed jump in yield to achieve future food security.

Tradeoffs between Maize Silage Yield and Nitrate Leaching in a Mediterranean Nitrate-Vulnerable Zone under Current and Projected Climate Scenarios

PubMed Central

Basso, Bruno; Giola, Pietro; Dumont, Benjamin; Migliorati, Massimiliano De Antoni; Cammarano, Davide; Pruneddu, Giovanni; Giunta, Francesco

2016-01-01

Future climatic changes may have profound impacts on cropping systems and affect the agronomic and environmental sustainability of current N management practices. The objectives of this work were to i) evaluate the ability of the SALUS crop model to reproduce experimental crop yield and soil nitrate dynamics results under different N fertilizer treatments in a farmer’s field, ii) use the SALUS model to estimate the impacts of different N fertilizer treatments on NO3- leaching under future climate scenarios generated by twenty nine different global circulation models, and iii) identify the management system that best minimizes NO3- leaching and maximizes yield under projected future climate conditions. A field experiment (maize-triticale rotation) was conducted in a nitrate vulnerable zone on the west coast of Sardinia, Italy to evaluate N management strategies that include urea fertilization (NMIN), conventional fertilization with dairy slurry and urea (CONV), and no fertilization (N0). An ensemble of 29 global circulation models (GCM) was used to simulate different climate scenarios for two Representative Circulation Pathways (RCP6.0 and RCP8.5) and evaluate potential nitrate leaching and biomass production in this region over the next 50 years. Data collected from two growing seasons showed that the SALUS model adequately simulated both nitrate leaching and crop yield, with a relative error that ranged between 0.4% and 13%. Nitrate losses under RCP8.5 were lower than under RCP6.0 only for NMIN. Accordingly, levels of plant N uptake, N use efficiency and biomass production were higher under RCP8.5 than RCP6.0. Simulations under both RCP scenarios indicated that the NMIN treatment demonstrated both the highest biomass production and NO3- losses. The newly proposed best management practice (BMP), developed from crop N uptake data, was identified as the optimal N fertilizer management practice since it minimized NO3- leaching and maximized biomass production over the long term. PMID:26784113

Comparison of SVAT models for simulating and optimizing deficit irrigation systems in arid and semi-arid countries under climate variability

NASA Astrophysics Data System (ADS)

Kloss, Sebastian; Schuetze, Niels; Schmitz, Gerd H.

2010-05-01

The strong competition for fresh water in order to fulfill the increased demand for food worldwide has led to a renewed interest in techniques to improve water use efficiency (WUE) such as controlled deficit irrigation. Furthermore, as the implementation of crop models into complex decision support systems becomes more and more common, it is imperative to reliably predict the WUE as ratio of water consumption and yield. The objective of this paper is the assessment of the problems the crop models - such as FAO-33, DAISY, and APSIM in this study - face when maximizing the WUE. We applied these crop models for calculating the risk in yield reduction in view of different sources of uncertainty (e.g. climate) employing a stochastic framework for decision support for the planning of water supply in irrigation. The stochastic framework consists of: (i) a weather generator for simulating regional impacts of climate change; (ii) a new tailor-made evolutionary optimization algorithm for optimal irrigation scheduling with limited water supply; and (iii) the above mentioned models for simulating water transport and crop growth in a sound manner. The results present stochastic crop water production functions (SCWPF) for different crops which can be used as basic tools for assessing the impact of climate variability on the risk for the potential yield. Case studies from India, Oman, Malawi, and France are presented to assess the differences in modeling water stress and yield response for the different crop models.

Site Specific Management of Cotton Production in the United States

USDA-ARS?s Scientific Manuscript database

Site-specific management or precision agriculture, as it is evolving in large-scale crop production, offers promising new methods for managing cotton production for optimized yields, maximized profitability, and minimized environmental pollution. However, adaptation of site-specific theory and meth...

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

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

Sensitivity of commercial pumpkin yield to potential decline among different groups of pollinating bees.

PubMed

Pfister, Sonja C; Eckerter, Philipp W; Schirmel, Jens; Cresswell, James E; Entling, Martin H

2017-05-01

The yield of animal-pollinated crops is threatened by bee declines, but its precise sensitivity is poorly known. We therefore determined the yield dependence of Hokkaido pumpkin in Germany on insect pollination by quantifying: (i) the relationship between pollen receipt and fruit set and (ii) the cumulative pollen deposition of each pollinator group. We found that approximately 2500 pollen grains per flower were needed to maximize fruit set. At the measured rates of flower visitation, we estimated that bumblebees (21 visits/flower lifetime, 864 grains/visit) or honeybees (123 visits, 260 grains) could individually achieve maximum crop yield, whereas halictid bees are ineffective (11 visits, 16 grains). The pollinator fauna was capable of delivering 20 times the necessary amount of pollen. We therefore estimate that pumpkin yield was not pollination-limited in our study region and that it is currently fairly resilient to single declines of honeybees or wild bumblebees.

Sensitivity of commercial pumpkin yield to potential decline among different groups of pollinating bees

PubMed Central

Eckerter, Philipp W.; Schirmel, Jens; Cresswell, James E.; Entling, Martin H.

2017-01-01

The yield of animal-pollinated crops is threatened by bee declines, but its precise sensitivity is poorly known. We therefore determined the yield dependence of Hokkaido pumpkin in Germany on insect pollination by quantifying: (i) the relationship between pollen receipt and fruit set and (ii) the cumulative pollen deposition of each pollinator group. We found that approximately 2500 pollen grains per flower were needed to maximize fruit set. At the measured rates of flower visitation, we estimated that bumblebees (21 visits/flower lifetime, 864 grains/visit) or honeybees (123 visits, 260 grains) could individually achieve maximum crop yield, whereas halictid bees are ineffective (11 visits, 16 grains). The pollinator fauna was capable of delivering 20 times the necessary amount of pollen. We therefore estimate that pumpkin yield was not pollination-limited in our study region and that it is currently fairly resilient to single declines of honeybees or wild bumblebees. PMID:28573019

[Maximization of economic yield, minimum cost optimal diets and cultivation diversification for small scale farmers of the highland region of Guatemala].

PubMed

Alarcón, J A; Immink, M D; Méndez, L F

1989-12-01

The present study was conducted as part of an evaluation of the economic and nutritional effects of a crop diversification program for small-scale farmers in the Western highlands of Guatemala. Linear programming models are employed in order to obtain optimal combinations of traditional and non-traditional food crops under different ecological conditions that: a) provide minimum cost diets for auto-consumption, and b) maximize net income and market availability of dietary energy. Data used were generated by means of an agroeconomic survey conducted in 1983 among 726 farming households. Food prices were obtained from the Institute of Agrarian Marketing; data on production costs, from the National Bank of Agricultural Development in Guatemala. The gestation periods for each crop were obtained from three different sources, and then averaged. The results indicated that the optimal cropping pattern for the minimum-cost diets for auto consumption include traditional foods (corn, beans, broad bean, wheat, potato), non-traditional foods (carrots, broccoli, beets) and foods of animal origin (milk, eggs). A significant number of farmers included in the sample did not have sufficient land availability to produce all foods included in the minimum-cost diet. Cropping patterns which maximize net incomes include only non-traditional foods: onions, carrots, broccoli and beets for farmers in the low highland areas, and raddish, broccoli, cauliflower and carrots for farmers in the higher parts. Optimal cropping patterns which maximize market availability of dietary energy include traditional and non-traditional foods; for farmers in the lower areas: wheat, corn, beets, carrots and onions; for farmers in the higher areas: potato, wheat, raddish, carrots and cabbage.

Optimizing cropland cover for stable food production in Sub-Saharan Africa using simulated yield and Modern Portfolio Theory

NASA Astrophysics Data System (ADS)

Bodin, P.; Olin, S.; Pugh, T. A. M.; Arneth, A.

2014-12-01

Food security can be defined as stable access to food of good nutritional quality. In Sub Saharan Africa access to food is strongly linked to local food production and the capacity to generate enough calories to sustain the local population. Therefore it is important in these regions to generate not only sufficiently high yields but also to reduce interannual variability in food production. Traditionally, climate impact simulation studies have focused on factors that underlie maximum productivity ignoring the variability in yield. By using Modern Portfolio Theory, a method stemming from economics, we here calculate optimum current and future crop selection that maintain current yield while minimizing variance, vs. maintaining variance while maximizing yield. Based on simulated yield using the LPJ-GUESS dynamic vegetation model, the results show that current cropland distribution for many crops is close to these optimum distributions. Even so, the optimizations displayed substantial potential to either increase food production and/or to decrease its variance regionally. Our approach can also be seen as a method to create future scenarios for the sown areas of crops in regions where local food production is important for food security.

Accelerating Commercial Remote Sensing

NASA Technical Reports Server (NTRS)

1995-01-01

Through the Visiting Investigator Program (VIP) at Stennis Space Center, Community Coffee was able to use satellites to forecast coffee crops in Guatemala. Using satellite imagery, the company can produce detailed maps that separate coffee cropland from wild vegetation and show information on the health of specific crops. The data can control coffee prices and eventually may be used to optimize application of fertilizers, pesticides and irrigation. This would result in maximal crop yields, minimal pollution and lower production costs. VIP is a mechanism involving NASA funding designed to accelerate the growth of commercial remote sensing by promoting general awareness and basic training in the technology.

Earth benefits of interdisciplinary CELSS-related research by the NSCORT in Bioregenerative Life Support

NASA Technical Reports Server (NTRS)

Mitchell, C.; Sherman, L.; Nielsen, S.; Nelson, P.; Trumbo, P.; Hodges, T.; Hasegawa, P.; Bressan, R.; Ladisch, M.; Auslander, D.

1996-01-01

Earth benefits of research from the NSCORT in Bioregenerative Life Support will include the following: development of active control mechanisms for light, CO2, and temperature to maximize photosynthesis of crop plants during important phases of crop development; automation of crop culture systems; creation of novel culture systems for optimum productivity; creation of value-added crops with superior nutritional, yield, and waste-process characteristics; environmental control of food and toxicant composition of crops; new process technologies and novel food products for safe, nutritious, palatable vegetarian diets; creation of menus for healthful vegetarian diets with psychological acceptability; enzymatic procedures to degrade recalcitrant crop residues occurring in municipal waste; control-system strategies to ensure sustainabilty of a CELSS that will enable management of diverse complex systems on Earth.

Earth benefits of interdisciplinary celss-related research by the NSCORT in Bioregenerative Life Support

NASA Astrophysics Data System (ADS)

Mitchell, C.; Sherman, L.; Nielsen, S.; Nelson, P.; Trumbo, P.; Hodges, T.; Hasegawa, P.; Bressan, R.; Ladisch, M.; Auslander, D.

Earth benefits of research from the NSCORT in Bioregenerative Life Support will include the following: development of active control mechanisms for light, CO_2, and temperature to maximize photosynthesis of crop plants during important phases of crop development; automation of crop culture systems; creation of novel culture systems for optimum productivity; creation of value-added crops with superior nutritional, yield, and waste-process characteristics; environmental control of food and toxicant composition of crops; new process technologies and novel food products for safe, nutritious, palatable vegetarian diets; creation of menus for healthful vegetarian diets with psychological acceptability; enzymatic procedures to degrade recalcitrant crop residues occurring in municipal waste; control-system strategies to ensure sustainability of a CELSS that will enable management of diverse complex systems on Earth.

Earth benefits of interdisciplinary CELSS-related research by the NSCORT in Bioregenerative Life Support.

PubMed

Mitchell, C; Sherman, L; Nielsen, S; Nelson, P; Trumbo, P; Hodges, T; Hasegawa, P; Bressan, R; Ladisch, M; Auslander, D

1996-01-01

Earth benefits of research from the NSCORT in Bioregenerative Life Support will include the following: development of active control mechanisms for light, CO2, and temperature to maximize photosynthesis of crop plants during important phases of crop development; automation of crop culture systems; creation of novel culture systems for optimum productivity; creation of value-added crops with superior nutritional, yield, and waste-process characteristics; environmental control of food and toxicant composition of crops; new process technologies and novel food products for safe, nutritious, palatable vegetarian diets; creation of menus for healthful vegetarian diets with psychological acceptability; enzymatic procedures to degrade recalcitrant crop residues occurring in municipal waste; control-system strategies to ensure sustainabilty of a CELSS that will enable management of diverse complex systems on Earth.

Irrigation scheduling: When, where, and how much?

USDA-ARS?s Scientific Manuscript database

Irrigation scheduling, a key element of proper water management, is the accurate forecasting of water application (amount and timing) for optimal crop production (yield and fruit quality). The goal is to apply the correct amount of water at the right time to minimize irrigation costs and maximize cr...

Topographic controls on soil nutrient variations in a Silvopasture system

USDA-ARS?s Scientific Manuscript database

Topography plays a crucial role in the spatial distribution of nutrients in soils because of its influence on the flow and (re)distribution of water and energy in a landscape. Information on the spatial pattern of soil nutrient distribution would benefit management decisions to maximize crop yield a...

Soybean Cultivar Variation in Response to Elevated Ozone Concentration

USDA-ARS?s Scientific Manuscript database

Crop losses to ozone damage are conservatively estimated to cost $1 to $3 billion in the U.S. These costs will rise as surface-level ozone increases over this century. A critical step in maximizing soybean yield in a future of rising tropospheric ozone is identifying variation in cultivar responses,...

Profitability and risk analysis of soybean planting date by maturity group

USDA-ARS?s Scientific Manuscript database

Limited knowledge exists on estimated soybean yield response to planting date to determine the profit-maximizing planting date for soybean production by maturity group (MG) in the southern United States. Furthermore, determining the optimal MG and crop insurance coverage level that is preferred by r...

Sunflower response to irrigation from limited water supplies with no-till management

USDA-ARS?s Scientific Manuscript database

Limited irrigation necessitates maximizing economic returns by rotating crops, so we conducted a field study during 2005-2009 in southwest Kansas to determine the yield response of sunflower to irrigation and evapotranspiration (ETc) and to measure plant growth parameters and soil water use. Sunflow...

The development and use of a molecular model for soybean maturity groups

USDA-ARS?s Scientific Manuscript database

Achieving appropriate maturity in a target environment is essential to maximizing crop yield potential. In soybean [Glycine max (L.) Merr.], the time to maturity is largely dependent on developmental response to dark periods. Once the critical photoperiod is reached, flowering is initiated and rep...

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

PubMed

Cui, Zhenling; Chen, Xinping; Zhang, Fusuo

2010-01-01

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

Spatial variability of surface temperature as related to cropping practice with implications for irrigation management

NASA Technical Reports Server (NTRS)

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

1980-01-01

Crop stress measured using thermal infrared emission is evaluated with the stress-degree-day (SDD) concept. Throughout the season, the accumulation of SDD during the reproductive stage of growth is inversely related to yield. This relationship is shown for durum wheat, hard red winter wheat, barley, grain sorghum and soybeans. It is noted that SDD can be used to schedule irrigations for maximizing yields and for applying remotely sensed data to management of water resources. An airborne flight with a thermal-IR scanner was used to examine the variability in temperature that may exist from one field to another and to determine realistic within-field temperature variations. It was found that the airborne and the ground-based data agreed very well and that there was less variability in the fields that were completely covered with crops than those of bare soil.

More crop per drop - Increasing input efficiency in sprinkler irrigated potatoes.

NASA Astrophysics Data System (ADS)

Kostka, Stan; Fang, Lisa; Ren, Haiqin; Glucksman, Robert; Gadd, Nick

2014-05-01

Water scarcity, climate change, and population growth are significant global challenges for producing sufficient food, fiber, and fuel in the 21st century. Feeding an increasingly hungry world necessitates innovative strategies and technologies to maximize crop production outputs while simultaneously increasing crop water productivity. In the 20th century, major advances in precision irrigation enabled producers to increase productivity while more efficiently applying water to crops. While pressurized irrigation systems can deliver water effectively to the soil surface, the efficiency of rootzone delivery may be compromised by intrinsic heterogeneities in soil wetting characteristics related to organic matter, biofilms, and hydrophobic coatings on soil particles and aggregates. Efficiently delivering applied irrigation water throughout the soil matrix is critical to increasing crop productivity. We propose that management of soil water access by surfactants is a viable management option to maintain or increase yields under deficit irrigation. Potato yield and tuber quality under sprinkler irrigation were evaluated under standard production practices or with the inclusion of an aqueous nonionic surfactant formulation (10 wt% alkoxylated polyols and 7% glucoethers) applied at 10L ha-1 between emergence and tuberization. Crop responses from multi-year evaluations conducted on irrigated potatoes in Idaho (USA) were compared to multi-year on farm grower evaluations in Australia and China. Surfactant treatment resulted in statistically significant increases in yield (+5%) and US No. 1 grades (+8%) while reducing culls (-10%) in trials conducted in Idaho, USA. Similar responses were observed in commercial grower evaluations conducted in Australia (+8% total yield, +18% mean tuber weight) and in China in 2011 (+8% total yield and +18% premium, -12% culls). Under diverse production conditions, a single application of the surfactant formulation improved crop water productivity in water stressed environments. Results from these trials support our hypothesis that surfactants may be a viable management practice to improve crop water productivity in a water stressed environments.

Growth and physiological changes in continuously cropped eggplant (Solanum melongena L.) upon relay intercropping with garlic (Allium sativum L.)

PubMed Central

Wang, Mengyi; Wu, Cuinan; Cheng, Zhihui; Meng, Huanwen

2015-01-01

Relay intercropping represents an alternative for sustainable production of vegetables, but the changes of internally antioxidant defense combined with the growth and yield are not clear. Field experiment was carried out to investigate the malondialdehyde (MDA) content and activity levels of superoxide dismutase (SOD), peroxidase (POD), polyphenol oxidase (PPO), and phenylalanine ammonia-lyase (PAL) in eggplant (Solanum melongena L.) and plant height, stem diameter, maximal leaf area, and yield of eggplant grown under successive cropping in the year 2011 and 2012 to see if relay intercropping with garlic (Allium sativum L.) could benefit to eggplant growth and yield. Three experimental treatments with three repeats in each were carried out (completely randomized block design): eggplant monoculture (CK), eggplant relay intercropping with normal garlic (NG), and eggplant relay intercropping with green garlic (GG). In both years, the MDA content was significantly lower and SOD and POD activities were generally lower in NG and GG compared with CK in most sampling dates. PPO activity trends were generally opposite to those of POD. The general trend of PAL activity was similar to MDA. The plant height and stem of eggplant was lower, but the maximal leaf area was larger in NG and GG in 2011; in 2012 the plant growth was stronger in relay intercropping treatments. For eggplant yield in 2011, NG was 2.85% higher than CK; after the time for the green garlic pulled out was moved forward in 2012, the yield was increased by 6.26 and 7.80%, respectively, in NG and GG. The lower MDA content and enzyme activities in relay intercropping treatments showed that the eggplant suffered less damage from environment and continuous cropping obstacles, which promoted healthier plant. Thus from both the growth and physiological perspective, it was concluded that eggplant/garlic relay intercropping is a beneficial cultivation practice maintaining stronger plant growth and higher yield. PMID:25964788

Growth and physiological changes in continuously cropped eggplant (Solanum melongena L.) upon relay intercropping with garlic (Allium sativum L.).

PubMed

Wang, Mengyi; Wu, Cuinan; Cheng, Zhihui; Meng, Huanwen

2015-01-01

Relay intercropping represents an alternative for sustainable production of vegetables, but the changes of internally antioxidant defense combined with the growth and yield are not clear. Field experiment was carried out to investigate the malondialdehyde (MDA) content and activity levels of superoxide dismutase (SOD), peroxidase (POD), polyphenol oxidase (PPO), and phenylalanine ammonia-lyase (PAL) in eggplant (Solanum melongena L.) and plant height, stem diameter, maximal leaf area, and yield of eggplant grown under successive cropping in the year 2011 and 2012 to see if relay intercropping with garlic (Allium sativum L.) could benefit to eggplant growth and yield. Three experimental treatments with three repeats in each were carried out (completely randomized block design): eggplant monoculture (CK), eggplant relay intercropping with normal garlic (NG), and eggplant relay intercropping with green garlic (GG). In both years, the MDA content was significantly lower and SOD and POD activities were generally lower in NG and GG compared with CK in most sampling dates. PPO activity trends were generally opposite to those of POD. The general trend of PAL activity was similar to MDA. The plant height and stem of eggplant was lower, but the maximal leaf area was larger in NG and GG in 2011; in 2012 the plant growth was stronger in relay intercropping treatments. For eggplant yield in 2011, NG was 2.85% higher than CK; after the time for the green garlic pulled out was moved forward in 2012, the yield was increased by 6.26 and 7.80%, respectively, in NG and GG. The lower MDA content and enzyme activities in relay intercropping treatments showed that the eggplant suffered less damage from environment and continuous cropping obstacles, which promoted healthier plant. Thus from both the growth and physiological perspective, it was concluded that eggplant/garlic relay intercropping is a beneficial cultivation practice maintaining stronger plant growth and higher yield.

Biochemical Disincentives to Fertilizing Cellulosic Ethanol Crops

NASA Astrophysics Data System (ADS)

Gallagher, M. E.; Hockaday, W. C.; Snapp, S.; McSwiney, C.; Baldock, J.

2010-12-01

Corn grain biofuel crops produce the highest yields when the cropping ecosystem is not nitrogen (N)-limited, achieved by application of fertilizer. There are environmental consequences for excessive fertilizer application to crops, including greenhouse gas emissions, hypoxic “dead zones,” and health problems from N runoff into groundwater. The increase in corn acreage in response to demand for alternative fuels (i.e. ethanol) could exacerbate these problems, and divert food supplies to fuel production. A potential substitute for grain ethanol that could reduce some of these impacts is cellulosic ethanol. Cellulosic ethanol feedstocks include grasses (switchgrass), hardwoods, and crop residues (e.g. corn stover, wheat straw). It has been assumed that these feedstocks will require similar N fertilization rates to grain biofuel crops to maximize yields, but carbohydrate yield versus N application has not previously been monitored. We report the biochemical stocks (carbohydrate, protein, and lignin in Mg ha-1) of a corn ecosystem grown under varying N levels. We measured biochemical yield in Mg ha-1 within the grain, leaf and stem, and reproductive parts of corn plants grown at seven N fertilization rates (0-202 kg N ha-1), to evaluate the quantity and quality of these feedstocks across a N fertilization gradient. The N fertilization rate study was performed at the Kellogg Biological Station-Long Term Ecological Research Site (KBS-LTER) in Michigan. Biochemical stocks were measured using 13C nuclear magnetic resonance spectroscopy (NMR), combined with a molecular mixing model (Baldock et al. 2004). Carbohydrate and lignin are the main biochemicals of interest in ethanol production since carbohydrate is the ethanol feedstock, and lignin hinders the carbohydrate to ethanol conversion process. We show that corn residue carbohydrate yields respond only weakly to N fertilization compared to grain. Grain carbohydrate yields plateau in response to fertilization at moderate levels (67 kg N ha-1). Increasing fertilizer application beyond the point of diminishing returns for grain (67 kg N ha-1) to double the regionally-recommended amount (202 kg N ha-1) resulted in only marginal increases (25%) in crop residue carbohydrate yield, while increasing lignin yields 41%. In the case of at least this ecosystem, high fertilization rates did not result in large carbohydrate yield increases in the crop residue, and instead produced a lower quality feedstock for cellulosic ethanol production.

Early planting dates maximize winter annual field pennycress (Thlaspi arvense L.) yield and oil content

USDA-ARS?s Scientific Manuscript database

Pennycress (Thlaspi arvense L.), a common weed species in North America, has received attention in recent years as a potential oilseed feedstock for biofuel production. However, little is known about best practices for its production as a managed crop. The objective of this study was to determine op...

Automated sensing of hydroponic macronutrients using a computer-controlled system with an array of ion-selective electrodes

USDA-ARS?s Scientific Manuscript database

Hydroponic production systems grow plants without soil, relying on a circulating solution to provide the necessary nutrients. Maintaining an optimum nutrient balance in this solution is important for maximizing crop growth and yield. Particularly in closed hydroponic systems it is important to monit...

Phenotyping of field-grown wheat in the UK highlights contribution of light response of photosynthesis and flag leaf longevity to grain yield.

PubMed

Carmo-Silva, Elizabete; Andralojc, P John; Scales, Joanna C; Driever, Steven M; Mead, Andrew; Lawson, Tracy; Raines, Christine A; Parry, Martin A J

2017-06-15

Improving photosynthesis is a major target for increasing crop yields and ensuring food security. Phenotyping of photosynthesis in the field is critical to understand the limits to crop performance in agricultural settings. Yet, detailed phenotyping of photosynthetic traits is relatively scarce in field-grown wheat, with previous studies focusing on narrow germplasm selections. Flag leaf photosynthetic traits, crop development, and yield traits were compared in 64 field-grown wheat cultivars in the UK. Pre-anthesis and post-anthesis photosynthetic traits correlated significantly and positively with grain yield and harvest index (HI). These traits included net CO2 assimilation measured at ambient CO2 concentrations and a range of photosynthetic photon flux densities, and traits associated with the light response of photosynthesis. In most cultivars, photosynthesis decreased post-anthesis compared with pre-anthesis, and this was associated with decreased Rubisco activity and abundance. Heritability of photosynthetic traits suggests that phenotypic variation can be used to inform breeding programmes. Specific cultivars were identified with traits relevant to breeding for increased crop yields in the UK: pre-anthesis photosynthesis, post-anthesis photosynthesis, light response of photosynthesis, and Rubisco amounts. The results indicate that flag leaf longevity and operating photosynthetic activity in the canopy can be further exploited to maximize grain filling in UK bread wheat. © The Author 2017. Published by Oxford University Press on behalf of the Society for Experimental Biology.

Intercropping Competition between Apple Trees and Crops in Agroforestry Systems on the Loess Plateau of China

PubMed Central

Gao, Lubo; Xu, Huasen; Bi, Huaxing; Xi, Weimin; Bao, Biao; Wang, Xiaoyan; Bi, Chao; Chang, Yifang

2013-01-01

Agroforestry has been widely practiced in the Loess Plateau region of China because of its prominent effects in reducing soil and water losses, improving land-use efficiency and increasing economic returns. However, the agroforestry practices may lead to competition between crops and trees for underground soil moisture and nutrients, and the trees on the canopy layer may also lead to shortage of light for crops. In order to minimize interspecific competition and maximize the benefits of tree-based intercropping systems, we studied photosynthesis, growth and yield of soybean (Glycine max L. Merr.) and peanut (Arachis hypogaea L.) by measuring photosynthetically active radiation, net photosynthetic rate, soil moisture and soil nutrients in a plantation of apple (Malus pumila M.) at a spacing of 4 m × 5 m on the Loess Plateau of China. The results showed that for both intercropping systems in the study region, soil moisture was the primary factor affecting the crop yields followed by light. Deficiency of the soil nutrients also had a significant impact on crop yields. Compared with soybean, peanut was more suitable for intercropping with apple trees to obtain economic benefits in the region. We concluded that apple-soybean and apple-peanut intercropping systems can be practical and beneficial in the region. However, the distance between crops and tree rows should be adjusted to minimize interspecies competition. Agronomic measures such as regular canopy pruning, root barriers, additional irrigation and fertilization also should be applied in the intercropping systems. PMID:23936246

Intercropping competition between apple trees and crops in agroforestry systems on the Loess Plateau of China.

PubMed

Gao, Lubo; Xu, Huasen; Bi, Huaxing; Xi, Weimin; Bao, Biao; Wang, Xiaoyan; Bi, Chao; Chang, Yifang

2013-01-01

Agroforestry has been widely practiced in the Loess Plateau region of China because of its prominent effects in reducing soil and water losses, improving land-use efficiency and increasing economic returns. However, the agroforestry practices may lead to competition between crops and trees for underground soil moisture and nutrients, and the trees on the canopy layer may also lead to shortage of light for crops. In order to minimize interspecific competition and maximize the benefits of tree-based intercropping systems, we studied photosynthesis, growth and yield of soybean (Glycine max L. Merr.) and peanut (Arachis hypogaea L.) by measuring photosynthetically active radiation, net photosynthetic rate, soil moisture and soil nutrients in a plantation of apple (Malus pumila M.) at a spacing of 4 m × 5 m on the Loess Plateau of China. The results showed that for both intercropping systems in the study region, soil moisture was the primary factor affecting the crop yields followed by light. Deficiency of the soil nutrients also had a significant impact on crop yields. Compared with soybean, peanut was more suitable for intercropping with apple trees to obtain economic benefits in the region. We concluded that apple-soybean and apple-peanut intercropping systems can be practical and beneficial in the region. However, the distance between crops and tree rows should be adjusted to minimize interspecies competition. Agronomic measures such as regular canopy pruning, root barriers, additional irrigation and fertilization also should be applied in the intercropping systems.

From Maximization to Optimization: A Paradigm Shift in Rice Production in Thailand to Improve Overall Quality of Life of Stakeholders

PubMed Central

Doi, Ryoichi; Pitiwut, Supachai

2014-01-01

The concept of crop yield maximization has been widely supported. In practice, however, yield maximization does not necessarily lead to maximum socioeconomic welfare. Optimization is therefore necessary to ensure quality of life of farmers and other stakeholders. In Thailand, a rice farmers' network has adopted a promising agricultural system aimed at the optimization of rice farming. Various feasible techniques were flexibly combined. The new system offers technical strengths and minimizes certain difficulties with which the rice farmers once struggled. It has resulted in fairly good yields of up to 8.75 t ha−1 or yield increases of up to 57% (from 4.38 to 6.88 t ha−1). Under the optimization paradigm, the farmers have established diversified sustainable relationships with the paddy fields in terms of ecosystem management through their own self-motivated scientific observations. The system has resulted in good health conditions for the farmers and villagers, financial security, availability of extra time, and additional opportunities and freedom and hence in the improvement of their overall quality of life. The underlying technical and social mechanisms are discussed herein. PMID:25089294

Effects of Controlled-Release Fertilizer on Leaf Area Index and Fruit Yield in High-Density Soilless Tomato Culture Using Low Node-Order Pinching

PubMed Central

Kinoshita, Takafumi; Yano, Takayoshi; Sugiura, Makoto; Nagasaki, Yuji

2014-01-01

To further development of a simplified fertigation system using controlled-release fertilizers (CRF), we investigated the effects of differing levels of fertilizers and plant density on leaf area index (LAI), fruit yields, and nutrient use in soilless tomato cultures with low node-order pinching and high plant density during spring-summer (SS), summer-fall (SF), and fall-winter (FW) seasons. Plants were treated with 1 of 3 levels of CRF in a closed system, or with liquid fertilizer (LF) with constant electrical conductivity (EC) in a drip-draining system. Two plant densities were examined for each fertilizer treatment. In CRF treatments, LAI at pinching increased linearly with increasing nutrient supply for all cropping seasons. In SS, both light interception by plant canopy at pinching and total marketable fruit yield increased linearly with increasing LAI up to 6 m2·m−2; the maximization point was not reached for any of the treatments. In FW, both light interception and yield were maximized at an LAI of approximately 4. These results suggest that maximizing the LAI in SS and FW to the saturation point for light interception is important for increasing yield. In SF, however, the yield maximized at an LAI of approximately 3, although the light interception linearly increased with increasing LAI, up to 4.5. According to our results, the optimal LAI at pinching may be 6 in SS, 3 in SF, and 4 in FW. In comparing LAI values with similar fruit yield, we found that nutrient supply was 32−46% lower with the CRF method than with LF. In conclusion, CRF application in a closed system enables growers to achieve a desirable LAI to maximize fruit yield with a regulated amount of nutrient supply per unit area. Further, the CRF method greatly reduced nutrient use without decreasing fruit yield at similar LAIs, as compared to the LF method. PMID:25402478

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

PubMed Central

Albrecht, Matthias

2016-01-01

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

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. © 2016 The Author(s).

Maintaining environmental quality while expanding biomass production: Sub-regional U.S. policy simulations

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

Egbendewe-Mondzozo, Aklesso; Swinton, S.; Izaurralde, Roberto C.

2013-03-01

This paper evaluates environmental policy effects on ligno-cellulosic biomass production and environ- mental outcomes using an integrated bioeconomic optimization model. The environmental policy integrated climate (EPIC) model is used to simulate crop yields and environmental indicators in current and future potential bioenergy cropping systems based on weather, topographic and soil data. The crop yield and environmental outcome parameters from EPIC are combined with biomass transport costs and economic parameters in a representative farmer profit-maximizing mathematical optimization model. The model is used to predict the impact of alternative policies on biomass production and environmental outcomes. We find that without environmental policy,more » rising biomass prices initially trigger production of annual crop residues, resulting in increased greenhouse gas emissions, soil erosion, and nutrient losses to surface and ground water. At higher biomass prices, perennial bioenergy crops replace annual crop residues as biomass sources, resulting in lower environmental impacts. Simulations of three environmental policies namely a carbon price, a no-till area subsidy, and a fertilizer tax reveal that only the carbon price policy systematically mitigates environmental impacts. The fertilizer tax is ineffectual and too costly to farmers. The no-till subsidy is effective only at low biomass prices and is too costly to government.« less

Interaction complexity matters: disentangling services and disservices of ant communities driving yield in tropical agroecosystems

PubMed Central

Wielgoss, Arno; Tscharntke, Teja; Rumede, Alfianus; Fiala, Brigitte; Seidel, Hannes; Shahabuddin, Saleh; Clough, Yann

2014-01-01

Owing to complex direct and indirect effects, impacts of higher trophic levels on plants is poorly understood. In tropical agroecosystems, ants interact with crop mutualists and antagonists, but little is known about how this integrates into the final ecosystem service, crop yield. We combined ant exclusion and introduction of invasive and native-dominant species in cacao agroecosystems to test whether (i) ant exclusion reduces yield, (ii) dominant species maximize certain intermediate ecosystem services (e.g. control of specific pests) rather than yield, which depends on several, cascading intermediate services and (iii) even, species-rich ant communities result in highest yields. Ants provided services, including reduced leaf herbivory and fruit pest damage and indirect pollination facilitation, but also disservices, such as increased mealybug density, phytopathogen dissemination and indirect pest damage enhancement. Yields were highest with unmanipulated, species-rich, even communities, whereas ant exclusion decreased yield by 27%. Introduction of an invasive-dominant ant decreased species density and evenness and resulted in 34% lower yields, whereas introduction of a non-invasive-dominant species resulted in similar species density and yields as in the unmanipulated control. Species traits and ant community structure affect services and disservices for agriculture in surprisingly complex ways, with species-rich and even communities promoting highest yield. PMID:24307667

Water savings of redistributing global crop production

NASA Astrophysics Data System (ADS)

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

2016-04-01

Human demand for crop production is expected to increase substantially in the coming decades as a result of population growth, richer diets and biofuel use. For food production to keep pace, unprecedented amounts of resources - water, fertilizers, energy - will be required. This has led to calls for 'sustainable intensification' in which yields are increased on existing croplands while seeking to minimize impacts on water and other agricultural resources. Recent studies have quantified aspects of this, showing that there is a large potential to improve crop yields and increase harvest frequencies to better meet human demand. Though promising, both solutions would necessitate large additional inputs of water and fertilizer in order to be achieved under current technologies. However, the question of whether the current distribution of crops is, in fact, the best for realizing maximized production has not been considered to date. To this end, we ask: Is it possible to minimize water demand by simply growing crops where soil and climate conditions are best suited? Here we use maps of agro-ecological suitability - a measure of physical and chemical soil fertility - for 15 major food crops to identify differences between current crop distributions and where they can most suitably be planted. By redistributing crops across currently cultivated lands, we determine what distribution of crops would maintain current calorie production and agricultural value while minimizing the water demand of crop production. In doing this, our study provides a novel tool for policy makers and managers to integrate food security, environmental sustainability, and rural livelihoods by improving the use of freshwater resources without compromising crop calorie production or rural livelihoods.

Calorie increase and water savings of redistributing global crop production

NASA Astrophysics Data System (ADS)

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

2015-12-01

Human demand for crop production is expected to increase substantially in the coming decades as a result of population growth, richer diets and biofuel use. In order for food production to keep pace, unprecedented amounts of resources - water, fertilizers, energy - will be required. This has led to calls for 'sustainable intensification' in which yields are increased on existing croplands while seeking to minimize impacts on water and other agricultural resources. Recent studies have quantified aspects of this, showing that there is a large potential to improve crop yields and increase harvest frequencies to better meet human demand. Though promising, both solutions would necessitate large additional inputs of water and fertilizer in order to be achieved under current technologies. However, the question of whether the current distribution of crops is, in fact, the best for realizing maximized production has not been considered to date. To this end, we ask: Is it possible to increase calorie production and minimize water demand by simply growing crops where soil and climate conditions are best suited? Here we use maps of agro-ecological suitability - a measure of physical and chemical soil fertility - for 15 major food crops to identify differences between current crop distributions and where they can most suitably be planted. By redistributing crops across currently cultivated lands, we determine the potential improvement in calorie production as well as the associated change in water demand. We also consider what distribution of crops would maintain current calorie production while minimizing crop water demand. In doing all of this, our study provides a novel tool for improving crop calorie production without necessarily increasing resource demands.

Implications for water use of a shift from annual to perennial crops - A stochastic modelling approach based on a trait meta-analysis

NASA Astrophysics Data System (ADS)

Vico, Giulia; Brunsell, Nathaniel

2017-04-01

The projected population growth and changes in climate and dietary habits will further increase the pressure on water resources globally. Within precision farming, a host of technical solutions has been developed to reduce water consumption for agricultural uses. The next frontier for a more sustainable agriculture is the combination of reduced water requirements with enhanced ecosystem services. Currently, staple grains are obtained from annuals crops. A shift from annual to perennial crops has been suggested as a way to enhance ecosystem services. In fact, perennial plants, with their continuous soil cover and the higher allocation of resources to the below ground, contribute to the reduction of soil erosion and nutrient losses, while enhancing carbon sequestration in the root zone. Nevertheless, the net effect of a shift to perennial crops on water use for agriculture is still unknown, despite its relevance for the sustainability of such a shift. We explore here the implications for water management at the field- to farm-scale of a shift from annual to perennial crops, under rainfed and irrigated agriculture. A probabilistic description of the soil water balance and crop development is employed to quantify water requirements and yields and their inter-annual variability, as a function of rainfall patterns, soil and crop features. Optimal irrigation strategies are thus defined in terms of maximization of yield and minimization of required irrigation volumes and their inter-annual variability. The probabilistic model is parameterized based on an extensive meta-analysis of traits of co-generic annual and perennial species to explore the consequences for water requirements of shifting from annual to perennial crops under current and future climates. We show that the larger and more developed roots of perennial crops may allow a better exploitation of soil water resources and a reduction of yield variability with respect to annual species. At the same time, perennial crops are larger and may require adequate water supply for longer periods, thus leading to higher water requirements. Furthermore, they lead to lower yields per unit area, thus requiring irrigation of larger areas.

Declining spatial efficiency of global cropland nitrogen allocation

NASA Astrophysics Data System (ADS)

Mueller, Nathaniel D.; Lassaletta, Luis; Runck, Bryan C.; Billen, Gilles; Garnier, Josette; Gerber, James S.

2017-02-01

Efficiently allocating nitrogen (N) across space maximizes crop productivity for a given amount of N input and reduces N losses to the environment. Here we quantify changes in the global spatial efficiency of cropland N use by calculating historical trade-off frontiers relating N inputs to possible N yield assuming efficient allocation. Time series cropland N budgets from 1961 to 2009 characterize the evolution of N input-yield response functions across 12 regions and are the basis for constructing trade-off frontiers. Improvements in agronomic technology have substantially increased cropping system yield potentials and expanded N-driven crop production possibilities. However, we find that these gains are compromised by the declining spatial efficiency of N use across regions. Since the start of the Green Revolution, N inputs and yields have moved farther from the optimal frontier over time; in recent years (1994-2009), global N surplus has grown to a value that is 69% greater than what is possible with efficient N allocation between regions. To reflect regional pollution and agricultural development goals, we construct scenarios that restrict reallocation, finding that these changes only slightly decrease potential gains in nitrogen use efficiency. Our results are inherently conservative due to the regional unit of analysis, meaning a larger potential exists than is quantified here for cross-scale policies to promote spatially efficient N use.

Assessment of physical and chemical indicators of sandy soil quality for sustainable crop production

NASA Astrophysics Data System (ADS)

Lipiec, Jerzy; Usowicz, Boguslaw

2017-04-01

Sandy soils are used in agriculture in many regions of the world. The share of sandy soils in Poland is about 55%. The aim of this study was to assess spatial variability of soil physical and chemical properties affecting soil quality and crop yields in the scale of field (40 x 600 m) during three years of different weather conditions. The experimental field was located on the post glacial and acidified sandy deposits of low productivity (Szaniawy, Podlasie Region, Poland). Physical soil quality indicators included: content of sand, silt, clay and water, bulk density and those chemical: organic carbon, cation exchange capacity, acidity (pH). Measurements of the most soil properties were done at spring and summer each year in topsoil and subsoil layer in 150 points. Crop yields were evaluated in places close to measuring points of the soil properties. Basic statistics including mean, standard deviation, skewness, kurtosis minimal, maximal and correlations between the soil properties and crop yields were calculated. Analysis of spatial dependence and distribution for each property was performed using geostatistical methods. Mathematical functions were fitted to the experimentally derived semivariograms that were used for mapping the soil properties and crop yield by kriging. The results showed that the largest variations had clay content (CV 67%) and the lowest: sand content (5%). The crop yield was most negatively correlated with sand content and most positively with soil water content and cation exchange capacity. In general the exponential semivariogram models fairly good matched to empirical data. The range of semivariogram models of the measured indicators varied from 14 m to 250 m indicate high and moderate spatial variability. The values of the nugget-to-sill+nugget ratios showed that most of the soil properties and crop yields exhibited strong and moderate spatial dependency. The kriging maps allowed identification of low yielding sub-field areas that correspond with low soil organic carbon and cation exchange capacity and high content of sand. These areas are considered as management zones to improve crop productivity and soil properties responsible for soil quality and functions. We conclude that soil organic carbon, cation exchange capacity and pH should be included as indicators of soil quality in sandy soils. The study was funded by HORIZON 2020, European Commission, Programme H2020-SFS-2015-2: Soil Care for profitable and sustainable crop production in Europe, project No. 677407 (SoilCare, 2016-2021).

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 likely benefit grassland bird populations, and bioenergy landscapes could be designed to maximize biodiversity benefits while meeting targets for biomass production.

Correlation studies on nitrogen for sunflower crop across the agroclimatic variability.

PubMed

Nasim, Wajid; Belhouchette, Hatem; Tariq, Muhammad; Fahad, Shah; Hammad, Hafiz Mohkum; Mubeen, Muhammad; Munis, Muhammad Farooq Hussain; Chaudhary, Hassan Javed; Khan, Imran; Mahmood, Faisal; Abbas, Tauqeer; Rasul, Fahd; Nadeem, Muhammad; Bajwa, Ali Ahsan; Ullah, Najeeb; Alghabari, Fahad; Saud, Shah; Mubarak, Hussani; Ahmad, Rafiq

2016-02-01

Nitrogen (N) fertilizer is an important yield limiting factor for sunflower production. The correlation between yield components and growth parameters of three sunflower hybrids (Hysun-33, Hysun-38, Pioneer-64A93) were studied with five N rates (0, 60, 120, 180, 240 kg ha(-1)) at three different experimental sites during the two consecutive growing seasons 2008 and 2009. The results revealed that total dry matter (TDM) production and grain yield were positively and linearly associated with leaf area index (LAI), leaf area duration (LAD), and crop growth rate (CGR) at all three sites of the experiments. The significant association of yield with growth components indicated that the humid climate was most suitable for sunflower production. Furthermore, the association of these components can be successfully used to predict the grain yield under diverse climatic conditions. The application of N at increased rate of 180 kg ha(-1) resulted in maximum yield as compared to standard rate (120 kg ha(-1)) at all the experimental sites. In this way, N application rate was significantly correlated with growth and development of sunflower under a variety of climatic conditions. Keeping in view such relationship, the N dose can be optimized for sunflower crop in a particular region to maximize the productivity. Multilocation trails help to predict the input rates precisely while taking climatic variations into account also. In the long run, results of this study provides basis for sustainable sunflower production under changing climate.

Winter cover crops as a best management practice for reducing nitrogen leaching

NASA Astrophysics Data System (ADS)

Ritter, W. F.; Scarborough, R. W.; Chirnside, A. E. M.

1998-10-01

The role of rye as a winter cover crop to reduce nitrate leaching was investigated over a three-year period on a loamy sand soil. A cover crop was planted after corn in the early fall and killed in late March or early April the following spring. No-tillage and conventional tillage systems were compared on large plots with irrigated corn. A replicated randomized block design experiment was conducted on small plots to evaluate a rye cover crop under no-tillage and conventional tillage and with commercial fertilizer, poultry manure and composted poultry manure as nitrogen fertilizer sources. Nitrogen uptake by the cover crop along with nitrate concentrations in groundwater and the soil profile (0-150 cm) were measured on the large plots. Soil nitrate concentrations and nitrogen uptake by the cover crop were measured on the small plots. There was no significant difference in nitrate concentrations in the groundwater or soil profile with and without a cover crop in either no-tillage or conventional tillage. Annual amounts of nitrate-N leached to the water-table varied from 136.0 to 190.1 kg/ha in 1989 and from 82.4 to 116.2 kg/ha in 1991. Nitrate leaching rates were somewhat lower with a cover crop in 1989, but not in 1990. There was no statistically significant difference in corn grain yields between the cover crop and non-cover crop treatments. The planting date and adequate rainfall are very important in maximizing nitrogen uptake in the fall with a rye cover crop. On the Delmarva Peninsula, the cover crop should probably be planted by October 1 to maximize nitrogen uptake rates in the fall. On loamy sand soils, rye winter cover crops cannot be counted on as a best management practice for reducing nitrate leaching in the Mid-Atlantic states.

Optimizing rice yields while minimizing yield-scaled global warming potential.

PubMed

Pittelkow, Cameron M; Adviento-Borbe, Maria A; van Kessel, Chris; Hill, James E; Linquist, Bruce A

2014-05-01

To meet growing global food demand with limited land and reduced environmental impact, agricultural greenhouse gas (GHG) emissions are increasingly evaluated with respect to crop productivity, i.e., on a yield-scaled as opposed to area basis. Here, we compiled available field data on CH4 and N2 O emissions from rice production systems to test the hypothesis that in response to fertilizer nitrogen (N) addition, yield-scaled global warming potential (GWP) will be minimized at N rates that maximize yields. Within each study, yield N surplus was calculated to estimate deficit or excess N application rates with respect to the optimal N rate (defined as the N rate at which maximum yield was achieved). Relationships between yield N surplus and GHG emissions were assessed using linear and nonlinear mixed-effects models. Results indicate that yields increased in response to increasing N surplus when moving from deficit to optimal N rates. At N rates contributing to a yield N surplus, N2 O and yield-scaled N2 O emissions increased exponentially. In contrast, CH4 emissions were not impacted by N inputs. Accordingly, yield-scaled CH4 emissions decreased with N addition. Overall, yield-scaled GWP was minimized at optimal N rates, decreasing by 21% compared to treatments without N addition. These results are unique compared to aerobic cropping systems in which N2 O emissions are the primary contributor to GWP, meaning yield-scaled GWP may not necessarily decrease for aerobic crops when yields are optimized by N fertilizer addition. Balancing gains in agricultural productivity with climate change concerns, this work supports the concept that high rice yields can be achieved with minimal yield-scaled GWP through optimal N application rates. Moreover, additional improvements in N use efficiency may further reduce yield-scaled GWP, thereby strengthening the economic and environmental sustainability of rice systems. © 2013 John Wiley & Sons Ltd.

The economic and environmental consequences of implementing nitrogen-efficient technologies and management practices in agriculture.

PubMed

Zhang, Xin; Mauzerall, Denise L; Davidson, Eric A; Kanter, David R; Cai, Ruohong

2015-03-01

Technologies and management practices (TMPs) that reduce the application of nitrogen (N) fertilizer while maintaining crop yields can improve N use efficiency (NUE) and are important tools for meeting the dual challenges of increasing food production and reducing N pollution. However, because farmers operate to maximize their profits, incentives to implement TMPs are limited, and TMP implementation will not always reduce N pollution. Therefore, we have developed the NUE Economic and Environmental impact analytical framework (NUE) to examine the economic and environmental consequences of implementing TMPs in agriculture, with a specific focus on farmer profits, N fertilizer consumption, N losses, and cropland demand. Our analytical analyses show that impact of TMPs on farmers' economic decision-making and the environment is affected by how TMPs change the yield ceiling and the N fertilization rate at the ceiling and by how the prices of TMPs, fertilizer, and crops vary. Technologies and management practices that increase the yield ceiling appear to create a greater economic incentive for farmers than TMPs that do not but may result in higher N application rates and excess N losses. Nevertheless, the negative environmental impacts of certain TMPs could be avoided if their price stays within a range determined by TMP yield response, fertilizer price, and crop price. We use a case study on corn production in the midwestern United States to demonstrate how NUE can be applied to farmers' economic decision-making and policy analysis. Our NUE framework provides an important tool for policymakers to understand how combinations of fertilizer, crop, and TMP prices affect the possibility of achieving win-win outcomes for farmers and the environment. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

Assessment of water use in the Spanish irrigation district "Río Adaja"

NASA Astrophysics Data System (ADS)

Naroua, Illiassou; Rodriguez-Sinobas, Leonor; Sánchez Calvo, Raúl

2013-04-01

Intensive agricultural practices combined with the increasing pressure of urbanization and the changing lifestyles, have strengthened the problems of competing users over limited water resources in a fragile and already stressed environment. Sustainable irrigated agriculture is prescribed as a policy approach that maximizes economic benefits while maintaining environmental quality. Within this framework a proper management of irrigation systems saving water is required. On the other hand, crops with high tolerance to water stress and deficit irrigation are recommended. However, crop yield, among other factors, is very sensitive to water Thus, studies addressing the relations among crop water requirements, irrigation depth and crop yield are necessary. This type of study has been carried out in the Spanish irrigation District "Río Adaja" in the year 2010-2011 with the crops: wheat, barley, sugarbeet, corn, onion, potato, sunflower, clover and carrot. A soil hydrology balance model was applied taking into account climatic data for the nearby weather station and soil characteristics. Effective precipitation was calculated by the index curve number. Crop water requirements were calculated by the FAO Penman-Monteith with the application of the dual crop coefficient. Likewise, productivity was measured by the following indexes: annual relative irrigation supply (ARIS), relative water supply (RWS), relative rainfall supply (RS) and water productivity (WP). Results show that water applied with the irrigation of clover, sugarbeet, corn and onion was less than their water requirements There was a 35 % difference between the amount of water simulated with the model and the gross amount applied during the irrigation period by the irrigation district. WP values differed among crops depending, mainly, on the crop`s market price and the amount of irrigation water. The highest values corresponded to potato and onion crops.

SWAT-MODSIM-PSO optimization of multi-crop planning in the Karkheh River Basin, Iran, under the impacts of climate change.

PubMed

Fereidoon, Majid; Koch, Manfred

2018-07-15

Agriculture is one of the environmental/economic sectors that may adversely be affected by climate change, especially, in already nowadays water-scarce regions, like the Middle East. One way to cope with future changes in absolute as well as seasonal (irrigation) water amounts can be the adaptation of the agricultural crop pattern in a region, i.e. by planting crops which still provide high yields and so economic benefits to farmers under such varying climate conditions. To do this properly, the whole cascade starting from climate change, effects on hydrology and surface water availability, subsequent effects on crop yield, agricultural areas available, and, finally, economic value of a multi-crop cultivation pattern must be known. To that avail, a complex coupled simulation-optimization tool SWAT-LINGO-MODSIM-PSO (SLMP) has been developed here and used to find the future optimum cultivation area of crops for the maximization of the economic benefits in five irrigation-fed agricultural plains in the south of the Karkheh River Basin (KRB) southwest Iran. Starting with the SWAT distributed hydrological model, the KR-streamflow as well as the inflow into the Karkheh-reservoir, as the major storage of irrigation water, is calibrated and validated, based on 1985-2004 observed discharge data. In the subsequent step, the SWAT-predicted streamflow is fed into the MODSIM river basin Decision Support System to simulate and optimize the water allocation between different water users (agricultural, environmental, municipal and industrial) under standard operating policy (SOP) rules. The final step is the maximization of the economic benefit in the five agricultural plains through constrained PSO (particle swarm optimization) by adjusting the cultivation areas (decision variables) of different crops (wheat, barley, maize and "others"), taking into account their specific prizes and optimal crop yields under water deficiency, with the latter computed in the LINGO-sub-optimization module embedded in the SLMP-tool. For the optimization of the agricultural benefits in the KRB in the near future (2038-2060), quantile-mapping (QM) bias-corrected downscaled predictors for daily precipitation and temperatures of the HadGEM2-ES GCM-model under RCP4.5- and RCP8.5-emission scenarios are used as climate drivers in the streamflow- and crop yield simulations of the SWAT-model, leading to corresponding changes in the final outcome (economic benefit) of the SLMP-tool. In fact, whereas for the historical period (1985-2004) a total annual benefit of 94.2 million US$ for all multi-crop areas in KRB is computed, there is a decrease to 88.3 million US$ and 72.1 million US$ for RCP4.5 and RCP8.5, respectively, in the near future (2038-2060) prediction period. In fact, this future income decrease is due to a substantial shift from cultivation areas devoted nowadays to high-price wheat and barley in the winter season to low-price maize-covered areas in the future summers, owing to a future seasonal change of SWAT-predicted irrigation water available, i.e. less in the winter and more in the summer. Copyright © 2018 Elsevier B.V. All rights reserved.

Derivation of Optimal Cropping Pattern in Part of Hirakud Command using Cuckoo Search

NASA Astrophysics Data System (ADS)

Rath, Ashutosh; Biswal, Sudarsan; Samantaray, Sandeep; Swain, Prakash Chandra, PROF.

2017-08-01

The economicgrowth of a Nation depends on agriculture which relies on the obtainable water resources, available land and crops. The contribution of water in an appropriate quantity at appropriate time plays avitalrole to increase the agricultural production. Optimal utilization of available resources can be achieved by proper planning and management of water resources projects and adoption of appropriate technology. In the present work, the command area of Sambalpur distribrutary System is taken up for investigation. Further, adoption of a fixed cropping pattern causes the reduction of yield. The present study aims at developing different crop planning strategies to increase the net benefit from the command area with minimum investment. Optimization models are developed for Kharif season using LINDO and Cuckoo Search (CS) algorithm for maximization of the net benefits. In process of development of Optimization model the factors such as cultivable land, seeds, fertilizers, man power, water cost, etc. are taken as constraints. The irrigation water needs of major crops and the total available water through canals in the command of Sambalpur Distributary are estimated. LINDO and Cuckoo Search models are formulated and used to derive the optimal cropping pattern yielding maximum net benefits. The net benefits of Rs.585.0 lakhs in Kharif Season are obtained by adopting LINGO and 596.07 lakhs from Cuckoo Search, respectively, whereas the net benefits of 447.0 lakhs is received by the farmers of the locality with the adopting present cropping pattern.

Crop Performance and Soil Properties in Two Artificially-Eroded Soils in North-Central Alberta

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

Izaurralde, R Cesar C.; Malhi, S. S.; Nyborg, M.

2006-09-01

Field experiments were conducted from 1991 to 1995 at Josephburg (Orthic Black Chernozem, Typic Cryoboroll) and Cooking Lake (Orthic Gray Luvisol, Typic Cryoboralf), Alberta, to determine impact of topsoil removal on selected soil properties, N-mineralization potential and crop yield, and effectiveness of various amendments for restoring the productivity of eroded soils. The simulated-erosion levels were established in the autumn of 1990 by removing 20 cm topsoil in 5-cm depth increments. The four amendments were: control, addition of 5 cm of topsoil, fertilizers to supply 100 kg N ha-1 and 20 kg P ha-1, and cattle manure at 75 Mg ha-1.more » Topsoil and manure were applied once in the autumn of 1990, while fertilizers were applied annually from 1991 to 1995. Available N and P, total C, N and P, and N-mineralization potential decreased, while bulk density increased with increasing depth of topsoil removal. Tiller number, plant height, spike density, thousand kernel weight, and leaf area index decreased with simulated erosion. Grain yield reductions due to simulated soil erosion were either linear or curvilinear functions of nutrient removal. Application of N and P fertilizers and manure improved grain yield and reduced the impact of yield loss due to erosion. Return of 5 cm of topsoil also increased grain yield, but to a lesser extent than manure or fertilizers. Grain yields were maximized when fertilizers were also applied to organic amendment treatments. In conclusion, the findings suggest the importance of integrated use of organic amendments and chemical fertilizers for best crop yields on severely-eroded soils.« less

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

PubMed Central

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

2017-01-01

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

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

PubMed

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

2017-01-01

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

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

DOE PAGES

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

2017-03-21

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

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

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

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

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

Trade-off between blue and grey water footprint of crop production at different nitrogen application rates under various field management practices.

PubMed

Chukalla, Abebe D; Krol, Maarten S; Hoekstra, Arjen Y

2018-06-01

In irrigated crop production, nitrogen (N) is often applied at high rates in order to maximize crop yield. With such high rates, the blue water footprint (WF) per unit of crop is low, but the N-related grey WF per unit of crop yield is relatively high. This study explores the trade-off between blue and grey WF at different N-application rates (from 25 to 300 kg N ha -1  y -1 ) under various field management practices. We first analyse this trade-off under a reference management package (applying inorganic-N, conventional tillage, full irrigation). Next, we estimate the economically optimal N-application rate when putting a price to pollution. Finally, we consider the blue-grey WF trade-off for other management packages, a combination of inorganic-N or organic-N with conventional tillage or no-tillage, and full or deficit irrigation. We use the APEX model to simulate soil water and N balances and crop growth. As a case study, we consider irrigated maize on loam soil for the period 1998-2012 in a semi-arid environment in Spain. The results for the reference package show that increasing N application from 50 to 200 kg N ha -1 , with crop yield growing by a factor 3, involves a trade-off, whereby the blue WF per tonne declines by 60% but the N-related grey WF increases by 210%. Increasing N application from 25 to 50 kg N ha -1 , with yield increasing by a factor 2, is a no-regret move, because blue and grey WFs per tonne are reduced by 40% and 8%, respectively. Decreasing N application from 300 to 200 kg N ha -1 is a no-regret move as well. The minimum blue WF per tonne is found at N application of 200 kg N ha -1 , with a price of 8 $ kg -1 of N load to water pollution the economically optimal N-application rate is 150 kg N ha -1 . Copyright © 2018 Elsevier B.V. All rights reserved.

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 increasing trend of ECe was observed and moderately saline and very saline soils were predominant during the survey period. The temporal dynamics of root zone ECe coincided with those of daily rainfall, water table and groundwater data. Long-range EMI surveys and data collection are needed to capture the spatial and temporal variability of soil and crop parameters. Such results allowed us to conclude that, cost-effective and efficient EMI surveys, as one part of multi-source data for DSM, could be successfully used to characterize the spatial variability of soil salinity, to monitor the spatial and temporal dynamics of soil salinity, and to spatially estimate potential crop yield. PMID:27203697

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 increasing trend of ECe was observed and moderately saline and very saline soils were predominant during the survey period. The temporal dynamics of root zone ECe coincided with those of daily rainfall, water table and groundwater data. Long-range EMI surveys and data collection are needed to capture the spatial and temporal variability of soil and crop parameters. Such results allowed us to conclude that, cost-effective and efficient EMI surveys, as one part of multi-source data for DSM, could be successfully used to characterize the spatial variability of soil salinity, to monitor the spatial and temporal dynamics of soil salinity, and to spatially estimate potential crop yield.

Poaceae vs. Abiotic Stress: Focus on Drought and Salt Stress, Recent Insights and Perspectives

PubMed Central

Landi, Simone; Hausman, Jean-Francois; Guerriero, Gea; Esposito, Sergio

2017-01-01

Poaceae represent the most important group of crops susceptible to abiotic stress. This large family of monocotyledonous plants, commonly known as grasses, counts several important cultivated species, namely wheat (Triticum aestivum), rice (Oryza sativa), maize (Zea mays), and barley (Hordeum vulgare). These crops, notably, show different behaviors under abiotic stress conditions: wheat and rice are considered sensitive, showing serious yield reduction upon water scarcity and soil salinity, while barley presents a natural drought and salt tolerance. During the green revolution (1940–1960), cereal breeding was very successful in developing high-yield crops varieties; however, these cultivars were maximized for highest yield under optimal conditions, and did not present suitable traits for tolerance under unfavorable conditions. The improvement of crop abiotic stress tolerance requires a deep knowledge of the phenomena underlying tolerance, to devise novel approaches and decipher the key components of agricultural production systems. Approaches to improve food production combining both enhanced water use efficiency (WUE) and acceptable yields are critical to create a sustainable agriculture in the future. This paper analyzes the latest results on abiotic stress tolerance in Poaceae. In particular, the focus will be directed toward various aspects of water deprivation and salinity response efficiency in Poaceae. Aspects related to cell wall metabolism will be covered, given the importance of the plant cell wall in sensing environmental constraints and in mediating a response; the role of silicon (Si), an important element for monocots' normal growth and development, will also be discussed, since it activates a broad-spectrum response to different exogenous stresses. Perspectives valorizing studies on landraces conclude the survey, as they help identify key traits for breeding purposes. PMID:28744298

The Nexus Land-Use model version 1.0, an approach articulating biophysical potentials and economic dynamics to model competition for land-use

NASA Astrophysics Data System (ADS)

Souty, F.; Brunelle, T.; Dumas, P.; Dorin, B.; Ciais, P.; Crassous, R.; Müller, C.; Bondeau, A.

2012-10-01

Interactions between food demand, biomass energy and forest preservation are driving both food prices and land-use changes, regionally and globally. This study presents a new model called Nexus Land-Use version 1.0 which describes these interactions through a generic representation of agricultural intensification mechanisms within agricultural lands. The Nexus Land-Use model equations combine biophysics and economics into a single coherent framework to calculate crop yields, food prices, and resulting pasture and cropland areas within 12 regions inter-connected with each other by international trade. The representation of cropland and livestock production systems in each region relies on three components: (i) a biomass production function derived from the crop yield response function to inputs such as industrial fertilisers; (ii) a detailed representation of the livestock production system subdivided into an intensive and an extensive component, and (iii) a spatially explicit distribution of potential (maximal) crop yields prescribed from the Lund-Postdam-Jena global vegetation model for managed Land (LPJmL). The economic principles governing decisions about land-use and intensification are adapted from the Ricardian rent theory, assuming cost minimisation for farmers. In contrast to the other land-use models linking economy and biophysics, crops are aggregated as a representative product in calories and intensification for the representative crop is a non-linear function of chemical inputs. The model equations and parameter values are first described in details. Then, idealised scenarios exploring the impact of forest preservation policies or rising energy price on agricultural intensification are described, and their impacts on pasture and cropland areas are investigated.

Exploring the Potential for Sustainable Future Bioenergy Production in the Arkansas-White-Red River Basin

NASA Astrophysics Data System (ADS)

Baskaran, L.; Jager, H.; Kreig, J.

2016-12-01

Bioenergy production in the US has been projected to increase in the next few years and this has raised concerns over environmentally sustainable production. Specifically, there are concerns that managing lands to produce bioenergy feedstocks in the Mississippi-Atchafalaya River Basin (MARB) may have impacts over the water quality in the streams draining these lands and hamper with efforts to reduce the size of the Gulf of Mexico's "Dead Zone" (hypoxic waters). However, with appropriate choice of feedstocks and good conservation practices, bioenergy production systems can be environmentally and economically sustainable. We evaluated opportunities for producing 2nd generation cellulosic feedstocks that are economically sustainable and improve water quality in the Arkansas-White-Red (AWR) river basin, which is major part of the MARB. We generated a future bioenergy landscape by downscaling county-scale projections of bioenergy crop production produced by an economic model, POLYSYS, at a market price of $60 per dry ton and a 1% annual yield increase. Our future bioenergy landscape includes perennial grasses (switchgrass and miscanthus), short-rotated woody crops (poplar and willow) and annual crops (high yield sorghum, sorghum stubble, corn stover and wheat straw). Using the Soil and Water Assessment Tool (SWAT) we analyzed changes in water quality and quantity by simulating a baseline scenario with the current landscape (2014 land cover) and a future scenario with the bioenergy landscape. Our results over the AWR indicate decreases in median nutrient and sediment loadings from the baseline scenario. We also explored methods to evaluate if conservation practices (such as reducing fertilizer applications, incorporating filter strips, planting cover crops and moving to a no-till system) can improve water quality, while maintaining biomass yield. We created a series of SWAT simulations with varying levels of conservation practices by crop and present our methods towards identifying future scenarios that may minimize water quality and maximize biomass yields.

Gene Expression Biomarkers Provide Sensitive Indicators of in Planta Nitrogen Status in Maize[W][OA

PubMed Central

Yang, Xiaofeng S.; Wu, Jingrui; Ziegler, Todd E.; Yang, Xiao; Zayed, Adel; Rajani, M.S.; Zhou, Dafeng; Basra, Amarjit S.; Schachtman, Daniel P.; Peng, Mingsheng; Armstrong, Charles L.; Caldo, Rico A.; Morrell, James A.; Lacy, Michelle; Staub, Jeffrey M.

2011-01-01

Over the last several decades, increased agricultural production has been driven by improved agronomic practices and a dramatic increase in the use of nitrogen-containing fertilizers to maximize the yield potential of crops. To reduce input costs and to minimize the potential environmental impacts of nitrogen fertilizer that has been used to optimize yield, an increased understanding of the molecular responses to nitrogen under field conditions is critical for our ability to further improve agricultural sustainability. Using maize (Zea mays) as a model, we have characterized the transcriptional response of plants grown under limiting and sufficient nitrogen conditions and during the recovery of nitrogen-starved plants. We show that a large percentage (approximately 7%) of the maize transcriptome is nitrogen responsive, similar to previous observations in other plant species. Furthermore, we have used statistical approaches to identify a small set of genes whose expression profiles can quantitatively assess the response of plants to varying nitrogen conditions. Using a composite gene expression scoring system, this single set of biomarker genes can accurately assess nitrogen responses independently of genotype, developmental stage, tissue type, or environment, including in plants grown under controlled environments or in the field. Importantly, the biomarker composite expression response is much more rapid and quantitative than phenotypic observations. Consequently, we have successfully used these biomarkers to monitor nitrogen status in real-time assays of field-grown maize plants under typical production conditions. Our results suggest that biomarkers have the potential to be used as agronomic tools to monitor and optimize nitrogen fertilizer usage to help achieve maximal crop yields. PMID:21980173

Gene expression biomarkers provide sensitive indicators of in planta nitrogen status in maize.

PubMed

Yang, Xiaofeng S; Wu, Jingrui; Ziegler, Todd E; Yang, Xiao; Zayed, Adel; Rajani, M S; Zhou, Dafeng; Basra, Amarjit S; Schachtman, Daniel P; Peng, Mingsheng; Armstrong, Charles L; Caldo, Rico A; Morrell, James A; Lacy, Michelle; Staub, Jeffrey M

2011-12-01

Over the last several decades, increased agricultural production has been driven by improved agronomic practices and a dramatic increase in the use of nitrogen-containing fertilizers to maximize the yield potential of crops. To reduce input costs and to minimize the potential environmental impacts of nitrogen fertilizer that has been used to optimize yield, an increased understanding of the molecular responses to nitrogen under field conditions is critical for our ability to further improve agricultural sustainability. Using maize (Zea mays) as a model, we have characterized the transcriptional response of plants grown under limiting and sufficient nitrogen conditions and during the recovery of nitrogen-starved plants. We show that a large percentage (approximately 7%) of the maize transcriptome is nitrogen responsive, similar to previous observations in other plant species. Furthermore, we have used statistical approaches to identify a small set of genes whose expression profiles can quantitatively assess the response of plants to varying nitrogen conditions. Using a composite gene expression scoring system, this single set of biomarker genes can accurately assess nitrogen responses independently of genotype, developmental stage, tissue type, or environment, including in plants grown under controlled environments or in the field. Importantly, the biomarker composite expression response is much more rapid and quantitative than phenotypic observations. Consequently, we have successfully used these biomarkers to monitor nitrogen status in real-time assays of field-grown maize plants under typical production conditions. Our results suggest that biomarkers have the potential to be used as agronomic tools to monitor and optimize nitrogen fertilizer usage to help achieve maximal crop yields.

Quinoa: An emerging new crop with potential for CELSS

NASA Technical Reports Server (NTRS)

Schlick, Greg; Bubenheim, David L.

1993-01-01

Chenopodium quinoa is being considered as a new crop for the Controlled Ecological Life Support System (CELSS) because of its high protein values (12 - 18%) and unique amino acid composition. Lysine, and essential amino acid that is deficient in many grain crops, is found in quinoa approaching Food and Agriculture Organization of the United Nations (FAO) standards set for humans. This 'new' crop, rich in protein and with desirable proportions of important amino acids, may provide greater versatility in meeting the needs of humans on long-term space missions. Initially, the cultivars CO407 x ISLUGA, CO407 Heat Tolerant Population 1, and Real' (a Bolivian variety) were examined. The first cultivar showed the most promise in greenhouse studies. When grown hydroponically in the greenhouse, with no attempt to maximize productivity, this cultivar produced 202 g m(exp -2) with a harvest index of 37%. None of the cultivars were greater than 70 cm in height. Initial results indicate that quinoa could be an excellent crop for CELSS because of the high concentration of protein, ease of use, versatility in preparation, and potential for greatly increased yields in controlled environments.

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Challenges towards Revitalizing Hemp: A Multifaceted Crop.

PubMed

Schluttenhofer, Craig; Yuan, Ling

2017-11-01

Hemp has been an important crop throughout human history for food, fiber, and medicine. Despite significant progress made by the international research community, the basic biology of hemp plants remains insufficiently understood. Clear objectives are needed to guide future research. As a semi-domesticated plant, hemp has many desirable traits that require improvement, including eliminating seed shattering, enhancing the quantity and quality of stem fiber, and increasing the accumulation of phytocannabinoids. Methods to manipulate the sex of hemp plants will also be important for optimizing yields of seed, fiber, and cannabinoids. Currently, research into trait improvement is hindered by the lack of molecular techniques adapted to hemp. Here we review how addressing these limitations will help advance our knowledge of plant biology and enable us to fully domesticate and maximize the agronomic potential of this promising crop. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Supplemental irrigation as an initiative to support water and food security: A global evaluation of the potential to support and increase precipitation-fed wheat production

NASA Astrophysics Data System (ADS)

Smilovic, M.; Gleeson, T. P.; Adamowski, J. F.; Langhorn, C.; Kienzle, S. W.

2016-12-01

Supplemental irrigation is the practice of supporting precipitation-fed agriculture with limited irrigation. Precipitation-fed agriculture dominates the agricultural landscape, but is vulnerable to intraseasonal and interannual variability in precipitation and climate. The interplay between food security, water resources, ecosystem health, energy, and livelihoods necessitates evaluating and integrating initiatives that increase agricultural production while reducing demands on water resources. Supplemental irrigation is the practice of minimally irrigating in an effort to stabilize and increase agricultural production, as well as increase water productivity - the amount of crop produced per unit of water. The potential of supplemental irrigation to support both water and food security has yet to be evaluated at regional and global scales. We evaluate whether supplemental irrigation could stabilize and increase agricultural production of wheat by determining locally-calibrated water use-crop yield relationships, known as crop-water production functions. Crop-water production functions are functions of seasonal water use and crop yield, and previous efforts have largely ignored the effects of the temporal distribution of water use throughout the growing season. We significantly improve upon these efforts and provide an opportunity to evaluate supplemental irrigation that appropriately acknowledges the effects of irrigation scheduling. Integrating agroclimatic and crop data with the crop-water model Aquacrop, we determine the increases in wheat production achieved by maximizing water productivity, sharing limited water between different years, and other irrigation scenarios. The methodology presented and evaluation of supplemental irrigation provides water mangers, policy makers, governments, and non-governmental organizations the tools to appropriately understand and determine the potential of this initiative to support precipitation-fed agriculture.

Hydrodistillation extraction time effect on essential oil yield, composition, and bioactivity of coriander oil.

PubMed

Zheljazkov, Valtcho D; Astatkie, Tess; Schlegel, Vicki

2014-01-01

Coriander (Coriandrum sativum L.) is a major essential oil crop grown throughout the world. Coriander essential oil is extracted from coriander fruits via hydrodistillation, with the industry using 180-240 min of distillation time (DT), but the optimum DT for maximizing essential oil yield, composition of constituents, and antioxidant activities are not known. This research was conducted to determine the effect of DT on coriander oil yield, composition, and bioactivity. The results show that essential oil yield at the shorter DT was low and generally increased with increasing DT with the maximum yields achieved at DT between 40 and 160 min. The concentrations of the low-boiling point essential oil constituents: α-pinene, camphene, β-pinene, myrcene, para-cymene, limonene, and γ-terpinene were higher at shorter DT (< 2.5 min) and decreased with increasing DT; but the trend reversed for the high-boiling point constituents: geraniol and geranyl-acetate. The concentration of the major essential oil constituent, linalool, was 51% at DT 1.15 min, and increased steadily to 68% with increasing DT. In conclusion, 40 min DT is sufficient to maximize yield of essential oil; and different DT can be used to obtain essential oil with differential composition. Its antioxidant capacity was affected by the DT, with 20 and 240 min DT showing higher antioxidant activity. Comparisons of coriander essential oil composition must consider the length of the DT.

Nitrogen Recycling and Flowering Time in Perennial Bioenergy Crops

PubMed Central

Schwartz, Christopher; Amasino, Richard

2013-01-01

Perennials have a number of traits important for profitability and sustainability of a biofuel crop. Perennialism is generally defined as the ability to grow and reproduce in multiple years. In temperate climates, many perennial plants enter dormancy during winter and recycle nutrients, such as nitrogen, to below ground structures for the next growing season. Nitrogen is expensive to produce and application of nitrogen increases the potent greenhouse gas NOx. Perennial bioenergy crops have been evaluated for biomass yields with nitrogen fertilization, location, year, and genotype as variables. Flowering time and dormancy are closely related to the N recycling program. Substantial variation for flowering time and dormancy has been identified in the switchgrass (Panicum virgatum L.) species, which provides a source to identify the genetic components of N recycling, and for use in breeding programs. Some studies have addressed recycling specifically, but flowering time and developmental differences were largely ignored, complicating interpretation of the results. Future studies on recycling need to appreciate plant developmental stage to allow comparison between experiments. A perennial/annual model(s) and more environmentally controlled experiments would be useful to determine the genetic components of nitrogen recycling. Increasing biomass yield per unit of nitrogen by maximizing recycling might mean the difference for profitability of a biofuel crop and has the added benefit of minimizing negative environmental effects from agriculture. PMID:23626592

Spatial Mapping of Agricultural Water Productivity Using the SWAT Model

NASA Astrophysics Data System (ADS)

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

2015-03-01

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

Estimating yield gaps at the cropping system level.

PubMed

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

2017-05-01

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

Weather-based forecasts of California crop yields

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

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

2005-09-26

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

Identifying Effective Policy and Technologic Reforms for Sustainable Groundwater Management in Oman

NASA Astrophysics Data System (ADS)

Madani, K.; Zekri, S.; Karimi, A.

2014-12-01

Oman has gone through three decades of efforts aimed at addressing groundwater over-pumping and the consequent seawater intrusion. Example of measures adopted by the government since the 1990's include a vast subsidy program of irrigation modernization, a freeze on drilling new wells, delimitation of several no-drill zones, a crop substitution program, re-use of treated wastewater and construction of recharge dams. With no major success through these measures, the government laid the ground for water quotas by creating a new regulation in 1995. Nevertheless, groundwater quotas have not been enforced to date due to the high implementation and monitoring costs of traditional flow meters. This presentation discusses how sustainable groundwater management can be secured in Oman using a suit of policy and technologic reforms at a reasonable economic, political and practical cost. Data collected from farms with smart meters and low-cost wireless smart irrigation systems have been used to propose sustainable groundwater withdrawal strategies for Oman using a detailed hydro-economic model that couples a MODFLOW-SEAWAT model of the coastal aquifers with a dynamic profit maximization model. The hydro-economic optimization model was flexible to be run both as a social planner model to maximize the social welfare in the region, and as an agent-based model to capture the behavior of farmers interested in maximizing their profits independently. This flexibility helped capturing the trade-off between the optimality of the social planner solution developed at the system's level and its practicality (stability) with respect to the concerns and behaviors of the profit-maximizing farmers. The idetified promising policy and technolgical reforms for Oman include strict enforcement of groundwater quotas, smart metering, changing crop mixes, improving irrigation technologies, and revising geographical distribution of the farming activities. The presentation will discuss how different combinations of these reforms would affect groundwater and energy use, groundwater level and salinity, crop yield, and agricultural revenues in the future.

The Implications of Future Food Demand on Global Land Use, Land-Use Change Emissions, and Climate

NASA Astrophysics Data System (ADS)

Calvin, K. V.; Wise, M.; Kyle, P.; Luckow, P.; Clarke, L.; Edmonds, J.; Eom, J.; Kim, S.; Moss, R.; Patel, P.

2011-12-01

In 2005, cropland accounted for approximately 10% of global land area. The amount of cropland needed in the future depends on a number of factors including global population, dietary preferences, and agricultural crop yields. In this paper, we explore the effect of various assumptions about global food demand and agricultural productivity between now and 2100 on global land use, land-use change emissions, and climate using the GCAM model. GCAM is a global integrated assessment model, linking submodules of the regionally disaggregated, global economy, energy system, agriculture and land-use, terrestrial carbon cycle, oceans and climate. GCAM simulates supply, demand, and prices for energy and agricultural goods from 2005 to 2100 in 5-year increments. In each time period, the model computes the allocation of land across a variety of land cover types in 151 different regions, assuming that farmers maximize profits and that food demand is relatively inelastic. For this analysis, we look at the effect of alternative socioeconomic pathways, crop yield improvement assumptions, and future meat demand scenarios on the demand for agricultural land. The three socioeconomic pathways explore worlds where global population in 2100 ranges from 6 billion people to 14 billion people. The crop yield improvement assumptions range from a world where yields do not improve beyond today's levels to a world with significantly higher crop productivity. The meat demand scenarios range from a vegetarian world to a world where meat is a dominant source of calories in the global diet. For each of these scenarios, we find that sufficient land exists to feed the global economy. However, rates of deforestation, bioenergy potential, land-use change emissions, and climate change differ across the scenarios. Under less favorable scenarios, deforestation rates, land-use change emissions, and the rate of climate change can be adversely affected.

Productivity and nutrient cycling in bioenergy cropping systems

NASA Astrophysics Data System (ADS)

Heggenstaller, Andrew Howard

One of the greatest obstacles confronting large-scale biomass production for energy applications is the development of cropping systems that balance the need for increased productive capacity with the maintenance of other critical ecosystem functions including nutrient cycling and retention. To address questions of productivity and nutrient dynamics in bioenergy cropping systems, we conducted two sets of field experiments during 2005-2007, investigating annual and perennial cropping systems designed to generate biomass energy feedstocks. In the first experiment we evaluated productivity and crop and soil nutrient dynamics in three prototypical bioenergy double-crop systems, and in a conventionally managed sole-crop corn system. Double-cropping systems included fall-seeded forage triticale (x Triticosecale Wittmack), succeeded by one of three summer-adapted crops: corn (Zea mays L.), sorghum-sudangrass [Sorghum bicolor (L.) Moench], or sunn hemp (Crotalaria juncea L.). Total dry matter production was greater for triticale/corn and triticale/sorghum-sudangrass compared to sole-crop corn. Functional growth analysis revealed that photosynthetic duration was more important than photosynthetic efficiency in determining biomass productivity of sole-crop corn and double-crop triticale/corn, and that greater yield in the tiritcale/corn system was the outcome of photosynthesis occurring over an extended duration. Increased growth duration in double-crop systems was also associated with reductions in potentially leachable soil nitrogen relative to sole-crop corn. However, nutrient removal in harvested biomass was also greater in the double-crop systems, indicating that over the long-term, double-cropping would mandate increased fertilizer inputs. In a second experiment we assessed the effects of N fertilization on biomass and nutrient partitioning between aboveground and belowground crop components, and on carbon storage by four perennial, warm-season grasses: big bluestem (Andropogon geradii Vitman), switchgrass (Panicum virgatum L.), indiangrass [ Sorghastrum nutans (L.) Nash], and eastern gamagrass (Tripsacum dactyloides L.). Generally, the optimum rate of fertilization for biomass yield by the grasses was 140 kg N ha-1. Nitrogen inputs also had pronounced but grass-specific effects on biomass and nutrient partitioning, and on carbon storage. For big bluestem and switchgrass, 140 kg N ha -1. maximized root biomass, favored allocation of nutrients to roots over shoots, and led to net increases in carbon storage over the study duration. In contrast, for indiangrass and eastern gamagrass, root biomass and root nutrient allocation were generally adversely affected by N fertilization and carbon storage increased only with 0 or 65 kg N ha-1. For all grasses, 220 kg N ha -1 tended to shift allocation of nutrients to shoots over roots and resulted in no net increase in carbon storage. Optimal nitrogen management strategies for perennial, warm-season grass energy crops should take into consideration the effects of N on biomass yield as well as factors such as nutrient and carbon balance that will also impact economic feasibility and environmental sustainability.

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 67% of conventional yield [corrected]. 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.

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

The dynamics of hydroponic crops for simulation studies of the CELSS initial reference configurations

NASA Technical Reports Server (NTRS)

Volk, Tyler

1993-01-01

During the past several years, the NASA Program in Controlled Ecological Life Support Systems (CELSS) has continued apace with crop research and logistic, technological, and scientific strides. These include the CELSS Test Facility planned for the space station and its prototype Engineering Development Unit, soon to be active at Ames Research Center (as well as the advanced crop growth research chamber at Ames); the large environmental growth chambers and the planned human test bed facility at Johnson Space Center; the NSCORT at Purdue with new candidate crops and diverse research into the CELSS components; the gas exchange data for soy, potatoes, and wheat from Kennedy Space Center (KSC); and the high-precision gas exchange data for wheat from Utah State University (USU). All these developments, taken together, speak to the need for crop modeling as a means to connect the findings of the crop physiologists with the engineers designing the system. A need also exists for crop modeling to analyze and predict the gas exchange data from the various locations to maximize the scientific yield from the experiments. One fruitful approach employs what has been called the 'energy cascade'. Useful as a basis for CELSS crop growth experimental design, the energy cascade as a generic modeling approach for CELSS crops is a featured accomplishment in this report. The energy cascade is a major tool for linking CELSS crop experiments to the system design. The energy cascade presented here can help collaborations between modelers and crop experimenters to develop the most fruitful experiments for pushing the limits of crop productivity. Furthermore, crop models using the energy cascade provide a natural means to compare, feature for feature, the crop growth components between different CELSS experiments, for example, at Utah State University and Kennedy Space Center.

Increasing crop diversity mitigates weather variations and improves yield stability.

PubMed

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

2015-01-01

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

An analysis of the energetic reward offered by field bean (Vicia faba) flowers: Nectar, pollen, and operative force.

PubMed

Bailes, Emily J; Pattrick, Jonathan G; Glover, Beverley J

2018-03-01

Global consumption of crops with a yield that is dependent on animal pollinators is growing, with greater areas planted each year. However, the floral traits that influence pollinator visitation are not usually the focus of breeding programmes, and therefore, it is likely that yield improvements may be made by optimizing floral traits to enhance pollinator visitation rates. We investigated the variation present in the floral reward of the bee-pollinated crop Vicia faba (field bean). We examined the genetic potential for breeding flowers with a greater reward into current commercial varieties and used bee behavioral experiments to gain insight into the optimal nectar concentration to maximize bee preference. There was a large range of variation in the amount of pollen and nectar reward of flowers in the genotypes investigated. Bee behavioral experiments using nectar sugar concentrations found in V. faba lines suggest that Bombus terrestris prefers 55% w/w sugar solution over 40% w/w, but has no preference between 55% w/w and 68% w/w sugar solution. We provide a first indication of the force required to open V. faba flowers. Our results provide a valuable starting point toward breeding for varieties with optimized floral reward. Field studies are now needed to verify whether the genetic potential for breeding more rewarding flowers can translate into higher yield and yield stability.

Bridging the gap between feedstock growers and users: the study of a coppice poplar-based biorefinery.

PubMed

Dou, Chang; Gustafson, Rick; Bura, Renata

2018-01-01

In the biofuel industry, land productivity is important to feedstock growers and conversion process product yield is important to the biorefinery. The crop productivity, however, may not positively correlate with bioconversion yield. Therefore, it is important to evaluate sugar yield and biomass productivity. In this study, 2-year-old poplar trees harvested in the first coppice cycle, including one low-productivity hybrid and one high-productivity hybrid, were collected from two poplar tree farms. Through steam pretreatment and enzymatic hydrolysis, the bioconversion yields of low- and high-productivity poplar hybrids were compared for both sites. The low-productivity hybrids had 9-19% higher sugar yields than the high-productivity hybrids, although they have the similar chemical composition. Economic calculations show the impact on the plantation and biorefinery of using the two feedstocks. Growing a high-productivity hybrid means the land owner would use 11-26% less land (which could be used for other crops) or collect $2.53-$3.46 MM/year extra revenue from the surplus feedstock. On the other side, the biorefinery would receive 5-10% additional revenue using the low-productivity hybrid. We propose a business model based on the integration of the plantation and the biorefinery. In this model, different feedstocks are assessed using a metric of product tonnage per unit land per year. Use of this new economic metric bridges the gap between feedstock growers and users to maximize the overall production efficiency.

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.

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

USDA-ARS?s Scientific Manuscript database

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

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

NASA Astrophysics Data System (ADS)

Vico, Giulia; Brunsell, Nathaniel A.

2018-02-01

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

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

NASA Astrophysics Data System (ADS)

Vanderwende, Brian; Lundquist, Julie K.

2016-03-01

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

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

DOE PAGES

Vanderwende, Brian; Lundquist, Julie K.

2015-11-07

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

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

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

Vanderwende, Brian; Lundquist, Julie K.

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

Agricultural interventions for water saving and crop yield improvement, in a Mediterranean area - an experimental design

NASA Astrophysics Data System (ADS)

Morianou, Giasemi; Kourgialas, Nektarios; Psarras, George; Koubouris, George; Arampatzis, George; Karatzas, George; Pavlidou, Elisavet

2017-04-01

This work is a part of LIFE+ AGROCLIMAWATER project and the aim is to improve the water efficiency, increase the adaptive capacity of tree corps and save water, in a Mediterranean area, under different climatic conditions and agricultural practices. The experimental design as well as preliminary results at farm and river basin scales are presented in this work. Specifically, ten (10) pilot farms, both organic and conventional ones have been selected in the sub-basin of Platanias in western Crete - Greece. These ten pilot farms were selected representing the most typical crops in Platanias area (olive trees and citrus trees), as well as the typical soil, landscape and agricultural practices differentiation for each crop (field slope, water availability, soil type, management regime). From the ten pilot farms, eight were olive farms and the rest two citrus. This proportion correspond adequacy to the presentence of olive and citrus crops in the extended area of Platanias prefecture. Each of the ten pilot farm has been divided in two parts, the first one will be used as a control part, while the other one as the demonstration part where the interventions will be applied. The action plans for each selected farm are based on the following groups of possible interventions: a) reduction of water evaporation losses from soil surface, b) reduction of transpiration water losses through winter pruning and summer pruning, c) reduction of deep percolation water and nutrient losses, d) reduction of surface runoff, e) measures in order to maximize the efficiency of irrigation and f) rationalization of fertilizers and agrochemicals utilized. Preliminary results indicate that water saving and crop yield can be significantly improved based on the above innervations both at farm and river basin scale.

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

DOE PAGES

Blanc, Élodie

2017-01-26

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

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

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

Blanc, Élodie

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

Yield and Economic Responses of Peanut to Crop Rotation Sequence

USDA-ARS?s Scientific Manuscript database

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

Using cover crops and cropping systems for nitrogen management

USDA-ARS?s Scientific Manuscript database

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

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

PubMed

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

2018-01-01

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

Increasing Crop Diversity Mitigates Weather Variations and Improves Yield Stability

PubMed Central

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

2015-01-01

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

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

USDA-ARS?s Scientific Manuscript database

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

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

USDA-ARS?s Scientific Manuscript database

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

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

NASA Astrophysics Data System (ADS)

Jayanthi, Harikishan

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

The Nexus Land-Use model version 1.0, an approach articulating biophysical potentials and economic dynamics to model competition for land-use

NASA Astrophysics Data System (ADS)

Souty, F.; Brunelle, T.; Dumas, P.; Dorin, B.; Ciais, P.; Crassous, R.; Müller, C.; Bondeau, A.

2012-02-01

Interactions between food demand, biomass energy and forest preservation are driving both food prices and land-use changes, regionally and globally. This study presents a new model called Nexus Land-Use version 1.0 which describes these interactions through a generic representation of agricultural intensification mechanisms. The Nexus Land-Use model equations combine biophysics and economics into a single coherent framework to calculate crop yields, food prices, and resulting pasture and cropland areas within 12 regions inter-connected with each other by international trade. The representation of cropland and livestock production systems in each region relies on three components: (i) a biomass production function derived from the crop yield response function to inputs such as industrial fertilisers; (ii) a detailed representation of the livestock production system subdivided into an intensive and an extensive component, and (iii) a spatially explicit distribution of potential (maximal) crop yields prescribed from the Lund-Postdam-Jena global vegetation model for managed Land (LPJmL). The economic principles governing decisions about land-use and intensification are adapted from the Ricardian rent theory, assuming cost minimisation for farmers. The land-use modelling approach described in this paper entails several advantages. Firstly, it makes it possible to explore interactions among different types of biomass demand for food and animal feed, in a consistent approach, including indirect effects on land-use change resulting from international trade. Secondly, yield variations induced by the possible expansion of croplands on less suitable marginal lands are modelled by using regional land area distributions of potential yields, and a calculated boundary between intensive and extensive production. The model equations and parameter values are first described in details. Then, idealised scenarios exploring the impact of forest preservation policies or rising energy price on agricultural intensification are described, and their impacts on pasture and cropland areas are investigated.

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

NASA Astrophysics Data System (ADS)

Zeyliger, Anatoly; Ermolaeva, Olga

2016-04-01

Development of modern irrigation technologies are balanced between the need to maximize production and the need to minimize water use which provides harmonious interaction of irrigated systems with closely-spaced environment. Thus requires an understanding of complex interrelationships between landscape and underground of irrigated and adjacent areas in present and future conditions aiming to minimize development of negative scenarios. In this way in each irrigated areas a combination of specific factors and drivers must be recognized and evaluated. Much can be obtained by improving the efficiency use of water applied for irrigation. Modern RS monitoring technologies offers the opportunity to develop and implement an effective irrigation control program permitting today to increase efficiency of irrigation water use. These technologies provide parameters with both high temporal and adequate spatial needed to monitor agrohydrological parameters of irrigated agricultural crops. Combination of these parameters with meteorological and biophysical parameters can be used to estimate crop water stress defined as ratio between actual (ETa) and potential (ETc) evapotranspiration. Aggregation of actual values of crop water stress with biomass (yield) data predicted by agrohydrological model based on weather forecasting and scenarios of irrigation water application may be used for indication of both rational timing and amount of irrigation water allocation. This type of analysis facilitating an efficient water management can be easily extended to irrigated areas by developing maps of water efficiency application serving as an irrigation advice system for farmers at his fields and as a decision support tool for the authorities on the large perimeter irrigation management. This contribution aims to communicate an illustrative explanation about the practical application of a data combination of agrohydrological modeling and ground & space based monitoring. For this aim some results of analyzing water stress during growing season of 2012 and yielded biomass of crops three types of crops alfalfa, corn and soya irrigated by sprinkling machines at left bank of Volga River at Saratov Region of Russia are presented and analyzed. For that a combination of data received from satellite, local meteorological station and farmers as well as SWAP model was used. Analyze of data sets of monitored water deficit of each crop averaged for irrigation period was done by linear regression with yielded biomass values. Following analyze of effectiveness of irrigation water application was done by SWAP agrohydrological model.

Economic Impact of Water Allocation on Agriculture in the Lower Chattahoochee River Basin

NASA Technical Reports Server (NTRS)

Limaye, Ashutosh S.; Paudel, Krishna P.; Musleh, Fuad; Cruise, James F.; Hatch, L. Upton

2004-01-01

The relative value of irrigation water was assessed for three important crops (corn, cotton, and peanuts) grown in the southeastern United States. A decision tool was developed with the objective of allocating limited available water among competing crops in a manner that would maximize the economic returns to the producers. The methodology was developed and tested for a hypothetical farm located in Henry County, Alabama in the Chattahoochee river basin. Crop yield - soil moisture response functions were developed using Monte Carlo simulated data for cotton, corn, and peanuts. A hydrologic model was employed to simulate runoff over the period of observed rainfall the county to provide inflows to storage facilities that could be used as constraints for the optimal allocation of the available water in the face of the uncertainty of future rainfall and runoff. Irrigation decisions were made on a weekly basis during the critical water deficit period in the region. An economic optimization model was employed with the crop responses, and soil moisture functions to determine the optimum amount of water place on each crop subject to the amount of irrigation water availability and climatic uncertainty. The results indicated even small amounts of irrigation could significantly benefit farmers in the region if applied judiciously. A weekly irrigation sequence was developed that maintained the available water on the crops that exhibited the most significant combination of water sensitivity and cash value.

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

PubMed

Dubey, Swatantra Kumar; Sharma, Devesh

2018-09-01

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

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

NASA Astrophysics Data System (ADS)

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

2012-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

USDA-ARS?s Scientific Manuscript database

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

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.

Progress and Challenges in Predicting Crop Responses to Atmospheric [CO2

NASA Astrophysics Data System (ADS)

Kent, J.; Paustian, K.

2017-12-01

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

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

UAV-Based Hyperspectral Remote Sensing for Precision Agriculture: Challenges and Opportunities

NASA Astrophysics Data System (ADS)

Angel, Y.; Parkes, S. D.; Turner, D.; Houborg, R.; Lucieer, A.; McCabe, M.

2017-12-01

Modern agricultural production relies on monitoring crop status by observing and measuring variables such as soil condition, plant health, fertilizer and pesticide effect, irrigation and crop yield. Managing all of these factors is a considerable challenge for crop producers. As such, providing integrated technological solutions that enable improved diagnostics of field condition to maximize profits, while minimizing environmental impacts, would be of much interest. Such challenges can be addressed by implementing remote sensing systems such as hyperspectral imaging to produce precise biophysical indicator maps across the various cycles of crop development. Recent progress in unmanned aerial vehicles (UAVs) have advanced traditional satellite-based capabilities, providing a capacity for high-spatial, spectral and temporal response. However, while some hyperspectral sensors have been developed for use onboard UAVs, significant investment is required to develop a system and data processing workflow that retrieves accurately georeferenced mosaics. Here we explore the use of a pushbroom hyperspectral camera that is integrated on-board a multi-rotor UAV system to measure the surface reflectance in 272 distinct spectral bands across a wavelengths range spanning 400-1000 nm, and outline the requirement for sensor calibration, integration onto a stable UAV platform enabling accurate positional data, flight planning, and development of data post-processing workflows for georeferenced mosaics. The provision of high-quality and geo-corrected imagery facilitates the development of metrics of vegetation health that can be used to identify potential problems such as production inefficiencies, diseases and nutrient deficiencies and other data-streams to enable improved crop management. Immense opportunities remain to be exploited in the implementation of UAV-based hyperspectral sensing (and its combination with other imaging systems) to provide a transferable and scalable integrated framework for crop growth monitoring and yield prediction. Here we explore some of the challenges and issues in translating the available technological capacity into a useful and useable image collection and processing flow-path that enables these potential applications to be better realized.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-08-01

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

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

PubMed

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

2017-08-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-07-01

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

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

NASA Astrophysics Data System (ADS)

Setiyono, T. D.

2014-12-01

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

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

NASA Technical Reports Server (NTRS)

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

2014-01-01

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

Investment risk in bioenergy crops

DOE PAGES

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

2015-11-18

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

Investment risk in bioenergy crops

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

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

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

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Maximizing the potential of cropping systems for nematode management.

PubMed

Noe, J P; Sasser, J N; Imbriani, J L

1991-07-01

Quantitative techniques were used to analyze and determine optimal potential profitability of 3-year rotations of cotton, Gossypium hirsutum cv. Coker 315, and soybean, Glycine max cv. Centennial, with increasing population densities of Hoplolaimus columbus. Data collected from naturally infested on-farm research plots were combined with economic information to construct a microcomputer spreadsheet analysis of the cropping system. Nonlinear mathematical functions were fitted to field data to represent damage functions and population dynamic curves. Maximum yield losses due to H. columbus were estimated to be 20% on cotton and 42% on soybean. Maximum at-harvest population densities were calculated to be 182/100 cm(3) soil for cotton and 149/100 cm(3) soil for soybean. Projected net incomes ranged from a $17.74/ha net loss for the soybean-cotton-soybean sequence to a net profit of $46.80/ha for the cotton-soybean-cotton sequence. The relative profitability of various rotations changed as nematode densities increased, indicating economic thresholds for recommending alternative crop sequences. The utility and power of quantitative optimization was demonstrated for comparisons of rotations under different economic assumptions and with other management alternatives.

Soil management shapes ecosystem service provision and trade-offs in agricultural landscapes.

PubMed

Tamburini, Giovanni; De Simone, Serena; Sigura, Maurizia; Boscutti, Francesco; Marini, Lorenzo

2016-08-31

Agroecosystems are principally managed to maximize food provisioning even if they receive a large array of supporting and regulating ecosystem services (ESs). Hence, comprehensive studies investigating the effects of local management and landscape composition on the provision of and trade-offs between multiple ESs are urgently needed. We explored the effects of conservation tillage, nitrogen fertilization and landscape composition on six ESs (crop production, disease control, soil fertility, water quality regulation, weed and pest control) in winter cereals. Conservation tillage enhanced soil fertility and pest control, decreased water quality regulation and weed control, without affecting crop production and disease control. Fertilization only influenced crop production by increasing grain yield. Landscape intensification reduced the provision of disease and pest control. We also found tillage and landscape composition to interactively affect water quality regulation and weed control. Under N fertilization, conventional tillage resulted in more trade-offs between ESs than conservation tillage. Our results demonstrate that soil management and landscape composition affect the provision of several ESs and that soil management potentially shapes the trade-offs between them. © 2016 The Author(s).

High-yield maize with large net energy yield and small global warming intensity

PubMed Central

Grassini, Patricio; Cassman, Kenneth G.

2012-01-01

Addressing concerns about future food supply and climate change requires management practices that maximize productivity per unit of arable land while reducing negative environmental impact. On-farm data were evaluated to assess energy balance and greenhouse gas (GHG) emissions of irrigated maize in Nebraska that received large nitrogen (N) fertilizer (183 kg of N⋅ha−1) and irrigation water inputs (272 mm or 2,720 m3 ha−1). Although energy inputs (30 GJ⋅ha−1) were larger than those reported for US maize systems in previous studies, irrigated maize in central Nebraska achieved higher grain and net energy yields (13.2 Mg⋅ha−1 and 159 GJ⋅ha−1, respectively) and lower GHG-emission intensity (231 kg of CO2e⋅Mg−1 of grain). Greater input-use efficiencies, especially for N fertilizer, were responsible for better performance of these irrigated systems, compared with much lower-yielding, mostly rainfed maize systems in previous studies. Large variation in energy inputs and GHG emissions across irrigated fields in the present study resulted from differences in applied irrigation water amount and imbalances between applied N inputs and crop N demand, indicating potential to further improve environmental performance through better management of these inputs. Observed variation in N-use efficiency, at any level of applied N inputs, suggests that an N-balance approach may be more appropriate for estimating soil N2O emissions than the Intergovernmental Panel on Climate Change approach based on a fixed proportion of applied N. Negative correlation between GHG-emission intensity and net energy yield supports the proposition that achieving high yields, large positive energy balance, and low GHG emissions in intensive cropping systems are not conflicting goals. PMID:22232684

Diverse rotations and poultry litter improves soybean yield

USDA-ARS?s Scientific Manuscript database

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

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

DOE PAGES

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

2017-06-27

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

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

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

Blanc, Elodie; Caron, Justin; Fant, Charles

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

Root-knot nematode management in double-cropped plasticulture vegetables.

PubMed

Desaeger, J A; Csinos, A S

2006-03-01

Combination treatments of chisel-injected fumigants (methyl bromide, 1,3-D, metam sodium, and chloropicrin) on a first crop, followed by drip-applied fumigants (metam sodium and 1,3-D +/- chloropicrin) on a second crop, with and without oxamyl drip applications were evaluated for control of Meloidogyne incognita in three different tests (2002 to 2004) in Tifton, GA. First crops were eggplant or tomato, and second crops were cantaloupe, squash, or jalapeno pepper. Double-cropped vegetables suffered much greater root-knot nematode (RKN) pressure than first crops, and almost-total yield loss occurred when second crops received no nematicide treatment. On a first crop of eggplant, all fumigants provided good nematode control and average yield increases of 10% to 15 %. On second crops, higher application rates and fumigant combinations (metam sodium and 1,3-D +/- chloropicrin) improved RKN control and increased yields on average by 20% to 35 % compared to the nonfumigated control. Oxamyl increased yields of the first crop in 2003 on average by 10% to 15% but had no effect in 2004 when RKN failed to establish itself. On double-cropped squash in 2003, oxamyl following fumigation provided significant additional reduction in nematode infection and increased squash yields on average by 30% to 75%.

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

NASA Astrophysics Data System (ADS)

Jeffries, G. R.; Cohn, A.

2016-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2011-06-01

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

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

PubMed

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

2017-04-01

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

Assessment of agronomic homogeneity and compatibility of soils in the Vladimir Opolie region

NASA Astrophysics Data System (ADS)

Shein, E. V.; Kiryushin, V. I.; Korchagin, A. A.; Mazirov, M. A.; Dembovetskii, A. V.; Il'in, L. I.

2017-10-01

Complexes of gray forest soils of different podzolization degrees with the participation of gray forest podzolized soils with the second humus horizon play a noticeable role in the soil cover patterns of Vladimir Opolie. The agronomic homogeneity and agronomic compatibility of gray forest soils in automorphic positions ("plakor" sites) were assessed on the test field of the Vladimir Agricultural Research Institute. The term "soil homogeneity" implies in our study the closeness of crop yield estimates (scores) for the soil polygons; the term "soil compatibility" implies the possibility to apply the same technologies in the same dates for different soil polygons within a field. To assess the agronomic homogeneity and compatibility of soils, the statistical analysis of the yields of test crop (oats) was performed, and the spatial distribution of the particular parameters of soil hydrothermic regime was studied. The analysis of crop yields showed their high variability: the gray forest soils on microhighs showed the minimal potential fertility, and the maximal fertility was typical of the soils with the second humus horizon in microlows. Soils also differed significantly in their hydrothermic regime, as the gray forest soils with the second humus horizon were heated and cooled slower than the background gray forest soils; their temperature had a stronger lag effect and displayed a narrower amplitude in seasonal fluctuations; and these soils were wetter during the first weeks (40 days) of the growing season. Being colder and wetter, the soils with the second humus horizons reached their physical ripeness later than the gray forest soils. Thus, the soil cover of the test plot in the automorphic position is heterogeneous; from the agronomic standpoint, its components are incompatible.

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

NASA Astrophysics Data System (ADS)

Botchway, E.

2016-12-01

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

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

USDA-ARS?s Scientific Manuscript database

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

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

PubMed

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

2018-05-31

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

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

USDA-ARS?s Scientific Manuscript database

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

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

USDA-ARS?s Scientific Manuscript database

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

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

NASA Astrophysics Data System (ADS)

Terres, J. M.; Cantelaube, P.

2003-04-01

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

Benefits of seasonal forecasts of crop yields

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

Nitrogen rate strategies for reducing yield-scaled nitrous oxide emissions in maize

NASA Astrophysics Data System (ADS)

Zhao, Xu; Nafziger, Emerson D.; Pittelkow, Cameron M.

2017-12-01

Mitigating nitrogen (N) losses from agriculture without negatively impacting crop productivity is a pressing environmental and economic challenge. Reductions in N fertilizer rate are often highlighted as a solution, yet the degree to which crop yields and economic returns may be impacted at the field-level remains unclear, in part due to limited data availability. Farmers are risk averse and potential yield losses may limit the success of voluntary N loss mitigation protocols, thus understanding field-level yield tradeoffs is critical to inform policy development. Using a case study of soil N2O mitigation in the US Midwest, we conducted an ex-post assessment of two economic and two environmental N rate reduction strategies to identify promising practices for maintaining maize yields and economic returns while reducing N2O emissions per unit yield (i.e. yield-scaled emissions) compared to an assumed baseline N input level. Maize yield response data from 201 on-farm N rate experiments were combined with an empirical equation predicting N2O emissions as a function of N rate. Results indicate that the economic strategy aimed at maximizing returns to N (MRTN) led to moderate but consistent reductions in yield-scaled N2O emissions with small negative impacts on yield and slight increases in median returns. The economic optimum N rate strategy reduced yield-scaled N2O emissions in 75% of cases but increased them otherwise, challenging the assumption that this strategy will automatically reduce environmental impacts per unit production. Both environmental strategies, one designed to increase N recovery efficiency and one to balance N inputs with grain N removal, further reduced yield-scaled N2O emissions but were also associated with negative yield penalties and decreased returns. These results highlight the inherent tension between achieving agronomic and economic goals while reducing environmental impacts which is often overlooked in policy discussions. To enable the development of more scalable environmental N loss mitigation strategies, yield tradeoffs occurring at the critical point of adoption (i.e. the farm-level) should be considered.

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

PubMed

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

2015-10-07

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

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

NASA Astrophysics Data System (ADS)

Gao, F.; Anderson, M. C.

2017-12-01

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

Food Crops Response to Climate Change

NASA Astrophysics Data System (ADS)

Butler, E.; Huybers, P.

2009-12-01

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

Root-Knot Nematode Management in Double-Cropped Plasticulture Vegetables

PubMed Central

Desaeger, J. A.; Csinos, A. S.

2006-01-01

Combination treatments of chisel-injected fumigants (methyl bromide, 1,3-D, metam sodium, and chloropicrin) on a first crop, followed by drip-applied fumigants (metam sodium and 1,3-D ± chloropicrin) on a second crop, with and without oxamyl drip applications were evaluated for control of Meloidogyne incognita in three different tests (2002 to 2004) in Tifton, GA. First crops were eggplant or tomato, and second crops were cantaloupe, squash, or jalapeno pepper. Double-cropped vegetables suffered much greater root-knot nematode (RKN) pressure than first crops, and almost-total yield loss occurred when second crops received no nematicide treatment. On a first crop of eggplant, all fumigants provided good nematode control and average yield increases of 10% to 15 %. On second crops, higher application rates and fumigant combinations (metam sodium and 1,3-D ± chloropicrin) improved RKN control and increased yields on average by 20% to 35 % compared to the nonfumigated control. Oxamyl increased yields of the first crop in 2003 on average by 10% to 15% but had no effect in 2004 when RKN failed to establish itself. On double-cropped squash in 2003, oxamyl following fumigation provided significant additional reduction in nematode infection and increased squash yields on average by 30% to 75%. PMID:19259431

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

Global biomass production potentials exceed expected future demand without the need for cropland expansion

PubMed Central

Mauser, Wolfram; Klepper, Gernot; Zabel, Florian; Delzeit, Ruth; Hank, Tobias; Putzenlechner, Birgitta; Calzadilla, Alvaro

2015-01-01

Global biomass demand is expected to roughly double between 2005 and 2050. Current studies suggest that agricultural intensification through optimally managed crops on today's cropland alone is insufficient to satisfy future demand. In practice though, improving crop growth management through better technology and knowledge almost inevitably goes along with (1) improving farm management with increased cropping intensity and more annual harvests where feasible and (2) an economically more efficient spatial allocation of crops which maximizes farmers' profit. By explicitly considering these two factors we show that, without expansion of cropland, today's global biomass potentials substantially exceed previous estimates and even 2050s' demands. We attribute 39% increase in estimated global production potentials to increasing cropping intensities and 30% to the spatial reallocation of crops to their profit-maximizing locations. The additional potentials would make cropland expansion redundant. Their geographic distribution points at possible hotspots for future intensification. PMID:26558436

Global biomass production potentials exceed expected future demand without the need for cropland expansion.

PubMed

Mauser, Wolfram; Klepper, Gernot; Zabel, Florian; Delzeit, Ruth; Hank, Tobias; Putzenlechner, Birgitta; Calzadilla, Alvaro

2015-11-12

Global biomass demand is expected to roughly double between 2005 and 2050. Current studies suggest that agricultural intensification through optimally managed crops on today's cropland alone is insufficient to satisfy future demand. In practice though, improving crop growth management through better technology and knowledge almost inevitably goes along with (1) improving farm management with increased cropping intensity and more annual harvests where feasible and (2) an economically more efficient spatial allocation of crops which maximizes farmers' profit. By explicitly considering these two factors we show that, without expansion of cropland, today's global biomass potentials substantially exceed previous estimates and even 2050s' demands. We attribute 39% increase in estimated global production potentials to increasing cropping intensities and 30% to the spatial reallocation of crops to their profit-maximizing locations. The additional potentials would make cropland expansion redundant. Their geographic distribution points at possible hotspots for future intensification.

Nature-based agricultural solutions: Scaling perennial grains across Africa.

PubMed

Peter, Brad G; Mungai, Leah M; Messina, Joseph P; Snapp, Sieglinde S

2017-11-01

Modern plant breeding tends to focus on maximizing yield, with one of the most ubiquitous implementations being shorter-duration crop varieties. It is indisputable that these breeding efforts have resulted in greater yields in ideal circumstances; however, many farmed locations across Africa suffer from one or more conditions that limit the efficacy of modern short-duration hybrids. In view of global change and increased necessity for intensification, perennial grains and long-duration varieties offer a nature-based solution for improving farm productivity and smallholder livelihoods in suboptimal agricultural areas. Specific conditions where perennial grains should be considered include locations where biophysical and social constraints reduce agricultural system efficiency, and where conditions are optimal for crop growth. Using a time-series of remotely-sensed data, we locate the marginal agricultural lands of Africa, identifying suboptimal temperature and precipitation conditions for the dominant crop, i.e., maize, as well as optimal climate conditions for two perennial grains, pigeonpea and sorghum. We propose that perennial grains offer a lower impact, sustainable nature-based solution to this subset of climatic drivers of marginality. Using spatial analytic methods and satellite-derived climate information, we demonstrate the scalability of perennial pigeonpea and sorghum across Africa. As a nature-based solution, we argue that perennial grains offer smallholder farmers of marginal lands a sustainable solution for enhancing resilience and minimizing risk in confronting global change, while mitigating social and edaphic drivers of low and variable production. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

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

PubMed

Qiao, Jianmin; Yu, Deyong; Liu, Yupeng

2017-10-01

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

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

PubMed

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

2015-10-01

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

Statistical Analysis of Large Simulated Yield Datasets for Studying Climate Effects

NASA Technical Reports Server (NTRS)

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

Spatial and Temporal Uncertainty of Crop Yield Aggregations

NASA Technical Reports Server (NTRS)

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

NASA Astrophysics Data System (ADS)

Sharma, A. N.

2015-12-01

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

Detection of meteorological extreme effect on historical crop yield anomaly

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2013-11-01

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

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

NASA Technical Reports Server (NTRS)

1978-01-01

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

Yield model development project implementation plan

NASA Technical Reports Server (NTRS)

Ambroziak, R. A.

1982-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Regional crop yield forecasting: a probabilistic approach

NASA Astrophysics Data System (ADS)

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

2009-04-01

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

Spatial Sampling of Weather Data for Regional Crop Yield Simulations

NASA Technical Reports Server (NTRS)

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

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

PubMed

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

2007-12-01

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

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

PubMed

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

2011-05-01

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

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

NASA Astrophysics Data System (ADS)

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

2011-02-01

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

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

DOE PAGES

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

2016-09-12

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

Yield and Economic Responses of Peanut to Crop Rotation Sequence

USDA-ARS?s Scientific Manuscript database

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

Hyperspectral imagery for mapping crop yield for precision agriculture

USDA-ARS?s Scientific Manuscript database

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

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.

Elucidating the impact of temperature variability and extremes on cereal croplands through remote sensing.

PubMed

Duncan, John M A; Dash, Jadunandan; Atkinson, Peter M

2015-04-01

Remote sensing-derived wheat crop yield-climate models were developed to highlight the impact of temperature variation during thermo-sensitive periods (anthesis and grain-filling; TSP) of wheat crop development. Specific questions addressed are: can the impact of temperature variation occurring during the TSP on wheat crop yield be detected using remote sensing data and what is the impact? Do crop critical temperature thresholds during TSP exist in real world cropping landscapes? These questions are tested in one of the world's major wheat breadbaskets of Punjab and Haryana, north-west India. Warming average minimum temperatures during the TSP had a greater negative impact on wheat crop yield than warming maximum temperatures. Warming minimum and maximum temperatures during the TSP explain a greater amount of variation in wheat crop yield than average growing season temperature. In complex real world cereal croplands there was a variable yield response to critical temperature threshold exceedance, specifically a more pronounced negative impact on wheat yield with increased warming events above 35 °C. The negative impact of warming increases with a later start-of-season suggesting earlier sowing can reduce wheat crop exposure harmful temperatures. However, even earlier sown wheat experienced temperature-induced yield losses, which, when viewed in the context of projected warming up to 2100 indicates adaptive responses should focus on increasing wheat tolerance to heat. This study shows it is possible to capture the impacts of temperature variation during the TSP on wheat crop yield in real world cropping landscapes using remote sensing data; this has important implications for monitoring the impact of climate change, variation and heat extremes on wheat croplands. © 2014 John Wiley & Sons Ltd.

Effect of cover crops on greenhouse gas emissions in an irrigated field under integrated soil fertility management

NASA Astrophysics Data System (ADS)

Guardia, Guillermo; Abalos, Diego; García-Marco, Sonia; Quemada, Miguel; Alonso-Ayuso, María; Cárdenas, Laura M.; Dixon, Elizabeth R.; Vallejo, Antonio

2016-09-01

Agronomical and environmental benefits are associated with replacing winter fallow by cover crops (CCs). Yet, the effect of this practice on nitrous oxide (N2O) emissions remains poorly understood. In this context, a field experiment was carried out under Mediterranean conditions to evaluate the effect of replacing the traditional winter fallow (F) by vetch (Vicia sativa L.; V) or barley (Hordeum vulgare L.; B) on greenhouse gas (GHG) emissions during the intercrop and the maize (Zea mays L.) cropping period. The maize was fertilized following integrated soil fertility management (ISFM) criteria. Maize nitrogen (N) uptake, soil mineral N concentrations, soil temperature and moisture, dissolved organic carbon (DOC) and GHG fluxes were measured during the experiment. Our management (adjusted N synthetic rates due to ISFM) and pedo-climatic conditions resulted in low cumulative N2O emissions (0.57 to 0.75 kg N2O-N ha-1 yr-1), yield-scaled N2O emissions (3-6 g N2O-N kg aboveground N uptake-1) and N surplus (31 to 56 kg N ha-1) for all treatments. Although CCs increased N2O emissions during the intercrop period compared to F (1.6 and 2.6 times in B and V, respectively), the ISFM resulted in similar cumulative emissions for the CCs and F at the end of the maize cropping period. The higher C : N ratio of the B residue led to a greater proportion of N2O losses from the synthetic fertilizer in these plots when compared to V. No significant differences were observed in CH4 and CO2 fluxes at the end of the experiment. This study shows that the use of both legume and nonlegume CCs combined with ISFM could provide, in addition to the advantages reported in previous studies, an opportunity to maximize agronomic efficiency (lowering synthetic N requirements for the subsequent cash crop) without increasing cumulative or yield-scaled N2O losses.

Cover crops support ecological intensification of arable cropping systems

NASA Astrophysics Data System (ADS)

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

2017-02-01

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

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

PubMed Central

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

2014-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-06-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

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

PubMed

Kukal, Meetpal S; Irmak, Suat

2018-02-22

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

Random Forests for Global and Regional Crop Yield Predictions.

PubMed

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

2016-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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.

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

NASA Astrophysics Data System (ADS)

Ben-Ari, Tamara; Makowski, David

2016-10-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

An Investigation of Generalized Differential Evolution Metaheuristic for Multiobjective Optimal Crop-Mix Planning Decision

PubMed Central

Olugbara, Oludayo

2014-01-01

This paper presents an annual multiobjective crop-mix planning as a problem of concurrent maximization of net profit and maximization of crop production to determine an optimal cropping pattern. The optimal crop production in a particular planting season is a crucial decision making task from the perspectives of economic management and sustainable agriculture. A multiobjective optimal crop-mix problem is formulated and solved using the generalized differential evolution 3 (GDE3) metaheuristic to generate a globally optimal solution. The performance of the GDE3 metaheuristic is investigated by comparing its results with the results obtained using epsilon constrained and nondominated sorting genetic algorithms—being two representatives of state-of-the-art in evolutionary optimization. The performance metrics of additive epsilon, generational distance, inverted generational distance, and spacing are considered to establish the comparability. In addition, a graphical comparison with respect to the true Pareto front for the multiobjective optimal crop-mix planning problem is presented. Empirical results generally show GDE3 to be a viable alternative tool for solving a multiobjective optimal crop-mix planning problem. PMID:24883369

An investigation of generalized differential evolution metaheuristic for multiobjective optimal crop-mix planning decision.

PubMed

Adekanmbi, Oluwole; Olugbara, Oludayo; Adeyemo, Josiah

2014-01-01

This paper presents an annual multiobjective crop-mix planning as a problem of concurrent maximization of net profit and maximization of crop production to determine an optimal cropping pattern. The optimal crop production in a particular planting season is a crucial decision making task from the perspectives of economic management and sustainable agriculture. A multiobjective optimal crop-mix problem is formulated and solved using the generalized differential evolution 3 (GDE3) metaheuristic to generate a globally optimal solution. The performance of the GDE3 metaheuristic is investigated by comparing its results with the results obtained using epsilon constrained and nondominated sorting genetic algorithms-being two representatives of state-of-the-art in evolutionary optimization. The performance metrics of additive epsilon, generational distance, inverted generational distance, and spacing are considered to establish the comparability. In addition, a graphical comparison with respect to the true Pareto front for the multiobjective optimal crop-mix planning problem is presented. Empirical results generally show GDE3 to be a viable alternative tool for solving a multiobjective optimal crop-mix planning problem.

The uncertainty of crop yield projections is reduced by improved temperature response functions.

PubMed

Wang, Enli; Martre, Pierre; Zhao, Zhigan; Ewert, Frank; Maiorano, Andrea; Rötter, Reimund P; Kimball, Bruce A; Ottman, Michael J; Wall, Gerard W; White, Jeffrey W; Reynolds, Matthew P; Alderman, Phillip D; Aggarwal, Pramod K; Anothai, Jakarat; Basso, Bruno; Biernath, Christian; Cammarano, Davide; Challinor, Andrew J; De Sanctis, Giacomo; Doltra, Jordi; Fereres, Elias; Garcia-Vila, Margarita; Gayler, Sebastian; Hoogenboom, Gerrit; Hunt, Leslie A; Izaurralde, Roberto C; Jabloun, Mohamed; Jones, Curtis D; Kersebaum, Kurt C; Koehler, Ann-Kristin; Liu, Leilei; Müller, Christoph; Naresh Kumar, Soora; Nendel, Claas; O'Leary, Garry; Olesen, Jørgen E; Palosuo, Taru; Priesack, Eckart; Eyshi Rezaei, Ehsan; Ripoche, Dominique; Ruane, Alex C; Semenov, Mikhail A; Shcherbak, Iurii; Stöckle, Claudio; Stratonovitch, Pierre; Streck, Thilo; Supit, Iwan; Tao, Fulu; Thorburn, Peter; Waha, Katharina; Wallach, Daniel; Wang, Zhimin; Wolf, Joost; Zhu, Yan; Asseng, Senthold

2017-07-17

Increasing the accuracy of crop productivity estimates is a key element in planning adaptation strategies to ensure global food security under climate change. Process-based crop models are effective means to project climate impact on crop yield, but have large uncertainty in yield simulations. Here, we show that variations in the mathematical functions currently used to simulate temperature responses of physiological processes in 29 wheat models account for >50% of uncertainty in simulated grain yields for mean growing season temperatures from 14 °C to 33 °C. We derived a set of new temperature response functions that when substituted in four wheat models reduced the error in grain yield simulations across seven global sites with different temperature regimes by 19% to 50% (42% average). We anticipate the improved temperature responses to be a key step to improve modelling of crops under rising temperature and climate change, leading to higher skill of crop yield projections.

The Uncertainty of Crop Yield Projections Is Reduced by Improved Temperature Response Functions

NASA Technical Reports Server (NTRS)

Wang, Enli; Martre, Pierre; Zhao, Zhigan; Ewert, Frank; Maiorano, Andrea; Rotter, Reimund P.; Kimball, Bruce A.; Ottman, Michael J.; White, Jeffrey W.; Reynolds, Matthew P.;

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

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

NASA Astrophysics Data System (ADS)

Li, X.; Troy, T. J.

2018-06-01

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

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

PubMed

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

2015-11-01

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

Quantifying yield gaps in wheat production in Russia

NASA Astrophysics Data System (ADS)

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

2014-08-01

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

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

NASA Technical Reports Server (NTRS)

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

2011-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

Rational Phosphorus Application Facilitates the Sustainability of the Wheat/Maize/Soybean Relay Strip Intercropping System

PubMed Central

Wang, Ke; Liu, Jing; Lu, Junyu; Xu, Kaiwei

2015-01-01

Wheat (Triticum aestivum L.)/maize (Zea mays L.)/soybean (Glycine max L.) relay strip intercropping (W/M/S) system is commonly used by the smallholders in the Southwest of China. However, little known is how to manage phosphorus (P) to enhance P use efficiency of the W/M/S system and to mitigate P leaching that is a major source of pollution. Field experiments were carried out in 2011, 2012, and 2013 to test the impact of five P application rates on yield and P use efficiency of the W/M/S system. The study measured grain yield, shoot P uptake, apparent P recovery efficiency (PRE) and soil P content. A linear-plateau model was used to determine the critical P rate that maximizes gains in the indexes of system productivity. The results show that increase in P application rates aggrandized shoot P uptake and crops yields at threshold rates of 70 and 71.5 kg P ha-1 respectively. With P application rates increasing, the W/M/S system decreased the PRE from 35.9% to 12.3% averaged over the three years. A rational P application rate, 72 kg P ha-1, or an appropriate soil Olsen-P level, 19.1 mg kg-1, drives the W/M/S system to maximize total grain yield while minimizing P surplus, as a result of the PRE up to 28.0%. We conclude that rational P application is an important approach for relay intercropping to produce high yield while mitigating P pollution and the rational P application-based integrated P fertilizer management is vital for sustainable intensification of agriculture in the Southwest of China. PMID:26540207

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Crop yield response to increasing biochar rates

USDA-ARS?s Scientific Manuscript database

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

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

NASA Astrophysics Data System (ADS)

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

2010-12-01

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

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

PubMed

Ierna, Anita

2010-01-15

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

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

Agricultural Management Practices Explain Variation in Global Yield Gaps of Major Crops

NASA Astrophysics Data System (ADS)

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

2010-12-01

The continued expansion and intensification of agriculture are key drivers of global environmental change. Meeting a doubling of food demand in the next half-century will further induce environmental change, requiring either large cropland expansion into carbon- and biodiversity-rich tropical forests or increasing yields on existing croplands. Closing the “yield gaps” between the most and least productive farmers on current agricultural lands is a necessary and major step towards preserving natural ecosystems and meeting future food demand. Here we use global climate, soils, and cropland datasets to quantify yield gaps for major crops using equal-area climate analogs. Consistent with previous studies, we find large yield gaps for many crops in Eastern Europe, tropical Africa, and parts of Mexico. To analyze the drivers of yield gaps, we collected sub-national agricultural management data and built a global dataset of fertilizer application rates for over 160 crops. We constructed empirical crop yield models for each climate analog using the global management information for 17 major crops. We find that our climate-specific models explain a substantial amount of the global variation in yields. These models could be widely applied to identify management changes needed to close yield gaps, analyze the environmental impacts of agricultural intensification, and identify climate change adaptation techniques.

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

PubMed Central

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

2015-01-01

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

7 CFR 400.651 - Definitions.

Code of Federal Regulations, 2012 CFR

2012-01-01

... unadjusted transitional yields and dividing the sum by the number of yields contained in the database, which will always contain at least four yields. The database may contain up to 10 consecutive crop years of... catastrophic risk protection. Crop of economic significance. A crop that has either contributed in the previous...

7 CFR 400.651 - Definitions.

Code of Federal Regulations, 2014 CFR

2014-01-01

... unadjusted transitional yields and dividing the sum by the number of yields contained in the database, which will always contain at least four yields. The database may contain up to 10 consecutive crop years of... catastrophic risk protection. Crop of economic significance. A crop that has either contributed in the previous...

7 CFR 400.651 - Definitions.

Code of Federal Regulations, 2013 CFR

2013-01-01

... unadjusted transitional yields and dividing the sum by the number of yields contained in the database, which will always contain at least four yields. The database may contain up to 10 consecutive crop years of... catastrophic risk protection. Crop of economic significance. A crop that has either contributed in the previous...

7 CFR 400.651 - Definitions.

Code of Federal Regulations, 2010 CFR

2010-01-01

... unadjusted transitional yields and dividing the sum by the number of yields contained in the database, which will always contain at least four yields. The database may contain up to 10 consecutive crop years of... catastrophic risk protection. Crop of economic significance. A crop that has either contributed in the previous...

7 CFR 400.651 - Definitions.

Code of Federal Regulations, 2011 CFR

2011-01-01

... unadjusted transitional yields and dividing the sum by the number of yields contained in the database, which will always contain at least four yields. The database may contain up to 10 consecutive crop years of... catastrophic risk protection. Crop of economic significance. A crop that has either contributed in the previous...

What's holding us back? Raising the alfalfa yield bar

USDA-ARS?s Scientific Manuscript database

Measuring yield of commodity crops is easy – weight and moisture content are determined on delivery. Consequently, reports of production or yield for grain crops can be made reliably to the agencies that track crop production, such as the USDA-National Agricultural Statistics Service (NASS). The s...

Probabilistic estimates of drought impacts on agricultural production

NASA Astrophysics Data System (ADS)

Madadgar, Shahrbanou; AghaKouchak, Amir; Farahmand, Alireza; Davis, Steven J.

2017-08-01

Increases in the severity and frequency of drought in a warming climate may negatively impact agricultural production and food security. Unlike previous studies that have estimated agricultural impacts of climate condition using single-crop yield distributions, we develop a multivariate probabilistic model that uses projected climatic conditions (e.g., precipitation amount or soil moisture) throughout a growing season to estimate the probability distribution of crop yields. We demonstrate the model by an analysis of the historical period 1980-2012, including the Millennium Drought in Australia (2001-2009). We find that precipitation and soil moisture deficit in dry growing seasons reduced the average annual yield of the five largest crops in Australia (wheat, broad beans, canola, lupine, and barley) by 25-45% relative to the wet growing seasons. Our model can thus produce region- and crop-specific agricultural sensitivities to climate conditions and variability. Probabilistic estimates of yield may help decision-makers in government and business to quantitatively assess the vulnerability of agriculture to climate variations. We develop a multivariate probabilistic model that uses precipitation to estimate the probability distribution of crop yields. The proposed model shows how the probability distribution of crop yield changes in response to droughts. During Australia's Millennium Drought precipitation and soil moisture deficit reduced the average annual yield of the five largest crops.

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

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

Land Use, Yield and Quality Changes of Minor Field Crops: Is There Superseded Potential to Be Reinvented in Northern Europe?

PubMed

Peltonen-Sainio, Pirjo; Jauhiainen, Lauri; Lehtonen, Heikki

2016-01-01

Diversification of agriculture was one of the strengthened aims of the greening payment of European Agricultural Policy (CAP) as diversification provides numerous ecosystems services compared to cereal-intensive crop rotations. This study focuses on current minor crops in Finland that have potential for expanded production and considers changes in their cropping areas, yield trends, breeding gains, roles in crop rotations and potential for improving resilience. Long-term datasets of Natural Resources Institute Finland and farmers' land use data from the Agency of Rural Affairs were used to analyze the above-mentioned trends and changes. The role of minor crops in rotations declined when early and late CAP periods were compared and that of cereal monocultures strengthened. Genetic yield potentials of minor crops have increased as also genetic improvements in quality traits, although some typical trade-offs with improved yields have also appeared. However, the gap between potential and attained yields has expanded, depending on the minor crop, as national yield trends have either stagnated or declined. When comparing genetic improvements of minor crops to those of the emerging major crop, spring wheat, breeding achievements in minor crops were lower. It was evident that the current agricultural policies in the prevailing market and the price environment have not encouraged cultivation of minor crops but further strengthened the role of cereal monocultures. We suggest optimization of agricultural land use, which is a core element of sustainable intensification, as a future means to couple long-term environmental sustainability with better success in economic profitability and social acceptability. This calls for development of effective policy instruments to support farmer's diversification actions.

Land Use, Yield and Quality Changes of Minor Field Crops: Is There Superseded Potential to Be Reinvented in Northern Europe?

PubMed Central

Peltonen-Sainio, Pirjo; Jauhiainen, Lauri; Lehtonen, Heikki

2016-01-01

Diversification of agriculture was one of the strengthened aims of the greening payment of European Agricultural Policy (CAP) as diversification provides numerous ecosystems services compared to cereal-intensive crop rotations. This study focuses on current minor crops in Finland that have potential for expanded production and considers changes in their cropping areas, yield trends, breeding gains, roles in crop rotations and potential for improving resilience. Long-term datasets of Natural Resources Institute Finland and farmers’ land use data from the Agency of Rural Affairs were used to analyze the above-mentioned trends and changes. The role of minor crops in rotations declined when early and late CAP periods were compared and that of cereal monocultures strengthened. Genetic yield potentials of minor crops have increased as also genetic improvements in quality traits, although some typical trade-offs with improved yields have also appeared. However, the gap between potential and attained yields has expanded, depending on the minor crop, as national yield trends have either stagnated or declined. When comparing genetic improvements of minor crops to those of the emerging major crop, spring wheat, breeding achievements in minor crops were lower. It was evident that the current agricultural policies in the prevailing market and the price environment have not encouraged cultivation of minor crops but further strengthened the role of cereal monocultures. We suggest optimization of agricultural land use, which is a core element of sustainable intensification, as a future means to couple long-term environmental sustainability with better success in economic profitability and social acceptability. This calls for development of effective policy instruments to support farmer’s diversification actions. PMID:27870865

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Potential Use of Halophytes to Remediate Saline Soils

PubMed Central

Hasanuzzaman, Mirza; Nahar, Kamrun; Alam, Md. Mahabub; Bhowmik, Prasanta C.; Hossain, Md. Amzad; Rahman, Motior M.; Prasad, Majeti Narasimha Vara; Ozturk, Munir; Fujita, Masayuki

2014-01-01

Salinity is one of the rising problems causing tremendous yield losses in many regions of the world especially in arid and semiarid regions. To maximize crop productivity, these areas should be brought under utilization where there are options for removing salinity or using the salt-tolerant crops. Use of salt-tolerant crops does not remove the salt and hence halophytes that have capacity to accumulate and exclude the salt can be an effective way. Methods for salt removal include agronomic practices or phytoremediation. The first is cost- and labor-intensive and needs some developmental strategies for implication; on the contrary, the phytoremediation by halophyte is more suitable as it can be executed very easily without those problems. Several halophyte species including grasses, shrubs, and trees can remove the salt from different kinds of salt-affected problematic soils through salt excluding, excreting, or accumulating by their morphological, anatomical, physiological adaptation in their organelle level and cellular level. Exploiting halophytes for reducing salinity can be good sources for meeting the basic needs of people in salt-affected areas as well. This review focuses on the special adaptive features of halophytic plants under saline condition and the possible ways to utilize these plants to remediate salinity. PMID:25110683

National Variation in Crop Yield Production Functions

NASA Astrophysics Data System (ADS)

Devineni, N.; Rising, J. A.

2017-12-01

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

Climate Risk assessment and management in rainfed agriculture areas in Jordan

NASA Astrophysics Data System (ADS)

Khresat, Saeb

2017-04-01

Agricultural production is closely tied to climate, making agriculture one of the most climate-sensitive of all economic sectors. Figures and data from official resources and previous studies demonstrated that most of agricultural areas in Jordan were rainfed which made agriculture in the country more susceptible to climate change. The percentage of harvested to cultivated areas in those areas over the past ten years ranged from 45-55%, indicating a high risk associated with rainfed agriculture in Jordan. The anticipated increase in temperature and decrease in precipitation would adversely affect crops and water availability, critically influencing the patterns of future agricultural production, threatens livelihoods and keeps vulnerable people insecure. The anticipated increase in temperature and decrease in precipitation would result in 15-20% yield reduction for major field crops and vegetable crops by 2050 and 2070. This study was conducted to help in formulating action plans to adapt to climate change by assessing the risk from climate change on rainfed agriculture. The scenarios of climate change were used to assess the impact of climate change on rainfed agriculture. The overall risk level was based on possible land use shifts and crop yield under the most probable climate change scenarios. Accordingly, adaptive measures were proposed to reduce the impacts of climate change on agriculture in Jordan. The adaptation measures included the improvement of soil water storage to maximize plant water availability, the management of crop residue and tillage to conserve soil and water, the selection of drought-tolerant crop varieties, the expansion of water harvesting schemes through encouraging the farmers to adopt and apply the in-situ water harvesting systems (micro-catchment). Finally, the study emphasized the need for capacity building and awareness creation at the levels of farmers and extension staff. This would require the formulation of plans and strategies to support services that would promote adoption and adaptation. The empowerment of farmer service centers to provide technical advice and information on viable adaptation options would be needed. This also would require the development of micro-credit/revolving grants to farmers to apply the developed adaptation systems.

Influence of poultry litter and double cropping on soybean yield

USDA-ARS?s Scientific Manuscript database

Continuous cultivation of mono-cropping systems coupled with inorganic fertilizer consumption has led to a decline in soil fertility, negatively influencing crop yields. Poultry litter application and double cropping are two management practices that could be used with conservation tillage to increa...

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

USDA-ARS?s Scientific Manuscript database

Stacked crop rotation and improved cultural practice have been used to control pests, but their impact on soil organic C (SOC) and crop yield are lacking. We evaluated the effects of stacked vs. alternate-year rotations and cultural practices on SOC at the 0- to 125-cm depth and annualized crop yiel...

Cura Annonae-Chemically Boosting Crop Yields Through Metabolic Feeding of a Plant Signaling Precursor.

PubMed

Vocadlo, David J

2017-05-22

The cream of the crop: With the world facing a projected shortfall of crops by 2050, new approaches are needed to boost crop yields. Metabolic feeding of plants with photocaged trehalose-6-phosphate (Tre6P) can increase levels of the signaling metabolite Tre6P in the plant. Reprogramming of cellular metabolism by Tre6P stimulates a program of plant growth and enhanced crop yields, while boosting starch content. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Management of Lesion Nematodes and Potato Early Dying with Rotation Crops

PubMed Central

LaMondia, J.A.

2006-01-01

Soil-incorporated rotation/green manure crops were evaluated for management of potato early dying caused by Verticillium dahliae and Pratylenchus penetrans. After two years of rotation/green manure and a subsequent potato crop, P. penetrans numbers were less after ‘Saia’ oat/‘Polynema’ marigold, ‘Triple S’ sorghum-sudangrass, or ‘Garry’ oat than ‘Superior’ potato or ‘Humus’ rapeseed. The area under the disease progress curve (AUDPC) for early dying was lowest after Saia oat/marigold, and tuber yields were greater than continuous potato after all crops except sorghum-sudangrass. Saia oat/marigold crops resulted in the greatest tuber yields. After one year of rotation/green manure, a marigold crop increased tuber yields and reduced AUDPC and P. penetrans. In the second potato crop after a single year of rotation, plots previously planted to marigolds had reduced P. penetrans densities and AUDPC and increased tuber yield. Rapeseed supported more P. penetrans than potato, but had greater yields. After two years of rotation/green manure crops and a subsequent potato crop, continuous potato had the highest AUDPC and lowest tuber weight. Rotation with Saia oats (2 yr) and Rudbeckia hirta (1 yr) reduced P. penetrans and increased tuber yields. AUDPC was lowest after R. hirta. Two years of sorghum-sudangrass did not affect P. penetrans, tuber yield or AUDPC. These results demonstrate that P. penetrans may be reduced by one or two years of rotation to non-host or antagonistic plants such as Saia oat, Polynema marigold, or R. hirta and that nematode control may reduce the severity of potato early dying. PMID:19259461

Grain production versus resource and environmental costs: towards increasing sustainability of nutrient use in China.

PubMed

Jiao, Xiaoqiang; Lyu, Yang; Wu, Xiaobin; Li, Haigang; Cheng, Lingyun; Zhang, Chaochun; Yuan, Lixing; Jiang, Rongfeng; Jiang, Baiwen; Rengel, Zed; Zhang, Fusuo; Davies, William J; Shen, Jianbo

2016-09-01

Over the past five decades, Chinese grain production has increased 4-fold, from 110 Mt in 1961 to 557 Mt in 2014, with less than 9% of the world's arable land feeding 22% of the world's population, indicating a substantial contribution to global food security. However, compared with developed economies, such as the USA and the European Union, more than half of the increased crop production in China can be attributed to a rapid increase in the consumption of chemicals, particularly fertilizers. Excessive fertilization has caused low nutrient use efficiency and high environmental costs in grain production. We analysed the key requirements underpinning increased sustainability of crop production in China, as follows: (i) enhance nutrient use efficiency and reduce nutrient losses by fertilizing roots not soil to maximize root/rhizosphere efficiency with innovative root zone nutrient management; (ii) improve crop productivity and resource use efficiency by matching the best agronomic management practices with crop improvement; and (iii) promote technology transfer of the root zone nutrient management to achieve the target of high yields and high efficiency with low environmental risks on a broad scale. Coordinating grain production and environmental protection by increasing the sustainability of nutrient use will be a key step in achieving sustainable crop production in Chinese agriculture. © The Author 2016. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

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

DOE PAGES

Leng, Guoyong; Huang, Maoyi

2017-05-03

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

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

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

Leng, Guoyong; Huang, Maoyi

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

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

PubMed

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

2014-09-01

Genetic markers can be used in combination with ecophysiological crop models to predict the performance of genotypes. Crop models can estimate the contribution of individual markers to crop performance in given environments. The objectives of this study were to explore the use of crop models to design markers and virtual ideotypes for improving yields of rice (Oryza sativa) under drought stress. Using the model GECROS, crop yield was dissected into seven easily measured parameters. Loci for these parameters were identified for a rice population of 94 introgression lines (ILs) derived from two parents differing in drought tolerance. Marker-based values of ILs for each of these parameters were estimated from additive allele effects of the loci, and were fed to the model in order to simulate yields of the ILs grown under well-watered and drought conditions and in order to design virtual ideotypes for those conditions. To account for genotypic yield differences, it was necessary to parameterize the model for differences in an additional trait 'total crop nitrogen uptake' (Nmax) among the ILs. Genetic variation in Nmax had the most significant effect on yield; five other parameters also significantly influenced yield, but seed weight and leaf photosynthesis did not. Using the marker-based parameter values, GECROS also simulated yield variation among 251 recombinant inbred lines of the same parents. The model-based dissection approach detected more markers than the analysis using only yield per se. Model-based sensitivity analysis ranked all markers for their importance in determining yield differences among the ILs. Virtual ideotypes based on markers identified by modelling had 10-36 % more yield than those based on markers for yield per se. This study outlines a genotype-to-phenotype approach that exploits the potential value of marker-based crop modelling in developing new plant types with high yields. The approach can provide more markers for selection programmes for specific environments whilst also allowing for prioritization. Crop modelling is thus a powerful tool for marker design for improved rice yields and for ideotyping under contrasting conditions. © The Author 2014. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

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

USDA-ARS?s Scientific Manuscript database

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

Simulating canopy temperature for modelling heat stress in cereals

USDA-ARS?s Scientific Manuscript database

Crop models must be improved to account for the large effects of heat stress effects on crop yields. To date, most approaches in crop models use air temperature despite evidence that crop canopy temperature better explains yield reductions associated with high temperature events. This study presents...

Long-term variation of Surface Ozone, NO2, temperature and relative humidity on crop yield over Andhra Pradesh (AP), India

NASA Astrophysics Data System (ADS)

Arunachalam, M. S.; Obili, Manjula; Srimurali, M.

2016-07-01

Long-term variation of Surface Ozone, NO2, Temperature, Relative humidity and crop yield datasets over thirteen districts of Andhra Pradesh(AP) has been studied with the help of OMI, MODIS, AIRS, ERA-Interim re-analysis and Directorate of Economics and Statistics (DES) of AP. Inter comparison of crop yield loss estimates according to exposure metrics such as AOT40 (accumulated ozone exposure over a threshold of 40) and non-linear variation of surface temperature for twenty and eighteen varieties of two major crop growing seasons namely, kharif (April-September) and rabi (October-March), respectively has been made. Study is carried to establish a new crop-yield-exposure relationship for different crop cultivars of AP. Both ozone and temperature are showing a correlation coefficient of 0.66 and 0.87 with relative humidity; and 0.72 and 0.80 with NO2. Alleviation of high surface ozone results in high food security and improves the economy thereby reduces the induced warming of the troposphere caused by ozone. Keywords: Surface Ozone, NO2, Temperature, Relative humidity, Crop yield, AOT 40.

The state of rhizospheric science in the era of multi-omics: A practical guide to omics technologies

DOE PAGES

White, Richard Allen; Rivas-Ubach, Albert; Borkum, Mark I.; ...

2017-05-06

Over the past century, the significance of the rhizosphere has been increasingly recognized by the scientific community. Furthermore, this complex biological system is comprised of vast interconnected networks of microbial organisms that interact directly with their plant hosts, including archaea, bacteria, fungi, picoeukaryotes, and viruses. The rhizosphere provides a nutritional base to the terrestrial biosphere, and is integral to plant growth, crop production, and ecosystem health. There is little mechanistic understanding of the rhizosphere, but, and that constitutes a critical knowledge gap. It inhibits our ability to predict and control the terrestrial ecosystem to achieve desirable outcomes, such as bioenergymore » production, crop yield maximization, and soil-based carbon sequestration. Multi-omics have the potential to significantly advance our knowledge of rhizospheric science. Our review covers multi-omic techniques and technologies; methods and protocols for specific rhizospheric science questions; and the challenges to be addressed during this century of rhizospheric science.« less

The state of rhizospheric science in the era of multi-omics: A practical guide to omics technologies

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

White, Richard Allen; Rivas-Ubach, Albert; Borkum, Mark I.

Over the past century, the significance of the rhizosphere has been increasingly recognized by the scientific community. Furthermore, this complex biological system is comprised of vast interconnected networks of microbial organisms that interact directly with their plant hosts, including archaea, bacteria, fungi, picoeukaryotes, and viruses. The rhizosphere provides a nutritional base to the terrestrial biosphere, and is integral to plant growth, crop production, and ecosystem health. There is little mechanistic understanding of the rhizosphere, but, and that constitutes a critical knowledge gap. It inhibits our ability to predict and control the terrestrial ecosystem to achieve desirable outcomes, such as bioenergymore » production, crop yield maximization, and soil-based carbon sequestration. Multi-omics have the potential to significantly advance our knowledge of rhizospheric science. Our review covers multi-omic techniques and technologies; methods and protocols for specific rhizospheric science questions; and the challenges to be addressed during this century of rhizospheric science.« less

The state of rhizospheric science in the era of multi-omics: A practical guide to omics technologies

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

White, Richard Allen; Rivas-Ubach, Albert; Borkum, Mark I.

Over the past century, the significance of the rhizosphere as a complex, biological system, comprised of vast, interconnected networks of microbial organisms that interact directly with their plant hosts (e.g., archæa, bacteria, fungi, eukaryotes, and viruses) has been increasingly recognized by the scientific community. Providing a nutritional base to the terrestrial biosphere, the rhizosphere is integral to plant growth, crop production and ecosystem health. Lack of mechanistic understanding of the rhizosphere constitutes a critical knowledge gap, inhibiting our ability to predict and control the terrestrial ecosystem in order to achieve desirable outcomes (e.g., bioenergy production, crop yield maximization, and soilbasedmore » carbon sequestration). Application of multi-omics has the potential to significantly advance our knowledge of rhizospheric science. This review covers: cutting- and bleeding-edge, multi-omic techniques and technologies; methods and protocols for specific rhizospheric science questions; and, challenges to be addressed during this century of rhizospheric science.« less

Mapping Crop Yield and Sow Date Using High Resolution Imagery

NASA Astrophysics Data System (ADS)

Royal, K.

2015-12-01

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

Tropical rotation crops influence nematode densities and vegetable yields.

PubMed

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

1994-09-01

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

Risk of water scarcity and water policy implications for crop production in the Ebro Basin in Spain

NASA Astrophysics Data System (ADS)

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

2010-08-01

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

Incorporating a Constrained Optimization Algorithm into Remote- Sensing/Precision Agriculture Methodology

NASA Astrophysics Data System (ADS)

Morgenthaler, George; Khatib, Nader; Kim, Byoungsoo

with information to improve their crop's vigor has been a major topic of interest. With world population growing exponentially, arable land being consumed by urbanization, and an unfavorable farm economy, the efficiency of farming must increase to meet future food requirements and to make farming a sustainable occupation for the farmer. "Precision Agriculture" refers to a farming methodology that applies nutrients and moisture only where and when they are needed in the field. The goal is to increase farm revenue by increasing crop yield and decreasing applications of costly chemical and water treatments. In addition, this methodology will decrease the environmental costs of farming, i.e., reduce air, soil, and water pollution. Sensing/Precision Agriculture has not grown as rapidly as early advocates envisioned. Technology for a successful Remote Sensing/Precision Agriculture system is now available. Commercial satellite systems can image (multi-spectral) the Earth with a resolution of approximately 2.5 m. Variable precision dispensing systems using GPS are available and affordable. Crop models that predict yield as a function of soil, chemical, and irrigation parameter levels have been formulated. Personal computers and internet access are in place in most farm homes and can provide a mechanism to periodically disseminate, e.g. bi-weekly, advice on what quantities of water and chemicals are needed in individual regions of the field. What is missing is a model that fuses the disparate sources of information on the current states of the crop and soil, and the remaining resource levels available with the decisions farmers are required to make. This must be a product that is easy for the farmer to understand and to implement. A "Constrained Optimization Feed-back Control Model" to fill this void will be presented. The objective function of the model will be used to maximize the farmer's profit by increasing yields while decreasing environmental costs and decreasing application of costly treatments. This model will incorporate information from remote sensing, in-situ weather sources, soil measurements, crop models, and tacit farmer knowledge of the relative productivity of the selected control regions of the farm to provide incremental advice throughout the growing season on water and chemical treatments. Genetic and meta-heuristic algorithms will be used to solve the constrained optimization problem that possesses complex constraints and a non-linear objective function. *

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

NASA Astrophysics Data System (ADS)

Zhang, Xiaoyang; Zhang, Qingyuan

2016-04-01

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

High-resolution, regional-scale crop yield simulations for the Southwestern United States

NASA Astrophysics Data System (ADS)

Stack, D. H.; Kafatos, M.; Medvigy, D.; El-Askary, H. M.; Hatzopoulos, N.; Kim, J.; Kim, S.; Prasad, A. K.; Tremback, C.; Walko, R. L.; Asrar, G. R.

2012-12-01

Over the past few decades, there have been many process-based crop models developed with the goal of better understanding the impacts of climate, soils, and management decisions on crop yields. These models simulate the growth and development of crops in response to environmental drivers. Traditionally, process-based crop models have been run at the individual farm level for yield optimization and management scenario testing. Few previous studies have used these models over broader geographic regions, largely due to the lack of gridded high-resolution meteorological and soil datasets required as inputs for these data intensive process-based models. In particular, assessment of regional-scale yield variability due to climate change requires high-resolution, regional-scale, climate projections, and such projections have been unavailable until recently. The goal of this study was to create a framework for extending the Agricultural Production Systems sIMulator (APSIM) crop model for use at regional scales and analyze spatial and temporal yield changes in the Southwestern United States (CA, AZ, and NV). Using the scripting language Python, an automated pipeline was developed to link Regional Climate Model (RCM) output with the APSIM crop model, thus creating a one-way nested modeling framework. This framework was used to combine climate, soil, land use, and agricultural management datasets in order to better understand the relationship between climate variability and crop yield at the regional-scale. Three different RCMs were used to drive APSIM: OLAM, RAMS, and WRF. Preliminary results suggest that, depending on the model inputs, there is some variability between simulated RCM driven maize yields and historical yields obtained from the United States Department of Agriculture (USDA). Furthermore, these simulations showed strong non-linear correlations between yield and meteorological drivers, with critical threshold values for some of the inputs (e.g. minimum and maximum temperature), beyond which the yields were negatively affected. These results are now being used for further regional-scale yield analysis as the aforementioned framework is adaptable to multiple geographic regions and crop types.

Land Husbandry: Biochar application to reduce land degradation and erosion on cassava production

NASA Astrophysics Data System (ADS)

Yuniwati, E. D.

2017-12-01

This field experiment was carried out to examine the effect of increasing crop yield on land degradation and erosion in cassava-based cropping systems. The experiment was also aimed at showing that with proper crop management, the planting of cassava does not result in land degradation, and therefore, a sustainable production system can be obtained. The experiment was done in a farmer's fields in Batu, about 15 km south east of Malang, East Java, Indonesia. The soils are Alfisols with a surface slope of about 8%. There were 8 experimental treatments with two replications. The experiment results show that biochar applications reduce of soil erosion rate of the cassava field were not necessarily higher than those of maize in terms of crop yield and crop management. At low-to-medium yield, also observed the nutrient uptake of cassava was lower than that of maize. At high yield, only the K uptake of cassava was higher than that of maize, whereas the N and P uptake was more or less similar. Soil erosion on the cassava field was significantly higher than that on the maize field; however, this only occurred when there was no suitable crop management. Simple crop managements, such as ridging, biochar application, or manure application could significantly reduce soil erosion. The results also revealed that proper management could prevent land degradation and increase crop yield. In turn, the increase in crop yield could decrease soil erosion and plant nutrient depletion.

Effects of fragmentation, supplementation and the addition of phase II compost to 2nd break compost on mushroom (Agaricus bisporus) yield.

PubMed

Royse, Daniel J

2010-01-01

Double-cropping offers growers an opportunity to increase production efficiency while reducing costs. We evaluated degree of fragmentation, supplementation, and addition of phase II compost (PIIC) to 2nd break compost (2BkC) on mushroom yield and biological efficiency (BE%). One crop was extended as a triple crop in which we evaluated effect of compost type, and addition of phase II compost and supplement. All crops involved removing the casing layer after 2nd break and then using 2BkC for the various treatments. Simple fragmentation of the compost increased mushroom yield by 30% compared to non-fragmented compost. Addition of a commercial supplement to fragmented compost increased mushroom yield by 53-56% over non-supplemented, fragmented 2BkC. Fragmented, supplemented 2BkC resulted in a 99% and 108% yield increase over the non-fragmented control depending on degree of fragmentation (3x, 1x, respectively). A 3rd crop of mushrooms was produced from 2BkC, but yields were about one-half that of the 1st and 2nd crops. Double-cropping (and even triple-cropping) offers growers an opportunity to increase bio-efficiency, reduce production costs, and increase profitability. The cost of producing Agaricus bisporus continues to rise due to increasing expenses including materials, energy, and labor. Optimizing production practices, through double- or triple-cropping, could help growers become more efficient and competitive, and ensure the availability of mushrooms for consumers.

Wheat yield and yield stability of eight dryland crop rotations

USDA-ARS?s Scientific Manuscript database

The winter wheat (Triticum aestivum L.)-fallow (WF) dryland production system employed in the Central Great Plains has evolved in the past 40 years to include a diversity of other crops, with a reduction in fallow frequency. Wheat remains the base crop for essentially all cropping systems. Decisions...

Effects of Management Practices on Meloidogyne incognita and Snap Bean Yield.

PubMed

Smittle, D A; Johnson, A W

1982-01-01

Phenamiphos applied at 6.7 kg ai/ha through a solid set or a center pivot irrigation system with 28 mm of water effectively controlled root-knot nematodes, Meloidogyne incognita, and resulted in greater snap bean growth and yields irrespective of growing season, tillage method, or cover crop system. The percentage yield increases attributed to this method of M. incognita control over nontreated controls were 45% in the spring crop, and 90% and 409% in the fall crops following winter rye and fallow, respectively. Root galling was not affected by tillage systems or cover crop, but disk tillage resulted in over 50% reduction in bean yield compared with yields from the subsoil-bed tillage system.

Meeting the demand for crop production: the challenge of yield decline in crops grown in short rotations.

PubMed

Bennett, Amanda J; Bending, Gary D; Chandler, David; Hilton, Sally; Mills, Peter

2012-02-01

There is a trend world-wide to grow crops in short rotation or in monoculture, particularly in conventional agriculture. This practice is becoming more prevalent due to a range of factors including economic market trends, technological advances, government incentives, and retailer and consumer demands. Land-use intensity will have to increase further in future in order to meet the demands of growing crops for both bioenergy and food production, and long rotations may not be considered viable or practical. However, evidence indicates that crops grown in short rotations or monoculture often suffer from yield decline compared to those grown in longer rotations or for the first time. Numerous factors have been hypothesised as contributing to yield decline, including biotic factors such as plant pathogens, deleterious rhizosphere microorganisms, mycorrhizas acting as pathogens, and allelopathy or autotoxicity of the crop, as well as abiotic factors such as land management practices and nutrient availability. In many cases, soil microorganisms have been implicated either directly or indirectly in yield decline. Although individual factors may be responsible for yield decline in some cases, it is more likely that combinations of factors interact to cause the problem. However, evidence confirming the precise role of these various factors is often lacking in field studies due to the complex nature of cropping systems and the numerous interactions that take place within them. Despite long-term knowledge of the yield-decline phenomenon, there are few tools to counteract it apart from reverting to longer crop rotations or break crops. Alternative cropping and management practices such as double-cropping or inter-cropping, tillage and organic amendments may prove valuable for combating some of the negative effects seen when crops are grown in short rotation. Plant breeding continues to be important, although this does require a specific breeding target to be identified. This review identifies gaps in our understanding of yield decline, particularly with respect to the complex interactions occurring between the different components of agro-ecosystems, which may well influence food security in the 21(st) Century. © 2011 The Authors. Biological Reviews © 2011 Cambridge Philosophical Society.

Global Gridded Crop Model Evaluation: Benchmarking, Skills, Deficiencies and Implications.

NASA Technical Reports Server (NTRS)

Muller, Christoph; Elliott, Joshua; Chryssanthacopoulos, James; Arneth, Almut; Balkovic, Juraj; Ciais, Philippe; Deryng, Delphine; Folberth, Christian; Glotter, Michael; Hoek, Steven;

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

NASA Astrophysics Data System (ADS)

Yokozawa, M.

2014-12-01

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

Understanding the weather signal in national crop-yield variability

NASA Astrophysics Data System (ADS)

Frieler, Katja; Schauberger, Bernhard; Arneth, Almut; Balkovič, Juraj; Chryssanthacopoulos, James; Deryng, Delphine; Elliott, Joshua; Folberth, Christian; Khabarov, Nikolay; Müller, Christoph; Olin, Stefan; Pugh, Thomas A. M.; Schaphoff, Sibyll; Schewe, Jacob; Schmid, Erwin; Warszawski, Lila; Levermann, Anders

2017-06-01

Year-to-year variations in crop yields can have major impacts on the livelihoods of subsistence farmers and may trigger significant global price fluctuations, with severe consequences for people in developing countries. Fluctuations can be induced by weather conditions, management decisions, weeds, diseases, and pests. Although an explicit quantification and deeper understanding of weather-induced crop-yield variability is essential for adaptation strategies, so far it has only been addressed by empirical models. Here, we provide conservative estimates of the fraction of reported national yield variabilities that can be attributed to weather by state-of-the-art, process-based crop model simulations. We find that observed weather variations can explain more than 50% of the variability in wheat yields in Australia, Canada, Spain, Hungary, and Romania. For maize, weather sensitivities exceed 50% in seven countries, including the United States. The explained variance exceeds 50% for rice in Japan and South Korea and for soy in Argentina. Avoiding water stress by simulating yields assuming full irrigation shows that water limitation is a major driver of the observed variations in most of these countries. Identifying the mechanisms leading to crop-yield fluctuations is not only fundamental for dampening fluctuations, but is also important in the context of the debate on the attribution of loss and damage to climate change. Since process-based crop models not only account for weather influences on crop yields, but also provide options to represent human-management measures, they could become essential tools for differentiating these drivers, and for exploring options to reduce future yield fluctuations.

Crop insurance evaluation in response to extreme events

NASA Astrophysics Data System (ADS)

Moriondo, Marco; Ferrise, Roberto; Bindi, Marco

2013-04-01

Crop yield insurance has been indicated as a tool to manage the uncertainties of crop yields (Sherrick et al., 2004) but the changes in crop yield variability as expected in the near future should be carefully considered for a better quantitative assessment of farmer's revenue risk and insurance values in a climatic change regime (Moriondo et al., 2011). Under this point of view, mechanistic crop growth models coupled to the output of General/Regional Circulation Models (GCMs, RCMs) offer a valuable tool to evaluate crop responses to climatic change and this approach has been extensively used to describe crop yield distribution in response to climatic change considering changes in both mean climate and variability. In this work, we studied the effect of a warmer climate on crop yield distribution of durum wheat (Triticum turgidum L. subsp durum) in order to assess the economic significance of climatic change in a risk decision context. Specifically, the outputs of 6 RCMs (Tmin, Tmax, Rainfall, Global Radiation) (van der Linden and Mitchell 2009) have been statistically downscaled by a stochastic weather generator over eight sites across the Mediterranean basin and used to feed the crop growth model Sirius Quality. Three time slices were considered i) the present period PP (average of the period 1975-1990, [CO2]=350 ppm), 2020 (average of the period 2010-2030, SRES scenario A1b, [CO2]=415 ppm) and 2040 (average of the period 2030-2050, SRES scenario A1b, [CO2]=480 ppm). The effect of extreme climate events (i.e. heat stress at anthesis stage) was also considered. The outputs of these simulations were used to estimate the expected payout per hectare from insurance triggered when yields fall below a specific threshold defined as "the insured yield". For each site, the threshold was calculated as a fraction (70%) of the median of yield distribution under PP that represents the percentage of median yield above which indemnity payments are triggered. The results indicated that when the effect of extreme events was not considered, climate change had a low or no impact on crop yield distribution in 2020 and 2040. This resulted into an expected payout close to what observed in the present period. Conversely, the simulation of the effect of extreme events highly affected the PDFs by reducing the expected yield. This highlights that insured yield in future projections may be overestimated when not considering the impact of extremes, leading to distortions in the risk management of crop insurance companies. References Moriondo M, Giannakopoulos C, Bindi M (2011) Climate ch'ange impact assessment: the role of climate extremes in crop yield simulation. Clim Change 104:679-701 Sherrick BJ, Zanini FC, Schnitkey GD, Irwin SH (2004) Crop Insurance Valuation under Alternative Yield Distributions. American Journal of Agricultural Economics, 86:406-419. van der Linden P, Mitchell JFB (eds) (2009) ENSEMBLES: climate change and its impacts: summary of research and results from the ENSEMBLES project. Met Office Hadley Centre, FitzRoy Road, Exeter EX1 3 PB, UK. 160 pp

Patterns of Cereal Yield Growth across China from 1980 to 2010 and Their Implications for Food Production and Food Security

PubMed Central

Li, Xiaoyun; Liu, Nianjie; You, Liangzhi; Ke, Xinli; Liu, Haijun; Huang, Malan; Waddington, Stephen R.

2016-01-01

After a remarkable 86% increase in cereal production from 1980 to 2005, recent crop yield growth in China has been slow. County level crop production data between 1980 and 2010 from eastern and middle China were used to analyze spatial and temporal patterns of rice, wheat and maize yield in five major farming systems that include around 90% of China's cereal production. Site-specific yield trends were assessed in areas where those crops have experienced increasing yield or where yields have stagnated or declined. We find that rice yields have continued to increase on over 12.3 million hectares (m. ha) or 41.8% of the rice area in China between 1980 and 2010. However, yields stagnated on 50% of the rice area (around 14.7 m. ha) over this time period. Wheat yields increased on 13.8 m. ha (58.2% of the total harvest area), but stagnated on around 3.8 m. ha (15.8% of the harvest area). Yields increased on a smaller proportion of the maize area (17.7% of harvest area, 5.3 m. ha), while yields have stagnated on over 54% (16.3 m. ha). Many parts of the lowland rice and upland intensive sub-tropical farming systems were more prone to stagnation with rice, the upland intensive sub-tropical system with wheat, and maize in the temperate mixed system. Large areas where wheat yield continues to rise were found in the lowland rice and temperate mixed systems. Land and water constraints, climate variability, and other environmental limitations undermine increased crop yield and agricultural productivity in these systems and threaten future food security. Technology and policy innovations must be implemented to promote crop yields and the sustainable use of agricultural resources to maintain food security in China. In many production regions it is possible to better match the crop with input resources to raise crop yields and benefits. Investments may be especially useful to intensify production in areas where yields continue to improve. For example, increased support to maize production in southern China, where yields are still rising, seems justified. PMID:27404110

On the Water-Food Nexus: an Optimization Approach for Water and Food Security

NASA Astrophysics Data System (ADS)

Mortada, Sarah; Abou Najm, Majdi; Yassine, Ali; Alameddine, Ibrahim; El-Fadel, Mutasem

2016-04-01

Water and food security is facing increased challenges with population increase, climate and land use change, as well as resource depletion coupled with pollution and unsustainable practices. Coordinated and effective management of limited natural resources have become an imperative to meet these challenges by optimizing the usage of resources under various constraints. In this study, an optimization model is developed for optimal resource allocation towards sustainable water and food security under nutritional, socio-economic, agricultural, environmental, and natural resources constraints. The core objective of this model is to maximize the composite water-food security status by recommending an optimal water and agricultural strategy. The model balances between the healthy nutritional demand side and the constrained supply side while considering the supply chain in between. It equally ensures that the population achieves recommended nutritional guidelines and population food-preferences by quantifying an optimum agricultural and water policy through transforming optimum food demands into optimum cropping policy given the water and land footprints of each crop or agricultural product. Through this process, water and food security are optimized considering factors that include crop-food transformation (food processing), water footprints, crop yields, climate, blue and green water resources, irrigation efficiency, arable land resources, soil texture, and economic policies. The model performance regarding agricultural practices and sustainable food and water security was successfully tested and verified both at a hypothetical and pilot scale levels.

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.

40 CFR 80.1401 - Definitions.

Code of Federal Regulations, 2014 CFR

2014-07-01

... and/or the distillers grains and solubles produced by a dry mill corn ethanol plant, most often by... biomass includes any portion of a crop or crop plant. Cropland is land used for production of crops for... bred to maximize cellulosic rather than sugar content. For the purposes of this section, energy cane...

40 CFR 80.1401 - Definitions.

Code of Federal Regulations, 2013 CFR

2013-07-01

... and/or the distillers grains and solubles produced by a dry mill corn ethanol plant, most often by... biomass includes any portion of a crop or crop plant. Cropland is land used for production of crops for... bred to maximize cellulosic rather than sugar content. For the purposes of this section, energy cane...

Agronomic & entomological results from 7 years of dryland cropping systems research at Briggsdale, Colorado

USDA-ARS?s Scientific Manuscript database

Dryland crop production in the semi-arid Great Plains is limited by both the quantity and timing of precipitation. Sustainable dryland cropping systems maximize precipitation use efficiency by managing precipitation capture, storage, and use. Pest management approaches are also critical for efficie...

A network-based approach for semi-quantitative knowledge mining and its application to yield variability

NASA Astrophysics Data System (ADS)

Schauberger, Bernhard; Rolinski, Susanne; Müller, Christoph

2016-12-01

Variability of crop yields is detrimental for food security. Under climate change its amplitude is likely to increase, thus it is essential to understand the underlying causes and mechanisms. Crop models are the primary tool to project future changes in crop yields under climate change. A systematic overview of drivers and mechanisms of crop yield variability (YV) can thus inform crop model development and facilitate improved understanding of climate change impacts on crop yields. Yet there is a vast body of literature on crop physiology and YV, which makes a prioritization of mechanisms for implementation in models challenging. Therefore this paper takes on a novel approach to systematically mine and organize existing knowledge from the literature. The aim is to identify important mechanisms lacking in models, which can help to set priorities in model improvement. We structure knowledge from the literature in a semi-quantitative network. This network consists of complex interactions between growing conditions, plant physiology and crop yield. We utilize the resulting network structure to assign relative importance to causes of YV and related plant physiological processes. As expected, our findings confirm existing knowledge, in particular on the dominant role of temperature and precipitation, but also highlight other important drivers of YV. More importantly, our method allows for identifying the relevant physiological processes that transmit variability in growing conditions to variability in yield. We can identify explicit targets for the improvement of crop models. The network can additionally guide model development by outlining complex interactions between processes and by easily retrieving quantitative information for each of the 350 interactions. We show the validity of our network method as a structured, consistent and scalable dictionary of literature. The method can easily be applied to many other research fields.

The impact of soil moisture extremes and their spatiotemporal variability on Zambian maize yields

NASA Astrophysics Data System (ADS)

Zhao, Y.; Estes, L. D.; Vergopolan, N.

2017-12-01

Food security in sub-Saharan Africa is highly sensitive to climate variability. While it is well understood that extreme heat has substantial negative impacts on crop yield, the impacts of precipitation extremes, particularly over large spatial extents, are harder to quantify. There are three primary reasons for this difficulty, which are (1) lack of high quality, high resolution precipitation data, (2) rainfall data provide incomplete information on plant water availability, the variable that most directly affects crop performance, and (3) the type of rainfall extreme that most affects crop yields varies throughout the crop development stage. With respect to the first reason, the spatial and temporal variation of precipitation is much greater than that of temperature, yet the spatial resolution of rainfall data is typically even coarser than it is for temperature, particularly within Africa. Even if there were high-resolution rainfall data, the amount of water available to crops also depends on other physical factors that affect evapotranspiration, which are strongly influenced by heterogeneity in the land surface related to topography, soil properties, and land cover. In this context, soil moisture provides a better measure of crop water availability than rainfall. Furthermore, soil moisture has significantly different influences on crop yield depending on the crop's growth stage. The goal of this study is to understand how the spatiotemporal scales of soil moisture extremes interact with crops, more specifically, the timing and the spatial scales of extreme events like droughts and flooding. In this study, we simulate daily-1km soil moisture using HydroBlocks - a physically based land surface model - and compare it with precipitation and remote sensing derived maize yields between 2000 and 2016 in Zambia. We use a novel combination of the SCYM (scalable satellite-based yield mapper) method with DSSAT crop model, which is a mechanistic model responsive to water stress. Understanding the relationships between soil moisture spatiotemporal variability and yields can help to improve agricultural drought risk assessment and seasonal crop yield forecasting as well as early season warning of potential famines.

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

Crop response to deep tillage - a meta-analysis

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Possible changes to arable crop yields by 2050

PubMed Central

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

2010-01-01

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

Possible changes to arable crop yields by 2050.

PubMed

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

2010-09-27

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

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

NASA Astrophysics Data System (ADS)

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

2015-10-01

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

Yield estimation of sugarcane based on agrometeorological-spectral models

NASA Technical Reports Server (NTRS)

Rudorff, Bernardo Friedrich Theodor; Batista, Getulio Teixeira

1990-01-01

This work has the objective to assess the performance of a yield estimation model for sugarcane (Succharum officinarum). The model uses orbital gathered spectral data along with yield estimated from an agrometeorological model. The test site includes the sugarcane plantations of the Barra Grande Plant located in Lencois Paulista municipality in Sao Paulo State. Production data of four crop years were analyzed. Yield data observed in the first crop year (1983/84) were regressed against spectral and agrometeorological data of that same year. This provided the model to predict the yield for the following crop year i.e., 1984/85. The model to predict the yield of subsequent years (up to 1987/88) were developed similarly, incorporating all previous years data. The yield estimations obtained from these models explained 69, 54, and 50 percent of the yield variation in the 1984/85, 1985/86, and 1986/87 crop years, respectively. The accuracy of yield estimations based on spectral data only (vegetation index model) and on agrometeorological data only (agrometeorological model) were also investigated.

Growing fresh food on future space missions: Environmental conditions and crop management.

PubMed

Meinen, Esther; Dueck, Tom; Kempkes, Frank; Stanghellini, Cecilia

2018-05-17

This paper deals with vegetable cultivation that could be faced in a space mission. This paper focusses on optimization, light, temperature and the harvesting process, while other factors concerning cultivation in space missions, i.e. gravity, radiation, were not addressed. It describes the work done in preparation of the deployment of a mobile test facility for vegetable production of fresh food at the Neumayer III Antarctic research station. A selection of vegetable crops was grown under varying light and temperature conditions to quantify crop yield response to climate factors that determine resource requirement of the production system. Crops were grown at 21 °C or 25 °C under light treatments varying from 200 to 600 μmol m -2   s -1 and simulated the dusk and dawn light spectrum. Fresh food biomass was harvested as spread harvesting (lettuce), before and after regrowth (herbs) and at the end of cultivation. Lettuce and red mustard responded well to increasing light intensities, by 35-90% with increasing light from 200 to 600 μmol m -2  s -1 , while the other crops responded more variably. However, the quality of the leafy greens often deteriorated at higher light intensities. The fruit biomass of both determinate tomato and cucumber increased by 8-15% from 300 to 600 μmol m -2  s -1 . With the increase in biomass, the number of tomato fruits also increased, while the number of cucumber fruits decreased, resulting in heavier individual fruits. Increasing the temperature had varied effects on production. While in some cases the production increased, regrowth of herbs often lagged behind in the 25 °C treatment. In terms of fresh food production, the most can be expected from lettuce, cucumber, radish, then tomato, although the 2 fruit vegetables require a considerable amount of crop management. Spread harvesting had a large influence on the amount of harvested biomass per unit area. In particular, yield of the 3 lettuce cultivars and spinach was ca. 400% than single harvesting. Increasing plant density and applying spread harvesting increased fresh food production. This information will be the basis for determining crop growth recipes and management to maximize the amount of fresh food available, in view of the constraints of space and energy requirement of such a production system.

Aerobic Decomposition and Organic Amendments Effects on Grain Yield of Triple-Cropped Rice in the Mekong Delta, Vietnam

USDA-ARS?s Scientific Manuscript database

Soil aeration during decomposition of incorporated crop residues and application of organic amendments might help improve soil quality and rice yield for sustainable intensive rice production. A field experiment was conducted on triple-cropped rice during three consecutive crops with five treatments...

Effects of Tropical Rotation Crops on Meloidogyne arenaria Population Densities and Vegetable Yields in Microplots.

PubMed

McSorley, R; Dickson, D W; de Brito, J A; Hewlett, T E; Frederick, J J

1994-06-01

The effects of 12 summer crop rotation treatments on population densities of Meloidogyne arenaria race 1 and on yields of subsequent spring vegetable crops were determined in microplots. The crop sequence was: (i) rotation crops during summer 1991 ; (ii) cover crop of rye (Secale cereale) during winter 1991-92; (iii) squash (Cucurbita pepo) during spring 1992; (iv) rotation crops during summer 1992; (v) rye during winter 1992-93; (vi) eggplant (Solanum melongena) during spring 1993. The 12 rotation treatments were castor (Ricinus communis), cotton (Gossypium hirsutum), velvetbean (Mucuna deeringiana), crotalaria (Crotalaria spectabilis), fallow, hairy indigo (Indigofera hirsuta), American jointvetch (Aeschynomene americana), sorghum-sudangrass (Sorghum bicolor x S. sudanense), soybean (Glycine max), horsebean (Canavalia ensiformis), sesame (Sesamum indicum), and peanut (Arachis hypogaea). Compared to peanut, the first eight rotation treatments resulted in lower (P

Sensitivity and requirement of improvements of four soybean crop simulation models for climate change studies in Southern Brazil

NASA Astrophysics Data System (ADS)

Battisti, R.; Sentelhas, P. C.; Boote, K. J.

2017-12-01

Crop growth models have many uncertainties that affect the yield response to climate change. Based on that, the aim of this study was to evaluate the sensitivity of crop models to systematic changes in climate for simulating soybean attainable yield in Southern Brazil. Four crop models were used to simulate yields: AQUACROP, MONICA, DSSAT, and APSIM, as well as their ensemble. The simulations were performed considering changes of air temperature (0, + 1.5, + 3.0, + 4.5, and + 6.0 °C), [CO2] (380, 480, 580, 680, and 780 ppm), rainfall (- 30, - 15, 0, + 15, and + 30%), and solar radiation (- 15, 0, + 15), applied to daily values. The baseline climate was from 1961 to 2014, totalizing 53 crop seasons. The crop models simulated a reduction of attainable yield with temperature increase, reaching 2000 kg ha-1 for the ensemble at + 6 °C, mainly due to shorter crop cycle. For rainfall, the yield had a higher rate of reduction when it was diminished than when rainfall was increased. The crop models increased yield variability when solar radiation was changed from - 15 to + 15%, whereas [CO2] rise resulted in yield gains, following an asymptotic response, with a mean increase of 31% from 380 to 680 ppm. The models used require further attention to improvements in optimal and maximum cardinal temperature for development rate; runoff, water infiltration, deep drainage, and dynamic of root growth; photosynthesis parameters related to soil water availability; and energy balance of soil-plant system to define leaf temperature under elevated CO2.

Sensitivity and requirement of improvements of four soybean crop simulation models for climate change studies in Southern Brazil

NASA Astrophysics Data System (ADS)

Battisti, R.; Sentelhas, P. C.; Boote, K. J.

2018-05-01

Crop growth models have many uncertainties that affect the yield response to climate change. Based on that, the aim of this study was to evaluate the sensitivity of crop models to systematic changes in climate for simulating soybean attainable yield in Southern Brazil. Four crop models were used to simulate yields: AQUACROP, MONICA, DSSAT, and APSIM, as well as their ensemble. The simulations were performed considering changes of air temperature (0, + 1.5, + 3.0, + 4.5, and + 6.0 °C), [CO2] (380, 480, 580, 680, and 780 ppm), rainfall (- 30, - 15, 0, + 15, and + 30%), and solar radiation (- 15, 0, + 15), applied to daily values. The baseline climate was from 1961 to 2014, totalizing 53 crop seasons. The crop models simulated a reduction of attainable yield with temperature increase, reaching 2000 kg ha-1 for the ensemble at + 6 °C, mainly due to shorter crop cycle. For rainfall, the yield had a higher rate of reduction when it was diminished than when rainfall was increased. The crop models increased yield variability when solar radiation was changed from - 15 to + 15%, whereas [CO2] rise resulted in yield gains, following an asymptotic response, with a mean increase of 31% from 380 to 680 ppm. The models used require further attention to improvements in optimal and maximum cardinal temperature for development rate; runoff, water infiltration, deep drainage, and dynamic of root growth; photosynthesis parameters related to soil water availability; and energy balance of soil-plant system to define leaf temperature under elevated CO2.

Liming can decrease legume crop yield and leaf gas exchange by enhancing root to shoot ABA signalling

PubMed Central

Rothwell, Shane A.; Elphinstone, E. David; Dodd, Ian C.

2015-01-01

To meet future requirements for food production, sustainable intensive agricultural systems need to optimize nutrient availability to maximize yield, traditionally achieved by maintaining soil pH within an optimal range (6–6.5) by applying lime (calcium carbonate). However, a field trial that applied recommended liming rates to a sandy loam soil (increasing soil pH from 5.5 to 6.2) decreased pod yield of field bean (Vicia faba L. cv. Fuego) by ~30%. Subsequent pot trials, with liming that raised soil pH to 6.3–6.7, reduced stomatal conductance (g s) by 63, 26, and 59% in V. faba, bean (Phaseolus vulgaris), and pea (Pisum sativum), respectively. Furthermore, liming reduced shoot dry biomass by 16–24% in these species. Ionomic analysis of root xylem sap and leaf tissue revealed a decrease in phosphorus concentration that was correlated with decreased g s: both reductions were partially reversed by adding superphosphate fertilizer. Further analysis of pea suggests that leaf gas exchange was reduced by a systemic increase (roots, xylem sap, and leaves) in the phytohormone abscisic acid (ABA) in response to lime-induced suboptimal plant phosphorus concentrations. Supplying synthetic ABA via the transpiration stream to detached pea leaves, at the same xylem sap concentrations induced by liming, decreased transpiration. Furthermore, the g s of the ABA-deficient mutant pea wilty was unresponsive to liming, apparently confirming that ABA mediates some responses to low phosphorus availability caused by liming. This research provides a detailed mechanistic understanding of the physiological processes by which lime application can limit crop yields, and questions the suitability of current liming recommendations. PMID:25740925

A Novel Approach for Forecasting Crop Production and Yield Using Remotely Sensed Satellite Images

NASA Astrophysics Data System (ADS)

Singh, R. K.; Budde, M. E.; Senay, G. B.; Rowland, J.

2017-12-01

Forecasting crop production in advance of crop harvest plays a significant role in drought impact management, improved food security, stabilizing food grain market prices, and poverty reduction. This becomes essential, particularly in Sub-Saharan Africa, where agriculture is a critical source of livelihoods, but lacks good quality agricultural statistical data. With increasing availability of low cost satellite data, faster computing power, and development of modeling algorithms, remotely sensed images are becoming a common source for deriving information for agricultural, drought, and water management. Many researchers have shown that the Normalized Difference Vegetation Index (NDVI), based on red and near-infrared reflectance, can be effectively used for estimating crop production and yield. Similarly, crop production and yield have been closely related to evapotranspiration (ET) also as there are strong linkages between production/yield and transpiration based on plant physiology. Thus, we combined NDVI and ET information from remotely sensed images for estimating total production and crop yield prior to crop harvest for Niger and Burkina Faso in West Africa. We identified the optimum time (dekads 23-29) for cumulating NDVI and ET and developed a new algorithm for estimating crop production and yield. We used the crop data from 2003 to 2008 to calibrate our model and the data from 2009 to 2013 for validation. Our results showed that total crop production can be estimated within 5% of actual production (R2 = 0.98) about 30-45 days before end of the harvest season. This novel approach can be operationalized to provide a valuable tool to decision makers for better drought impact management in drought-prone regions of the world.

An integrated modeling framework of socio-economic, biophysical, and hydrological processes in Midwest landscapes: Remote sensing data, agro-hydrological model, and agent-based model

NASA Astrophysics Data System (ADS)

Ding, Deng

Intensive human-environment interactions are taking place in Midwestern agricultural systems. An integrated modeling framework is suitable for predicting dynamics of key variables of the socio-economic, biophysical, hydrological processes as well as exploring the potential transitions of system states in response to changes of the driving factors. The purpose of this dissertation is to address issues concerning the interacting processes and consequent changes in land use, water balance, and water quality using an integrated modeling framework. This dissertation is composed of three studies in the same agricultural watershed, the Clear Creek watershed in East-Central Iowa. In the first study, a parsimonious hydrologic model, the Threshold-Exceedance-Lagrangian Model (TELM), is further developed into RS-TELM (Remote Sensing TELM) to integrate remote sensing vegetation data for estimating evapotranspiration. The goodness of fit of RS-TELM is comparable to a well-calibrated SWAT (Soil and Water Assessment Tool) and even slightly superior in capturing intra-seasonal variability of stream flow. The integration of RS LAI (Leaf Area Index) data improves the model's performance especially over the agriculture dominated landscapes. The input of rainfall datasets with spatially explicit information plays a critical role in increasing the model's goodness of fit. In the second study, an agent-based model is developed to simulate farmers' decisions on crop type and fertilizer application in response to commodity and biofuel crop prices. The comparison between simulated crop land percentage and crop rotations with satellite-based land cover data suggest that farmers may be underestimating the effects that continuous corn production has on yields (yield drag). The simulation results given alternative market scenarios based on a survey of agricultural land owners and operators in the Clear Creek Watershed show that, farmers see cellulosic biofuel feedstock production in the form of perennial grasses or corn stover as a more risky enterprise than their current crop production systems, likely because of market and production risks and lock in effects. As a result farmers do not follow a simple farm-profit maximization rule. In the third study, the consequent water quantity and quality change of the potential land use transitions given alternative biofuel crop market scenarios is explored in a case study in the Clear Creek watershed. A computer program is developed to implement the loose-coupling strategy to couple an agent-based land use model with SWAT. The simulation results show that watershed-scale water quantity (water yield and runoff) and quality variables (sediment and nutrient loads) decrease in values as switchgrass price increases. However, negligence of farmers risk aversions towards biofuel crop adoption would cause overestimation of the impacts of switchgrass price on water quantity and quality.

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

PubMed Central

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

2017-01-01

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

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

PubMed

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

2017-01-01

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

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

PubMed Central

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

2017-01-01

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

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

NASA Technical Reports Server (NTRS)

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

Development of transgenic crops based on photo-biotechnology.

PubMed

Ganesan, Markkandan; Lee, Hyo-Yeon; Kim, Jeong-Il; Song, Pill-Soon

2017-11-01

The phenotypes associated with plant photomorphogenesis such as the suppressed shade avoidance response and de-etiolation offer the potential for significant enhancement of crop yields. Of many light signal transducers and transcription factors involved in the photomorphogenic responses of plants, this review focuses on the transgenic overexpression of the photoreceptor genes at the uppermost stream of the signalling events, particularly phytochromes, crytochromes and phototropins as the transgenes for the genetic engineering of crops with improved harvest yields. In promoting the harvest yields of crops, the photoreceptors mediate the light regulation of photosynthetically important genes, and the improved yields often come with the tolerance to abiotic stresses such as drought, salinity and heavy metal ions. As a genetic engineering approach, the term photo-biotechnology has been coined to convey the idea that the greater the photosynthetic efficiency that crop plants can be engineered to possess, the stronger the resistance to biotic and abiotic stresses. Development of GM crops based on photoreceptor transgenes (mainly phytochromes, crytochromes and phototropins) is reviewed with the proposal of photo-biotechnology that the photoreceptors mediate the light regulation of photosynthetically important genes, and the improved yields often come with the added benefits of crops' tolerance to environmental stresses. © 2016 John Wiley & Sons Ltd.

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

PubMed Central

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

2017-01-01

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

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

PubMed

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

2017-08-29

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

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

USGS Publications Warehouse

Brumbelow, Kelly; Georgakakos, Aris P.

2000-01-01

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

Yield variability prediction by remote sensing sensors with different spatial resolution

NASA Astrophysics Data System (ADS)

Kumhálová, Jitka; Matějková, Štěpánka

2017-04-01

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

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

ERIC Educational Resources Information Center

Khan, A. H.; And Others

1996-01-01

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

Projected changes in crop yield mean and variability over West Africa in a world 1.5 K warmer than the pre-industrial era

NASA Astrophysics Data System (ADS)

Parkes, Ben; Defrance, Dimitri; Sultan, Benjamin; Ciais, Philippe; Wang, Xuhui

2018-02-01

The ability of a region to feed itself in the upcoming decades is an important issue. The West African population is expected to increase significantly in the next 30 years. The responses of crops to short-term climate change is critical to the population and the decision makers tasked with food security. This leads to three questions: how will crop yields change in the near future? What influence will climate change have on crop failures? Which adaptation methods should be employed to ameliorate undesirable changes? An ensemble of near-term climate projections are used to simulate maize, millet and sorghum in West Africa in the recent historic period (1986-2005) and a near-term future when global temperatures are 1.5 K above pre-industrial levels to assess the change in yield, yield variability and crop failure rate. Four crop models were used to simulate maize, millet and sorghum in West Africa in the historic and future climates. Across the majority of West Africa the maize, millet and sorghum yields are shown to fall. In the regions where yields increase, the variability also increases. This increase in variability increases the likelihood of crop failures, which are defined as yield negative anomalies beyond 1 standard deviation during the historic period. The increasing variability increases the frequency of crop failures across West Africa. The return time of crop failures falls from 8.8, 9.7 and 10.1 years to 5.2, 6.3 and 5.8 years for maize, millet and sorghum respectively. The adoption of heat-resistant cultivars and the use of captured rainwater have been investigated using one crop model as an idealized sensitivity test. The generalized doption of a cultivar resistant to high-temperature stress during flowering is shown to be more beneficial than using rainwater harvesting.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Variability in soybean yield in Brazil stemming from the interaction of heterogeneous management and climate variability

NASA Astrophysics Data System (ADS)

Cohn, A.; Bragança, A.; Jeffries, G. R.

2017-12-01

An increasing share of global agricultural production can be found in the humid tropics. Therefore, an improved understanding of the mechanisms governing variability in the output of tropical agricultural systems is of increasing importance for food security including through climate change adaptation. Yet, the long window over which many tropical crops can be sown, the diversity of crop varieties and management practices combine to challenge inference into climate risk to cropping output in analyses of tropical crop-climate sensitivity employing administrative data. In this paper, we leverage a newly developed spatially explicit dataset of soybean yields in Brazil to combat this problem. The dataset was built by training a model of remotely-sensed vegetation index data and land cover classification data using a rich in situ dataset of soybean yield and management variables collected over the period 2006 to 2016. The dataset contains soybean yields by plant date, cropping frequency, and maturity group for each 5km grid cell in Brazil. We model variation in these yields using an approach enabling the estimation of the influence of management factors on the sensitivity of soybean yields to variability in: cumulative solar radiation, extreme degree days, growing degree days, flooding rain in the harvest period, and dry spells in the rainy season. We find strong variation in climate sensitivity by management class. Planting date and maturity group each explained a great deal more variation in yield sensitivity than did cropping frequency. Brazil collects comparatively fine spatial resolution yield data. But, our attempt to replicate our results using administrative soy yield data revealed substantially lesser crop-climate sensitivity; suggesting that previous analyses employing administrative data may have underestimated climate risk to tropical soy production.

Seeing is believing I: The use of thermal sensing from satellite imagery to predict crop yield

NASA Astrophysics Data System (ADS)

B, Potgieter A.; D, Rodriguez; B, Power; J, Mclean; P, Davis

2014-02-01

Volatility in crop production has been part of the Australian environment since cropping began with the arrival of the first European settlers. Climate variability is the main factor affecting crop production at national, state and local scales. At field level spatial patterns on yield production are also determined by spatially changing soil properties in interaction with seasonal climate conditions and weather patterns at critical stages in the crop development. Here we used a combination of field level weather records, canopy characteristics, and satellite information to determine the spatial performance of a large field of wheat. The main objective of this research is to determine the ability of remote sensing technologies to capture yield losses due to water stress at the canopy level. The yield, canopy characteristics (i.e. canopy temperature and ground cover) and seasonal conditions of a field of wheat (~1400ha) (-29.402° South and 149.508°, New South Wales, Australia) were continuously monitored during the winter of 2011. Weather and crop variables were continuously monitored by installing three automatic weather stations in a transect covering different positions and soils in the landscape. Weather variables included rainfall, minimum and maximum temperatures and relative humidity, and crop characteristics included ground cover and canopy temperature. Satellite imagery Landsat TM 5 and 7 was collected at five different stages in the crop cycle. Weather variables and crop characteristics were used to calculate a crop stress index (CSI) at point and field scale (39 fields). Field data was used to validate a spatial satellite image derived index. Spatial yield data was downloaded from the harvester at the different locations in the field. We used the thermal band (land surface temperature, LST) and enhanced vegetation index (EVI) bands from the MODIS (250 m for visible bands and 1km for thermal band) and a derived EVI from Landsat TM 7 (25 m for visible and 90m for thermal) satellite platforms. Results showed that spatial variations in crop yield were related to a satellite derived canopy stress index (CSIsat) and a moisture stress index (MSIsat). A weather station level canopy stress index (CSIws) calculated at midday was correlated to the CSIsat at late morning. In addition, a strong linear relationship was observed between EVI and LST at point scale throughout the crop growth period. Differences were smallest at anthesis when the canopy closure was highest. This suggests that LST imagery data around flowering could be used to calculate crop stress over large areas of the crop. The harvested yield was related (R2 = 0.67) to CSIsat using a fix date across all fields. This relationship improved (R2 = 0.92) using both indices from all five dates across all fields during the crop growth period. Here we successfully showed that satellite derived crop attributes (CSIsat and MSIsat) can account for most of the variability in final crop yield and that they can be used to predict crop yield at field scales. Applications of these results could enhance the ability of producers to hedge their financial on -farm crop production losses due to in-season water stress by taking crop insurance. This is likely to further improve their adaptive capacity and thus strengthening the long-term viability of the industry domestically and elsewhere.

Design and analysis of mixed cropping experiments for indigenous Pacific Islands

Treesearch

Mareko P. Tofinga

1993-01-01

Mixed cropping (including agroforestry) often gives yield advan-tages as opposed to monocropping. Many criteria have been used to assess yield advantage in crop mixtures. Some of these are presented. In addition, the relative merits of replacement, additive and bivariate factorial designs are discussed. The concepts of analysis of mixed cropping are applied to an...

How changes of climate extremes affect summer and winter crop yields and water productivity in the southeast USA

NASA Astrophysics Data System (ADS)

Tian, D.; Cammarano, D.

2017-12-01

Modeling changes of crop production at regional scale is important to make adaptation measures for sustainably food supply under global change. In this study, we explore how changing climate extremes in the 20th and 21st century affect maize (summer crop) and wheat (winter crop) yields in an agriculturally important region: the southeast United States. We analyze historical (1950-1999) and projected (2006-2055) precipitation and temperature extremes by calculating the changes of 18 climate extreme indices using the statistically downscaled CMIP5 data from 10 general circulation models (GCMs). To evaluate how these climate extremes affect maize and wheat yields, historical baseline and projected maize and wheat yields under RCP4.5 and RCP8.5 scenarios are simulated using the DSSAT-CERES maize and wheat models driven by the same downscaled GCMs data. All of the changes are examined at 110 locations over the study region. The results show that most of the precipitation extreme indices do not have notable change; mean precipitation, precipitation intensity, and maximum 1-day precipitation are generally increased; the number of rainy days is decreased. The temperature extreme indices mostly showed increased values on mean temperature, number of high temperature days, diurnal temperature range, consecutive high temperature days, maximum daily maximum temperature, and minimum daily minimum temperature; the number of low temperature days and number of consecutive low temperature days are decreased. The conditional probabilistic relationships between changes in crop yields and changes in extreme indices suggested different responses of crop yields to climate extremes during sowing to anthesis and anthesis to maturity periods. Wheat yields and crop water productivity for wheat are increased due to an increased CO2 concentration and minimum temperature; evapotranspiration, maize yields, and crop water productivity for wheat are decreased owing to the increased temperature extremes. We found the effects of precipitation changes on both yields are relatively uncertain.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Nation-wide assessment of climate change impacts on crops in the Philippines and Peru as part of multi-disciplinary modelling framework

NASA Astrophysics Data System (ADS)

Fujisawa, Mariko; Kanamaru, Hideki

2016-04-01

Agriculture is vulnerable to environmental changes, and climate change has been recognized as one of the most devastating factors. In many developing countries, however, few studies have focused on nation-wide assessment of crop yield and crop suitability in the future, and hence there is a large pressure on science to provide policy makers with solid predictions for major crops in the countries in support of climate risk management policies and programmes. FAO has developed the tool MOSAICC (Modelling System for Agricultural Impacts of Climate Change) where statistical climate downscaling is combined with crop yield projections under climate change scenarios. Three steps are required to get the results: 1. The historical meteorological data such as temperature and precipitation for about 30 years were collected, and future climates were statistically downscaled to the local scale, 2. The historical crop yield data were collected and regression functions were made to estimate the yield by using observed climatic data and water balance during the growing period for each crop, and 3. The yield changes in the future were estimated by using the future climate data, produced by the first step, as an input to the yield regression functions. The yield was first simulated at sub-national scale and aggregated to national scale, which is intended to provide national policies with adaptation options. The methodology considers future changes in characteristics of extreme weather events as the climate projections are on daily scale while crop simulations are on 10-daily scale. Yields were simulated with two greenhouse gas concentration pathways (RCPs) for three GCMs per crop to account for uncertainties in projections. The crop assessment constitutes a larger multi-disciplinary assessment of climate change impacts on agriculture and vulnerability of livelihoods in terms of food security (e.g. water resources, agriculture market, household-level food security from socio-economic perspective). In our presentation we will show the cases of Peru and the Philippines, and discuss the implications for agriculture policies and risk management.

Using observed warming to identify hazards to Mozambique maize production

USGS Publications Warehouse

Funk, Christopher C.; Harrison, Laura; Eilerts, Gary

2011-01-01

New Perspectives on Crop Yield Constraints because of Climate Change. Climate change impact assessments usually focus on changes to precipitation because most global food production is from rainfed cropping systems; however, other aspects of climate change may affect crop growth and potential yields.A recent (2011) study by the University of California, Santa Barbara (UCSB) Climate Hazards Group, determined that climate change may be affecting Mozambique's primary food crop in a usually overlooked, but potentially significant way (Harrison and others, 2011). The study focused on the direct relation between maize crop development and growing season temperature. It determined that warming during the past three decades in Mozambique may be causing more frequent crop stress and yield reductions in that country's maize crop, independent of any changes occurring in rainfall. This report summarizes the findings and conclusions of that study.

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

PubMed

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

2010-11-16

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

Network Candidate Genes in Breeding for Drought Tolerant Crops

PubMed Central

Krannich, Christoph Tim; Maletzki, Lisa; Kurowsky, Christina; Horn, Renate

2015-01-01

Climate change leading to increased periods of low water availability as well as increasing demands for food in the coming years makes breeding for drought tolerant crops a high priority. Plants have developed diverse strategies and mechanisms to survive drought stress. However, most of these represent drought escape or avoidance strategies like early flowering or low stomatal conductance that are not applicable in breeding for crops with high yields under drought conditions. Even though a great deal of research is ongoing, especially in cereals, in this regard, not all mechanisms involved in drought tolerance are yet understood. The identification of candidate genes for drought tolerance that have a high potential to be used for breeding drought tolerant crops represents a challenge. Breeding for drought tolerant crops has to focus on acceptable yields under water-limited conditions and not on survival. However, as more and more knowledge about the complex networks and the cross talk during drought is available, more options are revealed. In addition, it has to be considered that conditioning a crop for drought tolerance might require the production of metabolites and might cost the plants energy and resources that cannot be used in terms of yield. Recent research indicates that yield penalty exists and efficient breeding for drought tolerant crops with acceptable yields under well-watered and drought conditions might require uncoupling yield penalty from drought tolerance. PMID:26193269

Network Candidate Genes in Breeding for Drought Tolerant Crops.

PubMed

Krannich, Christoph Tim; Maletzki, Lisa; Kurowsky, Christina; Horn, Renate

2015-07-17

Climate change leading to increased periods of low water availability as well as increasing demands for food in the coming years makes breeding for drought tolerant crops a high priority. Plants have developed diverse strategies and mechanisms to survive drought stress. However, most of these represent drought escape or avoidance strategies like early flowering or low stomatal conductance that are not applicable in breeding for crops with high yields under drought conditions. Even though a great deal of research is ongoing, especially in cereals, in this regard, not all mechanisms involved in drought tolerance are yet understood. The identification of candidate genes for drought tolerance that have a high potential to be used for breeding drought tolerant crops represents a challenge. Breeding for drought tolerant crops has to focus on acceptable yields under water-limited conditions and not on survival. However, as more and more knowledge about the complex networks and the cross talk during drought is available, more options are revealed. In addition, it has to be considered that conditioning a crop for drought tolerance might require the production of metabolites and might cost the plants energy and resources that cannot be used in terms of yield. Recent research indicates that yield penalty exists and efficient breeding for drought tolerant crops with acceptable yields under well-watered and drought conditions might require uncoupling yield penalty from drought tolerance.

Modelling crop yield in Iberia under drought conditions

NASA Astrophysics Data System (ADS)

Ribeiro, Andreia; Páscoa, Patrícia; Russo, Ana; Gouveia, Célia

2017-04-01

The improved assessment of the cereal yield and crop loss under drought conditions are essential to meet the increasing economy demands. The growing frequency and severity of the extreme drought conditions in the Iberian Peninsula (IP) has been likely responsible for negative impacts on agriculture, namely on crop yield losses. Therefore, a continuous monitoring of vegetation activity and a reliable estimation of drought impacts is crucial to contribute for the agricultural drought management and development of suitable information tools. This works aims to assess the influence of drought conditions in agricultural yields over the IP, considering cereal yields from mainly rainfed agriculture for the provinces with higher productivity. The main target is to develop a strategy to model drought risk on agriculture for wheat yield at a province level. In order to achieve this goal a combined assessment was made using a drought indicator (Standardized Precipitation Evapotranspiration Index, SPEI) to evaluate drought conditions together with a widely used vegetation index (Normalized Difference Vegetation Index, NDVI) to monitor vegetation activity. A correlation analysis between detrended wheat yield and SPEI was performed in order to assess the vegetation response to each time scale of drought occurrence and also identify the moment of the vegetative cycle when the crop yields are more vulnerable to drought conditions. The time scales and months of SPEI, together with the months of NDVI, better related with wheat yield were chosen to perform a multivariate regression analysis to simulate crop yield. Model results are satisfactory and highlighted the usefulness of such analysis in the framework of developing a drought risk model for crop yields. In terms of an operational point of view, the results aim to contribute to an improved understanding of crop yield management under dry conditions, particularly adding substantial information on the advantages of combining vegetation and hydro-meteorological drought indices for the assessment of cereal yield. Moreover, the present study will provide some guidance on user's decision making process in agricultural practices in the IP, assisting farmers in deciding whether to purchase crop insurance. Acknowledgements: This work was partially supported by national funds through FCT (Fundação para a Ciência e a Tecnologia, Portugal) under project IMDROFLOOD (WaterJPI/0004/2014). Ana Russo thanks FCT for granted support (SFRH/BPD/99757/2014). Andreia Ribeiro also thanks FCT for grant PD/BD/114481/2016.

Roguing with replacement in perennial crops: conditions for successful disease management.

PubMed

Sisterson, Mark S; Stenger, Drake C

2013-02-01

Replacement of diseased plants with healthy plants is commonly used to manage spread of plant pathogens in perennial cropping systems. This strategy has two potential benefits. First, removing infected plants may slow pathogen spread by eliminating inoculum sources. Second, replacing infected plants with uninfected plants may offset yield losses due to disease. The extent to which these benefits are realized depends on multiple factors. In this study, sensitivity analyses of two spatially explicit simulation models were used to evaluate how assumptions concerning implementation of a plant replacement program and pathogen spread interact to affect disease suppression. In conjunction, effects of assumptions concerning yield loss associated with disease and rates of plant maturity on yields were simultaneously evaluated. The first model was used to evaluate effects of plant replacement on pathogen spread and yield on a single farm, consisting of a perennial crop monoculture. The second model evaluated effects of plant replacement on pathogen spread and yield in a 100 farm crop growing region, with all farms maintaining a monoculture of the same perennial crop. Results indicated that efficient replacement of infected plants combined with a high degree of compliance among farms effectively slowed pathogen spread, resulting in replacement of few plants and high yields. In contrast, inefficient replacement of infected plants or limited compliance among farms failed to slow pathogen spread, resulting in replacement of large numbers of plants (on farms practicing replacement) with little yield benefit. Replacement of infected plants always increased yields relative to simulations without plant replacement provided that infected plants produced no useable yield. However, if infected plants produced useable yields, inefficient removal of infected plants resulted in lower yields relative to simulations without plant replacement for perennial crops with long maturation periods in some cases.

Strengths and Limitations of Operational Use of 1 Km EO Biophysical Products for Regional Prediction of Grain Yelds in Europe (wheat, barley and maize)

NASA Astrophysics Data System (ADS)

Meroni, M.; LEO, O.; Lopez-Lozano, R.; Baruth, B.; Duveiller, G.; Garcia-Condado, S.; Hooker, J.; Seguini, L.

2014-12-01

The site-specific relationship between EO indicators and actual crop yields has been explored in many different studies, describing semi-empirical regression models between spatially aggregated biophysical parameters or vegetation indices and observed yields (from field measurements or official statistics). However, when considering larger extensions -from countries to continents- agro-climatic conditions and crop management may differ substantially among regions, and these differences may greatly influence the relationship between biophysical indicators and the observed yields, which may be also driven by limiting factors other than green biomass formation. The present study aims to better assess the contribution of EO indicators within an operational crop yield forecasting system in Europe and neighbouring countries, by evaluating how these above mentioned geographic differences influence the relationship between biophysical indicators and crop yield. We therefore explore, as a first step, the correspondence between fAPAR time-series (1999-2013) and the inter-annual yield variability of wheat, barley and grain maize, at sub-national level across Europe (270-450 Administrative Units, depending on crop). In a second step, we map the agro-climatic contexts in which EO indicators better explain the observed yield inter-annual variability, identify the influence of some meteorological events on the fAPAR -yield relationship and provide some recommendations for further investigation. The results indicate that in water-limited environments (e.g. Mediterranean and Black Sea areas), fAPAR is highly correlated with yields whereas in northern Europe, crop yield appears much less limited by leaf area expansion along the season, and the relationship between yield and EO products becomes more difficult to interpret.

Sensitivity and requirement of improvements of four soybean crop simulation models for climate change studies in Southern Brazil.

PubMed

Battisti, R; Sentelhas, P C; Boote, K J

2018-05-01

Crop growth models have many uncertainties that affect the yield response to climate change. Based on that, the aim of this study was to evaluate the sensitivity of crop models to systematic changes in climate for simulating soybean attainable yield in Southern Brazil. Four crop models were used to simulate yields: AQUACROP, MONICA, DSSAT, and APSIM, as well as their ensemble. The simulations were performed considering changes of air temperature (0, + 1.5, + 3.0, + 4.5, and + 6.0 °C), [CO 2 ] (380, 480, 580, 680, and 780 ppm), rainfall (- 30, - 15, 0, + 15, and + 30%), and solar radiation (- 15, 0, + 15), applied to daily values. The baseline climate was from 1961 to 2014, totalizing 53 crop seasons. The crop models simulated a reduction of attainable yield with temperature increase, reaching 2000 kg ha -1 for the ensemble at + 6 °C, mainly due to shorter crop cycle. For rainfall, the yield had a higher rate of reduction when it was diminished than when rainfall was increased. The crop models increased yield variability when solar radiation was changed from - 15 to + 15%, whereas [CO 2 ] rise resulted in yield gains, following an asymptotic response, with a mean increase of 31% from 380 to 680 ppm. The models used require further attention to improvements in optimal and maximum cardinal temperature for development rate; runoff, water infiltration, deep drainage, and dynamic of root growth; photosynthesis parameters related to soil water availability; and energy balance of soil-plant system to define leaf temperature under elevated CO 2 .

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

NASA Astrophysics Data System (ADS)

Chen, Yi; Zhang, Zhao; Tao, Fulu

2018-05-01

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

Climate Effects on Corn Yield in Missouri(.

NASA Astrophysics Data System (ADS)

Hu, Qi; Buyanovsky, Gregory

2003-11-01

Understanding climate effects on crop yield has been a continuous endeavor aiming at improving farming technology and management strategy, minimizing negative climate effects, and maximizing positive climate effects on yield. Many studies have examined climate effects on corn yield in different regions of the United States. However, most of those studies used yield and climate records that were shorter than 10 years and were for different years and localities. Although results of those studies showed various influences of climate on corn yield, they could be time specific and have been difficult to use for deriving a comprehensive understanding of climate effects on corn yield. In this study, climate effects on corn yield in central Missouri are examined using unique long-term (1895 1998) datasets of both corn yield and climate. Major results show that the climate effects on corn yield can only be explained by within-season variations in rainfall and temperature and cannot be distinguished by average growing-season conditions. Moreover, the growing-season distributions of rainfall and temperature for high-yield years are characterized by less rainfall and warmer temperature in the planting period, a rapid increase in rainfall, and more rainfall and warmer temperatures during germination and emergence. More rainfall and cooler-than-average temperatures are key features in the anthesis and kernel-filling periods from June through August, followed by less rainfall and warmer temperatures during the September and early October ripening time. Opposite variations in rainfall and temperature in the growing season correspond to low yield. Potential applications of these results in understanding how climate change may affect corn yield in the region also are discussed.

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.

Climate change impacts on crop yield: evidence from China.

PubMed

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

2014-11-15

When estimating climate change impact on crop yield, a typical assumption is constant elasticity of yield with respect to a climate variable even though the elasticity may be inconstant. After estimating both constant and inconstant elasticities with respect to temperature and precipitation based on provincial panel data in China 1980-2008, our results show that during that period, the temperature change contributes positively to total yield growth by 1.3% and 0.4% for wheat and rice, respectively, but negatively by 12% for maize. The impacts of precipitation change are marginal. We also compare our estimates with other studies and highlight the implications of the inconstant elasticities for crop yield, harvest and food security. We conclude that climate change impact on crop yield would not be an issue in China if positive impacts of other socio-economic factors continue in the future. Copyright © 2014 Elsevier B.V. All rights reserved.

Recent patterns of crop yield growth and stagnation.

PubMed

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

2012-01-01

In the coming decades, continued population growth, rising meat and dairy consumption and expanding biofuel use will dramatically increase the pressure on global agriculture. Even as we face these future burdens, there have been scattered reports of yield stagnation in the world's major cereal crops, including maize, rice and wheat. Here we study data from ∼2.5 million census observations across the globe extending over the period 1961-2008. We examined the trends in crop yields for four key global crops: maize, rice, wheat and soybeans. Although yields continue to increase in many areas, we find that across 24-39% of maize-, rice-, wheat- and soybean-growing areas, yields either never improve, stagnate or collapse. This result underscores the challenge of meeting increasing global agricultural demands. New investments in underperforming regions, as well as strategies to continue increasing yields in the high-performing areas, are required.

Improved Satellite-based Crop Yield Mapping by Spatially Explicit Parameterization of Crop Phenology

NASA Astrophysics Data System (ADS)

Jin, Z.; Azzari, G.; Lobell, D. B.

2016-12-01

Field-scale mapping of crop yields with satellite data often relies on the use of crop simulation models. However, these approaches can be hampered by inaccuracies in the simulation of crop phenology. Here we present and test an approach to use dense time series of Landsat 7 and 8 acquisitions data to calibrate various parameters related to crop phenology simulation, such as leaf number and leaf appearance rates. These parameters are then mapped across the Midwestern United States for maize and soybean, and for two different simulation models. We then implement our recently developed Scalable satellite-based Crop Yield Mapper (SCYM) with simulations reflecting the improved phenology parameterizations, and compare to prior estimates based on default phenology routines. Our preliminary results show that the proposed method can effectively alleviate the underestimation of early-season LAI by the default Agricultural Production Systems sIMulator (APSIM), and that spatially explicit parameterization for the phenology model substantially improves the SCYM performance in capturing the spatiotemporal variation in maize and soybean yield. The scheme presented in our study thus preserves the scalability of SCYM, while significantly reducing its uncertainty.

Monitoring Crop Productivity over the U.S. Corn Belt using an Improved Light Use Efficiency Model

NASA Astrophysics Data System (ADS)

Wu, X.; Xiao, X.; Zhang, Y.; Qin, Y.; Doughty, R.

2017-12-01

Large-scale monitoring of crop yield is of great significance for forecasting food production and prices and ensuring food security. Satellite data that provide temporally and spatially continuous information that by themselves or in combination with other data or models, raises possibilities to monitor and understand agricultural productivity regionally. In this study, we first used an improved light use efficiency model-Vegetation Photosynthesis Model (VPM) to simulate the gross primary production (GPP). Model evaluation showed that the simulated GPP (GPPVPM) could well captured the spatio-temporal variation of GPP derived from FLUXNET sites. Then we applied the GPPVPM to further monitor crop productivity for corn and soybean over the U.S. Corn Belt and benchmarked with county-level crop yield statistics. We found VPM-based approach provides pretty good estimates (R2 = 0.88, slope = 1.03). We further showed the impacts of climate extremes on the crop productivity and carbon use efficiency. The study indicates the great potential of VPM in estimating crop yield and in understanding of crop yield responses to climate variability and change.

Prediction of County-Level Corn Yields Using an Energy-Crop Growth Index.

NASA Astrophysics Data System (ADS)

Andresen, Jeffrey A.; Dale, Robert F.; Fletcher, Jerald J.; Preckel, Paul V.

1989-01-01

Weather conditions significantly affect corn yields. while weather remains as the major uncontrolled variable in crop production, an understanding of the influence of weather on yields can aid in early and accurate assessment of the impact of weather and climate on crop yields and allow for timely agricultural extension advisories to help reduce farm management costs and improve marketing, decisions. Based on data for four representative countries in Indiana from 1960 to 1984 (excluding 1970 because of the disastrous southern corn leaf blight), a model was developed to estimate corn (Zea mays L.) yields as a function of several composite soil-crop-weather variables and a technology-trend marker, applied nitrogen fertilizer (N). The model was tested by predicting corn yields for 15 other counties. A daily energy-crop growth (ECG) variable in which different weights were used for the three crop-weather variables which make up the daily ECG-solar radiation intercepted by the canopy, a temperature function, and the ratio of actual to potential evapotranspiration-performed better than when the ECG components were weighted equally. The summation of the weighted daily ECG over a relatively short period (36 days spanning silk) was found to provide the best index for predicting county average corn yield. Numerical estimation results indicate that the ratio of actual to potential evapotranspiration (ET/PET) is much more important than the other two ECG factors in estimating county average corn yield in Indiana.

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;

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

PubMed

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

2016-02-01

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

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

NASA Technical Reports Server (NTRS)

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

2015-01-01

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

Effect of Tillage Practices on Soil Properties and Crop Productivity in Wheat-Mungbean-Rice Cropping System under Subtropical Climatic Conditions

PubMed Central

Islam, Md. Monirul; Hasanuzzaman, Mirza

2014-01-01

This study was conducted to know cropping cycles required to improve OM status in soil and to investigate the effects of medium-term tillage practices on soil properties and crop yields in Grey Terrace soil of Bangladesh under wheat-mungbean-T. aman cropping system. Four different tillage practices, namely, zero tillage (ZT), minimum tillage (MT), conventional tillage (CT), and deep tillage (DT), were studied in a randomized complete block (RCB) design with four replications. Tillage practices showed positive effects on soil properties and crop yields. After four cropping cycles, the highest OM accumulation, the maximum root mass density (0–15 cm soil depth), and the improved physical and chemical properties were recorded in the conservational tillage practices. Bulk and particle densities were decreased due to tillage practices, having the highest reduction of these properties and the highest increase of porosity and field capacity in zero tillage. The highest total N, P, K, and S in their available forms were recorded in zero tillage. All tillage practices showed similar yield after four years of cropping cycles. Therefore, we conclude that zero tillage with 20% residue retention was found to be suitable for soil health and achieving optimum yield under the cropping system in Grey Terrace soil (Aeric Albaquept). PMID:25197702

Climate analogues suggest limited potential for intensification of production on current croplands under climate change

PubMed Central

Pugh, T.A.M.; Müller, C.; Elliott, J.; Deryng, D.; Folberth, C.; Olin, S.; Schmid, E.; Arneth, A.

2016-01-01

Climate change could pose a major challenge to efforts towards strongly increase food production over the coming decades. However, model simulations of future climate-impacts on crop yields differ substantially in the magnitude and even direction of the projected change. Combining observations of current maximum-attainable yield with climate analogues, we provide a complementary method of assessing the effect of climate change on crop yields. Strong reductions in attainable yields of major cereal crops are found across a large fraction of current cropland by 2050. These areas are vulnerable to climate change and have greatly reduced opportunity for agricultural intensification. However, the total land area, including regions not currently used for crops, climatically suitable for high attainable yields of maize, wheat and rice is similar by 2050 to the present-day. Large shifts in land-use patterns and crop choice will likely be necessary to sustain production growth rates and keep pace with demand. PMID:27646707

Climate Analogues Suggest Limited Potential for Intensification of Production on Current Croplands Under Climate Change

NASA Technical Reports Server (NTRS)

Pugh, T. A. M.; Mueller, C.; Elliott, J.; Deryng, D.; Folberth, C.; Olin, S.; Schmid, E.; Arneth, A.

2016-01-01

Climate change could pose a major challenge to efforts towards strongly increase food production over the coming decades. However, model simulations of future climate-impacts on crop yields differ substantially in the magnitude and even direction of the projected change. Combining observations of current maximum-attainable yield with climate analogues, we provide a complementary method of assessing the effect of climate change on crop yields. Strong reductions in attainable yields of major cereal crops are found across a large fraction of current cropland by 2050. These areas are vulnerable to climate change and have greatly reduced opportunity for agricultural intensification. However, the total land area, including regions not currently used for crops, climatically suitable for high attainable yields of maize, wheat and rice is similar by 2050 to the present-day. Large shifts in land-use patterns and crop choice will likely be necessary to sustain production growth rates and keep pace with demand.

Climate analogues suggest limited potential for intensification of production on current croplands under climate change

NASA Astrophysics Data System (ADS)

Pugh, T. A. M.; Müller, C.; Elliott, J.; Deryng, D.; Folberth, C.; Olin, S.; Schmid, E.; Arneth, A.

2016-09-01

Climate change could pose a major challenge to efforts towards strongly increase food production over the coming decades. However, model simulations of future climate-impacts on crop yields differ substantially in the magnitude and even direction of the projected change. Combining observations of current maximum-attainable yield with climate analogues, we provide a complementary method of assessing the effect of climate change on crop yields. Strong reductions in attainable yields of major cereal crops are found across a large fraction of current cropland by 2050. These areas are vulnerable to climate change and have greatly reduced opportunity for agricultural intensification. However, the total land area, including regions not currently used for crops, climatically suitable for high attainable yields of maize, wheat and rice is similar by 2050 to the present-day. Large shifts in land-use patterns and crop choice will likely be necessary to sustain production growth rates and keep pace with demand.

Crop responses to climatic variation

PubMed Central

Porter, John R; Semenov, Mikhail A

2005-01-01

The yield and quality of food crops is central to the well being of humans and is directly affected by climate and weather. Initial studies of climate change on crops focussed on effects of increased carbon dioxide (CO2) level and/or global mean temperature and/or rainfall and nutrition on crop production. However, crops can respond nonlinearly to changes in their growing conditions, exhibit threshold responses and are subject to combinations of stress factors that affect their growth, development and yield. Thus, climate variability and changes in the frequency of extreme events are important for yield, its stability and quality. In this context, threshold temperatures for crop processes are found not to differ greatly for different crops and are important to define for the major food crops, to assist climate modellers predict the occurrence of crop critical temperatures and their temporal resolution. This paper demonstrates the impacts of climate variability for crop production in a number of crops. Increasing temperature and precipitation variability increases the risks to yield, as shown via computer simulation and experimental studies. The issue of food quality has not been given sufficient importance when assessing the impact of climate change for food and this is addressed. Using simulation models of wheat, the concentration of grain protein is shown to respond to changes in the mean and variability of temperature and precipitation events. The paper concludes with discussion of adaptation possibilities for crops in response to drought and argues that characters that enable better exploration of the soil and slower leaf canopy expansion could lead to crop higher transpiration efficiency. PMID:16433091

Satellite-based mapping of field-scale stress indicators for crop yield forecasting: an application over Mead, NE

NASA Astrophysics Data System (ADS)

Yang, Y.; Anderson, M. C.; Gao, F.; Wardlow, B.; Hain, C.; Otkin, J.; Sun, L.; Dulaney, W.

2017-12-01

In agricultural regions, water is one of the most widely limiting factors of crop performance and production. Evapotranspiration (ET) describes crop water use through transpiration and water lost through direct soil evaporation, which makes it a good indicator of soil moisture availability and vegetation health and thus has been an integral part of many yield estimation efforts. The Evaporative Stress Index (ESI) describes temporal anomalies in a normalized evapotranspiration metric (fRET) as derived from satellite remote sensing and has demonstrated capacity to explain regional yield variability in water limited crop growing regions. However, its performance in some regions where the vegetation cycle is intensively managed appears to be degraded. In this study we generated maps of ET, fRET, and ESI at high spatiotemporal resolution (30-m pixels, daily timesteps) using a multi-sensor data fusion method, integrating information from satellite platforms with good temporal coverage and other platforms that provide field-scale spatial detail. The study was conducted over the period 2010-2014, covering a region around Mead, Nebraska that includes both rainfed and irrigated crops. Correlations between ESI and measurements of corn yield are investigated at both the field and county level to assess the value of ESI as a yield forecasting tool. To examine the role of phenology in ESI-yield correlations, annual input fRET timeseries were aligned by both calendar day and by biophysically relevant dates (e.g. days since planting or emergence). Results demonstrate that mapping of fRET and ESI at 30-m has the advantage of being able to resolve different crop types with varying phenology. The study also suggests that incorporating phenological information significantly improves yield-correlations by accounting for effects of phenology such as variable planting date and emergence date. The yield-ESI relationship in this study well captures the inter-annual variability of yields and thus has potential to be used for yield prediction, or for ingestion into a crop simulation model as a crop-specific moisture stress function.

Interactive effects of pests increase seed yield.

PubMed

Gagic, Vesna; Riggi, Laura Ga; Ekbom, Barbara; Malsher, Gerard; Rusch, Adrien; Bommarco, Riccardo

2016-04-01

Loss in seed yield and therefore decrease in plant fitness due to simultaneous attacks by multiple herbivores is not necessarily additive, as demonstrated in evolutionary studies on wild plants. However, it is not clear how this transfers to crop plants that grow in very different conditions compared to wild plants. Nevertheless, loss in crop seed yield caused by any single pest is most often studied in isolation although crop plants are attacked by many pests that can cause substantial yield losses. This is especially important for crops able to compensate and even overcompensate for the damage. We investigated the interactive impacts on crop yield of four insect pests attacking different plant parts at different times during the cropping season. In 15 oilseed rape fields in Sweden, we estimated the damage caused by seed and stem weevils, pollen beetles, and pod midges. Pest pressure varied drastically among fields with very low correlation among pests, allowing us to explore interactive impacts on yield from attacks by multiple species. The plant damage caused by each pest species individually had, as expected, either no, or a negative impact on seed yield and the strongest negative effect was caused by pollen beetles. However, seed yield increased when plant damage caused by both seed and stem weevils was high, presumably due to the joint plant compensatory reaction to insect attack leading to overcompensation. Hence, attacks by several pests can change the impact on yield of individual pest species. Economic thresholds based on single species, on which pest management decisions currently rely, may therefore result in economically suboptimal choices being made and unnecessary excessive use of insecticides.

Application of Thermal Infrared Remote Sensing for Quantitative Evaluation of Crop Characteristics

NASA Technical Reports Server (NTRS)

Shaw, J.; Luvall, J.; Rickman, D.; Mask, P.; Wersinger, J.; Sullivan, D.; Arnold, James E. (Technical Monitor)

2002-01-01

Evidence suggests that thermal infrared emittance (TIR) at the field-scale is largely a function of the integrated crop/soil moisture continuum. Because soil moisture dynamics largely determine crop yields in non-irrigated farming (85 % of Alabama farms are non-irrigated), TIR may be an effective method of mapping within field crop yield variability, and possibly, absolute yields. The ability to map yield variability at juvenile growth stages can lead to improved soil fertility and pest management, as well as facilitating the development of economic forecasting. Researchers at GHCC/MSFC/NASA and Auburn University are currently investigating the role of TIR in site-specific agriculture. Site-specific agriculture (SSA), or precision farming, is a method of crop production in which zones and soils within a field are delineated and managed according to their unique properties. The goal of SSA is to improve farm profits and reduce environmental impacts through targeted agrochemical applications. The foundation of SSA depends upon the spatial and temporal characterization of soil and crop properties through the creation of management zones. Management zones can be delineated using: 1) remote sensing (RS) data, 2) conventional soil testing and soil mapping, and 3) yield mapping. Portions of this research have concentrated on using remote sensing data to map yield variability in corn (Zea mays L.) and soybean (Glycine max L.) crops. Remote sensing data have been collected for several fields in the Tennessee Valley region at various crop growth stages during the last four growing seasons. Preliminary results of this study will be presented.

Global assessment of nitrogen losses and trade-offs with yields from major crop cultivations.

PubMed

Liu, Wenfeng; Yang, Hong; Liu, Junguo; Azevedo, Ligia B; Wang, Xiuying; Xu, Zongxue; Abbaspour, Karim C; Schulin, Rainer

2016-12-01

Agricultural application of reactive nitrogen (N) for fertilization is a cause of massive negative environmental problems on a global scale. However, spatially explicit and crop-specific information on global N losses into the environment and knowledge of trade-offs between N losses and crop yields are largely lacking. We use a crop growth model, Python-based Environmental Policy Integrated Climate (PEPIC), to determine global N losses from three major food crops: maize, rice, and wheat. Simulated total N losses into the environment (including water and atmosphere) are 44TgNyr -1 . Two thirds of these, or 29TgNyr -1 , are losses to water alone. Rice accounts for the highest N losses, followed by wheat and maize. The N loss intensity (NLI), defined as N losses per unit of yield, is used to address trade-offs between N losses and crop yields. The NLI presents high variation among different countries, indicating diverse N losses to produce the same amount of yields. Simulations of mitigation scenarios indicate that redistributing global N inputs and improving N management could significantly abate N losses and at the same time even increase yields without any additional total N inputs. Copyright © 2016 Elsevier B.V. All rights reserved.

Using statistical model to simulate the impact of climate change on maize yield with climate and crop uncertainties

NASA Astrophysics Data System (ADS)

Zhang, Yi; Zhao, Yanxia; Wang, Chunyi; Chen, Sining

2017-11-01

Assessment of the impact of climate change on crop productions with considering uncertainties is essential for properly identifying and decision-making agricultural practices that are sustainable. In this study, we employed 24 climate projections consisting of the combinations of eight GCMs and three emission scenarios representing the climate projections uncertainty, and two crop statistical models with 100 sets of parameters in each model representing parameter uncertainty within the crop models. The goal of this study was to evaluate the impact of climate change on maize ( Zea mays L.) yield at three locations (Benxi, Changling, and Hailun) across Northeast China (NEC) in periods 2010-2039 and 2040-2069, taking 1976-2005 as the baseline period. The multi-models ensembles method is an effective way to deal with the uncertainties. The results of ensemble simulations showed that maize yield reductions were less than 5 % in both future periods relative to the baseline. To further understand the contributions of individual sources of uncertainty, such as climate projections and crop model parameters, in ensemble yield simulations, variance decomposition was performed. The results indicated that the uncertainty from climate projections was much larger than that contributed by crop model parameters. Increased ensemble yield variance revealed the increasing uncertainty in the yield simulation in the future periods.

Opposing effects of different soil organic matter fractions on crop yields.

PubMed

Wood, Stephen A; Sokol, Noah; Bell, Colin W; Bradford, Mark A; Naeem, Shahid; Wallenstein, Matthew D; Palm, Cheryl A

2016-10-01

Soil organic matter is critical to sustainable agriculture because it provides nutrients to crops as it decomposes and increases nutrient- and water-holding capacity when built up. Fast- and slow-cycling fractions of soil organic matter can have different impacts on crop production because fast-cycling fractions rapidly release nutrients for short-term plant growth and slow-cycling fractions bind nutrients that mineralize slowly and build up water-holding capacity. We explored the controls on these fractions in a tropical agroecosystem and their relationship to crop yields. We performed physical fractionation of soil organic matter from 48 farms and plots in western Kenya. We found that fast-cycling, particulate organic matter was positively related to crop yields, but did not have a strong effect, while slower-cycling, mineral-associated organic matter was negatively related to yields. Our finding that slower-cycling organic matter was negatively related to yield points to a need to revise the view that stabilization of organic matter positively impacts food security. Our results support a new paradigm that different soil organic matter fractions are controlled by different mechanisms, potentially leading to different relationships with management outcomes, like crop yield. Effectively managing soils for sustainable agriculture requires quantifying the effects of specific organic matter fractions on these outcomes. © 2016 by the Ecological Society of America.

The importance of key floral bioactive compounds to honey bees for the detection and attraction of hybrid vegetable crops and increased seed yield.

PubMed

Mas, Flore; Harper, Aimee; Horner, Rachael; Welsh, Taylor; Jaksons, Peter; Suckling, David M

2018-02-15

Crop breeding programmes generally select for traits for improved yield and human consumption preferences. Yet, they often overlook one fundamental trait essential for insect-pollinated crops: pollinator attraction. This is even more critical for hybrid plants that rely on cross-pollination between the male-fertile line and the male-sterile line to set seeds. This study investigated the role of floral odours for honey bee pollination that could explain the poor seed yield in hybrid crops. The key floral bioactive compounds that honey bees detect were identified for three vegetable hybrid crops. It was found that 30% of the variation in bioactive compound quantities was explained by variety. Differences in quantities of the bioactive compounds triggered different degrees of olfactory response and were also associated with varied appetitive response. Correlating the abundance of each bioactive compound with seed yield, it was found that aldehydes such as nonanal and decanal can have a strong negative influence on seed yield with increasing quantity. Using these methodologies to identify relevant bioactive compounds associated with honey bee pollination, plant breeding programmes should also consider selecting for floral traits attractive to honey bees to improve crop pollination for enhanced seed yield. © 2018 Society of Chemical Industry. © 2018 Society of Chemical Industry.

Contrasting effects of landscape composition on crop yield mediated by specialist herbivores.

PubMed

Perez-Alvarez, Ricardo; Nault, Brian A; Poveda, Katja

2018-04-01

Landscape composition not only affects a variety of arthropod-mediated ecosystem services, but also disservices, such as herbivory by insect pests that may have negative effects on crop yield. Yet, little is known about how different habitats influence the dynamics of multiple herbivore species, and ultimately their collective impact on crop production. Using cabbage as a model system, we examined how landscape composition influenced the incidence of three specialist cruciferous pests (aphids, flea beetles, and leaf-feeding Lepidoptera), lepidopteran parasitoids, and crop yield across a gradient of landscape composition in New York, USA. We expected that landscapes with a higher proportion of cropland and lower habitat diversity would lead to an increase in pest pressure of the specialist herbivores and a reduction in crop yield. However, results indicated that neither greater cropland area nor lower landscape diversity influenced pest pressure or yield. Rather, pest pressure and yield were best explained by the presence of non-crop habitats (i.e., meadows) in the landscape. Specifically, cabbage was infested with fewer Lepidoptera in landscapes with a higher proportion of meadows likely resulting from increased parasitism. Conversely, cabbage was infested with more flea beetles and aphids as the proportion of meadows in the landscape increased, suggesting that these pests benefit from non-crop habitats. Furthermore, path analysis confirmed that these landscape-mediated effects on pest populations can have either positive or negative cascading effects on crop yield. Our findings illustrate how different pest species within the same cropping system show contrasting responses to landscape composition with respect to both the direction and spatial scale of the relationship. Such tradeoffs resulting from the complex interaction between multiple-pests, natural enemies, and landscape composition must be considered, if we are to manage landscapes for pest suppression benefits. © 2018 by the Ecological Society of America.

Characterizing drought stress and trait influence on maize yield under current and future conditions.

PubMed

Harrison, Matthew T; Tardieu, François; Dong, Zhanshan; Messina, Carlos D; Hammer, Graeme L

2014-03-01

Global climate change is predicted to increase temperatures, alter geographical patterns of rainfall and increase the frequency of extreme climatic events. Such changes are likely to alter the timing and magnitude of drought stresses experienced by crops. This study used new developments in the classification of crop water stress to first characterize the typology and frequency of drought-stress patterns experienced by European maize crops and their associated distributions of grain yield, and second determine the influence of the breeding traits anthesis-silking synchrony, maturity and kernel number on yield in different drought-stress scenarios, under current and future climates. Under historical conditions, a low-stress scenario occurred most frequently (ca. 40%), and three other stress types exposing crops to late-season stresses each occurred in ca. 20% of cases. A key revelation shown was that the four patterns will also be the most dominant stress patterns under 2050 conditions. Future frequencies of low drought stress were reduced by ca. 15%, and those of severe water deficit during grain filling increased from 18% to 25%. Despite this, effects of elevated CO2 on crop growth moderated detrimental effects of climate change on yield. Increasing anthesis-silking synchrony had the greatest effect on yield in low drought-stress seasonal patterns, whereas earlier maturity had the greatest effect in crops exposed to severe early-terminal drought stress. Segregating drought-stress patterns into key groups allowed greater insight into the effects of trait perturbation on crop yield under different weather conditions. We demonstrate that for crops exposed to the same drought-stress pattern, trait perturbation under current climates will have a similar impact on yield as that expected in future, even though the frequencies of severe drought stress will increase in future. These results have important ramifications for breeding of maize and have implications for studies examining genetic and physiological crop responses to environmental stresses. © 2013 John Wiley & Sons Ltd.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

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

PubMed

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

2014-08-01

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

Soil water in small drainages farmed with no-tillage and inversion tillage in northeastern Oregon

USDA-ARS?s Scientific Manuscript database

Crop productivity in the semi-arid inland Pacific Northwest (IPNW), USA is dependent on the capture and storage of precipitation as soil water. To maximize soil water in this region, the conventional crop strategy is a two year crop – fallow system in which winter wheat (W, Triticum aestivum L.) is ...

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

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

Soil properties, greenhouse gas emissions and crop yield under compost, biochar and co-composted biochar in two tropical agronomic systems.

PubMed

Bass, Adrian M; Bird, Michael I; Kay, Gavin; Muirhead, Brian

2016-04-15

The addition of organic amendments to agricultural soils has the potential to increase crop yields, reduce dependence on inorganic fertilizers and improve soil condition and resilience. We evaluated the effect of biochar (B), compost (C) and co-composted biochar (COMBI) on the soil properties, crop yield and greenhouse gas emissions from a banana and a papaya plantation in tropical Australia in the first harvest cycle. Biochar, compost and COMBI organic amendments improved soil properties, including significant increases in soil water content, CEC, K, Ca, NO3, NH4 and soil carbon content. However, increases in soil nutrient content and improvements in physical properties did not translate to improved fruit yield. Counter to our expectations, banana crop yield (weight per bunch) was reduced by 18%, 12% and 24% by B, C and COMBI additions respectively, and no significant effect was observed on the papaya crop yield. Soil efflux of CO2 was elevated by addition of C and COMBI amendments, likely due to an increase in labile carbon for microbial processing. Our data indicate a reduction in N2O flux in treatments containing biochar. The application of B, C and COMBI amendments had a generally positive effect on soil properties, but this did not translate into a crop productivity increase in this study. The benefits to soil nutrient content, soil carbon storage and N2O emission reduction need to be carefully weighed against potentially deleterious effects on crop yield, at least in the short-term. Copyright © 2016 Elsevier B.V. All rights reserved.

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

NASA Astrophysics Data System (ADS)

Childers, Katelin

2015-04-01

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

7 CFR 760.602 - Definitions.

Code of Federal Regulations, 2014 CFR

2014-01-01

... territory or possession of the United States. Subsequent crop means any crop planted after an initial crop... itself to the greatest level of accuracy, as determined by the FSA State committee. USDA means United... history yield means the average of the actual production history yields for each insurable or noninsurable...

7 CFR 760.602 - Definitions.

Code of Federal Regulations, 2012 CFR

2012-01-01

... territory or possession of the United States. Subsequent crop means any crop planted after an initial crop... itself to the greatest level of accuracy, as determined by the FSA State committee. USDA means United... history yield means the average of the actual production history yields for each insurable or noninsurable...

Crop damage and livestock depredation by wildlife: a case study from Nanda Devi Biosphere Reserve, India.

PubMed

Rao, K S; Maikhuri, R K; Nautiyal, S; Saxena, K G

2002-11-01

The success of conserving biological resources in any Biosphere Reserve or protected area depends on the extent of support and positive attitudes and perceptions of local people have towards such establishments. Ignoring the dependence of the local people for their subsistence needs on resources of such areas leads to conflicts between protected area managers and the local inhabitants. Crop yield losses and livestock depredation were serious problems observed in most buffer zone villages of Nanda Devi Biosphere Reserve. In the present study 10 villages situated in the buffer zone of Nanada Devi Biosphere Reserve (1612 km2 area) in Chamoli district of Uttaranchal, India were studied during 1996-97 using a questionnaire survey of each household (419 = households; 2253 = total population in 1991; 273 ha = cultivated area). Estimates of crop yield losses were made using paired plots technique in four representative villages for each crop species. The magnitude of crop yield losses varied significantly with the distance of agricultural field from forest boundary. The total crop yield losses were high for wheat and potato in all the villages. The spatial distribution of total crop yield losses in any village indicated that they were highest in the area near to forest and least in the area near to village for all crops. Losses from areas near to forest contributed to more than 50% of total losses for each crop in all villages. However, in Lata, Peng and Tolma villages, the losses are high for kidney bean and chemmi (local variety of kidney bean) which varied between 18.5% to 30% of total losses in those villages. Potato alone represents 43.6% of total crop yield loss due to wildlife in Dronagiri village in monetary terms. Among the crops, the monetary value of yield losses are least for amaranth and highest for kidney bean. The projected total value of crop yield losses due to wildlife damage for buffer zone villages located in Garhwal Himalaya is about Rs. 538,620 (US$ 15,389). Besides food grains, horticultural crops i.e. apple, also suffered maximum damage. Major wildlife agents responsible for crop damage were wild boar, bear, porcupine, monkey, musk deer and partridge (chokor). Monkey and wild boar alone accounted for about 50% to 60% of total crop damage in the study villages. Goat and sheep are the major livestock killed by leopard. The total value of livestock losses at prevailing market rates is about Rs. 1,024,520 (US$ 29,272) in the study villages. Due to existing conservation policies and laxity in implementation of preventive measures, the problems for local inhabitants are increasing. Potential solutions discussed emphasize the need to undertake suitable and appropriate protective measures to minimize the crop losses. Change in cropping and crop composition, particularly cultivation of medicinal plants (high value low volume crops), were also suggested. Besides, fair and quick disbursement of compensation for crop loss and livestock killing need to be adopted. Local people of the buffer zone area already have a negative attitude towards park/reserve establishment due to socio-political changes inducing major economic losses and this attitude may lead to clashes and confrontations if proper ameliorative measures are not taken immediately.

Combination of wet irrigation and nitrification inhibitor reduced nitrous oxide and methane emissions from a rice cropping system.

PubMed

Liu, Gang; Yu, Haiyang; Zhang, Guangbin; Xu, Hua; Ma, Jing

2016-09-01

To conserve water resources and guarantee food security, a new technology termed as "wet irrigation" is developed and practiced in rice fields; thus, its impact on radiative forcing derived from nitrous oxide (N2O) and methane (CH4) emissions merits serious attention. Dicyandiamide (DCD), a kind of nitrification inhibitor, is proposed as a viable means to mitigate greenhouse gas (GHG) emission while enhancing crop productivity. However, little is known about the response of GHG emission and grain yield to DCD application in a rice system under wet irrigation. In these regard, effects of water regime and DCD application on CH4 and N2O emissions, grain yield, global warming potential (GWP), and greenhouse gas intensity (GHGI) from rice fields were studied. For this study, a field experiment, designed: Treatment II (intermittent irrigation), Treatment WI (wet irrigation), Treatment IID (II plus DCD), and Treatment WID (WI plus DCD), was conducted in Jurong, Jiangsu Province, China, from 2011 to 2012. Relative to Treatment II, Treatment WI decreased CH4 emission significantly by 49-71 % while increasing N2O emission by 33-72 %. By integrating CH4 and N2O emissions and grain yield, Treatment WI was 20-28 and 11-15 % lower than Treatment II in GWP and GHGI, respectively. The use of DCD under wet irrigation reduced N2O emission significantly by 25-38 % (p < 0.05) and CH4 emission by 7-8 %, relative to Treatment WI, resulting in a decline of 18-30 % in GWP. Due to the increase in N use efficiency, maximal grain yield (6-7 %) and minimal GHGI (22-34 %) was observed in Treatment WID. These findings indicate that combined application of N fertilizer and DCD is a win-win strategy in water-saving high-yield rice production with less GHG emission.

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

NASA Astrophysics Data System (ADS)

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

2009-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Crop yield monitoring in the Sahel using root zone soil moisture anomalies derived from SMOS soil moisture data assimilation

NASA Astrophysics Data System (ADS)

Gibon, François; Pellarin, Thierry; Alhassane, Agali; Traoré, Seydou; Baron, Christian

2017-04-01

West Africa is greatly vulnerable, especially in terms of food sustainability. Mainly based on rainfed agriculture, the high variability of the rainy season strongly impacts the crop production driven by the soil water availability in the soil. To monitor this water availability, classical methods are based on daily precipitation measurements. However, the raingauge network suffers from the poor network density in Africa (1/10000km2). Alternatively, real-time satellite-derived precipitations can be used, but they are known to suffer from large uncertainties which produce significant error on crop yield estimations. The present study proposes to use root soil moisture rather than precipitation to evaluate crop yield variations. First, a local analysis of the spatiotemporal impact of water deficit on millet crop production in Niger was done, from in-situ soil moisture measurements (AMMA-CATCH/OZCAR (French Critical Zone exploration network)) and in-situ millet yield survey. Crop yield measurements were obtained for 10 villages located in the Niamey region from 2005 to 2012. The mean production (over 8 years) is 690 kg/ha, and ranges from 381 to 872 kg/ha during this period. Various statistical relationships based on soil moisture estimates were tested, and the most promising one (R>0.9) linked the 30-cm soil moisture anomalies from mid-August to mid-September (grain filling period) to the crop yield anomalies. Based on this local study, it was proposed to derive regional statistical relationships using 30-cm soil moisture maps over West Africa. The selected approach was to use a simple hydrological model, the Antecedent Precipitation Index (API), forced by real-time satellite-based precipitation (CMORPH, PERSIANN, TRMM3B42). To reduce uncertainties related to the quality of real-time rainfall satellite products, SMOS soil moisture measurements were assimilated into the API model through a Particular Filter algorithm. Then, obtained soil moisture anomalies were compared to 17 years of crop yield estimates from the FAOSTAT database (1998-2014). Results showed that the 30-cm soil moisture anomalies explained 89% of the crop yield variation in Niger, 72% in Burkina Faso, 82% in Mali and 84% in Senegal.

Benefits of supplementing an industrial waste anaerobic digester with energy crops for increased biogas production

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

Nges, Ivo Achu, E-mail: Nges.Ivo_Achu@biotek.lu.se; Escobar, Federico; Fu Xinmei

2012-01-15

Highlights: Black-Right-Pointing-Pointer This study demonstrates the feasibility of co-digestion food industrial waste with energy crops. Black-Right-Pointing-Pointer Laboratory batch co-digestion led to improved methane yield and carbon to nitrogen ratio as compared to mono-digestion of industrial waste. Black-Right-Pointing-Pointer Co-digestion was also seen as a means of degrading energy crops with nutrients addition as crops are poor in nutrients. Black-Right-Pointing-Pointer Batch co-digestion methane yields were used to predict co-digestion methane yield in full scale operation. Black-Right-Pointing-Pointer It was concluded that co-digestion led an over all economically viable process and ensured a constant supply of feedstock. - Abstract: Currently, there is increasing competitionmore » for waste as feedstock for the growing number of biogas plants. This has led to fluctuation in feedstock supply and biogas plants being operated below maximum capacity. The feasibility of supplementing a protein/lipid-rich industrial waste (pig manure, slaughterhouse waste, food processing and poultry waste) mesophilic anaerobic digester with carbohydrate-rich energy crops (hemp, maize and triticale) was therefore studied in laboratory scale batch and continuous stirred tank reactors (CSTR) with a view to scale-up to a commercial biogas process. Co-digesting industrial waste and crops led to significant improvement in methane yield per ton of feedstock and carbon-to-nitrogen ratio as compared to digestion of the industrial waste alone. Biogas production from crops in combination with industrial waste also avoids the need for micronutrients normally required in crop digestion. The batch co-digestion methane yields were used to predict co-digestion methane yield in full scale operation. This was done based on the ratio of methane yields observed for laboratory batch and CSTR experiments compared to full scale CSTR digestion of industrial waste. The economy of crop-based biogas production is limited under Swedish conditions; therefore, adding crops to existing industrial waste digestion could be a viable alternative to ensure a constant/reliable supply of feedstock to the anaerobic digester.« less

Maximizing water use efficiency in designing microirrigation unit (IrriLab Software)

NASA Astrophysics Data System (ADS)

Baiamonte, Giorgio

2016-04-01

As the year 2050 approaches, the world population will reach 9 billion - so does the challenge of doubling crop yields. To meet this crop yields demand, the associated dramatic improving of water productivity (WP) must necessarily be accompanied by maximization of water use efficiency (WUE) (Ragab 2011, UNEP 2014). In this work, a recently developed software (IrriLab, https://www.facebook.com/irrilab) moving in this direction is presented. IrriLab is a very simple toll allows to design microirrigation unit optimizing WUE, pressure energy and irrigation unit costs. Irrigation software available in commerce provide microirrigation system designs, by mainly looking at the maximum flow rate uniformity criteria. Thus, each emitter installed along the laterals operates with an operating pressure head occurring in between an established range of pressure head variability (Dh < Dhadm). However, the latter condition does not always corresponds to the cheapest and to the maximizing WUE solution; in fact, it is not assured if the entire range of the admitted pressure head is profited and used by the emitters. IrriLab allows this occurrence because, for the entire Irrigation Unit Area, IUA, each design solution assures that at least two emitters rigorously operates, one with the minimum admitted pressure head, and the other one with the maximum admitted (Dh = Dhadm), (Baiamonte et al., 2015; Baiamonte, 2016). The same extreme values of pressure head are those that in the common design criteria delimit the range of pressure head, but without assuring their achievement. Compared to the common design criteria, this condition i) for fixed laterals' length and inside diameter, allows reducing the inlet required pressure head whereas, ii) for fixed pressure head at the inlet, provides an increasing in laterals and manifold lengths and in the associated IUA. Based on analytical solutions, IrriLab follows a very simple rectangular sketch, any way oriented in the space, and defined by two slope values, one for the laterals and one for the manifold. By considering the possible combinations of i) horizontal, downward or upward sloped laterals and manifold, ii) the manifold position in respect to the laterals and iii) the inlet position in respect to the manifold, which can be equal to 0%, 24% or 50%, in respect to their lengths (Baiamonte, 2016), IrriLab accounts for 25 optimal irrigation unit layouts, for each of them providing maximum WUE.

Increasing influence of heat stress on French maize yields from the 1960s to the 2030s

PubMed Central

Hawkins, Ed; Fricker, Thomas E; Challinor, Andrew J; Ferro, Christopher A T; Kit Ho, Chun; Osborne, Tom M

2013-01-01

Improved crop yield forecasts could enable more effective adaptation to climate variability and change. Here, we explore how to combine historical observations of crop yields and weather with climate model simulations to produce crop yield projections for decision relevant timescales. Firstly, the effects on historical crop yields of improved technology, precipitation and daily maximum temperatures are modelled empirically, accounting for a nonlinear technology trend and interactions between temperature and precipitation, and applied specifically for a case study of maize in France. The relative importance of precipitation variability for maize yields in France has decreased significantly since the 1960s, likely due to increased irrigation. In addition, heat stress is found to be as important for yield as precipitation since around 2000. A significant reduction in maize yield is found for each day with a maximum temperature above 32 °C, in broad agreement with previous estimates. The recent increase in such hot days has likely contributed to the observed yield stagnation. Furthermore, a general method for producing near-term crop yield projections, based on climate model simulations, is developed and utilized. We use projections of future daily maximum temperatures to assess the likely change in yields due to variations in climate. Importantly, we calibrate the climate model projections using observed data to ensure both reliable temperature mean and daily variability characteristics, and demonstrate that these methods work using retrospective predictions. We conclude that, to offset the projected increased daily maximum temperatures over France, improved technology will need to increase base level yields by 12% to be confident about maintaining current levels of yield for the period 2016–2035; the current rate of yield technology increase is not sufficient to meet this target. PMID:23504849

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

USDA-ARS?s Scientific Manuscript database

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

Independent Peer Evaluation of the Large Area Crop Inventory Experiment (LACIE): The LACIE Symposium

NASA Technical Reports Server (NTRS)

1978-01-01

Yield models and crop estimate accuracy are discussed within the Large Area Crop Inventory Experiment. The wheat yield estimates in the United States, Canada, and U.S.S.R. are emphasized. Experimental results design, system implementation, data processing systems, and applications were considered.

Row and forage crop rotation effects on maize mineral nutrition and yield

USDA-ARS?s Scientific Manuscript database

Extended crop rotations provide many attributes in support of sustainable agriculture. Objectives were to investigate rotations that included row crops and forages in terms of their effects on soil characteristics as well as on maize (Zea mays L.) stover biomass, grain yield, and mineral components...

7 CFR 760.602 - Definitions.

Code of Federal Regulations, 2013 CFR

2013-01-01

... history yield means the average of the actual production history yields for each insurable or noninsurable..., excluding value loss crops, the product obtained by multiplying: (i) 100 percent of the per unit price for... established price for the crop, times (ii) The relevant per unit quantity of the crop produced on the farm...

Climate driven crop planting date in the ACME Land Model (ALM): Impacts on productivity and yield

NASA Astrophysics Data System (ADS)

Drewniak, B.

2017-12-01

Climate is one of the key drivers of crop suitability and productivity in a region. The influence of climate and weather on the growing season determine the amount of time crops spend in each growth phase, which in turn impacts productivity and, more importantly, yields. Planting date can have a strong influence on yields with earlier planting generally resulting in higher yields, a sensitivity that is also present in some crop models. Furthermore, planting date is already changing and may continue, especially if longer growing seasons caused by future climate change drive early (or late) planting decisions. Crop models need an accurate method to predict plant date to allow these models to: 1) capture changes in crop management to adapt to climate change, 2) accurately model the timing of crop phenology, and 3) improve crop simulated influences on carbon, nutrient, energy, and water cycles. Previous studies have used climate as a predictor for planting date. Climate as a plant date predictor has more advantages than fixed plant dates. For example, crop expansion and other changes in land use (e.g., due to changing temperature conditions), can be accommodated without additional model inputs. As such, a new methodology to implement a predictive planting date based on climate inputs is added to the Accelerated Climate Model for Energy (ACME) Land Model (ALM). The model considers two main sources of climate data important for planting: precipitation and temperature. This method expands the current temperature threshold planting trigger and improves the estimated plant date in ALM. Furthermore, the precipitation metric for planting, which synchronizes the crop growing season with the wettest months, allows tropical crops to be introduced to the model. This presentation will demonstrate how the improved model enhances the ability of ALM to capture planting date compared with observations. More importantly, the impact of changing the planting date and introducing tropical crops will be explored. Those impacts include discussions on productivity, yield, and influences on carbon and energy fluxes.

Evaluation of weed control efficacy and crop safety of the new HPPD-inhibiting herbicide-QYR301.

PubMed

Wang, Hengzhi; Liu, Weitang; Zhao, Kongping; Yu, Hui; Zhang, Jia; Wang, Jinxin

2018-05-21

QYR301, 1,3-Dimethyl-1H-pyrazole-4-carboxylic acid 4-[2-chloro-3-(3,5-dimethyl-pyrazol-1-ylmethyl)-4-methanesulfonyl-benzoyl]-2,5-dimethyl-2H-pyrazol-3-yl ester, is a novel HPPD-inhibiting herbicide and was evaluated to provide a reference for post-emergence (POST) application under greenhouse and field conditions. The crop safety (180 and 360 g active ingredient (a.i.) ha -1 treatments) experiment revealed that wheat, paddy, garlic and corn were the only four crops without injury at both examined herbicide rates. The weed control efficacy (60 and 120 g a.i. ha -1 ) experiment showed that QYR301 exhibited high efficacy against many weeds, especially weeds infesting paddy fields. Furthermore, it is interesting that both susceptible and multiple herbicide resistant Echinochloa crus-galli (L.) Beauv. and Echinochloa phyllopogon (Stapf) Koss, two notorious weed species in paddy field, remained susceptible to QYR301. Further crop tolerance results indicated that 20 tested paddy hybrids displayed different levels of tolerance to QYR301, with the japonica paddy hybrids having more tolerance than indica paddy hybrids under greenhouse conditions. Results obtained from field experiments showed that QYR301 POST at 135 to 180 g a.i. ha -1 was recommended to provide satisfactory full-season control of E. crus-galli and Leptochloa chinensis (L.) Nees and to maximize rice yields. These findings indicate that QYR301 possesses great potential for the management of weeds in paddy fields.

Separating out the influence of climatic trend, fluctuations, and extreme events on crop yield: a case study in Hunan Province, China

NASA Astrophysics Data System (ADS)

Wang, Zhu; Shi, Peijun; Zhang, Zhao; Meng, Yongchang; Luan, Yibo; Wang, Jiwei

2017-09-01

Separating out the influence of climatic trend, fluctuations and extreme events on crop yield is of paramount importance to climate change adaptation, resilience, and mitigation. Previous studies lack systematic and explicit assessment of these three fundamental aspects of climate change on crop yield. This research attempts to separate out the impacts on rice yields of climatic trend (linear trend change related to mean value), fluctuations (variability surpassing the "fluctuation threshold" which defined as one standard deviation (1 SD) of the residual between the original data series and the linear trend value for each climatic variable), and extreme events (identified by absolute criterion for each kind of extreme events related to crop yield). The main idea of the research method was to construct climate scenarios combined with crop system simulation model. Comparable climate scenarios were designed to express the impact of each climate change component and, were input to the crop system model (CERES-Rice), which calculated the related simulated yield gap to quantify the percentage impacts of climatic trend, fluctuations, and extreme events. Six Agro-Meteorological Stations (AMS) in Hunan province were selected to study the quantitatively impact of climatic trend, fluctuations and extreme events involving climatic variables (air temperature, precipitation, and sunshine duration) on early rice yield during 1981-2012. The results showed that extreme events were found to have the greatest impact on early rice yield (-2.59 to -15.89%). Followed by climatic fluctuations with a range of -2.60 to -4.46%, and then the climatic trend (4.91-2.12%). Furthermore, the influence of climatic trend on early rice yield presented "trade-offs" among various climate variables and AMS. Climatic trend and extreme events associated with air temperature showed larger effects on early rice yield than other climatic variables, particularly for high-temperature events (-2.11 to -12.99%). Finally, the methodology use to separate out the influences of the climatic trend, fluctuations, and extreme events on crop yield was proved to be feasible and robust. Designing different climate scenarios and feeding them into a crop system model is a potential way to evaluate the quantitative impact of each climate variable.

Effects of input uncertainty on cross-scale crop modeling

NASA Astrophysics Data System (ADS)

Waha, Katharina; Huth, Neil; Carberry, Peter

2014-05-01

The quality of data on climate, soils and agricultural management in the tropics is in general low or data is scarce leading to uncertainty in process-based modeling of cropping systems. Process-based crop models are common tools for simulating crop yields and crop production in climate change impact studies, studies on mitigation and adaptation options or food security studies. Crop modelers are concerned about input data accuracy as this, together with an adequate representation of plant physiology processes and choice of model parameters, are the key factors for a reliable simulation. For example, assuming an error in measurements of air temperature, radiation and precipitation of ± 0.2°C, ± 2 % and ± 3 % respectively, Fodor & Kovacs (2005) estimate that this translates into an uncertainty of 5-7 % in yield and biomass simulations. In our study we seek to answer the following questions: (1) are there important uncertainties in the spatial variability of simulated crop yields on the grid-cell level displayed on maps, (2) are there important uncertainties in the temporal variability of simulated crop yields on the aggregated, national level displayed in time-series, and (3) how does the accuracy of different soil, climate and management information influence the simulated crop yields in two crop models designed for use at different spatial scales? The study will help to determine whether more detailed information improves the simulations and to advise model users on the uncertainty related to input data. We analyse the performance of the point-scale crop model APSIM (Keating et al., 2003) and the global scale crop model LPJmL (Bondeau et al., 2007) with different climate information (monthly and daily) and soil conditions (global soil map and African soil map) under different agricultural management (uniform and variable sowing dates) for the low-input maize-growing areas in Burkina Faso/West Africa. We test the models' response to different levels of input data from very little to very detailed information, and compare the models' abilities to represent the spatial variability and temporal variability in crop yields. We display the uncertainty in crop yield simulations from different input data and crop models in Taylor diagrams which are a graphical summary of the similarity between simulations and observations (Taylor, 2001). The observed spatial variability can be represented well from both models (R=0.6-0.8) but APSIM predicts higher spatial variability than LPJmL due to its sensitivity to soil parameters. Simulations with the same crop model, climate and sowing dates have similar statistics and therefore similar skill to reproduce the observed spatial variability. Soil data is less important for the skill of a crop model to reproduce the observed spatial variability. However, the uncertainty in simulated spatial variability from the two crop models is larger than from input data settings and APSIM is more sensitive to input data then LPJmL. Even with a detailed, point-scale crop model and detailed input data it is difficult to capture the complexity and diversity in maize cropping systems.

Reduce pests, enhance production: benefits of intercropping at high densities for okra farmers in Cameroon.

PubMed

Singh, Akanksha; Weisser, Wolfgang W; Hanna, Rachid; Houmgny, Raissa; Zytynska, Sharon E

2017-10-01

Intercropping can help reduce insect pest populations. However, the results of intercropping can be pest- and crop-species specific, with varying effects on crop yield, and pest suppression success. In Cameroon, okra vegetable is often grown in intercropped fields and sown with large distances between planting rows (∼ 2 m). Dominant okra pests include cotton aphids, leaf beetles and whiteflies. In a field experiment, we intercropped okra with maize and bean in different combinations (okra monoculture, okra-bean, okra-maize and okra-bean-maize) and altered plant densities (high and low) to test for the effects of diversity, crop identity and planting distances on okra pests, their predators and yield. We found crop identity and plant density, but not crop diversity to influence okra pests, their predators and okra yield. Only leaf beetles decreased okra yield and their abundance reduced at high plant density. Overall, okra grown with bean at high density was the most economically profitable combination. We suggest that when okra is grown at higher densities, legumes (e.g. beans) should be included as an additional crop. Intercropping with a leguminous crop can enhance nitrogen in the soil, benefiting other crops, while also being harvested and sold at market for additional profit. Manipulating planting distances and selecting plants based on their beneficial traits may thus help to eliminate yield gaps in sustainable agriculture. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

Weed Diversity Affects Soybean and Maize Yield in a Long Term Experiment in Michigan, USA.

PubMed

Ferrero, Rosana; Lima, Mauricio; Davis, Adam S; Gonzalez-Andujar, Jose L

2017-01-01

Managing production environments in ways that promote weed community diversity may enhance both crop production and the development of a more sustainable agriculture. This study analyzed data of productivity of maize (corn) and soybean in plots in the Main Cropping System Experiment (MCSE) at the W. K. Kellogg Biological Station Long-Term Ecological Research (KBS-LTER) in Michigan, USA, from 1996 to 2011. We used models derived from population ecology to explore how weed diversity, temperature, and precipitation interact with crop yields. Using three types of models that considered internal and external (climate and weeds) factors, with additive or non-linear variants, we found that changes in weed diversity were associated with changes in rates of crop yield increase over time for both maize and soybeans. The intrinsic capacity for soybean yield increase in response to the environment was greater under more diverse weed communities. Soybean production risks were greatest in the least weed diverse systems, in which each weed species lost was associated with progressively greater crop yield losses. Managing for weed community diversity, while suppressing dominant, highly competitive weeds, may be a helpful strategy for supporting long term increases in soybean productivity. In maize, there was a negative and non-additive response of yields to the interaction between weed diversity and minimum air temperatures. When cold temperatures constrained potential maize productivity through limited resources, negative interactions with weed diversity became more pronounced. We suggest that: (1) maize was less competitive in cold years allowing higher weed diversity and the dominance of some weed species; or (2) that cold years resulted in increased weed richness and prevalence of competitive weeds, thus reducing crop yields. Therefore, we propose to control dominant weed species especially in the years of low yield and extreme minimum temperatures to improve maize yields. Results of our study indicate that through the proactive management of weed diversity, it may be possible to promote both high productivity of crops and environmental sustainability.

Weed Diversity Affects Soybean and Maize Yield in a Long Term Experiment in Michigan, USA

PubMed Central

Ferrero, Rosana; Lima, Mauricio; Davis, Adam S.; Gonzalez-Andujar, Jose L.

2017-01-01

Managing production environments in ways that promote weed community diversity may enhance both crop production and the development of a more sustainable agriculture. This study analyzed data of productivity of maize (corn) and soybean in plots in the Main Cropping System Experiment (MCSE) at the W. K. Kellogg Biological Station Long-Term Ecological Research (KBS-LTER) in Michigan, USA, from 1996 to 2011. We used models derived from population ecology to explore how weed diversity, temperature, and precipitation interact with crop yields. Using three types of models that considered internal and external (climate and weeds) factors, with additive or non-linear variants, we found that changes in weed diversity were associated with changes in rates of crop yield increase over time for both maize and soybeans. The intrinsic capacity for soybean yield increase in response to the environment was greater under more diverse weed communities. Soybean production risks were greatest in the least weed diverse systems, in which each weed species lost was associated with progressively greater crop yield losses. Managing for weed community diversity, while suppressing dominant, highly competitive weeds, may be a helpful strategy for supporting long term increases in soybean productivity. In maize, there was a negative and non-additive response of yields to the interaction between weed diversity and minimum air temperatures. When cold temperatures constrained potential maize productivity through limited resources, negative interactions with weed diversity became more pronounced. We suggest that: (1) maize was less competitive in cold years allowing higher weed diversity and the dominance of some weed species; or (2) that cold years resulted in increased weed richness and prevalence of competitive weeds, thus reducing crop yields. Therefore, we propose to control dominant weed species especially in the years of low yield and extreme minimum temperatures to improve maize yields. Results of our study indicate that through the proactive management of weed diversity, it may be possible to promote both high productivity of crops and environmental sustainability. PMID:28286509

Spectral considerations for modeling yield of canola

USDA-ARS?s Scientific Manuscript database

Conspicuous yellow flowers that are present in a Brassica oilseed crop such as canola require careful consideration when selecting a spectral index for yield estimation. This study evaluated spectral indices for multispectral sensors that correlate with the seed yield of Brassica oilseed crops. A ...

Increasing temperature cuts back crop yields in Hungary over the last 90 years.

PubMed

Pinke, Zsolt; Lövei, Gábor L

2017-12-01

The transformation of climatic regime has an undeniable impact on plant production, but we rarely have long enough date series to examine the unfolding of such effects. The clarification of the relationship between crop plants and climate has a near-immediate importance due to the impending human-made global change. This study investigated the relationship between temperature, precipitation, drought intensity and the yields of four major cereals in Hungary between 1921 and 2010. The analysis of 30-year segments indicated a monotonously increasing negative impact of temperature on crop yields. A 1°C temperature increase reduced the yield of the four main cereals by 9.6%-14.8% in 1981-2010, which revealed the vulnerability of Eastern European crop farming to recent climate change. Climate accounted for 17%-39% of yield variability over the past 90 years, but this figure reached 33%-67% between 1981 and 2010. Our analysis supports the claim that the mid-20th century green revolution improved yields "at the mercy of the weather": during this period, the impact of increasing fertilization and mechanisation coincided with climatic conditions that were more favourable than today. Crop yields in Eastern Europe have been stagnating or decreasing since the mid-1980s. Although usually attributed to the large socio-economic changes sweeping the region, our analysis indicates that a warming climate is at least partially responsible for this trend. Such a robust impact of increasing temperatures on crop yields also constitutes an obvious warning for this core grain-growing region of the world. © 2017 John Wiley & Sons Ltd.

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 a positive impact on crop yields for most crops. This positive impact is minimal for corn which is a C4 crop that is already CO2 efficient. The net response is an increase in yields for dryland agriculture and depends on the crop type for irrigated agriculture. Although, climate change results in increased water shortages and water rights curtailment in the region, this does not translate into an increased negative effect on yields. This could be attributed to higher water use efficiency under elevated CO2 levels as well crops getting through growth stages earlier in the season with wetter spring conditions. The non linear and non monotonic nature of the response of climate change on crop yields is discussed. In accounting for biophysical effects of climate change on crop yields, socio-economic effects cannot be ignored because biophysical effects are nested with the framework of human decision making. We also discuss our results in the context of socioeconomic factors . Current results assume no adaptation strategies and incorporating this is our next step.

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

PubMed

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

2018-02-01

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

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

NASA Technical Reports Server (NTRS)

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

2017-01-01

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

Effects of ditch-buried straw return on water percolation, nitrogen leaching and crop yields in a rice-wheat rotation system.

PubMed

Yang, Haishui; Xu, Mingmin; Koide, Roger T; Liu, Qian; Dai, Yajun; Liu, Ling; Bian, Xinmin

2016-03-15

Crop residue management and nitrogen loss are two important environmental problems in the rice-wheat rotation system in China. This study investigated the effects of burial of straw on water percolation, nitrogen loss by leaching, crop growth and yield. Greenhouse mesocosm experiments were conducted over the course of three simulated cropping seasons in a rice1-wheat-rice2 rotation. Greater amounts of straw resulted in more water percolation, irrespective of crop season. Burial at 20 and 35 cm significantly reduced, but burial at 50 cm increased nitrogen leaching. Straw at 500 kg ha(-1) reduced, but at 1000 kg ha(-1) and at 1500 kg ha(-1) straw increased nitrogen leaching in three consecutive crop rotations. In addition, straw at 500 kg ha(-1) buried at 35 cm significantly increased yield and its components for both crops. This study suggests that N losses via leaching from the rice-wheat rotation may be reduced by the burial of the appropriate amount of straw at the appropriate depth. Greater amounts of buried straw, however, may promote nitrogen leaching and negatively affect crop growth and yields. Complementary field experiments must be performed to make specific agronomic recommendations. © 2015 Society of Chemical Industry.

Analyzing and modelling the effect of long-term fertilizer management on crop yield and soil organic carbon in China.

PubMed

Zhang, Jie; Balkovič, Juraj; Azevedo, Ligia B; Skalský, Rastislav; Bouwman, Alexander F; Xu, Guang; Wang, Jinzhou; Xu, Minggang; Yu, Chaoqing

2018-06-15

This study analyzes the influence of various fertilizer management practices on crop yield and soil organic carbon (SOC) based on the long-term field observations and modelling. Data covering 11 years from 8 long-term field trials were included, representing a range of typical soil, climate, and agro-ecosystems in China. The process-based model EPIC (Environmental Policy Integrated Climate model) was used to simulate the response of crop yield and SOC to various fertilization regimes. The results showed that the yield and SOC under additional manure application treatment were the highest while the yield under control treatment was the lowest (30%-50% of NPK yield) at all sites. The SOC in northern sites appeared more dynamic than that in southern sites. The variance partitioning analysis (VPA) showed more variance of crop yield could be explained by the fertilization factor (42%), including synthetic nitrogen (N), phosphorus (P), potassium (K) fertilizers, and fertilizer NPK combined with manure. The interactive influence of soil (total N, P, K, and available N, P, K) and climate factors (mean annual temperature and precipitation) determine the largest part of the SOC variance (32%). EPIC performs well in simulating both the dynamics of crop yield (NRMSE = 32% and 31% for yield calibration and validation) and SOC (NRMSE = 13% and 19% for SOC calibration and validation) under diverse fertilization practices in China. EPIC can assist in predicting the impacts of different fertilization regimes on crop growth and soil carbon dynamics, and contribute to the optimization of fertilizer management for different areas in China. Copyright © 2018. Published by Elsevier B.V.

Management of Lignite Fly Ash for Improving Soil Fertility and Crop Productivity

NASA Astrophysics Data System (ADS)

Ram, Lal C.; Srivastava, Nishant K.; Jha, Sangeet K.; Sinha, Awadhesh K.; Masto, Reginald E.; Selvi, Vetrivel A.

2007-09-01

Lignite fly ash (LFA), being alkaline and endowed with excellent pozzolanic properties, a silt loam texture, and plant nutrients, has the potential to improve soil quality and productivity. Long-term field trials with groundnut, maize, and sun hemp were carried out to study the effect of LFA on growth and yield. Before crop I was sown, LFA was applied at various doses with and without press mud (an organic waste from the sugar industry, used as an amendment and source of nutrients). LFA with and without press mud was also applied before crops III and V were cultivated. Chemical fertilizer, along with gypsum, humic acid, and biofertilizer, was applied in all treatments, including the control. With one-time and repeat applications of LFA (with and without press mud), yield increased significantly (7.0-89.0%) in relation to the control crop. The press mud enhanced the yield (3.0-15.0%) with different LFA applications. The highest yield LFA dose was 200 t/ha for one-time and repeat applications, the maximum yield being with crop III (combination treatment). One-time and repeat application of LFA (alone and in combination with press mud) improved soil quality and the nutrient content of the produce. The highest dose of LFA (200 t/ha) with and without press mud showed the best residual effects (eco-friendly increases in the yield of succeeding crops). Some increase in trace- and heavy-metal contents and in the level of γ-emitters in soil and crop produce, but well within permissible limits, was observed. Thus, LFA can be used on a large scale to boost soil fertility and productivity with no adverse effects on the soil or crops, which may solve the problem of bulk disposal of fly ash in an eco-friendly manner.

The Response of Durum Wheat to the Preceding Crop in a Mediterranean Environment

PubMed Central

Ercoli, Laura; Masoni, Alessandro; Pampana, Silvia; Mariotti, Marco; Arduini, Iduna

2014-01-01

Crop sequence is an important management practice that may affect durum wheat (Triticum durum Desf.) production. Field research was conducted in 2007-2008 and 2008-2009 seasons in a rain-fed cold Mediterranean environment to examine the impact of the preceding crops alfalfa (Medicago sativa L.), maize (Zea mays L.), sunflower (Helianthus annuus L.), and bread wheat (Triticum aestivum L.) on yield and N uptake of four durum wheat varieties. The response of grain yield of durum wheat to the preceding crop was high in 2007-2008 and was absent in the 2008-2009 season, because of the heavy rainfall that negatively impacted establishment, vegetative growth, and grain yield of durum wheat due to waterlogging. In the first season, durum wheat grain yield was highest following alfalfa, and was 33% lower following wheat. The yield increase of durum wheat following alfalfa was mainly due to an increased number of spikes per unit area and number of kernels per spike, while the yield decrease following wheat was mainly due to a reduction of spike number per unit area. Variety growth habit and performance did not affect the response to preceding crop and varieties ranked in the order Levante > Saragolla = Svevo > Normanno. PMID:25401153

Soil ecology and agricultural technology; An integrated approach towards improved soil management for sustainable farming

NASA Astrophysics Data System (ADS)

Pulleman, Mirjam; Pérès, Guénola; Crittenden, Stephen; Heddadj, Djilali; Sukkel, Wijnand

2014-05-01

Intensive arable food production systems are in need of smart solutions that combine ecological knowledge and farm technology to maximize yields while protecting natural resources. The huge diversity of soil organisms and their interactions is of crucial importance for soil functions and ecosystem services, such as organic matter incorporation and break down, nutrient mineralization, soil structure formation, water regulation and disease and pest control. Soil management decisions that take into account the soil biodiversity and associated functions are thus essential to (i) maintain soil productivity in the long term, (ii) reduce the dependency on external inputs and non-renewables such as fossil fuels, and (iii) make agroecosystems more resilient against biotic and abiotic stresses. Organic farming systems and reduced tillage systems are two approaches that aim to increase soil biodiversity and general soil quality, through improved management of organic matter but differ in their emphasis on the use of chemical inputs for crop protection or soil disturbance, respectively. In North-western Europe experience with and knowledge of reduced tillage systems is still scarce, both in conventional and organic farming. Our study targeted both conventional and organic farming and aimed at 1) documenting reduced tillage practices within different agroecological contexts in NW Europe; 2) evaluating the effects of reduced tillage systems on soil biodiversity and soil ecosystem services; 3) increase understanding of agroecological factors that determine trade-offs between different ecosystem services. Earthworm species and nematode taxa were selected as indicator organisms to be studied for their known response to soil management and effects on soil functions. Additionally, soil organic matter, physical soil parameters and processes, and crop yields have been measured across multiple sites. Data have been collected over several cropping seasons in long term field experiments and farmers field sites in France (Brittanny) and the Netherlands (Flevopolder, Hoeksche Waard). The observed diversity in earthworm communities in terms of species, abundance, and trait diversity could be related to soil quality and soil functioning. Data integration across sites allows for the evaluation of the impact of reduced tillage systems on the provision of ecosystem services via proxies such as crop yields, soil organic matter content, aggregate stability and water infiltration. We will present results of this collaborative work to shed light on some of the benefits and trade-offs associated with reduced tillage systems in NW Europe, and in particular on the role of soil organism groups for soil functioning and crop performance. Finally, scope for improvement of soil management based on novel farm technologies and farming system designs will be discussed.

Sugarcane for bioenergy production: an assessment of yield and regulation of sucrose content.

PubMed

Waclawovsky, Alessandro J; Sato, Paloma M; Lembke, Carolina G; Moore, Paul H; Souza, Glaucia M

2010-04-01

An increasing number of plant scientists, including breeders, agronomists, physiologists and molecular biologists, are working towards the development of new and improved energy crops. Research is increasingly focused on how to design crops specifically for bioenergy production and increased biomass generation for biofuel purposes. The most important biofuel to date is bioethanol produced from sugars (sucrose and starch). Second generation bioethanol is also being targeted for studies to allow the use of the cell wall (lignocellulose) as a source of carbon. If a crop is to be used for bioenergy production, the crop should be high yielding, fast growing, low lignin content and requiring relatively small energy inputs for its growth and harvest. Obtaining high yields in nonprime agricultural land is a key for energy crop development to allow sustainability and avoid competition with food production. Sugarcane is the most efficient bioenergy crop of tropical and subtropical regions, and biotechnological tools for the improvement of this crop are advancing rapidly. We focus this review on the studies of sugarcane genes associated with sucrose content, biomass and cell wall metabolism and the preliminary physiological characterization of cultivars that contrast for sugar and biomass yield.

Characterization of coffee (Coffea arabica) husk lignin and degradation products obtained after oxygen and alkali addition

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

de Carvalho Oliveira, Fernanda; Srinivas, Keerthi; Helms, Gregory L.

The full use of biomass in future biorefineries has stimulated studies on utilization of lignin from agricultural crops, such as coffee husk, a major residue from coffee processing. This study focuses on characterizing the lignin obtained from coffee husk and its further wet oxidation products as a function of alkali loading, temperature and residence time. The lignin fraction after diluted acid and alkali pretreatments is composed primarily of p-hydroxylphenyl units (≥ 49%), with fewer guaiacyl and syringyl units. Linkages appear to be mainly β-O-4 ether linkages. Thermal degradation of pretreated lignin occurred in two stages. Carboxylic acids were the mainmore » degradation product. Due to the condensed structure of this lignin, relatively low yields of aromatic aldehydes were achieved, except from conditions with temperatures over 210 °C, 5 min residence time and 11.7wt% NaOH. Optimization of the pretreatment and oxidation parameters are important to maximizing yield of higher-value bioproducts from lignin.« less

Carbon source-sink limitations differ between two species with contrasting growth strategies.

PubMed

Burnett, Angela C; Rogers, Alistair; Rees, Mark; Osborne, Colin P

2016-11-01

Understanding how carbon source and sink strengths limit plant growth is a critical knowledge gap that hinders efforts to maximize crop yield. We investigated how differences in growth rate arise from source-sink limitations, using a model system comparing a fast-growing domesticated annual barley (Hordeum vulgare cv. NFC Tipple) with a slow-growing wild perennial relative (Hordeum bulbosum). Source strength was manipulated by growing plants at sub-ambient and elevated CO 2 concentrations ([CO 2 ]). Limitations on vegetative growth imposed by source and sink were diagnosed by measuring relative growth rate, developmental plasticity, photosynthesis and major carbon and nitrogen metabolite pools. Growth was sink limited in the annual but source limited in the perennial. RGR and carbon acquisition were higher in the annual, but photosynthesis responded weakly to elevated [CO 2 ] indicating that source strength was near maximal at current [CO 2 ]. In contrast, photosynthetic rate and sink development responded strongly to elevated [CO 2 ] in the perennial, indicating significant source limitation. Sink limitation was avoided in the perennial by high sink plasticity: a marked increase in tillering and root:shoot ratio at elevated [CO 2 ], and lower non-structural carbohydrate accumulation. Alleviating sink limitation during vegetative development could be important for maximizing growth of elite cereals under future elevated [CO 2 ]. © 2016 John Wiley & Sons Ltd.

Ensembles modeling approach to study Climate Change impacts on Wheat

NASA Astrophysics Data System (ADS)

Ahmed, Mukhtar; Claudio, Stöckle O.; Nelson, Roger; Higgins, Stewart

2017-04-01

Simulations of crop yield under climate variability are subject to uncertainties, and quantification of such uncertainties is essential for effective use of projected results in adaptation and mitigation strategies. In this study we evaluated the uncertainties related to crop-climate models using five crop growth simulation models (CropSyst, APSIM, DSSAT, STICS and EPIC) and 14 general circulation models (GCMs) for 2 representative concentration pathways (RCP) of atmospheric CO2 (4.5 and 8.5 W m-2) in the Pacific Northwest (PNW), USA. The aim was to assess how different process-based crop models could be used accurately for estimation of winter wheat growth, development and yield. Firstly, all models were calibrated for high rainfall, medium rainfall, low rainfall and irrigated sites in the PNW using 1979-2010 as the baseline period. Response variables were related to farm management and soil properties, and included crop phenology, leaf area index (LAI), biomass and grain yield of winter wheat. All five models were run from 2000 to 2100 using the 14 GCMs and 2 RCPs to evaluate the effect of future climate (rainfall, temperature and CO2) on winter wheat phenology, LAI, biomass, grain yield and harvest index. Simulated time to flowering and maturity was reduced in all models except EPIC with some level of uncertainty. All models generally predicted an increase in biomass and grain yield under elevated CO2 but this effect was more prominent under rainfed conditions than irrigation. However, there was uncertainty in the simulation of crop phenology, biomass and grain yield under 14 GCMs during three prediction periods (2030, 2050 and 2070). We concluded that to improve accuracy and consistency in simulating wheat growth dynamics and yield under a changing climate, a multimodel ensemble approach should be used.

Conservation Agriculture Practices in Rainfed Uplands of India Improve Maize-Based System Productivity and Profitability

PubMed Central

Pradhan, Aliza; Idol, Travis; Roul, Pravat K.

2016-01-01

Traditional agriculture in rainfed uplands of India has been experiencing low agricultural productivity as the lands suffer from poor soil fertility, susceptibility to water erosion and other external pressures of development and climate change. A shift toward more sustainable cropping systems such as conservation agriculture production systems (CAPSs) may help in maintaining soil quality as well as improving crop production and farmer’s net economic benefit. This research assessed the effects over 3 years (2011–2014) of reduced tillage, intercropping, and cover cropping practices customized for maize-based production systems in upland areas of Odisha, India. The study focused on crop yield, system productivity and profitability through maize equivalent yield and dominance analysis. Results showed that maize grain yield did not differ significantly over time or among CAPS treatments while cowpea yield was considered as an additional yield in intercropping systems. Mustard and horsegram grown in plots after maize cowpea intercropping recorded higher grain yields of 25 and 37%, respectively, as compared to those without intercropping. Overall, the full CAPS implementation, i.e., minimum tillage, maize–cowpea intercropping and mustard residue retention had significantly higher system productivity and net benefits than traditional farmer practices, i.e., conventional tillage, sole maize cropping, and no mustard residue retention. The dominance analysis demonstrated increasing benefits of combining conservation practices that exceeded thresholds for farmer adoption. Given the use of familiar crops and technologies and the magnitude of yield and income improvements, these types of CAPS should be acceptable and attractive for smallholder farmers in the area. This in turn should support a move toward sustainable intensification of crop production to meet future household income and nutritional needs. PMID:27471508

Conservation Agriculture Practices in Rainfed Uplands of India Improve Maize-Based System Productivity and Profitability.

PubMed

Pradhan, Aliza; Idol, Travis; Roul, Pravat K

2016-01-01

Traditional agriculture in rainfed uplands of India has been experiencing low agricultural productivity as the lands suffer from poor soil fertility, susceptibility to water erosion and other external pressures of development and climate change. A shift toward more sustainable cropping systems such as conservation agriculture production systems (CAPSs) may help in maintaining soil quality as well as improving crop production and farmer's net economic benefit. This research assessed the effects over 3 years (2011-2014) of reduced tillage, intercropping, and cover cropping practices customized for maize-based production systems in upland areas of Odisha, India. The study focused on crop yield, system productivity and profitability through maize equivalent yield and dominance analysis. Results showed that maize grain yield did not differ significantly over time or among CAPS treatments while cowpea yield was considered as an additional yield in intercropping systems. Mustard and horsegram grown in plots after maize cowpea intercropping recorded higher grain yields of 25 and 37%, respectively, as compared to those without intercropping. Overall, the full CAPS implementation, i.e., minimum tillage, maize-cowpea intercropping and mustard residue retention had significantly higher system productivity and net benefits than traditional farmer practices, i.e., conventional tillage, sole maize cropping, and no mustard residue retention. The dominance analysis demonstrated increasing benefits of combining conservation practices that exceeded thresholds for farmer adoption. Given the use of familiar crops and technologies and the magnitude of yield and income improvements, these types of CAPS should be acceptable and attractive for smallholder farmers in the area. This in turn should support a move toward sustainable intensification of crop production to meet future household income and nutritional needs.

Population dynamics of plant nematodes in cultivated soil: length of rotation in newly cleared and old agricultural land.

PubMed

Good, J M; Murphy, W S; Brodie, B B

1973-04-01

During a 6-year study of 1-, 2-, and 3-year crop rotations, population densities of Pratylenchus brachyurus, Trichodorus christiei, and Meloidogyne incognita were significantly affected by the choice of crops but not by length of crop rotation. The density of P. brachyurus and T. christiei increased rapidly on milo (Sorghum vulgate). In addition, populations of P. brachyurus increased significantly in cropping systems that involved crotalaria (C. rnucronata), millet (Setaria italica), and sudangrass (Sorghum sudanense). Lowest numbers of P. brachyurus occurred where okra (Hibiscus esculentus) was grown or where land was fallow. The largest increase in populations of T. christiei occurred in cropping systems that involved millet, sudangrass, and okra whereas the smallest increase occurred in cropping systems that involved crotalaria or fallow. A winter cover of rye (Secale cereale) had no distinguishable effect on population densities of P. brachyurus or T. christiei. Meloidogyne incognita was detected during the fourth year in both newly cleared and old agricultural land when okra was included in the cropping system. Detectable populations of M. incognita did not develop in any of the other cropping systems. Yields of tomato transplants were higher on the newly cleared land than on the old land. Highest yields were obtained when crotalaria was included in the cropping system. Lowest yields were obtained when milo, or fallow were included in the cropping system. Length of rotation had no distinguishable effect on yields of tomato transplants.

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

PubMed

Hijri, Mohamed

2016-04-01

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

Soybean yield in relation to distance from the Itaipu reservoir

NASA Astrophysics Data System (ADS)

de Faria, Rogério Teixeira; Junior, Ruy Casão; Werner, Simone Silmara; Junior, Luiz Antônio Zanão; Hoogenboom, Gerrit

2016-07-01

Crops close to small water bodies may exhibit changes in yield if the water mass causes significant changes in the microclimate of areas near the reservoir shoreline. The scientific literature describes this effect as occurring gradually, with higher intensity in the sites near the shoreline and decreasing intensity with distance from the reservoir. Experiments with two soybean cultivars were conducted during four crop seasons to evaluate soybean yield in relation to distance from the Itaipu reservoir and determine the effect of air temperature and water availability on soybean crop yield. Fifteen experimental sites were distributed in three transects perpendicular to the Itaipu reservoir, covering an area at approximately 10 km from the shoreline. The yield gradient between the site closest to the reservoir and the sites farther away in each transect did not show a consistent trend, but varied as a function of distance, crop season, and cultivar. This finding indicates that the Itaipu reservoir does not affect the yield of soybean plants grown within approximately 10 km from the shoreline. In addition, the variation in yield among the experimental sites was not attributed to thermal conditions because the temperature was similar within transects. However, the crop water availability was responsible for higher differences in yield among the neighboring experimental sites related to water stress caused by spatial variability in rainfall, especially during the soybean reproductive period in January and February.

Engineering crop nutrient efficiency for sustainable agriculture.

PubMed

Chen, Liyu; Liao, Hong

2017-10-01

Increasing crop yields can provide food, animal feed, bioenergy feedstocks and biomaterials to meet increasing global demand; however, the methods used to increase yield can negatively affect sustainability. For example, application of excess fertilizer can generate and maintain high yields but also increases input costs and contributes to environmental damage through eutrophication, soil acidification and air pollution. Improving crop nutrient efficiency can improve agricultural sustainability by increasing yield while decreasing input costs and harmful environmental effects. Here, we review the mechanisms of nutrient efficiency (primarily for nitrogen, phosphorus, potassium and iron) and breeding strategies for improving this trait, along with the role of regulation of gene expression in enhancing crop nutrient efficiency to increase yields. We focus on the importance of root system architecture to improve nutrient acquisition efficiency, as well as the contributions of mineral translocation, remobilization and metabolic efficiency to nutrient utilization efficiency. © 2017 Institute of Botany, Chinese Academy of Sciences.

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. Copyright © 2016, American Association for the Advancement of Science.

Estimation of Rice Crop Yields Using Random Forests in Taiwan

NASA Astrophysics Data System (ADS)

Chen, C. F.; Lin, H. S.; Nguyen, S. T.; Chen, C. R.

2017-12-01

Rice is globally one of the most important food crops, directly feeding more people than any other crops. Rice is not only the most important commodity, but also plays a critical role in the economy of Taiwan because it provides employment and income for large rural populations. The rice harvested area and production are thus monitored yearly due to the government's initiatives. Agronomic planners need such information for more precise assessment of food production to tackle issues of national food security and policymaking. This study aimed to develop a machine-learning approach using physical parameters to estimate rice crop yields in Taiwan. We processed the data for 2014 cropping seasons, following three main steps: (1) data pre-processing to construct input layers, including soil types and weather parameters (e.g., maxima and minima air temperature, precipitation, and solar radiation) obtained from meteorological stations across the country; (2) crop yield estimation using the random forests owing to its merits as it can process thousands of variables, estimate missing data, maintain the accuracy level when a large proportion of the data is missing, overcome most of over-fitting problems, and run fast and efficiently when handling large datasets; and (3) error verification. To execute the model, we separated the datasets into two groups of pixels: group-1 (70% of pixels) for training the model and group-2 (30% of pixels) for testing the model. Once the model is trained to produce small and stable out-of-bag error (i.e., the mean squared error between predicted and actual values), it can be used for estimating rice yields of cropping seasons. The results obtained from the random forests-based regression were compared with the actual yield statistics indicated the values of root mean square error (RMSE) and mean absolute error (MAE) achieved for the first rice crop were respectively 6.2% and 2.7%, while those for the second rice crop were 5.3% and 2.9%, respectively. Although there are several uncertainties attributed to the data quality of input layers, our study demonstrates the promising application of random forests for estimating rice crop yields at the national level in Taiwan. This approach could be transferable to other regions of the world for improving large-scale estimation of rice crop yields.

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

PubMed

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

2015-07-01

Crop yield, vegetative or reproductive, depends on access to an adequate supply of essential mineral nutrients. At the same time, a crop plant's growth and development, and thus yield, also depend on in situ production of plant hormones. Thus optimizing mineral nutrition and providing supplemental hormones are two mechanisms for gaining appreciable yield increases. Optimizing the mineral nutrient supply is a common and accepted agricultural practice, but the co-application of nitrogen-based fertilizers with plant hormones or plant growth regulators is relatively uncommon. Our review discusses possible uses of plant hormones (gibberellins, auxins, cytokinins, abscisic acid and ethylene) and specific growth regulators (glycine betaine and polyamines) to enhance and optimize crop yield when co-applied with nitrogen-based fertilizers. We conclude that use of growth-active gibberellins, together with a nitrogen-based fertilizer, can result in appreciable and significant additive increases in shoot dry biomass of crops, including forage crops growing under low-temperature conditions. There may also be a potential for use of an auxin or cytokinin, together with a nitrogen-based fertilizer, for obtaining additive increases in dry shoot biomass and/or reproductive yield. Further research, though, is needed to determine the potential of co-application of nitrogen-based fertilizers with abscisic acid, ethylene and other growth regulators. © 2014 Society of Chemical Industry.

Assessment of crop yield losses in Punjab and Haryana using two years of continuous in-situ ozone measurements

NASA Astrophysics Data System (ADS)

Sinha, B.; Singh Sangwan, K.; Maurya, Y.; Kumar, V.; Sarkar, C.; Chandra, B. P.; Sinha, V.

2015-01-01

In this study we use a high quality dataset of in-situ ozone measurements at a suburban site called Mohali in the state of Punjab to estimate ozone related crop yield losses for wheat, rice, cotton and maize for Punjab and the neighbouring state Haryana for the years 2011-2013. We inter-compare crop yield loss estimates according to different exposure metrics such as AOT40 and M7 for the two major crop growing seasons of Kharif (June-October) and Rabi (November-April) and establish a new crop yield exposure relationship for South Asian wheat and rice cultivars. These are a factor of two more sensitive to ozone induced crop yield losses compared to their European and American counterparts. Relative yield losses based on the AOT40 metrics ranged from 27-41% for wheat, 21-26% for rice, 9-11% for maize and 47-58% for cotton. Crop production losses for wheat amounted to 20.8 million t in fiscal year 2012-2013 and 10.3 million t in fiscal year 2013-2014 for Punjab and Haryana jointly. Crop production losses for rice totalled 5.4 million t in fiscal year 2012-2013 and 3.2 million t year 2013-2014 for Punjab and Haryana jointly. The Indian National Food Security Ordinance entitles ~ 820 million of India's poor to purchase about 60 kg of rice/wheat per person annually at subsidized rates. The scheme requires 27.6 Mt of wheat and 33.6 Mt of rice per year. Mitigation of ozone related crop production losses in Punjab and Haryana alone could provide >50% of the wheat and ~10% of the rice required for the scheme. The total economic cost losses in Punjab and Haryana amounted to USD 6.5 billion in the fiscal year 2012-2013 and USD 3.7 billion in the fiscal year 2013-2014. This economic loss estimate represents a very conservative lower limit based on the minimum support price of the crop, which is lower than the actual production costs. The upper limit for ozone related crop yield losses in entire India currently amounts to 3.5-20% of India's GDP. Mitigation of high surface ozone would require relatively little investment in comparison to economic losses incurred presently. Therefore, ozone mitigation can yield massive benefits in terms of ensuring food security and boosting the economy. Co-benefits of ozone mitigation also include a decrease in the ozone related mortality, morbidity and a reduction of the ozone induced warming in the lower troposphere.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

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's ability to represent the seasonal GPP, TER and NEE fluxes using observations at 6 European FluxNet winter wheat and grain maize sites and compare it with the fluxes of the current terrestrial carbon cycle model of CarbonTracker Europe: the Simple Biosphere - Carnegie-Ames-Stanford Approach (SiBCASA) model. We find that the new model framework provides a detailed, realistic, and strongly observation-driven estimate of carbon exchange over European croplands. Its products will be made available to the scientific community through the ICOS Carbon Portal, and serve as a new cropland component in CarbonTracker Europe flux estimates.

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

USDA-ARS?s Scientific Manuscript database

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...

Long-term conventional and no-tillage effects on field hydrology and yields of a dryland crop rotation

USDA-ARS?s Scientific Manuscript database

Semiarid dryland crop yields with no-till, NT, residue management are often greater than stubble-mulch, SM, tillage as a result of improved soil conditions and water conservation, but information on long-term tillage effects on field hydrology and sustained crop production are needed. Our objective ...

Simulated vs. empirical weather responsiveness of crop yields: US evidence and implications for the agricultural impacts of climate change

DOE PAGES

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

2017-07-10

Global gridded crop models (GGCMs) are the workhorse of assessments of the agricultural impacts of climate change. Yet the changes in crop yields projected by different models in response to the same meteorological forcing can differ substantially. Through an inter-method comparison, we provide a first glimpse into the origins and implications of this divergence—both among GGCMs and between GGCMs and historical observations. We examine yields of rainfed maize, wheat, and soybeans simulated by six GGCMs as part of the Inter-Sectoral Impact Model Intercomparison Project-Fast Track (ISIMIP-FT) exercise, comparing 1981–2004 hindcast yields over the coterminous United States (US) against US Departmentmore » of Agriculture (USDA) time series for about 1000 counties. Leveraging the empirical climate change impacts literature, we estimate reduced-form econometric models of crop yield responses to temperature and precipitation exposures for both GGCMs and observations. We find that up to 60% of the variance in both simulated and observed yields is attributable to weather variation. A majority of the GGCMs have difficulty reproducing the observed distribution of percentage yield anomalies, and exhibit aggregate responses that show yields to be more weather-sensitive than in the observational record over the predominant range of temperature and precipitation conditions. In conclusion, this disparity is largely attributable to heterogeneity in GGCMs' responses, as opposed to uncertainty in historical weather forcings, and is responsible for widely divergent impacts of climate on future crop yields.« less

Simulated vs. empirical weather responsiveness of crop yields: US evidence and implications for the agricultural impacts of climate change

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

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

Global gridded crop models (GGCMs) are the workhorse of assessments of the agricultural impacts of climate change. Yet the changes in crop yields projected by different models in response to the same meteorological forcing can differ substantially. Through an inter-method comparison, we provide a first glimpse into the origins and implications of this divergence—both among GGCMs and between GGCMs and historical observations. We examine yields of rainfed maize, wheat, and soybeans simulated by six GGCMs as part of the Inter-Sectoral Impact Model Intercomparison Project-Fast Track (ISIMIP-FT) exercise, comparing 1981–2004 hindcast yields over the coterminous United States (US) against US Departmentmore » of Agriculture (USDA) time series for about 1000 counties. Leveraging the empirical climate change impacts literature, we estimate reduced-form econometric models of crop yield responses to temperature and precipitation exposures for both GGCMs and observations. We find that up to 60% of the variance in both simulated and observed yields is attributable to weather variation. A majority of the GGCMs have difficulty reproducing the observed distribution of percentage yield anomalies, and exhibit aggregate responses that show yields to be more weather-sensitive than in the observational record over the predominant range of temperature and precipitation conditions. In conclusion, this disparity is largely attributable to heterogeneity in GGCMs' responses, as opposed to uncertainty in historical weather forcings, and is responsible for widely divergent impacts of climate on future crop yields.« less

Simulated vs. empirical weather responsiveness of crop yields: US evidence and implications for the agricultural impacts of climate change

NASA Astrophysics Data System (ADS)

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

2017-07-01

Global gridded crop models (GGCMs) are the workhorse of assessments of the agricultural impacts of climate change. Yet the changes in crop yields projected by different models in response to the same meteorological forcing can differ substantially. Through an inter-method comparison, we provide a first glimpse into the origins and implications of this divergence—both among GGCMs and between GGCMs and historical observations. We examine yields of rainfed maize, wheat, and soybeans simulated by six GGCMs as part of the Inter-Sectoral Impact Model Intercomparison Project-Fast Track (ISIMIP-FT) exercise, comparing 1981-2004 hindcast yields over the coterminous United States (US) against US Department of Agriculture (USDA) time series for about 1000 counties. Leveraging the empirical climate change impacts literature, we estimate reduced-form econometric models of crop yield responses to temperature and precipitation exposures for both GGCMs and observations. We find that up to 60% of the variance in both simulated and observed yields is attributable to weather variation. A majority of the GGCMs have difficulty reproducing the observed distribution of percentage yield anomalies, and exhibit aggregate responses that show yields to be more weather-sensitive than in the observational record over the predominant range of temperature and precipitation conditions. This disparity is largely attributable to heterogeneity in GGCMs’ responses, as opposed to uncertainty in historical weather forcings, and is responsible for widely divergent impacts of climate on future crop yields.

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

DOE Data Explorer

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

2016-07-13

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

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

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

Davis, Maggie R.; Hellwinkel, Chad; Eaton, Laurence

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

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

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

NASA Astrophysics Data System (ADS)

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

2016-11-01

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

An economic assessment of the health effects and crop yield losses caused by air pollution in mainland China.

PubMed

Miao, Weijie; Huang, Xin; Song, Yu

2017-06-01

Air pollution is severe in China, and pollutants such as PM 2.5 and surface O 3 may cause major damage to human health and crops, respectively. Few studies have considered the health effects of PM 2.5 or the loss of crop yields due to surface O 3 using model-simulated air pollution data in China. We used gridded outputs from the WRF-Chem model, high resolution population data, and crop yield data to evaluate the effects on human health and crop yield in mainland China. Our results showed that outdoor PM 2.5 pollution was responsible for 1.70-1.99 million cases of all-cause mortality in 2006. The economic costs of these health effects were estimated to be 151.1-176.9 billion USD, of which 90% were attributed to mortality. The estimated crop yield losses for wheat, rice, maize, and soybean were approximately 9, 4.6, 0.44, and 0.34 million tons, respectively, resulting in economic losses of 3.4 billion USD. The total economic losses due to ambient air pollution were estimated to be 154.5-180.3 billion USD, accounting for approximately 5.7%-6.6% of the total GDP of China in 2006. Our results show that both population health and staple crop yields in China have been significantly affected by exposure to air pollution. Measures should be taken to reduce emissions, improve air quality, and mitigate the economic loss. Copyright © 2016. Published by Elsevier B.V.

A generic hydroeconomic model to assess future water scarcity

NASA Astrophysics Data System (ADS)

Neverre, Noémie; Dumas, Patrice

2015-04-01

We developed a generic hydroeconomic model able to confront future water supply and demand on a large scale, taking into account man-made reservoirs. The assessment is done at the scale of river basins, using only globally available data; the methodology can thus be generalized. On the supply side, we evaluate the impacts of climate change on water resources. The available quantity of water at each site is computed using the following information: runoff is taken from the outputs of CNRM climate model (Dubois et al., 2010), reservoirs are located using Aquastat, and the sub-basin flow-accumulation area of each reservoir is determined based on a Digital Elevation Model (HYDRO1k). On the demand side, agricultural and domestic demands are projected in terms of both quantity and economic value. For the agricultural sector, globally available data on irrigated areas and crops are combined in order to determine irrigated crops localization. Then, crops irrigation requirements are computed for the different stages of the growing season using Allen (1998) method with Hargreaves potential evapotranspiration. Irrigation water economic value is based on a yield comparison approach between rainfed and irrigated crops. Potential irrigated and rainfed yields are taken from LPJmL (Blondeau et al., 2007), or from FAOSTAT by making simple assumptions on yield ratios. For the domestic sector, we project the combined effects of demographic growth, economic development and water cost evolution on future demands. The method consists in building three-blocks inverse demand functions where volume limits of the blocks evolve with the level of GDP per capita. The value of water along the demand curve is determined from price-elasticity, price and demand data from the literature, using the point-expansion method, and from water costs data. Then projected demands are confronted to future water availability. Operating rules of the reservoirs and water allocation between demands are based on the maximization of water benefits, over time and space. A parameterisation-simulation-optimisation approach is used. This gives a projection of future water scarcity in the different locations and an estimation of the associated direct economic losses from unsatisfied demands. This generic hydroeconomic model can be easily applied to large-scale regions, in particular developing regions where little reliable data is available. We will present an application to Algeria, up to the 2050 horizon.

7 CFR 1437.3 - Definitions.

Code of Federal Regulations, 2011 CFR

2011-01-01

... (including ornamental fish), and floriculture, an environment in which everything that can practicably be..., as determined by CCC. Good farming practices means the cultural practices generally used for the crop... good farming practices. T-Yield means the yield which is based on the county expected yield of the crop...

Relationship between cotton yield and soil electrical conductivity, topography, and landsat imagery

USDA-ARS?s Scientific Manuscript database

Understanding spatial and temporal variability in crop yield is a prerequisite to implementing site-specific management of crop inputs. Apparent soil electrical conductivity (ECa), soil brightness, and topography are easily obtained data that can explain yield variability. The objectives of this stu...

7 CFR 1437.102 - Yield determinations.

Code of Federal Regulations, 2014 CFR

2014-01-01

... Determining Yield Coverage Using Actual Production History § 1437.102 Yield determinations. (a) An actual... used in the actual production history base period when less than four consecutive crop years of actual... calculated, in the actual production history base period when the producer reports acreage for the crop but...

7 CFR 1437.102 - Yield determinations.

Code of Federal Regulations, 2011 CFR

2011-01-01

... Determining Yield Coverage Using Actual Production History § 1437.102 Yield determinations. (a) An actual... used in the actual production history base period when less than four consecutive crop years of actual... calculated, in the actual production history base period when the producer reports acreage for the crop but...

7 CFR 1437.102 - Yield determinations.

Code of Federal Regulations, 2010 CFR

2010-01-01

... Determining Yield Coverage Using Actual Production History § 1437.102 Yield determinations. (a) An actual... used in the actual production history base period when less than four consecutive crop years of actual... calculated, in the actual production history base period when the producer reports acreage for the crop but...

Linear unmixing of multidate hyperspectral imagery for crop yield estimation

USDA-ARS?s Scientific Manuscript database

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 ...

Crop Diversity for Yield Increase

PubMed Central

Li, Chengyun; He, Xiahong; Zhu, Shusheng; Zhou, Huiping; Wang, Yunyue; Li, Yan; Yang, Jing; Fan, Jinxiang; Yang, Jincheng; Wang, Guibin; Long, Yunfu; Xu, Jiayou; Tang, Yongsheng; Zhao, Gaohui; Yang, Jianrong; Liu, Lin; Sun, Yan; Xie, Yong; Wang, Haining; Zhu, Youyong

2009-01-01

Traditional farming practices suggest that cultivation of a mixture of crop species in the same field through temporal and spatial management may be advantageous in boosting yields and preventing disease, but evidence from large-scale field testing is limited. Increasing crop diversity through intercropping addresses the problem of increasing land utilization and crop productivity. In collaboration with farmers and extension personnel, we tested intercropping of tobacco, maize, sugarcane, potato, wheat and broad bean – either by relay cropping or by mixing crop species based on differences in their heights, and practiced these patterns on 15,302 hectares in ten counties in Yunnan Province, China. The results of observation plots within these areas showed that some combinations increased crop yields for the same season between 33.2 and 84.7% and reached a land equivalent ratio (LER) of between 1.31 and 1.84. This approach can be easily applied in developing countries, which is crucial in face of dwindling arable land and increasing food demand. PMID:19956624

A meteorologically-driven yield reduction model for spring and winter wheat

NASA Technical Reports Server (NTRS)

Ravet, F. W.; Cremins, W. J.; Taylor, T. W.; Ashburn, P.; Smika, D.; Aaronson, A. (Principal Investigator)

1983-01-01

A yield reduction model for spring and winter wheat was developed for large-area crop condition assessment. Reductions are expressed in percentage from a base yield and are calculated on a daily basis. The algorithm contains two integral components: a two-layer soil water budget model and a crop calendar routine. Yield reductions associated with hot, dry winds (Sukhovey) and soil moisture stress are determined. Input variables include evapotranspiration, maximum temperature and precipitation; subsequently crop-stage, available water holding percentage and stress duration are evaluated. No specific base yield is required and may be selected by the user; however, it may be generally characterized as the maximum likely to be produced commercially at a location.

Effect of chemical and mechanical weed control on cassava yield, soil quality and erosion under cassava cropping system

NASA Astrophysics Data System (ADS)

Islami, Titiek; Wisnubroto, Erwin; Utomo, Wani

2016-04-01

Three years field experiments were conducted to study the effect of chemical and mechanical weed control on soil quality and erosion under cassava cropping system. The experiment were conducted at University Brawijaya field experimental station, Jatikerto, Malang, Indonesia. The experiments were carried out from 2011 - 2014. The treatments consist of three cropping system (cassava mono culture; cassava + maize intercropping and cassava + peanut intercropping), and two weed control method (chemical and mechanical methods). The experimental result showed that the yield of cassava first year and second year did not influenced by weed control method and cropping system. However, the third year yield of cassava was influence by weed control method and cropping system. The cassava yield planted in cassava + maize intercropping system with chemical weed control methods was only 24 t/ha, which lower compared to other treatments, even with that of the same cropping system used mechanical weed control. The highest cassava yield in third year was obtained by cassava + peanuts cropping system with mechanical weed control method. After three years experiment, the soil of cassava monoculture system with chemical weed control method possessed the lowest soil organic matter, and soil aggregate stability. During three years of cropping soil erosion in chemical weed control method, especially on cassava monoculture, was higher compared to mechanical weed control method. The soil loss from chemical control method were 40 t/ha, 44 t/ha and 54 t/ha for the first, second and third year crop. The soil loss from mechanical weed control method for the same years was: 36 t/ha, 36 t/ha and 38 t/ha. Key words: herbicide, intercropping, soil organic matter, aggregate stability.

Assessing the impacts of current and future concentrations of surface ozone on crop yield with meta-analysis

NASA Astrophysics Data System (ADS)

Feng, Zhaozhong; Kobayashi, Kazuhiko

Meta-analysis was conducted to quantitatively assess the effects of rising ozone concentrations ([O 3]) on yield and yield components of major food crops: potato, barley, wheat, rice, bean and soybean in 406 experimental observations. Yield loss of the crops under current and future [O 3] was expressed relative to the yield under base [O 3] (≤26 ppb). With potato, current [O 3] (31-50 ppb) reduced the yield by 5.3%, and it reduced the yield of barley, wheat and rice by 8.9%, 9.7% and 17.5%, respectively. In bean and soybean, the yield losses were 19.0% and 7.7%, respectively. Compared with yield loss at current [O 3], future [O 3] (51-75 ppb) drove a further 10% loss in yield of soybean, wheat and rice, and 20% loss in bean. Mass of individual grain, seed, or tuber was often the major cause of the yield loss at current and future [O 3], whereas other yield components also contributed to the yield loss in some cases. No significant difference was found between the responses in crops grown in pots and those in the ground for any yield parameters. The ameliorating effect of elevated [CO 2] was significant in the yields of wheat and potato, and the individual grain weight in wheat exposed to future [O 3]. These findings confirm the rising [O 3] as a threat to food security for the growing global population in this century.

Pesticides reduce symbiotic efficiency of nitrogen-fixing rhizobia and host plants

PubMed Central

Fox, Jennifer E.; Gulledge, Jay; Engelhaupt, Erika; Burow, Matthew E.; McLachlan, John A.

2007-01-01

Unprecedented agricultural intensification and increased crop yield will be necessary to feed the burgeoning world population, whose global food demand is projected to double in the next 50 years. Although grain production has doubled in the past four decades, largely because of the widespread use of synthetic nitrogenous fertilizers, pesticides, and irrigation promoted by the “Green Revolution,” this rate of increased agricultural output is unsustainable because of declining crop yields and environmental impacts of modern agricultural practices. The last 20 years have seen diminishing returns in crop yield in response to increased application of fertilizers, which cannot be completely explained by current ecological models. A common strategy to reduce dependence on nitrogenous fertilizers is the production of leguminous crops, which fix atmospheric nitrogen via symbiosis with nitrogen-fixing rhizobia bacteria, in rotation with nonleguminous crops. Here we show previously undescribed in vivo evidence that a subset of organochlorine pesticides, agrichemicals, and environmental contaminants induces a symbiotic phenotype of inhibited or delayed recruitment of rhizobia bacteria to host plant roots, fewer root nodules produced, lower rates of nitrogenase activity, and a reduction in overall plant yield at time of harvest. The environmental consequences of synthetic chemicals compromising symbiotic nitrogen fixation are increased dependence on synthetic nitrogenous fertilizer, reduced soil fertility, and unsustainable long-term crop yields. PMID:17548832

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.

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

PubMed

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

2014-08-01

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

Modeling global yield growth of major crops under multiple socioeconomic pathways

NASA Astrophysics Data System (ADS)

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

2016-12-01

Global gridded crop models (GGCMs) are a key tool in deriving global food security scenarios under climate change. However, it is difficult for GGCMs to reproduce the reported yield growth patterns—rapid growth, yield stagnation and yield collapse. Here, we propose a set of parameterizations for GGCMs to capture the contributions to yield from technological improvements at the national and multi-decadal scales. These include country annual per capita gross domestic product (GDP)-based parameterizations for the nitrogen application rate and crop tolerance to stresses associated with high temperature, low temperature, water deficit and water excess. Using a GGCM combined with the parameterizations, we present global 140-year (1961-2100) yield growth simulations for maize, soybean, rice and wheat under multiple shared socioeconomic pathways (SSPs) and no climate change. The model reproduces the major characteristics of reported global and country yield growth patterns over the 1961-2013 period. Under the most rapid developmental pathway SSP5, the simulated global yields for 2091-2100, relative to 2001-2010, are the highest (1.21-1.82 times as high, with variations across the crops), followed by SSP1 (1.14-1.56 times as high), SSP2 (1.12-1.49 times as high), SSP4 (1.08-1.38 times as high) and SSP3 (1.08-1.36 times as high). Future country yield growth varies substantially by income level as well as by crop and by SSP. These yield pathways offer a new baseline for addressing the interdisciplinary questions related to global agricultural development, food security and climate change.

Estimating variability in grain legume yields across Europe and the Americas

NASA Astrophysics Data System (ADS)

Cernay, Charles; Ben-Ari, Tamara; Pelzer, Elise; Meynard, Jean-Marc; Makowski, David

2015-06-01

Grain legume production in Europe has recently come under scrutiny. Although legume crops are often promoted to provide environmental services, European farmers tend to turn to non-legume crops. It is assumed that high variability in legume yields explains this aversion, but so far this hypothesis has not been tested. Here, we estimate the variability of major grain legume and non-legume yields in Europe and the Americas from yield time series over 1961-2013. Results show that grain legume yields are significantly more variable than non-legume yields in Europe. These differences are smaller in the Americas. Our results are robust at the level of the statistical methods. In all regions, crops with high yield variability are allocated to less than 1% of cultivated areas. Although the expansion of grain legumes in Europe may be hindered by high yield variability, some species display risk levels compatible with the development of specialized supply chains.

Managing Nitrogen in the anthropocene: integrating social and ecological science

NASA Astrophysics Data System (ADS)

Zhang, X.; Mauzerall, D. L.; Davidson, E. A.; Kanter, D.; Cai, R.; Searchinger, T.

2014-12-01

Human alteration of the global nitrogen cycle by agricultural activities has provided nutritious food to society, but also poses increasing threats to human and ecosystem health through unintended pollution. Managing nitrogen more efficiently in crop production is critical for addressing both food security and environmental challenges. Technologies and management practices have been developed to increase the uptake of applied nitrogen by crops. However, nitrogen use efficiency (NUE, yield per unit nitrogen input) is also affected by social and economic factors. For example, to maximize profit, farmers may change crop choice or their nitrogen application rate, both of which lead to a change in NUE. To evaluate such impacts, we use both theoretical and empirical approaches on micro (farm) and macro (national) scales: 1) We developed a bio-economic model (NUE3) on a farm scale to investigate how market signals (e.g. fertilizer and crop prices), government policies, and nitrogen-efficient technologies affect NUE. We demonstrate that if factors that influence nitrogen inputs (e.g. fertilizer-to-crop price ratios) are not considered, NUE projections will be poorly constrained. The impact of nitrogen-efficient technologies on NUE not only depends on how technology changes the production function, but also relies on the prices of the technologies, fertilizers, and crops. 2) We constructed a database of the nitrogen budget in crop production for major crops and major crop producing countries from 1961 to 2010. Using this database, we investigate historical trends of NUE and its relationship to agronomic, economic, social, and policy factors. We find that NUE in most developed countries follows a "U-shape" relationship with income level, consistent with the Environmental Kuznets Curve theory. According to the dynamics revealed in the NUE3 model, we propose three major pathways by which economic development affects NUE, namely consumption, technology, and public policy. Overall, our research suggests that it is critical to include social and economic processes when studying perturbations of the global nitrogen cycle and crafting environmental and food security policy. Better collaboration across disciplines is essential to improve nitrogen management in the anthropocene.

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

Impacts of multiple global environmental changes on African crop yield and water use efficiency: Implications to food and water security

NASA Astrophysics Data System (ADS)

Pan, S.; Yang, J.; Zhang, J.; Xu, R.; Dangal, S. R. S.; Zhang, B.; Tian, H.

2016-12-01

Africa is one of the most vulnerable regions in the world to climate change and climate variability. Much concern has been raised about the impacts of climate and other environmental factors on water resource and food security through the climate-water-food nexus. Understanding the responses of crop yield and water use efficiency to environmental changes is particularly important because Africa is well known for widespread poverty, slow economic growth and agricultural systems particularly sensitive to frequent and persistent droughts. However, the lack of integrated understanding has limited our ability to quantify and predict the potential of Africa's agricultural sustainability and freshwater supply, and to better manage the system for meeting an increasing food demand in a way that is socially and environmentally or ecologically sustainable. By using the Dynamic Land Ecosystem Model (DLEM-AG2) driven by spatially-explicit information on land use, climate and other environmental changes, we have assessed the spatial and temporal patterns of crop yield, evapotranspiration (ET) and water use efficiency across entire Africa in the past 35 years (1980-2015) and the rest of the 21st century (2016-2099). Our preliminary results indicate that African crop yield in the past three decades shows an increasing trend primarily due to cropland expansion (about 50%), elevated atmospheric CO2 concentration, and nitrogen deposition. However, crop yield shows substantially spatial and temporal variation due to inter-annual and inter-decadal climate variability and spatial heterogeneity of environmental drivers. Climate extremes especially droughts and heat wave have largely reduced crop yield in the most vulnerable regions. Our results indicate that N fertilizer could be a major driver to improve food security in Africa. Future climate warming could reduce crop yield and shift cropland distribution. Our study further suggests that improving water use efficiency through land management practices including the increased uses of fertilizers and irrigation will be the key for reducing the loss of crop yield in a warming climate and extreme weather.

Targeting carbon for crop yield and drought resilience

PubMed Central

Griffiths, Cara A

2017-01-01

Abstract Current methods of crop improvement are not keeping pace with projected increases in population growth. Breeding, focused around key traits of stem height and disease resistance, delivered the step‐change yield improvements of the green revolution of the 1960s. However, subsequently, yield increases through conventional breeding have been below the projected requirement of 2.4% per year required by 2050. Genetic modification (GM) mainly for herbicide tolerance and insect resistance has been transformational, akin to a second green revolution, although GM has yet to make major inroads into intrinsic yield processes themselves. Drought imposes the major restriction on crop yields globally but, as yet, has not benefited substantially from genetic improvement and still presents a major challenge to agriculture. Much still has to be learnt about the complex process of how drought limits yield and what should be targeted. Mechanisms of drought adaptation from the natural environment cannot be taken into crops without significant modification for the agricultural environment because mechanisms of drought tolerance are often in contrast with mechanisms of high productivity required in agriculture. However, through convergence of fundamental and translational science, it would appear that a mechanism of sucrose allocation in crops can be modified for both productivity and resilience to drought and other stresses. Recent publications show how this mechanism can be targeted by GM, natural variation and a new chemical approach. Here, with an emphasis on drought, we highlight how understanding fundamental science about how crops grow, develop and what limits their growth and yield can be combined with targeted genetic selection and pioneering chemical intervention technology for transformational yield improvements. © 2017 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry. PMID:28653336

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

Xiong, Wei; Balkovic, Juraj; van der Velde, M.

Crop models are increasingly used to assess impacts of climate change/variability and management practices on productivity and environmental performance of alternative cropping systems. Calibration is an important procedure to improve reliability of model simulations, especially for large area applications. However, global-scale crop model calibration has rarely been exercised due to limited data availability and expensive computing cost. Here we present a simple approach to calibrate Environmental Policy Integrated Climate (EPIC) model for a global implementation of rice. We identify four parameters (potential heat unit – PHU, planting density – PD, harvest index – HI, and biomass energy ratio – BER)more » and calibrate them regionally to capture the spatial pattern of reported rice yield in 2000. Model performance is assessed by comparing simulated outputs with independent FAO national data. The comparison demonstrates that the global calibration scheme performs satisfactorily in reproducing the spatial pattern of rice yield, particularly in main rice production areas. Spatial agreement increases substantially when more parameters are selected and calibrated, but with varying efficiencies. Among the parameters, PHU and HI exhibit the highest efficiencies in increasing the spatial agreement. Simulations with different calibration strategies generate a pronounced discrepancy of 5–35% in mean yields across latitude bands, and a small to moderate difference in estimated yield variability and yield changing trend for the period of 1981–2000. Present calibration has little effects in improving simulated yield variability and trends at both regional and global levels, suggesting further works are needed to reproduce temporal variability of reported yields. This study highlights the importance of crop models’ calibration, and presents the possibility of a transparent and consistent up scaling approach for global crop simulations given current availability of global databases of weather, soil, crop calendar, fertilizer and irrigation management information, and reported yield.« less

Meteorological fluctuations define long-term crop yield patterns in conventional and organic production systems

USDA-ARS?s Scientific Manuscript database

Periodic variability in meteorological patterns presents significant challenges to crop production consistency and yield stability. Meteorological influences on corn and soybean grain yields were analyzed over an 18-year period at a long-term experiment in Beltsville, Maryland, U.S.A., comparing c...

Surprising yields with no-till cropping systems

USDA-ARS?s Scientific Manuscript database

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...

Surprising yields with no-till cropping systems

USDA-ARS?s Scientific Manuscript database

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...

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

NASA Technical Reports Server (NTRS)

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

1977-01-01

Airborne and ground measurements were made on April 1 and 29, 1976, over a USDA test site consisting mostly of wheat in various stages of water stress, but also including alfalfa and bare soil. These measurements were made to evaluate the feasibility of measuring crop temperatures from aircraft so that a parameter termed stress degree day, SDD, could be computed. Ground studies have shown that SDD is a valuable indicator of a crop's water needs, and that it can be related to irrigation scheduling and yield. The aircraft measurement program required predawn and afternoon flights coincident with minimum and maximum crop temperatures. Airborne measurements were made with an infrared line scanner and with color IR photography. The scanner data were registered, subtracted, and color-coded to yield pseudo-colored temperature-difference images. Pseudo-colored images reading directly in daily SDD increments were also produced. These maps enable a user to assess plant water status and thus determine irrigation needs and crop yield potentials.

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

NASA Astrophysics Data System (ADS)

Smith, T.; McLaughlin, D.

2017-12-01

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

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

Estimating Field Scale Crop Evapotranspiration using Landsat and MODIS Satellite Observations

NASA Astrophysics Data System (ADS)

Wong, A.; Jin, Y.; Snyder, R. L.; Daniele, Z.; Gao, F.

2016-12-01

Irrigation accounts for 80% of human freshwater consumption, and most of it return to the atmosphere through Evapotranspiration (ET). Given the challenges of already-stressed water resources and ground water regulation in California, a cost-effective, timely, and consistent spatial estimate of crop ET, from the farm to watershed level, is becoming increasingly important. The Priestley-Taylor (PT) approach, calibrated with field data and driven by satellite observations, shows great promise for accurate ET estimates across diverse ecosystems. We here aim to improve the robustness of the PT approach in agricultural lands, to enable growers and farm managers to tailor irrigation management based on in-field spatial variability and in-season variation. We optimized the PT coefficients for each crop type with available ET measurements from eddy covariance towers and/or surface renewal stations at six crop fields (Alfalfa, Almond, Citrus, Corn, Pistachio and Rice) in California. Good agreement was found between satellite-based estimates and field measurements of net radiation, with a RMSE of less than 36 W m-2. The crop type specific optimization performed well, with a RMSE of 30 W m-2 and a correlation of 0.81 for predicted daily latent heat flux. The calibrated algorithm was used to estimate ET at 30 m resolution over the Sacramento-San Joaquin Delta region for 2015 water year. It captures well the seasonal dynamics and spatial distribution of ET in Sacramento-San Joaquin Delta. A continuous monitoring of the dynamics and spatial heterogeneity of canopy and consumptive water use at a field scale, will help the growers to be well prepared and informed to adaptively manage water, canopy, and grove density to maximize the yield with the least amount of water.

Fast repurposing of high-resolution stereo video content for mobile use

NASA Astrophysics Data System (ADS)

Karaoglu, Ali; Lee, Bong Ho; Boev, Atanas; Cheong, Won-Sik; Gotchev, Atanas

2012-06-01

3D video content is captured and created mainly in high resolution targeting big cinema or home TV screens. For 3D mobile devices, equipped with small-size auto-stereoscopic displays, such content has to be properly repurposed, preferably in real-time. The repurposing requires not only spatial resizing but also properly maintaining the output stereo disparity, as it should deliver realistic, pleasant and harmless 3D perception. In this paper, we propose an approach to adapt the disparity range of the source video to the comfort disparity zone of the target display. To achieve this, we adapt the scale and the aspect ratio of the source video. We aim at maximizing the disparity range of the retargeted content within the comfort zone, and minimizing the letterboxing of the cropped content. The proposed algorithm consists of five stages. First, we analyse the display profile, which characterises what 3D content can be comfortably observed in the target display. Then, we perform fast disparity analysis of the input stereoscopic content. Instead of returning the dense disparity map, it returns an estimate of the disparity statistics (min, max, meanand variance) per frame. Additionally, we detect scene cuts, where sharp transitions in disparities occur. Based on the estimated input, and desired output disparity ranges, we derive the optimal cropping parameters and scale of the cropping window, which would yield the targeted disparity range and minimize the area of cropped and letterboxed content. Once the rescaling and cropping parameters are known, we perform resampling procedure using spline-based and perceptually optimized resampling (anti-aliasing) kernels, which have also a very efficient computational structure. Perceptual optimization is achieved through adjusting the cut-off frequency of the anti-aliasing filter with the throughput of the target display.

Dryland pea production and water use in responses to tillage, crop rotation, and weed management practice

USDA-ARS?s Scientific Manuscript database

Pea has been used to replace fallow and sustain dryland crop yields in arid and semiarid regions, but information to optimize its management is required. We evaluated pea growth, yield, and water use in response to tillage, crop rotation, and weed management practice from 2005 to 2010 in the norther...

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

USDA-ARS?s Scientific Manuscript database

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

7 CFR 457.131 - Macadamia nut crop insurance provisions.

Code of Federal Regulations, 2011 CFR

2011-01-01

... the orchard for the purpose of picking all or a portion of the crop. Graft. The uniting of a macadamia.... Picking of mature macadamia nuts from the ground. Interplanted. Acreage on which two or more crops are... information that we request in order to establish your approved yield. We will reduce the yield used to...

Are GM Crops for Yield and Resilience Possible?

PubMed

Paul, Matthew J; Nuccio, Michael L; Basu, Shib Sankar

2018-01-01

Crop yield improvements need to accelerate to avoid future food insecurity. Outside Europe, genetically modified (GM) crops for herbicide- and insect-resistance have been transformative in agriculture; other traits have also come to market. However, GM of yield potential and stress resilience has yet to impact on food security. Genes have been identified for yield such as grain number, size, leaf growth, resource allocation, and signaling for drought tolerance, but there is only one commercialized drought-tolerant GM variety. For GM and genome editing to impact on yield and resilience there is a need to understand yield-determining processes in a cell and developmental context combined with evaluation in the grower environment. We highlight a sugar signaling mechanism as a paradigm for this approach. Copyright © 2017 Elsevier Ltd. All rights reserved.

Aging and body size in solitary bees

USDA-ARS?s Scientific Manuscript database

Solitary bees are important pollinators of crops and non-domestic plants. Osmia lignaria is a native, commercially-reared solitary bee used to maximize pollination in orchard crops. In solitary bees, adult body size is extremely variable depending on the nutritional resources available to the develo...

Integrated remote sensing imagery and two-dimensional hydraulic modeling approach for impact evaluation of flood on crop yields

NASA Astrophysics Data System (ADS)

Chen, Huili; Liang, Zhongyao; Liu, Yong; Liang, Qiuhua; Xie, Shuguang

2017-10-01

The projected frequent occurrences of extreme flood events will cause significant losses to crops and will threaten food security. To reduce the potential risk and provide support for agricultural flood management, prevention, and mitigation, it is important to account for flood damage to crop production and to understand the relationship between flood characteristics and crop losses. A quantitative and effective evaluation tool is therefore essential to explore what and how flood characteristics will affect the associated crop loss, based on accurately understanding the spatiotemporal dynamics of flood evolution and crop growth. Current evaluation methods are generally integrally or qualitatively based on statistic data or ex-post survey with less diagnosis into the process and dynamics of historical flood events. Therefore, a quantitative and spatial evaluation framework is presented in this study that integrates remote sensing imagery and hydraulic model simulation to facilitate the identification of historical flood characteristics that influence crop losses. Remote sensing imagery can capture the spatial variation of crop yields and yield losses from floods on a grid scale over large areas; however, it is incapable of providing spatial information regarding flood progress. Two-dimensional hydraulic model can simulate the dynamics of surface runoff and accomplish spatial and temporal quantification of flood characteristics on a grid scale over watersheds, i.e., flow velocity and flood duration. The methodological framework developed herein includes the following: (a) Vegetation indices for the critical period of crop growth from mid-high temporal and spatial remote sensing imagery in association with agricultural statistics data were used to develop empirical models to monitor the crop yield and evaluate yield losses from flood; (b) The two-dimensional hydraulic model coupled with the SCS-CN hydrologic model was employed to simulate the flood evolution process, with the SCS-CN model as a rainfall-runoff generator and the two-dimensional hydraulic model implementing the routing scheme for surface runoff; and (c) The spatial combination between crop yield losses and flood dynamics on a grid scale can be used to investigate the relationship between the intensity of flood characteristics and associated loss extent. The modeling framework was applied for a 50-year return period flood that occurred in Jilin province, Northeast China, which caused large agricultural losses in August 2013. The modeling results indicated that (a) the flow velocity was the most influential factor that caused spring corn, rice and soybean yield losses from extreme storm event in the mountainous regions; (b) the power function archived the best results that fit the velocity-loss relationship for mountainous areas; and (c) integrated remote sensing imagery and two-dimensional hydraulic modeling approach are helpful for evaluating the influence of historical flood event on crop production and investigating the relationship between flood characteristics and crop yield losses.

Impacts of enhanced fertilizer applications on tropospheric ozone and crop damage over sub-Saharan Africa

NASA Astrophysics Data System (ADS)

Huang, Yaoxian; Hickman, Jonathan E.; Wu, Shiliang

2018-05-01

Fertilizer-induced nitrogen oxides (NOx) emissions in sub-Saharan Africa are expected to increase substantially in the coming decades, driven by increasing application of fertilizers to increase crop yields in an effort to attain food security across the continent. In many parts of sub-Saharan Africa, surface ozone (O3) is sensitive to increasing atmospheric concentrations of NOx. In this study, we employ the GEOS-Chem chemical transport model to conduct a preliminary investigation of the impacts on O3 air quality and the consequential crop damage associated with increasing fertilizer-induced NOx emissions in sub-Saharan Africa. Our simulation results, constrained by field NO flux measurements for the years 2011 and 2012 in response to a variety of fertilizer application rates in western Kenya, show that the enhancements in NO flux with fertilizer application rate of 150 kg N ha-1 can increase surface NOx and O3 concentrations by up to 0.36 and 2.8 ppbv respectively during the growing season. At the same time, accumulated O3 exposure during the crop growing season (expressed as AOT40 values) could increase by up to 496 ppb h, leading to crop yield decline of about 0.8% for O3-sensitive crops. Our results suggest that, when accounting for the consequential impacts on surface O3 air quality and crop damage over sub-Saharan Africa, agricultural intensification is possible without substantial impacts on crop productivity because the relatively small decline of crop yield resulting from O3 damage appears unlikely to outweigh the gain in crop yield from fertilization.

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

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

PubMed

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

2010-08-10

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

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Prediction of Seasonal Climate-induced Variations in Global Food Production

NASA Technical Reports Server (NTRS)

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

2013-01-01

Consumers, including the poor in many countries, are increasingly dependent on food imports and are therefore exposed to variations in yields, production, and export prices in the major food-producing regions of the world. National governments and commercial entities are paying increased attention to the cropping forecasts of major food-exporting countries as well as to their own domestic food production. Given the increased volatility of food markets and the rising incidence of climatic extremes affecting food production, food price spikes may increase in prevalence in future years. Here we present a global assessment of the reliability of crop failure hindcasts for major crops at two lead times derived by linking ensemble seasonal climatic forecasts with statistical crop models. We assessed the reliability of hindcasts (i.e., retrospective forecasts for the past) of crop yield loss relative to the previous year for two lead times. Pre-season yield predictions employ climatic forecasts and have lead times of approximately 3 to 5 months for providing information regarding variations in yields for the coming cropping season. Within-season yield predictions use climatic forecasts with lead times of 1 to 3 months. Pre-season predictions can be of value to national governments and commercial concerns, complemented by subsequent updates from within-season predictions. The latter incorporate information on the most recent climatic data for the upcoming period of reproductive growth. In addition to such predictions, hindcasts using observations from satellites were performed to demonstrate the upper limit of the reliability of crop forecasting.

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

DOE Data Explorer

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

2016-07-13

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

Combined low temperature-high light effects on gas exchange properties of jojoba leaves.

PubMed

Loreto, F; Bongi, G

1989-12-01

Jojoba (Simmondsia chinensis [Link] Schneider) is an important crop in desert climates. A relatively high frequency of periods of chilling and high photon flux density (PFD) in this environment makes photoinhibition likely, resulting in a reduction of assimilation capacity in overwintering leaves. This could explain the low net photosynthesis found in shoots from the field (4-6 micromoles per square meter per second) when compared to greenhouse grown plants (12-15 micromoles per square meter per second). The responses of photosynthesis and stomatal conductance to changes in absorbed PFD and in substomatal partial pressure of CO(2) were measured on jojoba leaves recovering from chilling temperature (4 degrees C) in high or low PFD. No measurable gas exchange was found immediately after chilling in either high or low PFD. For leaves chilled in low PFD, the original quantum yield was restored after 24 hours. The time course of recovery from chilling in high PFD was much longer. Quantum yield recovered to 60% of its original value in 72 hours but failed to recover fully after 1 week. Measurements of PSII chlorophyll fluorescence at 77 K showed that the reduced quantum yield was caused by photoinhibition. The ratio of variable to maximal fluorescence fell from a control level of 0.82 to 0.41 after the photoinhibitory treatment and recovery was slow. We also found a large increase in net assimilation rate and little closure of stomata as CO(2) was increased from ambient partial pressure of 35 to 85 pascals. For plants grown in full light, the increase in net assimilation rate was 100%. The photosynthetic response at high CO(2) concentration may constitute an ecological advantage of jojoba as a crop in the future.

Combined Low Temperature-High Light Effects on Gas Exchange Properties of Jojoba Leaves 1

PubMed Central

Loreto, Francesco; Bongi, Guido

1989-01-01

Jojoba (Simmondsia chinensis [Link] Schneider) is an important crop in desert climates. A relatively high frequency of periods of chilling and high photon flux density (PFD) in this environment makes photoinhibition likely, resulting in a reduction of assimilation capacity in overwintering leaves. This could explain the low net photosynthesis found in shoots from the field (4-6 micromoles per square meter per second) when compared to greenhouse grown plants (12-15 micromoles per square meter per second). The responses of photosynthesis and stomatal conductance to changes in absorbed PFD and in substomatal partial pressure of CO2 were measured on jojoba leaves recovering from chilling temperature (4°C) in high or low PFD. No measurable gas exchange was found immediately after chilling in either high or low PFD. For leaves chilled in low PFD, the original quantum yield was restored after 24 hours. The time course of recovery from chilling in high PFD was much longer. Quantum yield recovered to 60% of its original value in 72 hours but failed to recover fully after 1 week. Measurements of PSII chlorophyll fluorescence at 77 K showed that the reduced quantum yield was caused by photoinhibition. The ratio of variable to maximal fluorescence fell from a control level of 0.82 to 0.41 after the photoinhibitory treatment and recovery was slow. We also found a large increase in net assimilation rate and little closure of stomata as CO2 was increased from ambient partial pressure of 35 to 85 pascals. For plants grown in full light, the increase in net assimilation rate was 100%. The photosynthetic response at high CO2 concentration may constitute an ecological advantage of jojoba as a crop in the future. PMID:16667220

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

PubMed Central

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

2015-01-01

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

Research in the application of spectral data to crop identification and assessment, volume 2

NASA Technical Reports Server (NTRS)

Daughtry, C. S. T. (Principal Investigator); Hixson, M. M.; Bauer, M. E.

1980-01-01

The development of spectrometry crop development stage models is discussed with emphasis on models for corn and soybeans. One photothermal and four thermal meteorological models are evaluated. Spectral data were investigated as a source of information for crop yield models. Intercepted solar radiation and soil productivity are identified as factors related to yield which can be estimated from spectral data. Several techniques for machine classification of remotely sensed data for crop inventory were evaluated. Early season estimation, training procedures, the relationship of scene characteristics to classification performance, and full frame classification methods were studied. The optimal level for combining area and yield estimates of corn and soybeans is assessed utilizing current technology: digital analysis of LANDSAT MSS data on sample segments to provide area estimates and regression models to provide yield estimates.

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

PubMed Central

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

2018-01-01

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

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

PubMed

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

2017-01-01

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

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

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

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 practicesmore » [crop residue removal rates (0-75%), conservation practices (no till, contour cropping, strip cropping, terracing)].« less

What limits photosynthetic energy conversion efficiency in nature? Lessons from the oceans.

PubMed

Falkowski, Paul G; Lin, Hanzhi; Gorbunov, Maxim Y

2017-09-26

Constraining photosynthetic energy conversion efficiency in nature is challenging. In principle, two yield measurements must be made simultaneously: photochemistry, fluorescence and/or thermal dissipation. We constructed two different, extremely sensitive and precise active fluorometers: one measures the quantum yield of photochemistry from changes in variable fluorescence, the other measures fluorescence lifetimes in the picosecond time domain. By deploying the pair of instruments on eight transoceanic cruises over six years, we obtained over 200 000 measurements of fluorescence yields and lifetimes from surface waters in five ocean basins. Our results revealed that the average quantum yield of photochemistry was approximately 0.35 while the average quantum yield of fluorescence was approximately 0.07. Thus, closure on the energy budget suggests that, on average, approximately 58% of the photons absorbed by phytoplankton in the world oceans are dissipated as heat. This extraordinary inefficiency is associated with the paucity of nutrients in the upper ocean, especially dissolved inorganic nitrogen and iron. Our results strongly suggest that, in nature, most of the time, most of the phytoplankton community operates at approximately half of its maximal photosynthetic energy conversion efficiency because nutrients limit the synthesis or function of essential components in the photosynthetic apparatus.This article is part of the themed issue 'Enhancing photosynthesis in crop plants: targets for improvement'. © 2017 The Author(s).

Evaluating a satellite-based seasonal evapotranspiration product and identifying its relationship with other satellite-derived products and crop yield: A case study for Ethiopia

USGS Publications Warehouse

Tadesse, Tsegaye; Senay, Gabriel B.; Berhan, Getachew; Regassa, Teshome; Beyene, Shimelis

2015-01-01

Satellite-derived evapotranspiration anomalies and normalized difference vegetation index (NDVI) products from Moderate Resolution Imaging Spectroradiometer (MODIS) data are currently used for African agricultural drought monitoring and food security status assessment. In this study, a process to evaluate satellite-derived evapotranspiration (ETa) products with a geospatial statistical exploratory technique that uses NDVI, satellite-derived rainfall estimate (RFE), and crop yield data has been developed. The main goal of this study was to evaluate the ETa using the NDVI and RFE, and identify a relationship between the ETa and Ethiopia’s cereal crop (i.e., teff, sorghum, corn/maize, barley, and wheat) yields during the main rainy season. Since crop production is one of the main factors affecting food security, the evaluation of remote sensing-based seasonal ETa was done to identify the appropriateness of this tool as a proxy for monitoring vegetation condition in drought vulnerable and food insecure areas to support decision makers. The results of this study showed that the comparison between seasonal ETa and RFE produced strong correlation (R2 > 0.99) for all 41 crop growing zones in Ethiopia. The results of the spatial regression analyses of seasonal ETa and NDVI using Ordinary Least Squares and Geographically Weighted Regression showed relatively weak yearly spatial relationships (R2 < 0.7) for all cropping zones. However, for each individual crop zones, the correlation between NDVI and ETa ranged between 0.3 and 0.84 for about 44% of the cropping zones. Similarly, for each individual crop zones, the correlation (R2) between the seasonal ETa anomaly and de-trended cereal crop yield was between 0.4 and 0.82 for 76% (31 out of 41) of the crop growing zones. The preliminary results indicated that the ETa products have a good predictive potential for these 31 identified zones in Ethiopia. Decision makers may potentially use ETa products for monitoring cereal crop yields and early warning of food insecurity during drought years for these identified zones.

Evaluating a satellite-based seasonal evapotranspiration product and identifying its relationship with other satellite-derived products and crop yield: A case study for Ethiopia

NASA Astrophysics Data System (ADS)

Tadesse, Tsegaye; Senay, Gabriel B.; Berhan, Getachew; Regassa, Teshome; Beyene, Shimelis

2015-08-01

Satellite-derived evapotranspiration anomalies and normalized difference vegetation index (NDVI) products from Moderate Resolution Imaging Spectroradiometer (MODIS) data are currently used for African agricultural drought monitoring and food security status assessment. In this study, a process to evaluate satellite-derived evapotranspiration (ETa) products with a geospatial statistical exploratory technique that uses NDVI, satellite-derived rainfall estimate (RFE), and crop yield data has been developed. The main goal of this study was to evaluate the ETa using the NDVI and RFE, and identify a relationship between the ETa and Ethiopia's cereal crop (i.e., teff, sorghum, corn/maize, barley, and wheat) yields during the main rainy season. Since crop production is one of the main factors affecting food security, the evaluation of remote sensing-based seasonal ETa was done to identify the appropriateness of this tool as a proxy for monitoring vegetation condition in drought vulnerable and food insecure areas to support decision makers. The results of this study showed that the comparison between seasonal ETa and RFE produced strong correlation (R2 > 0.99) for all 41 crop growing zones in Ethiopia. The results of the spatial regression analyses of seasonal ETa and NDVI using Ordinary Least Squares and Geographically Weighted Regression showed relatively weak yearly spatial relationships (R2 < 0.7) for all cropping zones. However, for each individual crop zones, the correlation between NDVI and ETa ranged between 0.3 and 0.84 for about 44% of the cropping zones. Similarly, for each individual crop zones, the correlation (R2) between the seasonal ETa anomaly and de-trended cereal crop yield was between 0.4 and 0.82 for 76% (31 out of 41) of the crop growing zones. The preliminary results indicated that the ETa products have a good predictive potential for these 31 identified zones in Ethiopia. Decision makers may potentially use ETa products for monitoring cereal crop yields and early warning of food insecurity during drought years for these identified zones.

Humans as Sensors: Assessing the Information Value of Qualitative Farmer's Crop Condition Surveys for Crop Yield Monitoring and Forecasting

NASA Astrophysics Data System (ADS)

Beguería, S.

2017-12-01

While large efforts are devoted to developing crop status monitoring and yield forecasting systems trough the use of Earth observation data (mostly remotely sensed satellite imagery) and observational and modeled weather data, here we focus on the information value of qualitative data on crop status from direct observations made by humans. This kind of data has a high value as it reflects the expert opinion of individuals directly involved in the development of the crop. However, they have issues that prevent their direct use in crop monitoring and yield forecasting systems, such as their non-spatially explicit nature, or most importantly their qualitative nature. Indeed, while the human brain is good at categorizing the status of physical systems in terms of qualitative scales (`very good', `good', `fair', etcetera), it has difficulties in quantifying it in physical units. This has prevented the incorporation of this kind of data into systems that make extensive use of numerical information. Here we show an example of using qualitative crop condition data to estimate yields of the most important crops in the US early in the season. We use USDA weekly crop condition reports, which are based on a sample of thousands of reporters including mostly farmers and people in direct contact with them. These reporters provide subjective evaluations of crop conditions, in a scale including five levels ranging from `very poor' to `excellent'. The USDA report indicates, for each state, the proportion of reporters fort each condition level. We show how is it possible to model the underlying non-observed quantitative variable that reflects the crop status on each state, and how this model is consistent across states and years. Furthermore, we show how this information can be used to monitor the status of the crops and to produce yield forecasts early in the season. Finally, we discuss approaches for blending this information source with other, more classical earth data sources such as remote sensing or weather data, in the context of hierarchical regression models.

Future crop production threatened by extreme heat

NASA Astrophysics Data System (ADS)

Siebert, Stefan; Ewert, Frank

2014-04-01

Heat is considered to be a major stress limiting crop growth and yields. While important findings on the impact of heat on crop yield have been made based on experiments in controlled environments, little is known about the effects under field conditions at larger scales. The study of Deryng et al (2014 Global crop yield response to extreme heat stress under multiple climate change futures Environ. Res. Lett. 9 034011), analysing the impact of heat stress on maize, spring wheat and soya bean under climate change, represents an important contribution to this emerging research field. Uncertainties in the occurrence of heat stress under field conditions, plant responses to heat and appropriate adaptation measures still need further investigation.

Robust features of future climate change impacts on sorghum yields in West Africa

NASA Astrophysics Data System (ADS)

Sultan, B.; Guan, K.; Kouressy, M.; Biasutti, M.; Piani, C.; Hammer, G. L.; McLean, G.; Lobell, D. B.

2014-10-01

West Africa is highly vulnerable to climate hazards and better quantification and understanding of the impact of climate change on crop yields are urgently needed. Here we provide an assessment of near-term climate change impacts on sorghum yields in West Africa and account for uncertainties both in future climate scenarios and in crop models. Towards this goal, we use simulations of nine bias-corrected CMIP5 climate models and two crop models (SARRA-H and APSIM) to evaluate the robustness of projected crop yield impacts in this area. In broad agreement with the full CMIP5 ensemble, our subset of bias-corrected climate models projects a mean warming of +2.8 °C in the decades of 2031-2060 compared to a baseline of 1961-1990 and a robust change in rainfall in West Africa with less rain in the Western part of the Sahel (Senegal, South-West Mali) and more rain in Central Sahel (Burkina Faso, South-West Niger). Projected rainfall deficits are concentrated in early monsoon season in the Western part of the Sahel while positive rainfall changes are found in late monsoon season all over the Sahel, suggesting a shift in the seasonality of the monsoon. In response to such climate change, but without accounting for direct crop responses to CO2, mean crop yield decreases by about 16-20% and year-to-year variability increases in the Western part of the Sahel, while the eastern domain sees much milder impacts. Such differences in climate and impacts projections between the Western and Eastern parts of the Sahel are highly consistent across the climate and crop models used in this study. We investigate the robustness of impacts for different choices of cultivars, nutrient treatments, and crop responses to CO2. Adverse impacts on mean yield and yield variability are lowest for modern cultivars, as their short and nearly fixed growth cycle appears to be more resilient to the seasonality shift of the monsoon, thus suggesting shorter season varieties could be considered a potential adaptation to ongoing climate changes. Easing nitrogen stress via increasing fertilizer inputs would increase absolute yields, but also make the crops more responsive to climate stresses, thus enhancing the negative impacts of climate change in a relative sense. Finally, CO2 fertilization would significantly offset the negative climate impacts on sorghum yields by about 10%, with drier regions experiencing the largest benefits, though the net impacts of climate change remain negative even after accounting for CO2.

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

Using FACE systems to screen wheat cultivars for yield increases at elevated CO2

USDA-ARS?s Scientific Manuscript database

Because of continuing increases in atmospheric CO2, identifying cultivars of crops with larger yield increases at elevated CO2 may provide an avenue to increase crop yield potential in future climates. Free-air CO2 enrichment (FACE) systems have most often been used with multiple replications of ea...

Increased yield stability of field-grown winter barley (Hordeum vulgare L.) varietal mixtures through ecological processes

PubMed Central

Creissen, Henry E.; Jorgensen, Tove H.; Brown, James K.M.

2016-01-01

Crop variety mixtures have the potential to increase yield stability in highly variable and unpredictable environments, yet knowledge of the specific mechanisms underlying enhanced yield stability has been limited. Ecological processes in genetically diverse crops were investigated by conducting field trials with winter barley varieties (Hordeum vulgare), grown as monocultures or as three-way mixtures in fungicide treated and untreated plots at three sites. Mixtures achieved yields comparable to the best performing monocultures whilst enhancing yield stability despite being subject to multiple predicted and unpredicted abiotic and biotic stresses including brown rust (Puccinia hordei) and lodging. There was compensation through competitive release because the most competitive variety overyielded in mixtures thereby compensating for less competitive varieties. Facilitation was also identified as an important ecological process within mixtures by reducing lodging. This study indicates that crop varietal mixtures have the capacity to stabilise productivity even when environmental conditions and stresses are not predicted in advance. Varietal mixtures provide a means of increasing crop genetic diversity without the need for extensive breeding efforts. They may confer enhanced resilience to environmental stresses and thus be a desirable component of future cropping systems for sustainable arable farming. PMID:27375312

Maximum soil organic carbon storage in Midwest U.S. cropping systems when crops are optimally nitrogen-fertilized

USDA-ARS?s Scientific Manuscript database

Nitrogen fertilizer is critical to optimize short-term crop yield, but its long-term effect on soil organic C (SOC) is actively debated. Using 60 site-years of maize (Zea mays L.) yield response to a wide range of N fertilizer rates in continuous maize and annually rotated maize-soybean [Glycine max...

Organic weed conrol and cover crop residue integration impacts on weed control, quality, and yield and economics in conservation tillage tomato - A case study

USDA-ARS?s Scientific Manuscript database

The increased use of conservation tillage in vegetable production requires more information be developed on the role of cover crops in weed control, tomato quality and yield. Three conservation-tillage systems utilizing crimson clover, brassica and cereal rye as winter cover crops were compared to ...

A diversified no-till crop rotation reduces nitrous oxide emissions, increases soybean yields, and promotes soil C accrual

USDA-ARS?s Scientific Manuscript database

We evaluated the impact of crop rotational diversity on greenhouse gas (GHG) emissions, global warming potential (GWP), and crop yields. Under no-till, rain-fed conditions, a two-yr (corn (Zea mays L.)-soybean (Glycine max (L.) Merr.)) rotation and a four-yr (corn-field peas (Pisum sativum L.)-winte...

The potential of cover crops for improving soil function

NASA Astrophysics Data System (ADS)

Stoate, Chris; Crotty, Felicity

2017-04-01

Cover crops can be grown over the autumn and winter ensuring green cover throughout the year. They have been described as improving soil structure, reducing soil erosion and potentially even a form of grass weed control. These crops retain nutrients within the plant, potentially making them available for future crops, as well as increasing soil organic matter. Over the last three years, we have investigated how different cover crop regimes affect soil quality. Three separate experiments over each autumn/winter period have investigated how different cover crops affect soil biology, physics and chemistry, with each experiment building on the previous one. There have been significant effects of cover crops on soil structure, as well as significantly lower weed biomass and increased yields in the following crop - in comparison to bare stubble. For example, the effect of drilling the cover crops on soil structure in comparison to a bare stubble control that had not been driven on by machinery was quantified, and over the winter period the soil structure of the cover crop treatments changed, with compaction reduced in the cover crop treatments, whilst the bare stubble control remained unchanged. Weeds were found in significantly lower biomass in the cover crop mixes in comparison to the bare stubble control, and significantly lower weed biomass continued to be found in the following spring oat crop where the cover crops had been, indicating a weed suppressive effect that has a continued legacy in the following crop. The following spring oats have shown similar results in the last two years, with higher yields in the previous cover crop areas compared to the bare stubble controls. Overall, these results are indicating that cover crops have the potential to provide improvements to soil quality, reduce weeds and improve yields. We discuss the economic implications.

Maximal yields from multispecies fisheries systems: rules for systems with multiple trophic levels.

PubMed

Matsuda, Hiroyuki; Abrams, Peter A

2006-02-01

Increasing centralization of the control of fisheries combined with increased knowledge of food-web relationships is likely to lead to attempts to maximize economic yield from entire food webs. With the exception of predator-prey systems, we lack any analysis of the nature of such yield-maximizing strategies. We use simple food-web models to investigate the nature of yield- or profit-maximizing exploitation of communities including two types of three-species food webs and a variety of six-species systems with as many as five trophic levels. These models show that, for most webs, relatively few species are harvested at equilibrium and that a significant fraction of the species is lost from the web. These extinctions occur for two reasons: (1) indirect effects due to harvesting of species that had positive effects on the extinct species, and (2) intentional eradication of species that are not themselves valuable, but have negative effects on more valuable species. In most cases, the yield-maximizing harvest involves taking only species from one trophic level. In no case was an unharvested top predator part of the yield-maximizing strategy. Analyses reveal that the existence of direct density dependence in consumers has a large effect on the nature of the optimal harvest policy, typically resulting in harvest of a larger number of species. A constraint that all species must be retained in the system (a "constraint of biodiversity conservation") usually increases the number of species and trophic levels harvested at the yield-maximizing policy. The reduction in total yield caused by such a constraint is modest for most food webs but can be over 90% in some cases. Independent harvesting of species within the web can also cause extinctions but is less likely to do so.

Yield Model Development (YMD) implementation plan for fiscal years 1981 and 1982

NASA Technical Reports Server (NTRS)

Ambroziak, R. A. (Principal Investigator)

1981-01-01

A plan is described for supporting USDA crop production forecasting and estimation by (1) testing, evaluating, and selecting crop yield models for application testing; (2) identifying areas of feasible research for improvement of models; and (3) conducting research to modify existing models and to develop new crop yield assessment methods. Tasks to be performed for each of these efforts are described as well as for project management and support. The responsibilities of USDA, USDC, USDI, and NASA are delineated as well as problem areas to be addressed.

Spatiotemporal analysis of projected impacts of climate change on the major C3 and C4 crop yield under representative concentration pathway 4.5: Insight from the coasts of Tamil Nadu, South India

PubMed Central

A, Ramachandran; Praveen, Dhanya; R, Jaganathan; D, RajaLakshmi; K, Palanivelu

2017-01-01

India's dependence on a climate sensitive sector like agriculture makes it highly vulnerable to its impacts. However, agriculture is highly heterogeneous across the country owing to regional disparities in exposure, sensitivity, and adaptive capacity. It is essential to know and quantify the possible impacts of changes in climate on crop yield for successful agricultural management and planning at a local scale. The Hadley Centre Global Environment Model version 2-Earth System (HadGEM-ES) was employed to generate regional climate projections for the study area using the Regional Climate Model (RCM) RegCM4.4. The dynamics in potential impacts at the sub-district level were evaluated using the Representative Concentration Pathway 4.5 (RCPs). The aim of this study was to simulate the crop yield under a plausible change in climate for the coastal areas of South India through the end of this century. The crop simulation model, the Decision Support System for Agrotechnology Transfer (DSSAT) 4.5, was used to understand the plausible impacts on the major crop yields of rice, groundnuts, and sugarcane under the RCP 4.5 trajectory. The findings reveal that under the RCP 4.5 scenario there will be decreases in the major C3 and C4 crop yields in the study area. This would affect not only the local food security, but the livelihood security as well. This necessitates timely planning to achieve sustainable crop productivity and livelihood security. On the other hand, this situation warrants appropriate adaptations and policy intervention at the sub-district level for achieving sustainable crop productivity in the future. PMID:28753605

Spatiotemporal analysis of projected impacts of climate change on the major C3 and C4 crop yield under representative concentration pathway 4.5: Insight from the coasts of Tamil Nadu, South India.

PubMed

A, Ramachandran; Praveen, Dhanya; R, Jaganathan; D, RajaLakshmi; K, Palanivelu

2017-01-01

India's dependence on a climate sensitive sector like agriculture makes it highly vulnerable to its impacts. However, agriculture is highly heterogeneous across the country owing to regional disparities in exposure, sensitivity, and adaptive capacity. It is essential to know and quantify the possible impacts of changes in climate on crop yield for successful agricultural management and planning at a local scale. The Hadley Centre Global Environment Model version 2-Earth System (HadGEM-ES) was employed to generate regional climate projections for the study area using the Regional Climate Model (RCM) RegCM4.4. The dynamics in potential impacts at the sub-district level were evaluated using the Representative Concentration Pathway 4.5 (RCPs). The aim of this study was to simulate the crop yield under a plausible change in climate for the coastal areas of South India through the end of this century. The crop simulation model, the Decision Support System for Agrotechnology Transfer (DSSAT) 4.5, was used to understand the plausible impacts on the major crop yields of rice, groundnuts, and sugarcane under the RCP 4.5 trajectory. The findings reveal that under the RCP 4.5 scenario there will be decreases in the major C3 and C4 crop yields in the study area. This would affect not only the local food security, but the livelihood security as well. This necessitates timely planning to achieve sustainable crop productivity and livelihood security. On the other hand, this situation warrants appropriate adaptations and policy intervention at the sub-district level for achieving sustainable crop productivity in the future.

The CRISPR/Cas Genome-Editing Tool: Application in Improvement of Crops

PubMed Central

Khatodia, Surender; Bhatotia, Kirti; Passricha, Nishat; Khurana, S. M. P.; Tuteja, Narendra

2016-01-01

The Clustered Regularly Interspaced Short Palindromic Repeats associated Cas9/sgRNA system is a novel targeted genome-editing technique derived from bacterial immune system. It is an inexpensive, easy, most user friendly and rapidly adopted genome editing tool transforming to revolutionary paradigm. This technique enables precise genomic modifications in many different organisms and tissues. Cas9 protein is an RNA guided endonuclease utilized for creating targeted double-stranded breaks with only a short RNA sequence to confer recognition of the target in animals and plants. Development of genetically edited (GE) crops similar to those developed by conventional or mutation breeding using this potential technique makes it a promising and extremely versatile tool for providing sustainable productive agriculture for better feeding of rapidly growing population in a changing climate. The emerging areas of research for the genome editing in plants include interrogating gene function, rewiring the regulatory signaling networks and sgRNA library for high-throughput loss-of-function screening. In this review, we have described the broad applicability of the Cas9 nuclease mediated targeted plant genome editing for development of designer crops. The regulatory uncertainty and social acceptance of plant breeding by Cas9 genome editing have also been described. With this powerful and innovative technique the designer GE non-GM plants could further advance climate resilient and sustainable agriculture in the future and maximizing yield by combating abiotic and biotic stresses. PMID:27148329

Assessing and modelling ecohydrologic processes at the agricultural field scale

NASA Astrophysics Data System (ADS)

Basso, Bruno

2015-04-01

One of the primary goals of agricultural management is to increase the amount of crop produced per unit of fertilizer and water used. World record corn yields demonstrated that water use efficiency can increase fourfold with improved agronomic management and cultivars able to tolerate high densities. Planting crops with higher plant density can lead to significant yield increases, and increase plant transpiration vs. soil water evaporation. Precision agriculture technologies have been adopted for the last twenty years but seldom have the data collected been converted to information that led farmers to different agronomic management. These methods are intuitively appealing, but yield maps and other spatial layers of data need to be properly analyzed and interpreted to truly become valuable. Current agro-mechanic and geospatial technologies allow us to implement a spatially variable plan for agronomic inputs including seeding rate, cultivars, pesticides, herbicides, fertilizers, and water. Crop models are valuable tools to evaluate the impact of management strategies (e.g., cover crops, tile drains, and genetically-improved cultivars) on yield, soil carbon sequestration, leaching and greenhouse gas emissions. They can help farmers identify adaptation strategies to current and future climate conditions. In this paper I illustrate the key role that precision agriculture technologies (yield mapping technologies, within season soil and crop sensing), crop modeling and weather can play in dealing with the impact of climate variability on soil ecohydrologic processes. Case studies are presented to illustrate this concept.

Improving the Yield and Nutritional Quality of Forage Crops

PubMed Central

Capstaff, Nicola M.; Miller, Anthony J.

2018-01-01

Despite being some of the most important crops globally, there has been limited research on forages when compared with cereals, fruits, and vegetables. This review summarizes the literature highlighting the significance of forage crops, the current improvements and some of future directions for improving yield and nutritional quality. We make the point that the knowledge obtained from model plant and grain crops can be applied to forage crops. The timely development of genomics and bioinformatics together with genome editing techniques offer great scope to improve forage crops. Given the social, environmental and economic importance of forage across the globe and especially in poorer countries, this opportunity has enormous potential to improve food security and political stability. PMID:29740468

Making biodiversity-friendly cocoa pay: combining yield, certification, and REDD for shade management.

PubMed

Waldron, A; Justicia, R; Smith, L E

2015-03-01

The twin United Nations' Millennium Development Goals of biodiversity preservation and poverty reduction both strongly depend on actions in the tropics. In particular, traditional agroforestry could be critical to both biological conservation and human livelihoods in human-altered rainforest areas. However, traditional agroforestry is rapidly disappearing, because the system itself is economically precarious, and because the forest trees that shade traditional crops are now perceived to be overly detrimental to agricultural yield. Here, we show a case where the commonly used agroforestry shade metric, canopy cover, would indeed suggest complete removal of shade trees to maximize yield, with strongly negative biodiversity and climate implications. However, a yield over 50% higher was achievable if approximately 100 shade trees per hectare were planted in a spatially organized fashion, a win-win for biodiversity and the smallholder. The higher yield option was detected by optimizing simultaneously for canopy cover, and a second shade metric, neighboring tree density, which was designed to better capture the yield value of ecological services flowing from forest trees. Nevertheless, even a 50% yield increase may prove insufficient to stop farmers converting away from traditional agroforestry. To further increase agroforestry rents, we apply our results to the design of a sustainable certification (eco-labelling) scheme for cocoa-based products in a biodiversity hotspot, and consider their implications for the use of the United Nations REDD (reducing emissions from deforestation and forest degradation) program in agroforestry systems. Combining yield boost, certification, and REDD has the potential to incentivize eco-friendly agroforestry and lift smallholders out of poverty, simultaneously.

A Remote Sensing-Derived Corn Yield Assessment Model

NASA Astrophysics Data System (ADS)

Shrestha, Ranjay Man

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

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

Integrating multiple satellite data for crop monitoring

USDA-ARS?s Scientific Manuscript database

Remote sensing provides a valuable data source for detecting crop types, monitoring crop condition and predicting crop yields from space. Routine and continuous remote sensing data are critical for agricultural research and operational applications. Since crop field dimensions tend to be relatively ...

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

NASA Astrophysics Data System (ADS)

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

2013-04-01

The use of crop models allows simulating plant development, growth and yield under different environmental and management conditions. When combined with high spatial and temporal resolution remote sensing data, these models provide new perspectives for crop monitoring at regional scale. We propose here an approach to estimate time courses of dry aboveground biomass, yield and evapotranspiration (ETR) for summer (maize, sunflower) and winter crops (wheat) by assimilating Green Area Index (GAI) data, obtained from satellite observations, into a simple crop model. Only high spatial resolution and gap-free satellite time series can provide enough information for efficient crop monitoring applications. The potential of remote sensing data is often limited by cloud cover and/or gaps in observation. Data from different sensor systems need then to be combined. For this work, we employed a unique set of Formosat-2 and SPOT images (164 images) and in-situ measurements, acquired from 2006 to 2010 in southwest France. Among the several land surface biophysical variables accessible from satellite observations, the GAI is the one that has a key role in soil-plant-atmosphere interactions and in biomass accumulation process. Many methods have been developed to relate GAI to optical remote sensing signal. Here, seasonal dynamics of remotely sensed GAI were estimated by applying a method based on the inversion of a radiative transfer model using artificial neural networks. The modelling approach is based on the Simple Algorithm for Yield and Evapotranspiration estimate (SAFYE) model, which couples the FAO-56 model with an agro-meteorological model, based on Monteith's light-use efficiency theory. The SAFYE model is a daily time step crop model that simulates time series of GAI, dry aboveground biomass, grain yield and ETR. Crop and soil model parameters were determined using both in-situ measurements and values found in the literature. Phenological parameters were calibrated by the assimilation of the remotely sensed GAI time series. The calibration process led to accurate spatial estimates of GAI, ETR as well as of biomass and yield over the study area (24 km x 24 km window). The results highlight the interest of using a combined approach (crop model coupled with high spatial and temporal resolution remote sensing data) for the estimation of agronomical variables. At local scale, the model reproduced correctly the biomass production and ETR for summer crops (with relative RMSE of 29% and 35%, respectively). At regional scale, estimated yield and water requirement for irrigation were compared to regional statistics of yield and irrigation inventories provided by the local water agency. Results showed good agreements for inter-annual dynamics of yield estimates. Differences between water requirement for irrigation and actual supply were lower than 10% and inter-annual variability was well represented as well. The work, initially focused on summer crops, is being adapted to winter crops.

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

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

PubMed Central

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

2015-01-01

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

A Fast Track approach to deal with the temporal dimension of crop water footprint

NASA Astrophysics Data System (ADS)

Tuninetti, Marta; Tamea, Stefania; Laio, Francesco; Ridolfi, Luca

2017-07-01

Population growth, socio-economic development and climate changes are placing increasing pressure on water resources. Crop water footprint is a key indicator in the quantification of such pressure. It is determined by crop evapotranspiration and crop yield, which can be highly variable in space and time. While the spatial variability of crop water footprint has been the objective of several investigations, the temporal variability remains poorly studied. In particular, some studies approached this issue by associating the time variability of crop water footprint only to yield changes, while considering evapotranspiration patterns as marginal. Validation of this Fast Track approach has yet to be provided. In this Letter we demonstrate its feasibility through a comprehensive validation, an assessment of its uncertainty, and an example of application. Our results show that the water footprint changes are mainly driven by yield trends, while evapotranspiration plays a minor role. The error due to considering constant evapotranspiration is three times smaller than the uncertainty of the model used to compute the crop water footprint. These results confirm the suitability of the Fast Track approach and enable a simple, yet appropriate, evaluation of time-varying crop water footprint.

Ultraweak photon emission and proteomics analyses in soybean under abiotic stress.

PubMed

Komatsu, Setsuko; Kamal, Abu Hena Mostafa; Makino, Takahiro; Hossain, Zahed

2014-07-01

Biophotons are ultraweak photon emissions that are closely related to various biological activities and processes. In mammals, biophoton emissions originate from oxidative bursts in immunocytes during immunological responses. Biophotons emitted from plant organs provide novel information about the physiological state of plant under in vivo condition. In this review, the principles and recent advances in the measurement of biophoton emissions in plants are described. Furthermore, examples of biophoton emission and proteomics in soybean under abiotic stress are reviewed and discussed. Finally, this review suggests that the application of proteomics should provide a better interpretation of plant response to biophoton emission and allow the identification of genes that will allow the screening of crops able to produce maximal yields, even in stressful environments. Copyright © 2014 Elsevier B.V. All rights reserved.

Relationships between primary production and crop yields in semi-arid and arid irrigated agro-ecosystems

NASA Astrophysics Data System (ADS)

Jaafar, H. H.; Ahmad, F. A.

2015-04-01

In semi-arid areas within the MENA region, food security problems are the main problematic imposed. Remote sensing can be a promising too early diagnose food shortages and further prevent the population from famine risks. This study is aimed at examining the possibility of forecasting yield before harvest from remotely sensed MODIS-derived Enhanced Vegetation Index (EVI), Net photosynthesis (net PSN), and Gross Primary Production (GPP) in semi-arid and arid irrigated agro-ecosystems within the conflict affected country of Syria. Relationships between summer yield and remotely sensed indices were derived and analyzed. Simple regression spatially-based models were developed to predict summer crop production. The validation of these models was tested during conflict years. A significant correlation (p<0.05) was found between summer crop yield and EVI, GPP and net PSN. Results indicate the efficiency of remotely sensed-based models in predicting summer yield, mostly for cotton yields and vegetables. Cumulative summer EVI-based model can predict summer crop yield during crisis period, with deviation less than 20% where vegetables are the major yield. This approach prompts to an early assessment of food shortages and lead to a real time management and decision making, especially in periods of crisis such as wars and drought.

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

PubMed

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

2018-04-01

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

Cotton yield estimation using very high-resolution digital images acquired on a low-cost small unmanned aerial vehicle

USDA-ARS?s Scientific Manuscript database

Yield estimation is a critical task in crop management. A number of traditional methods are available for crop yield estimation but they are costly, time-consuming and difficult to expand to a relatively large field. Remote sensing provides techniques to develop quick coverage over a field at any sc...

7 CFR 400.55 - Qualification for actual production history coverage program.

Code of Federal Regulations, 2013 CFR

2013-01-01

... APH yield is calculated from a database containing a minimum of four yields and will be updated each subsequent crop year. The database may contain a maximum of the 10 most recent crop years and may include... only occur in the database when there are less than four years of actual and/or assigned yields. (b...

7 CFR 400.55 - Qualification for actual production history coverage program.

Code of Federal Regulations, 2011 CFR

2011-01-01

... APH yield is calculated from a database containing a minimum of four yields and will be updated each subsequent crop year. The database may contain a maximum of the 10 most recent crop years and may include... only occur in the database when there are less than four years of actual and/or assigned yields. (b...

7 CFR 400.55 - Qualification for actual production history coverage program.

Code of Federal Regulations, 2010 CFR

2010-01-01

... APH yield is calculated from a database containing a minimum of four yields and will be updated each subsequent crop year. The database may contain a maximum of the 10 most recent crop years and may include... only occur in the database when there are less than four years of actual and/or assigned yields. (b...

7 CFR 400.55 - Qualification for actual production history coverage program.

Code of Federal Regulations, 2012 CFR

2012-01-01

... APH yield is calculated from a database containing a minimum of four yields and will be updated each subsequent crop year. The database may contain a maximum of the 10 most recent crop years and may include... only occur in the database when there are less than four years of actual and/or assigned yields. (b...

Genotypic diversity in the responses of yield and yield components to elevated ozone of diverse inbred and hybrid maize

USDA-ARS?s Scientific Manuscript database

Current tropospheric ozone concentrations ([O3]), an important air pollutant, are phytotoxic and detrimental to crop yield causing significant losses of ~14-26 billion in 4 of the world’s major crops. Until recent years, it was believed that agricultural and economically important C4 plants, such as...

Global warming threatens agricultural productivity in Africa and South Asia

NASA Astrophysics Data System (ADS)

Sultan, Benjamin

2012-12-01

The Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC; Christensen et al 2007) has, with greater confidence than previous reports, warned the international community that the increase in anthropogenic greenhouse gases emissions will result in global climate change. One of the most direct and threatening impacts it may have on human societies is the potential consequences on global crop production. Indeed agriculture is considered as the most weather-dependent of all human activities (Hansen 2002) since climate is a primary determinant for agricultural productivity. The potential impact of climate change on crop productivity is an additional strain on the global food system which is already facing the difficult challenge of increasing food production to feed a projected 9 billion people by 2050 with changing consumption patterns and growing scarcity of water and land (Beddington 2010). In some regions such as Sub-Saharan Africa or South Asia that are already food insecure and where most of the population increase and economic development will take place, climate change could be the additional stress that pushes systems over the edge. A striking example, if needed, is the work from Collomb (1999) which estimates that by 2050 food needs will more than quintuple in Africa and more than double in Asia. Better knowledge of climate change impacts on crop productivity in those vulnerable regions is crucial to inform policies and to support adaptation strategies that may counteract the adverse effects. Although there is a growing literature on the impact of climate change on crop productivity in tropical regions, it is difficult to provide a consistent assessment of future yield changes because of large uncertainties in regional climate change projections, in the response of crops to environmental change (rainfall, temperature, CO2 concentration), in the coupling between climate models and crop productivity functions, and in the adaptation of agricultural systems to progressive climate change (Roudier et al 2011, Challinor et al 2007). These uncertainties result in a large spread of crop yield projections indicating a low confidence in future yield projections. A recent study by Knox et al (2012) is among the first to provide robust evidence of how climate change will impact productivity of major crops in Africa and South Asia. Using a meta-analysis, which is widely used in epidemiology and medicine and consists in comparing and combining results from different independent published studies, Knox et al (2012) show a consistent yield loss by the 2050s of major crops (wheat, maize, sorghum and millet) in both regions. This systematic review and meta-analysis of data in 52 original publications from an initial screen of 1144 studies nicely extend previous works by Müller et al (2011) and Roudier et al (2011), confirming the threat of negative climate change impacts in Africa but also in South Asia. Knox et al (2012) estimate that mean yield change for all crops is -8% by the 2050s with strong variations among crops and regions. For instance evidence of yield reduction up to -40% are detected for some regions of Africa while no mean yield change is detected for rice in India. Variations in crop yield projections decrease when considering a large number of climate models confirming the relevance of the expanded use of multi-model ensembles of projections of future climate change adopted in the IPCC Fourth Assessment Report. Conversely, variations in crop yield projections increase with the crop model complexity especially when using process-based crop models over statistical models. Such differences in crop yield variations may be attributed either to the structural differences between crop model approaches or to the spatial scale differences; biophysical crop models operating at finer spatial scales and thus reproducing the higher variability of impacts at these scales. Such robust evidence of future yield change in Africa and South Asia can be surprising in regards to the diverging projections in a warmer climate of summer monsoon rainfall, the primary driver for rainfed crop productivity in the region, especially in West Africa where some studies make projections of wetter conditions and some predict more frequent droughts (Druyan 2011). This is because of the adverse role of higher temperatures in shortening the crop cycle duration and increasing evapotranspiration demand and thus reducing crop yields, irrespective of rainfall changes (Berg et al 2012, Roudier et al 2011, Schlenker and Lobell 2010). Potential wetter conditions or elevated CO2 concentrations hardly counteract the adverse effect of higher temperatures. Although such systematic reviews and meta-analyses conducted by Knox et al (2012), Müller et al (2011) or Roudier et al (2011) can provide important insights about sign, magnitude and uncertainty of climate change impacts, direct comparison among studies suffers from inevitable limitations. In particular the diversity of the studies selected for the meta-analysis, encompassing a range of different countries, scales, crops and methods (climate models and scenarios, crop models, downscaling technique), makes it difficult to aggregate crop yield projections to provide a consistent and precise impact assessment. A rigorous multi-ensembles approach, with varying climate models, emissions scenarios, crop models, and downscaling techniques, as recommended by Challinor et al (2007), would enable a move towards a more complete sampling of uncertainty in crop yield projections. In that sense, coordinated modeling experiments such as the ones conducted throughout the Agricultural Model Intercomparison and Improvement Project (AgMIP; www.agmip.org/) are likely to improve substantially the characterization of the threat of crop yield losses and food insecurity due to climate change. In spite of the threat of crop yield losses in a warmer climate, it is important to keep in mind, as discussed by Berg et al (2012), that developing countries in the tropics have the potential to more than offset such adverse impacts by implementing more intensive agricultural practices and adapting agriculture to climate and environmental change. Indeed Africa and in a lesser extend South Asia are among the only regions of the world where there is an untapped potential for raising agricultural productivity since poor soil fertility and low input levels, combined with extensive agricultural practices, contribute to a large gap between actual and potential yields (Licker et al 2010). References Beddington J 2010 Food security: contributions from science to a new and greener revolution Phil. Trans. R. Soc. B 365 61-71 Berg A, de Noblet-Ducoudré N, Sultan B, Lengaigne N and Guimberteau M 2012 Projections of climate change impacts on potential crop productivity over tropical regions Agric. For. Meteorol. at press (doi:10.1016/j.agrformet.2011.12.003) Challinor A, Wheeler T, Garforth C, Craufurd P and Kassam A 2007 Assessing the vulnerability of food crop systems in Africa to climate change Clim. Change 83 381-99 Christensen J H et al 2007 Regional climate projections Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change ed S Solomon, D Qin, M Manning, Z Chen, M Marquis, K B Averyt, M Tignor and H L Miller (Cambridge: Cambridge University Press) Collomb P 1999 A narrow road to food security from now to 2050 FAO Economica (Paris: FAO) Druyan L M 2011 Studies of 21st-century precipitation trends over West Africa Int. J. Climatol. 31 1415-572 Hansen J W 2002 Realizing the potential benefits of climate prediction to agriculture: issues, approaches, challenges Agric. Syst. 74 309-30 Knox J, Hess T, Daccache A and Wheeler T 2012 Climate change impacts on crop productivity in Africa and South Asia Environ. Res. Lett. 7 034032 Licker R, Johnston M, Foley J A, Barford C, Kucharik C J, Monfreda C and Ramankutty N 2010 Mind the gap: how do climate and agricultural management explain the 'yield gap' of croplands around the world? Glob. Ecol. Biogeogr. 19 769-82 Müller C, Cramer W, Hare W L and Lotze-Campen H 2011 Climate change risks for African agriculture Proc. Natl Acad. Sci. USA 108 4313-5 Roudier P, Sultan S, Quirion P and Berg A 2011 The impact of future climate change on West African crop yields: what does the recent literature say? Glob. Environ. Change 21 1073-83 Schlenker W and Lobell D 2010 Robust negative impacts of climate change on African agriculture Environ. Res. Lett. 5 014010

Plausible rice yield losses under future climate warming.

PubMed

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

2016-12-19

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

Balancing Immunity and Yield in Crop Plants.

PubMed

Ning, Yuese; Liu, Wende; Wang, Guo-Liang

2017-12-01

Crop diseases cause enormous yield losses and threaten global food[ED1] security. The use of highly resistant cultivars can effectively control plant diseases, but in crops, genetic immunity to disease often comes with an unintended reduction in growth and yield. Here, we review recent advances in understanding how nucleotide-binding domain, leucine-rich repeat (NLR) receptors and cell wall-associated kinase (WAK) proteins function in balancing immunity and yield. We also discuss the role of plant hormones and transcription factors in regulating the trade-offs between plant growth and immunity. Finally, we describe how a novel mechanism of translational control of defense proteins can enhance immunity without the reduction in fitness. Copyright © 2017 Elsevier Ltd. All rights reserved.

Soil Moisture Anomaly as Predictor of Crop Yield Deviation in Germany

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

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, phenological, geological, agronomic, and socio-economic variables are also considered to extend the model in order to reveal the proper causal relation. First results show that dry as well as wet extremes of SMI have a negative impact on crop yield for winter wheat. This indicates that soil moisture has at least a limiting affect on crop production.

Using a time-series statistical framework to quantify trends and abrupt change in US corn, soybean, and wheat yields from 1970-2016

NASA Astrophysics Data System (ADS)

Zhang, J.; Ives, A. R.; Turner, M. G.; Kucharik, C. J.

2017-12-01

Previous studies have identified global agricultural regions where "stagnation" of long-term crop yield increases has occurred. These studies have used a variety of simple statistical methods that often ignore important aspects of time series regression modeling. These methods can lead to differing and contradictory results, which creates uncertainty regarding food security given rapid global population growth. Here, we present a new statistical framework incorporating time series-based algorithms into standard regression models to quantify spatiotemporal yield trends of US maize, soybean, and winter wheat from 1970-2016. Our primary goal was to quantify spatial differences in yield trends for these three crops using USDA county level data. This information was used to identify regions experiencing the largest changes in the rate of yield increases over time, and to determine whether abrupt shifts in the rate of yield increases have occurred. Although crop yields continue to increase in most maize-, soybean-, and winter wheat-growing areas, yield increases have stagnated in some key agricultural regions during the most recent 15 to 16 years: some maize-growing areas, except for the northern Great Plains, have shown a significant trend towards smaller annual yield increases for maize; soybean has maintained an consistent long-term yield gains in the Northern Great Plains, the Midwest, and southeast US, but has experienced a shift to smaller annual increases in other regions; winter wheat maintained a moderate annual increase in eastern South Dakota and eastern US locations, but showed a decline in the magnitude of annual increases across the central Great Plains and western US regions. Our results suggest that there were abrupt shifts in the rate of annual yield increases in a variety of US regions among the three crops. The framework presented here can be broadly applied to additional yield trend analyses for different crops and regions of the Earth.

Nutritional composition and in vitro digestibility of grass and legume winter (cover) crops.

PubMed

Brown, A N; Ferreira, G; Teets, C L; Thomason, W E; Teutsch, C D

2018-03-01

In dairy farming systems, growing winter crops for forage is frequently limited to annual grasses grown in monoculture. The objectives of this study were to determine how cropping grasses alone or in mixtures with legumes affects the yield, nutritional composition, and in vitro digestibility of fresh and ensiled winter crops and the yield, nutritional composition, and in vitro digestibility of the subsequent summer crops. Experimental plots were planted with 15 different winter crops at 3 locations in Virginia. At each site, 4 plots of each treatment were planted in a randomized complete block design. The 15 treatments included 5 winter annual grasses [barley (BA), ryegrass (RG), rye (RY), triticale (TR), and wheat (WT)] in monoculture [i.e., no legumes (NO)] or with 1 of 2 winter annual legumes [crimson clover (CC) and hairy vetch (HV)]. After harvesting the winter crops, corn and forage sorghum were planted within the same plots perpendicular to the winter crop plantings. The nutritional composition and the in vitro digestibility of winter and summer crops were determined for fresh and ensiled samples. Growing grasses in mixtures with CC increased forage dry matter (DM) yield (2.84 Mg/ha), but the yield of mixtures with HV (2.47 Mg/ha) was similar to that of grasses grown in monoculture (2.40 Mg/ha). Growing grasses in mixtures with legumes increased the crude protein concentration of the fresh forage from 13.0% to 15.5% for CC and to 17.3% for HV. For neutral detergent fiber (NDF) concentrations, the interaction between grasses and legumes was significant for both fresh and ensiled forages. Growing BA, RY, and TR in mixtures with legumes decreased NDF concentrations, whereas growing RG and WT with legumes did not affect the NDF concentrations of either the fresh or the ensiled forages. Growing grasses in mixtures with legumes decreased the concentration of sugars of fresh forages relative to grasses grown in monoculture. Primarily, this decrease can be attributed to low concentrations of sugars of mixtures with HV (10.5%). Growing grasses in mixtures with legumes reduced the fiber digestibility of both winter crops (75.7% to 72.8% NDF). Growing grasses in mixtures with legumes did not affect estimated DM yield, nutritional composition, or digestibility of the succeeding summer crops. In conclusion, growing grasses in mixtures with legumes as winter forage crops can increase forage estimated DM yields and its nutritional quality in dairy farming sytems. Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

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

NASA Astrophysics Data System (ADS)

Lee, Juhwan; Necpalova, Magdalena; Six, Johan

2017-04-01

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