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,...
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.
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...
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.
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.
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...
Survival or productivity? Global synthesis of root and tuber production during drought
NASA Astrophysics Data System (ADS)
Daryanto, S.; Wang, L.; Jacinthe, P. A.
2016-12-01
According to FAO, there are six major root and tuber crops: potato, cassava, sweet potato, yam, taro, and yautia. Some root and tuber crops (e.g., sweet potato and cassava) are considered to be `drought-resistant', although quantitative evidence that support the premise was still lacking. Greater uncertainties exist on how drought effects co-vary with: 1) soil texture, 2) agro-ecological region, and 3) drought timing. To address these uncertainties, we collected literature data between 1980 and 2015 that reported monoculture root and tuber yield responses to drought under field conditions, and analyzed this large data set using meta-analysis techniques. Our results showed that the amount of water reduction was positively related with yield reduction, but the extent of the impact varied with root or tuber species and the phenological phase during which drought occurred. In contrast to common assumptions regarding drought resistance of certain root and tuber crops, we found that yield reduction was similar between potato and species thought to be `drought-resistant' such as cassava and sweet potato. Here we suggest that drought-resistance in cassava and sweet potato could be more related to survival rather than yield. All roots or tubers crops, however, experienced greater yield reduction when drought occurred during the tuberization period compared to during their vegetative phase. The effect of soil texture as well as region (and related climatic factors) on yield reduction and crop sensitivity were less obvious. Our study provides useful information that could inform agricultural planning, and influence the direction of research for improving the productivity and the resilience of these under-utilized crops in the drought-prone regions of the world.
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
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
Balancing Immunity and Yield in Crop Plants.
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.
Simulating crop yield losses in Switzerland for historical and present Tambora climate scenarios
NASA Astrophysics Data System (ADS)
Flückiger, Simon; Brönnimann, Stefan; Holzkämper, Annelie; Fuhrer, Jürg; Krämer, Daniel; Pfister, Christian; Rohr, Christian
2017-07-01
Severe climatic anomalies in summer 1816, partly due to the eruption of Tambora in April 1815, contributed to delayed growth and poor harvests of important crops in Central Europe. Coinciding with adverse socio-economic conditions, this event triggered the last subsistence crisis in the western World. Here, we model reductions in potential crop yields for 1816 and 1817 and address the question, what impact a similar climatic anomaly would have today. We reconstructed daily weather for Switzerland for 1816/17 on a 2 km grid using historical observations and an analogue resampling method. These data were used to simulate potential crop yields for potato, grain maize, and winter barley using the CropSyst model calibrated for current crop cultivars. We also simulated yields for the same weather anomalies, but referenced to a present-day baseline temperature. Results show that reduced temperature delayed growth and harvest considerably, and in combination with reduced solar irradiance led to a substantial reduction (20%-50%) in the potential yield of potato in 1816. Effects on winter barley were smaller. Significant reductions were also modelled for 1817 and were mainly due to a cold late spring. Relative reductions for the present-day scenario for the two crops were almost indistinguishable from the historical ones. An even stronger response was found for maize, which was not yet common in 1816/17. Waterlogging, which we assessed using a stress-day approach, likely added to the simulated reductions. The documented, strong east-west gradient in malnutrition across Switzerland in 1817/18 could not be explained by biophysical yield limitations (though excess-water limitation might have contributed), but rather by economic, political and social factors. This highlights the importance of these factors for a societies’ ability to cope with extreme climate events. While the adaptive capacity of today’s society in Switzerland is much greater than in the early 19th century, our results emphasize the need for interdisciplinary approaches to climate change adaptation considering not only biophysical, but also social, economic and political aspects.
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.
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.
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.
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.
Peng, Zhengping; Liu, Yanan; Li, Yingchun; Abawi, Yahya; Wang, Yanqun; Men, Mingxin; An-Vo, Duc-Anh
2017-01-01
Nitrogen (N) is an essential macronutrient for plant growth and excessive application rates can decrease crop yield and increase N loss into the environment. Field experiments were carried out to understand the effects of N fertilizers on N utilization, crop yield and net income in wheat and maize rotation system of the North China Plain (NCP). Compared to farmers’ N rate (FN), the yield of wheat and maize in reduction N rate by 21–24% based on FN (RN) was improved by 451 kg ha-1, N uptakes improved by 17 kg ha-1 and net income increased by 1671 CNY ha-1, while apparent N loss was reduced by 156 kg ha-1. The controlled-release fertilizer with a 20% reduction of RN (CRF80%), a 20% reduction of RN together with dicyandiamide (RN80%+DCD) and a 20% reduction of RN added with nano-carbon (RN80%+NC) all resulted in an improvement in crop yield and decreased the apparent N losses compared to RN. Contrasted with RN80%+NC, the total crop yield in RN80%+DCD improved by 1185 kg ha-1, N uptake enhanced by 9 kg ha-1 and net income increased by 3929 CNY ha-1, while apparent N loss was similar. Therefore, a 37–39% overall decrease in N rate compared to farmers plus the nitrification inhibitor, DCD, was effective N control measure that increased crop yields, enhanced N efficiencies, and improved economic benefits, while mitigating apparent N loss. There is considerable scope for improved N use effieincy in the intensive wheat -maize rotation of the NCP. PMID:28228772
Effects of Management Practices on Meloidogyne incognita and Snap Bean Yield.
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.
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.
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 .
Kaur, Ravinder; Paul, Madhumita; Malik, Rashmi
2007-06-01
Conjunctive use of saline/non-saline irrigation waters is generally aimed at minimizing yield losses and enhancing flexibility of cropping, without much alteration in farming operations. Recommendation of location-specific suitable conjunctive water use plans requires assessment of their long-term impacts on soil salinization/sodification and crop yield reductions. This is conventionally achieved through long-term field experiments. However such impact evaluations are site specific, expensive and time consuming. Appropriate decision support systems (DSS) can be time-efficient and cost-effective means for such long-term impact evaluations. This study demonstrates the application of one such (indigenously developed) DSS for recommending best conjunctive water use plans for a, rice-wheat growing, salt affected farmer's field in Gurgaon district of Haryana (India). Before application, the DSS was extensively validated on several farmers and controlled experimental fields in Gurgaon and Karnal districts of Haryana (India). Validation of DSS showed its potential to give realistic estimates of root zone soil salinity (with R = 0.76-0.94; AMRE = 0.03-0.06; RMSPD = 0.51-0.90); sodicity (with R = 0.99; AMRE = 0.02; RMSPD = 0.84) and relative crop yield reductions (AMRE = 0.24), under existing (local) resource management practices. Long term (10 years) root zone salt build ups and associated rice/wheat crop yield reductions, in a salt affected farmer's field, under varied conjunctive water use scenarios were evaluated with the validated DSS. It was observed that long-term applications of canal (CW) and tube well (TW) waters in a cycle and in 1:1 mixed mode, during Kharif season, predicted higher average root zone salt reductions (2-9%) and lower rice crop yield reductions (4-5%) than the existing practice of 3-CW, 3-TW, 3-CW. Besides this, long-term application of 75% CW mixed with 25% TW, during Rabi season, predicted about 17% lower average root-zone salt reductions than the cyclic applications of (1-CW, 1-TW, 2-CW) and (2-CW, 1-TW, 1-CW, i.e., existing irrigation strategy). However, average wheat crop yield reductions (16-17%) simulated under all these strategies were almost at par. In general, cyclic-conjunctive water use strategies emerged as better options than the blending modes. These results were in complete confirmation with actual long-term conjunctive water use experiments on similar soils. It was thus observed that such pre-validated tools could be efficient means for designing, local resource and target crop yield-specific, appropriate conjunctive water use plans for irrigated agricultural lands.
Root-knot nematode management in double-cropped plasticulture vegetables.
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%.
Teshager, Awoke Dagnew; Gassman, Philip W; Secchi, Silvia; Schoof, Justin T
2017-12-31
About 50% of U.S. water pollution problems are caused by non-point source (NPS) pollution, primarily sediment and nutrients from agricultural areas, despite the widespread implementation of agricultural Best Management Practices (BMPs). However, the effectiveness of implementation strategies and type of BMPs at watershed scale are still not well understood. In this study, the Soil and Water Assessment Tool (SWAT) ecohydrological model was used to assess the effectiveness of pollutant mitigation strategies in the Raccoon River watershed (RRW) in west-central Iowa, USA. We analyzed fourteen management scenarios based on systematic combinations of five strategies: fertilizer/manure management, changing row-crop land to perennial grass, vegetative filter strips, cover crops and shallower tile drainage systems, specifically aimed at reducing nitrate and total suspended sediment yields from hotspot areas in the RRW. Moreover, we assessed implications of climate change on management practices, and the impacts of management practices on water availability, row crop yield, and total agricultural production. Our results indicate that sufficient reduction of nitrate load may require either implementation of multiple management practices (38.5% with current setup) or conversion of extensive areas into perennial grass (up to 49.7%) to meet and maintain the drinking water standard. However, climate change may undermine the effectiveness of management practices, especially late in the 21st century, cutting the reduction by up to 65% for nitrate and more for sediment loads. Further, though our approach is targeted, it resulted in a slight decrease (~5%) in watershed average crop yield and hence an overall reduction in total crop production, mainly due to the conversion of row-crop lands to perennial grass. Such yield reductions could be quite spatially heterogeneously distributed (0 to 40%). Copyright © 2017 Elsevier B.V. All rights reserved.
Effects of halving pesticide use on wheat production
Hossard, L.; Philibert, A.; Bertrand, M.; Colnenne-David, C.; Debaeke, P.; Munier-Jolain, N.; Jeuffroy, M. H.; Richard, G.; Makowski, D.
2014-01-01
Pesticides pose serious threats to both human health and the environment. In Europe, farmers are encouraged to reduce their use, and in France a recent environmental policy fixed a target of halving the pesticide use by 2018. Organic and integrated cropping systems have been proposed as possible solutions for reducing pesticide use, but the effect of reducing pesticide use on crop yield remains unclear. Here we use a set of cropping system experiments to quantify the yield losses resulting from a reduction of pesticide use for winter wheat in France. Our estimated yield losses resulting from a 50% reduction in pesticide use ranged from 5 to 13% of the yield obtained with the current pesticide use. At the scale of the whole country, these losses would decrease the French wheat production by about 2 to 3 millions of tons, which represent about 15% of the French wheat export. PMID:24651597
Effects of halving pesticide use on wheat production
NASA Astrophysics Data System (ADS)
Hossard, L.; Philibert, A.; Bertrand, M.; Colnenne-David, C.; Debaeke, P.; Munier-Jolain, N.; Jeuffroy, M. H.; Richard, G.; Makowski, D.
2014-03-01
Pesticides pose serious threats to both human health and the environment. In Europe, farmers are encouraged to reduce their use, and in France a recent environmental policy fixed a target of halving the pesticide use by 2018. Organic and integrated cropping systems have been proposed as possible solutions for reducing pesticide use, but the effect of reducing pesticide use on crop yield remains unclear. Here we use a set of cropping system experiments to quantify the yield losses resulting from a reduction of pesticide use for winter wheat in France. Our estimated yield losses resulting from a 50% reduction in pesticide use ranged from 5 to 13% of the yield obtained with the current pesticide use. At the scale of the whole country, these losses would decrease the French wheat production by about 2 to 3 millions of tons, which represent about 15% of the French wheat export.
Effects of halving pesticide use on wheat production.
Hossard, L; Philibert, A; Bertrand, M; Colnenne-David, C; Debaeke, P; Munier-Jolain, N; Jeuffroy, M H; Richard, G; Makowski, D
2014-03-20
Pesticides pose serious threats to both human health and the environment. In Europe, farmers are encouraged to reduce their use, and in France a recent environmental policy fixed a target of halving the pesticide use by 2018. Organic and integrated cropping systems have been proposed as possible solutions for reducing pesticide use, but the effect of reducing pesticide use on crop yield remains unclear. Here we use a set of cropping system experiments to quantify the yield losses resulting from a reduction of pesticide use for winter wheat in France. Our estimated yield losses resulting from a 50% reduction in pesticide use ranged from 5 to 13% of the yield obtained with the current pesticide use. At the scale of the whole country, these losses would decrease the French wheat production by about 2 to 3 millions of tons, which represent about 15% of the French wheat export.
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).
Root-Knot Nematode Management in Double-Cropped Plasticulture Vegetables
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
Using observed warming to identify hazards to Mozambique maize production
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.
Probabilistic Description of the Hydrologic Risk in Agriculture
NASA Astrophysics Data System (ADS)
Vico, G.; Porporato, A. M.
2011-12-01
Supplemental irrigation represents one of the main strategies to mitigate the effects of climatic variability on agroecosystems productivity and profitability, at the expenses of increasing water requirements for irrigation purposes. Optimizing water allocation for crop yield preservation and sustainable development needs to account for hydro-climatic variability, which is by far the main source of uncertainty affecting crop yields and irrigation water requirements. In this contribution, a widely applicable probabilistic framework is proposed to quantitatively define the hydrologic risk of yield reduction for both rainfed and irrigated agriculture. The occurrence of rainfall events and irrigation applications are linked probabilistically to crop development during the growing season. Based on these linkages, long-term and real-time yield reduction risk indices are defined as a function of climate, soil and crop parameters, as well as irrigation strategy. The former risk index is suitable for long-term irrigation strategy assessment and investment planning, while the latter risk index provides a rigorous probabilistic quantification of the emergence of drought conditions during a single growing season. This probabilistic framework allows also assessing the impact of limited water availability on crop yield, thus guiding the optimal allocation of water resources for human and environmental needs. Our approach employs relatively few parameters and is thus easily and broadly applicable to different crops and sites, under current and future climate scenarios, thus facilitating the assessment of the impact of increasingly frequent water shortages on agricultural productivity, profitability, and sustainability.
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.
NASA Astrophysics Data System (ADS)
Chen, H.; Yu, C.; Li, C.
2015-12-01
Sustainable agricultural intensification demand optimum resource managements of agro-ecosystems. Detailed information on the impacts of water use and nutrient application on agro-ecosystem services including crop yields, greenhouse gas (GHG) emissions and nitrogen (N) loss is the key to guide field managements. In this study, we use the DeNitrification-DeComposition (DNDC) model to simulate the biogeochemical processes for rice rotated cropping systems in China. We set varied scenarios of water use in more than 1600 counties, and derived optimal rates of N application for each county in accordance to water use scenarios. Our results suggest that 0.88 ± 0.33 Tg per year (mean ± standard deviation) of synthetic N could be reduced without reducing rice yields, which accounts for 15.7 ± 5.9% of current N application in China. Field managements with shallow flooding and optimal N applications could enhance ecosystem services on a national scale, leading to 34.3% reduction of GHG emissions (CH4, N2O, and CO2), 2.8% reduction of overall N loss (NH3 volatilization, denitrification and N leaching) and 1.7% increase of rice yields, as compared to current management conditions. Among provinces with major rice production, Jiangsu, Yunnan, Guizhou, and Hubei could achieve more than 40% reduction of GHG emissions under appropriate water managements, while Zhejiang, Guangdong, and Fujian could reduce more than 30% N loss with optimal N applications. Our modeling efforts suggest that China is likely to benefit from reforming water and fertilization managements for rice rotated cropping system in terms of sustainable crop yields, GHG emission mitigation and N loss reduction, and the reformation should be prioritized in the above-mentioned provinces. Keywords: water regime, nitrogen fertilization, sustainable management, ecological modeling, DNDC
Wei Gao; Youfei Zheng; James R. Slusser; Gordon M. Heisler
2003-01-01
The stratospheric ozone depletion and enhanced solar ultraviolet-B (UV-B) irradiance may have adverse impacts on the productivity of agricultural crops. The effect of UV-B enhancements on agricultural crops includes reduction in yield, alteration in species competition, decrease in photosynthetic activity, susceptibility to disease, and changes in structure and...
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
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.
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.
Analytical steady-state solutions for water-limited cropping systems using saline irrigation water
NASA Astrophysics Data System (ADS)
Skaggs, T. H.; Anderson, R. G.; Corwin, D. L.; Suarez, D. L.
2014-12-01
Due to the diminishing availability of good quality water for irrigation, it is increasingly important that irrigation and salinity management tools be able to target submaximal crop yields and support the use of marginal quality waters. In this work, we present a steady-state irrigated systems modeling framework that accounts for reduced plant water uptake due to root zone salinity. Two explicit, closed-form analytical solutions for the root zone solute concentration profile are obtained, corresponding to two alternative functional forms of the uptake reduction function. The solutions express a general relationship between irrigation water salinity, irrigation rate, crop salt tolerance, crop transpiration, and (using standard approximations) crop yield. Example applications are illustrated, including the calculation of irrigation requirements for obtaining targeted submaximal yields, and the generation of crop-water production functions for varying irrigation waters, irrigation rates, and crops. Model predictions are shown to be mostly consistent with existing models and available experimental data. Yet the new solutions possess advantages over available alternatives, including: (i) the solutions were derived from a complete physical-mathematical description of the system, rather than based on an ad hoc formulation; (ii) the analytical solutions are explicit and can be evaluated without iterative techniques; (iii) the solutions permit consideration of two common functional forms of salinity induced reductions in crop water uptake, rather than being tied to one particular representation; and (iv) the utilized modeling framework is compatible with leading transient-state numerical models.
THE USE OF AIR QUALITY FORECASTS TO ASSESS IMPACTS OF AIR POLLUTION ON CROPS
Assessing O3 damage to crops is challenging due to the difficulties in determining the reduction in crop yield that results from exposure to surface O3, for which monitors are limited and deployed mostly in non-rural areas. This work explores the potential b...
Qingjiang Hou; James Brandle; Kenneth Hubbard; Michele Schoeneberger; Carlos Nieto; Charles Francis
2003-01-01
Root-pruning is generally recommended as an appropriate treatment to reduce competition for soil water and/or nutrients and suppression of crop yield in areas adjacent to windbreaks. Several recent studies suggest, however, that factors other than soil water might be causing yield reduction at the interface. For two consecutive years, we evaluated root-pruning effects...
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.
NASA Astrophysics Data System (ADS)
Chukalla, Abebe D.; Krol, Maarten S.; Hoekstra, Arjen Y.
2018-06-01
Grey water footprint (WF) reduction is essential given the increasing water pollution associated with food production and the limited assimilation capacity of fresh water. Fertilizer application can contribute significantly to the grey WF as a result of nutrient leaching to groundwater and runoff to streams. The objective of this study is to explore the effect of the nitrogen application rate (from 25 to 300 kg N ha-1), nitrogen form (inorganic N or manure N), tillage practice (conventional or no-tillage) and irrigation strategy (full or deficit irrigation) on the nitrogen load to groundwater and surface water, crop yield and the N-related grey water footprint of crop production by a systematic model-based assessment. As a case study, we consider irrigated maize grown in Spain on loam soil in a semi-arid environment, whereby we simulate the 20-year period 1993-2012. The water and nitrogen balances of the soil and plant growth at the field scale were simulated with the Agricultural Policy Environmental eXtender (APEX) model. As a reference management package, we assume the use of inorganic N (nitrate), conventional tillage and full irrigation. For this reference, the grey WF at a usual N application rate of 300 kg N ha-1 (with crop yield of 11.1 t ha-1) is 1100 m3 t-1, which can be reduced by 91 % towards 95 m3 t-1 when the N application rate is reduced to 50 kg N ha-1 (with a yield of 3.7 t ha-1). The grey WF can be further reduced to 75 m3 t-1 by shifting the management package to manure N and deficit irrigation (with crop yield of 3.5 t ha-1). Although water pollution can thus be reduced dramatically, this comes together with a great yield reduction, and a much lower water productivity (larger green plus blue WF) as well. The overall (green, blue and grey) WF per tonne is found to be minimal at an N application rate of 150 kg N ha-1, with manure, no-tillage and deficit irrigation (with crop yield of 9.3 t ha-1). The paper shows that there is a trade-off between grey WF and crop yield, as well as a trade-off between reducing water pollution (grey WF) and water consumption (green and blue WF). Applying manure instead of inorganic N and deficit instead of full irrigation are measures that reduce both water pollution and water consumption with a 16 % loss in yield.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Leng, Guoyong
Temperature is known to be correlated with crop yields, causing reduction of crop yield with climate warming without adaptations or CO2 fertilization effects. The historical temperature-crop yield relation has often been used for informing future changes. This relationship, however, may change over time following alternations in other environmental factors. Results show that the strength of the relationship between the interannual variability of growing season temperature and corn yield (RGST_CY) has declined in the United States between 1980 and 2010 with a loss in the statistical significance. The regression slope which represents the anomalies in corn yield that occur in associationmore » with 1 degree temperature anomaly has decreased significantly from -6.9%/K of the first half period to -2.4%/K~-3.5%/K of the second half period. This implies that projected corn yield reduction will be overestimated by a fact of 2 in a given warming scenario, if the corn-temperature relation is derived from the earlier historical period. Changes in RGST_CY are mainly observed in Midwest Corn Belt and central High Plains, and are well reproduced by 11 process-based crop models. In Midwest rain-fed systems, the decrease of negative temperature effects coincides with an increase in water availability by precipitation. In irrigated areas where water stress is minimized, the decline of beneficial temperature effects is significantly related to the increase in extreme hot days. The results indicate that an extrapolation of historical yield response to temperature may bias the assessment of agriculture vulnerability to climate change. Efforts to reduce climate impacts on agriculture should pay attention not only to climate change, but also to changes in climate-crop yield relations. There are some caveats that should be acknowledged as the analysis is restricted to the changes in the linear relation between growing season mean temperature and corn yield for the specific study period.« less
Leng, Guoyong
2017-12-15
Temperature is known to be correlated with crop yields, causing reduction of crop yield with climate warming without adaptations or CO 2 fertilization effects. The historical temperature-crop yield relation has often been used for informing future changes. This relationship, however, may change over time following alternations in other environmental factors. Results show that the strength of the relationship between the interannual variability of growing season temperature and corn yield (R GST_CY ) has declined in the United States between 1980 and 2010 with a loss in the statistical significance. The regression slope which represents the anomalies in corn yield that occur in association with 1 degree temperature anomaly has decreased significantly from -6.9%/K of the first half period to -2.4%/K--3.5%/K of the second half period. This implies that projected corn yield reduction will be overestimated by a fact of 2 in a given warming scenario, if the corn-temperature relation is derived from the earlier historical period. Changes in R GST_CY are mainly observed in Midwest Corn Belt and central High Plains, but are partly reproduced by 11 process-based crop models. In Midwest rain-fed systems, the decrease of negative temperature effects coincides with an increase in water availability by precipitation. In irrigated areas where water stress is minimized, the decline of beneficial temperature effects is significantly related to the increase in extreme hot days. The results indicate that an extrapolation of historical yield response to temperature may bias the assessment of agriculture vulnerability to climate change. Efforts to reduce climate impacts on agriculture should pay attention not only to climate change, but also to changes in climate-crop yield relations. There are some caveats that should be acknowledged as the analysis is restricted to the changes in the linear relation between growing season mean temperature and corn yield for the specific study period. Copyright © 2017 Elsevier B.V. All rights reserved.
Analysing reduced tillage practices within a bio-economic modelling framework.
Townsend, Toby J; Ramsden, Stephen J; Wilson, Paul
2016-07-01
Sustainable intensification of agricultural production systems will require changes in farm practice. Within arable cropping systems, reducing the intensity of tillage practices (e.g. reduced tillage) potentially offers one such sustainable intensification approach. Previous researchers have tended to examine the impact of reduced tillage on specific factors such as yield or weed burden, whilst, by definition, sustainable intensification necessitates a system-based analysis approach. Drawing upon a bio-economic optimisation model, 'MEETA', we quantify trade-off implications between potential yield reductions, reduced cultivation costs and increased crop protection costs. We extend the MEETA model to quantify farm-level net margin, in addition to quantifying farm-level gross margin, net energy, and greenhouse gas emissions. For the lowest intensity tillage system, zero tillage, results demonstrate financial benefits over a conventional tillage system even when the zero tillage system includes yield penalties of 0-14.2% (across all crops). Average yield reductions from zero tillage literature range from 0 to 8.5%, demonstrating that reduced tillage offers a realistic and attainable sustainable intensification intervention, given the financial and environmental benefits, albeit that yield reductions will require more land to compensate for loss of calories produced, negating environmental benefits observed at farm-level. However, increasing uptake of reduced tillage from current levels will probably require policy intervention; an extension of the recent changes to the CAP ('Greening') provides an opportunity to do this.
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
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.
The Response of Durum Wheat to the Preceding Crop in a Mediterranean Environment
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
Interactions of Mean Climate Change and Climate Variability on Food Security Extremes
NASA Technical Reports Server (NTRS)
Ruane, Alexander C.; McDermid, Sonali; Mavromatis, Theodoros; Hudson, Nicholas; Morales, Monica; Simmons, John; Prabodha, Agalawatte; Ahmad, Ashfaq; Ahmad, Shakeel; Ahuja, Laj R.
2015-01-01
Recognizing that climate change will affect agricultural systems both through mean changes and through shifts in climate variability and associated extreme events, we present preliminary analyses of climate impacts from a network of 1137 crop modeling sites contributed to the AgMIP Coordinated Climate-Crop Modeling Project (C3MP). At each site sensitivity tests were run according to a common protocol, which enables the fitting of crop model emulators across a range of carbon dioxide, temperature, and water (CTW) changes. C3MP can elucidate several aspects of these changes and quantify crop responses across a wide diversity of farming systems. Here we test the hypothesis that climate change and variability interact in three main ways. First, mean climate changes can affect yields across an entire time period. Second, extreme events (when they do occur) may be more sensitive to climate changes than a year with normal climate. Third, mean climate changes can alter the likelihood of climate extremes, leading to more frequent seasons with anomalies outside of the expected conditions for which management was designed. In this way, shifts in climate variability can result in an increase or reduction of mean yield, as extreme climate events tend to have lower yield than years with normal climate.C3MP maize simulations across 126 farms reveal a clear indication and quantification (as response functions) of mean climate impacts on mean yield and clearly show that mean climate changes will directly affect the variability of yield. Yield reductions from increased climate variability are not as clear as crop models tend to be less sensitive to dangers on the cool and wet extremes of climate variability, likely underestimating losses from water-logging, floods, and frosts.
NASA Astrophysics Data System (ADS)
Fung, K. M.; Tai, A. P. K.; Yong, T.; Liu, X.
2017-12-01
The fast-growing world population will impose a severe pressure on our current global food production system. Meanwhile, boosting crop yield by increasing fertilizer use comes with a cascade of environmental problems including air pollution. In China, agricultural activities contribute to 95% of total ammonia emissions. Such emissions are attributable to 20% of the fine particulate matter (PM2.5) formed in the downwind regions, which imposes severe health risks to the citizens. Field studies of soybean intercropping have demonstrated its potential to enhance crop yield, lower fertilizer use, and thus reduce ammonia emissions by taking advantage of legume nitrogen fixation and enabling mutualistic crop-crop interactions between legumes and non-legume crops. In our work, we revise the process-based biogeochemical model, DeNitrification-DeComposition (DNDC) to capture the belowground interactions of intercropped crops and show that with intercropping, only 58% of fertilizer is required to yield the same maize production of its monoculture counterpart, corresponding to a reduction in ammonia emission by 43% over China. Using the GEOS-Chem global 3-D chemical transport model, we estimate that such ammonia reduction can lessen downwind inorganic PM2.5 by up to 2.1% (equivalent to 1.3 μg m-3), which saves the Chinese air pollution-related health costs by up to US$1.5 billion each year. With the more enhanced crop growth and land management algorithms in the Community Land Model (CLM), we also implement into CLM the new parametrization of the belowground interactions to simulate large-scale adoption of intercropping around the globe and study their beneficial effects on food production, fertilizer usage and ammonia reduction. This study can serve as a scientific basis for policy makers and intergovernmental organizations to consider promoting large-scale intercropping to maintain a sustainable global food supply to secure both future crop production and air quality.
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.
Pesticides reduce symbiotic efficiency of nitrogen-fixing rhizobia and host plants
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
USDA-ARS?s Scientific Manuscript database
Cotton (Gossypium hirsutum L.) yield losses by southern root-knot nematode [Meloidogyne incognita (Kofoid & White) Chitwood] (RKN) are usually estimated after significant damage has been caused. However, estimation of potential yield reduction before planting is possible by using crop simulation mod...
Characterization of yield reduction in Ethiopia using a GIS-based crop water balance model
Senay, G.B.; Verdin, J.
2003-01-01
In many parts of sub-Saharan Africa, subsistence agriculture is characterized by significant fluctuations in yield and production due to variations in moisture availability to staple crops. Widespread drought can lead to crop failures, with associated deterioration in food security. Ground data collection networks are sparse, so methods using geospatial rainfall estimates derived from satellite and gauge observations, where available, have been developed to calculate seasonal crop water balances. Using conventional crop production data for 4 years in Ethiopia (1996-1999), it was found that water-limited and water-unlimited growing regions can be distinguished. Furthermore, maize growing conditions are also indicative of conditions for sorghum. However, another major staple, teff, was found to behave sufficiently differently from maize to warrant studies of its own.
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
Global Synthesis of Drought Effects on Food Legume Production
Daryanto, Stefani; Wang, Lixin; Jacinthe, Pierre-André
2015-01-01
Food legume crops play important roles in conservation farming systems and contribute to food security in the developing world. However, in many regions of the world, their production has been adversely affected by drought. Although water scarcity is a severe abiotic constraint of legume crops productivity, it remains unclear how the effects of drought co-vary with legume species, soil texture, agroclimatic region, and drought timing. To address these uncertainties, we collected literature data between 1980 and 2014 that reported monoculture legume yield responses to drought under field conditions, and analyzed this data set using meta-analysis techniques. Our results showed that the amount of water reduction was positively related with yield reduction, but the extent of the impact varied with legume species and the phenological state during which drought occurred. Overall, lentil (Lens culinaris), groundnut (Arachis hypogaea), and pigeon pea (Cajanus cajan) were found to experience lower drought-induced yield reduction compared to legumes such as cowpea (Vigna unguiculata) and green gram (Vigna radiate). Yield reduction was generally greater when legumes experienced drought during their reproductive stage compared to during their vegetative stage. Legumes grown in soil with medium texture also exhibited greater yield reduction compared to those planted on soil of either coarse or fine texture. In contrast, regions and their associated climatic factors did not significantly affect legume yield reduction. In the face of changing climate, our study provides useful information for agricultural planning and research directions for development of drought-resistant legume species to improve adaptation and resilience of agricultural systems in the drought-prone regions of the world. PMID:26061704
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
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.
Biological control as an alternative measure for TPB in Mississippi
USDA-ARS?s Scientific Manuscript database
The tarnished plant bug (TPB), Lygus lineolaris (Palisot de Beauvois), is a common pest of the main agricultural crops in Mississippi, particularly of cotton in the Mississippi Delta. TPB in cotton is economically important through reductions of crop yield and losses may vary depend on TPB populatio...
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.
Linkages among climate change, crop yields and Mexico–US cross-border migration
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.
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.
NASA Astrophysics Data System (ADS)
Chukalla, Abebe D.; Krol, Maarten S.; Hoekstra, Arjen Y.
2017-07-01
Reducing the water footprint (WF) of the process of growing irrigated crops is an indispensable element in water management, particularly in water-scarce areas. To achieve this, information on marginal cost curves (MCCs) that rank management packages according to their cost-effectiveness to reduce the WF need to support the decision making. MCCs enable the estimation of the cost associated with a certain WF reduction target, e.g. towards a given WF permit (expressed in m3 ha-1 per season) or to a certain WF benchmark (expressed in m3 t-1 of crop). This paper aims to develop MCCs for WF reduction for a range of selected cases. AquaCrop, a soil-water-balance and crop-growth model, is used to estimate the effect of different management packages on evapotranspiration and crop yield and thus the WF of crop production. A management package is defined as a specific combination of management practices: irrigation technique (furrow, sprinkler, drip or subsurface drip); irrigation strategy (full or deficit irrigation); and mulching practice (no, organic or synthetic mulching). The annual average cost for each management package is estimated as the annualized capital cost plus the annual costs of maintenance and operations (i.e. costs of water, energy and labour). Different cases are considered, including three crops (maize, tomato and potato); four types of environment (humid in UK, sub-humid in Italy, semi-arid in Spain and arid in Israel); three hydrologic years (wet, normal and dry years) and three soil types (loam, silty clay loam and sandy loam). For each crop, alternative WF reduction pathways were developed, after which the most cost-effective pathway was selected to develop the MCC for WF reduction. When aiming at WF reduction one can best improve the irrigation strategy first, next the mulching practice and finally the irrigation technique. Moving from a full to deficit irrigation strategy is found to be a no-regret measure: it reduces the WF by reducing water consumption at negligible yield reduction while reducing the cost for irrigation water and the associated costs for energy and labour. Next, moving from no to organic mulching has a high cost-effectiveness, reducing the WF significantly at low cost. Finally, changing from sprinkler or furrow to drip or subsurface drip irrigation reduces the WF, but at a significant cost.
Increasing influence of heat stress on French maize yields from the 1960s to the 2030s
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
Jeong, Hanseok; Bhattarai, Rabin
2018-05-01
It is vital to manage the excessive use of nitrogen (N) fertilizer in corn production, the single largest consumer of N fertilizer in the United States, in order to achieve more sustainable agroecosystems. This study comprehensively explored the effects of N fertilization alternatives on nitrate loss and crop yields using the Root Zone Water Quality Model (RZWQM) in tile-drained fields in central Illinois. The RZWQM was tested for the prediction of tile flow, nitrate loss, and crop yields using eight years (1993-2000) of observed data and showed satisfactory model performances from statistical and graphical evaluations. Our model simulations demonstrated the maximum return to nitrogen (MRTN) rate (193 kgha -1 ), a newly advised N recommendation by the Illinois Nutrient Loss Reduction Strategy (INLRS), can be further reduced. Nitrate loss was reduced by 10.3% and 29.8%, but corn yields decreased by 0.3% and 1.9% at 156 and 150 kgha -1 of N fertilizer rate in the study sites A and E, respectively. Although adjustment of N fertilization timing presented a further reduction in nitrate loss, there was no optimal timing to ensure nitrate loss reduction and corn productivity. For site A, 100% spring application was the most productive and 40% fall, 10% pre-plant, and 50% side dress application generated the lowest nitrate loss. For site E, the conventional N application timing was verified as the best practice in both corn production and nitrate loss reduction. Compared to surface broadcast placement, injected N fertilizer in spring increased corn yield, but may also escalate nitrate loss. This study presented the need of an adaptive N fertilizer management due to the heterogeneity in agricultural systems, and raised the importance of timing and placement of N fertilizer, as well as further reduction in fertilizer rate to devise a better in-field N management practice. Copyright © 2018 Elsevier Ltd. All rights reserved.
Contrasting effects of landscape composition on crop yield mediated by specialist herbivores.
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.
Erb, Karl-Heinz; Haberl, Helmut; Plutzar, Christoph
2012-08-01
The future bioenergy crop potential depends on (1) changes in the food system (food demand, agricultural technology), (2) political stability and investment security, (3) biodiversity conservation, (4) avoidance of long carbon payback times from deforestation, and (5) energy crop yields. Using a biophysical biomass-balance model, we analyze how these factors affect global primary bioenergy potentials in 2050. The model calculates biomass supply and demand balances for eleven world regions, eleven food categories, seven food crop types and two livestock categories, integrating agricultural forecasts and scenarios with a consistent global land use and NPP database. The TREND scenario results in a global primary bioenergy potential of 77 EJ/yr, alternative assumptions on food-system changes result in a range of 26-141 EJ/yr. Exclusion of areas for biodiversity conservation and inaccessible land in failed states reduces the bioenergy potential by up to 45%. Optimistic assumptions on future energy crop yields increase the potential by up to 48%, while pessimistic assumptions lower the potential by 26%. We conclude that the design of sustainable bioenergy crop production policies needs to resolve difficult trade-offs such as food vs. energy supply, renewable energy vs. biodiversity conservation or yield growth vs. reduction of environmental problems of intensive agriculture.
Erb, Karl-Heinz; Haberl, Helmut; Plutzar, Christoph
2012-01-01
The future bioenergy crop potential depends on (1) changes in the food system (food demand, agricultural technology), (2) political stability and investment security, (3) biodiversity conservation, (4) avoidance of long carbon payback times from deforestation, and (5) energy crop yields. Using a biophysical biomass-balance model, we analyze how these factors affect global primary bioenergy potentials in 2050. The model calculates biomass supply and demand balances for eleven world regions, eleven food categories, seven food crop types and two livestock categories, integrating agricultural forecasts and scenarios with a consistent global land use and NPP database. The TREND scenario results in a global primary bioenergy potential of 77 EJ/yr, alternative assumptions on food-system changes result in a range of 26–141 EJ/yr. Exclusion of areas for biodiversity conservation and inaccessible land in failed states reduces the bioenergy potential by up to 45%. Optimistic assumptions on future energy crop yields increase the potential by up to 48%, while pessimistic assumptions lower the potential by 26%. We conclude that the design of sustainable bioenergy crop production policies needs to resolve difficult trade-offs such as food vs. energy supply, renewable energy vs. biodiversity conservation or yield growth vs. reduction of environmental problems of intensive agriculture. PMID:23576836
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
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).
NASA Astrophysics Data System (ADS)
Valkama, Elena; Lemola, Riitta; Känkänen, Hannu; Turtola, Eila
2016-04-01
Sustainable farms produce adequate amounts of a high-quality product, protect their resources and are both environmentally friendly and economically profitable. Nitrogen (N) fertilization decisively influences the cereal yields as well as increases soil N balance (N input in fertilizer - N output in harvested yield), thereby leading to N losses to the environment. However, while N input reduction affects soil N balance, such approach would markedly reduce N leaching loss only in case of abnormally high N balances. As an alternative approach, the growing of catch crops aims to prevent nutrient leaching in autumn after harvest and during the following winter, but due to competition, catch crops may also reduce yields of the main crop. Although studies have explored the environmental effects of catch crops in cereal production in the Nordic countries (Denmark, Sweden, Finland and Norway) during the past 40 years, none has yet carried out a meta-analysis. We quantitatively summarized 35 studies on the effect of catch crops (non-legume and legume) undersown in spring cereals on N leaching loss or its risk as estimated by the content of soil nitrate N or its sum with ammonium in late autumn. The meta-analysis also included the grain yield and N content of spring cereals. To identify sources of variation, we studied the effects of soil texture and management (ploughing time, the amount of N applied, fertilizer type), as well as climatic (annual precipitation) and experimental conditions (duration of experiments, lysimeter vs. field experiments). Finally, we examined whether the results differed between the countries or over the decades. Compared to control groups with no catch crops, non-legume catch crops, mainly ryegrass species, reduced N leaching loss by 50% on average, and soil nitrate N or inorganic N by 35% in autumn. Italian ryegrass depleted soil N more effectively (by 60%) than did perennial ryegrass or Westerwolds ryegrass (by 25%). In contrast, legumes (white and red clovers) did not diminish the risk for N leaching. Otherwise, the effect on N leaching and its risk were consistent across the studies conducted in different countries on clay and coarse-textured mineral soils with different ploughing times, N fertilization rates (50-160 kg/ ha), and amounts of annual precipitation (480-1040 mm). Non-legume catch crops reduced grain yield by 3% with no changes in grain N content. In contrast, legumes and mixed catch crops increased both grain yield and grain N content by 6%. In spring cereal production, undersown non-legume catch crops are deemed a universal and effective method for reducing N leaching loss across the various soils, management practices and weather conditions in the Nordic countries. The environmental benefits of using non-legume catch crops appear considerable compared to the adverse reduction in grain yields, amounting to only a few percent. Catch crops are advisable for fields at high risk for N leaching (e.g., sandy soils or soils and crops requiring high N fertilization).
The role of ants, birds and bats for ecosystem functions and yield in oil palm plantations.
Denmead, Lisa H; Darras, Kevin; Clough, Yann; Diaz, Patrick; Grass, Ingo; Hoffmann, Munir P; Nurdiansyah, Fuad; Fardiansah, Rico; Tscharntke, Teja
2017-07-01
One of the world's most important and rapidly expanding crops, oil palm, is associated with low levels of biodiversity. Changes in predator communities might alter ecosystem services and subsequently sustainable management but these links have received little attention to date. Here, for the first time, we manipulated ant and flying vertebrate (birds and bats) access to oil palms in six smallholder plantations in Sumatra (Indonesia) and measured effects on arthropod communities, related ecosystem functions (herbivory, predation, decomposition and pollination) and crop yield. Arthropod predators increased in response to reductions in ant and bird access, but the overall effect of experimental manipulations on ecosystem functions was minimal. Similarly, effects on yield were not significant. We conclude that ecosystem functions and productivity in oil palm are, under current levels of low pest pressure and large pollinator populations, robust to large reductions of major predators. © 2017 by the Ecological Society of America.
Avnery, Shiri; Mauzerall, Denise L; Fiore, Arlene M
2013-01-01
Meeting the projected 50% increase in global grain demand by 2030 without further environmental degradation poses a major challenge for agricultural production. Because surface ozone (O3) has a significant negative impact on crop yields, one way to increase future production is to reduce O3-induced agricultural losses. We present two strategies whereby O3 damage to crops may be reduced. We first examine the potential benefits of an O3 mitigation strategy motivated by climate change goals: gradual emission reductions of methane (CH4), an important greenhouse gas and tropospheric O3 precursor that has not yet been targeted for O3 pollution abatement. Our second strategy focuses on adapting crops to O3 exposure by selecting cultivars with demonstrated O3 resistance. We find that the CH4 reductions considered would increase global production of soybean, maize, and wheat by 23–102 Mt in 2030 – the equivalent of a ∼2–8% increase in year 2000 production worth $3.5–15 billion worldwide (USD2000), increasing the cost effectiveness of this CH4 mitigation policy. Choosing crop varieties with O3 resistance (relative to median-sensitivity cultivars) could improve global agricultural production in 2030 by over 140 Mt, the equivalent of a 12% increase in 2000 production worth ∼$22 billion. Benefits are dominated by improvements for wheat in South Asia, where O3-induced crop losses would otherwise be severe. Combining the two strategies generates benefits that are less than fully additive, given the nature of O3 effects on crops. Our results demonstrate the significant potential to sustainably improve global agricultural production by decreasing O3-induced reductions in crop yields. PMID:23504903
NASA Astrophysics Data System (ADS)
Xu, Hanqing; Tian, Zhan; Zhong, Honglin; Fan, Dongli; Shi, Runhe; Niu, Yilong; He, Xiaogang; Chen, Maosi
2017-09-01
Peanut is one of the major edible vegetable oil crops in China, whose growth and yield are very sensitive to climate change. In addition, agriculture climate resources are expected to be redistributed under climate change, which will further influence the growth, development, cropping patterns, distribution and production of peanut. In this study, we used the DSSAT-Peanut model to examine the climate change impacts on peanut production, oil industry and oil food security in China. This model is first calibrated using site observations including 31 years' (1981-2011) climate, soil and agronomy data. This calibrated model is then employed to simulate the future peanut yield based on 20 climate scenarios from 5 Global Circulation Models (GCMs) developed by the InterSectoral Impact Model Intercomparison Project (ISIMIP) driven by 4 Representative Concentration Pathways (RCPs). Results indicate that the irrigated peanut yield will decrease 2.6% under the RCP 2.6 scenario, 9.9% under the RCP 4.5 scenario and 29% under the RCP 8.5 scenario, respectively. Similarly, the rain-fed peanut yield will also decrease, with a 2.5% reduction under the RCP 2.6 scenario, 11.5% reduction under the RCP 4.5 scenario and 30% reduction under the RCP 8.5 scenario, respectively.
Effect of selenium application on arsenic uptake in rice (Oryza sativa L.).
Kaur, Sumandeep; Singh, Dhanwinder; Singh, Kuldip
2017-09-01
Alluvial aquifers of the agrarian state of Punjab of southwestern arid zone used for irrigation of rice crops are rich in arsenic concentration. In the present study, rice (Oryza sativa L.) crops were raised in pots in a greenhouse with a purpose to study whether selenium (Se) application was effective in ameliorating As uptake. The rice crop was irrigated with arsenic laced water (0, 2.5, 5.0, 10.0 μM As L -1 ) throughout the growing period, without and with selenium (0.05 and 0.10 mg kg -1 ) added through mustard biomass, grown ex situ in seleniferous soil. Arsenic uptake and dry matter yield in different parts of the rice crop were assayed after application of As alone and simultaneous supplementations (As + Se). An antagonistic interaction between Se and As was observed. Addition of As through irrigation water significantly reduced yield of rice grain, straw and root. However, subsequent addition of Se helped in mitigating the harmful effect of As and countered the yield reduction caused due to As toxicity. The effect of Se on dry matter yield was more pronounced at its higher dose (0.10 mg kg -1 ) as compared to its lower dose (0.05 mg kg -1 ). The presence of Se either alone or added along with As significantly reduced the As concentration and its uptake by different parts of rice and higher reduction in As concentration was observed with addition of the highest level of applied Se (0.10 mg kg -1 ). Our observations indicated that Se supplementation might be favourable to reduce As accumulation and toxicity in rice crops.
Electrical resistivity tomography to delineate greenhouse soil variability
NASA Astrophysics Data System (ADS)
Rossi, R.; Amato, M.; Bitella, G.; Bochicchio, R.
2013-03-01
Appropriate management of soil spatial variability is an important tool for optimizing farming inputs, with the result of yield increase and reduction of the environmental impact in field crops. Under greenhouses, several factors such as non-uniform irrigation and localized soil compaction can severely affect yield and quality. Additionally, if soil spatial variability is not taken into account, yield deficiencies are often compensated by extra-volumes of crop inputs; as a result, over-irrigation and overfertilization in some parts of the field may occur. Technology for spatially sound management of greenhouse crops is therefore needed to increase yield and quality and to address sustainability. In this experiment, 2D-electrical resistivity tomography was used as an exploratory tool to characterize greenhouse soil variability and its relations to wild rocket yield. Soil resistivity well matched biomass variation (R2=0.70), and was linked to differences in soil bulk density (R2=0.90), and clay content (R2=0.77). Electrical resistivity tomography shows a great potential in horticulture where there is a growing demand of sustainability coupled with the necessity of stabilizing yield and product quality.
USDA-ARS?s Scientific Manuscript database
Whether yield reduction risk of cotton fertilized with fall-applied poultry litter in regions with warm fall or winter months can be minimized by applying the litter in subsurface bands in conjunction with winter cover crop is unknown. A field study was conducted in Mississippi to test whether litte...
USDA-ARS?s Scientific Manuscript database
Yield reduction and reduced crop vigor, resulting from soil acidification, are of increasing concern in eastern Washington and northern Idaho. In this region, soil pH has been decreasing at an accelerated rate, primarily due to the long-term use of ammonium based fertilizers. In no-till systems, the...
Plausible rice yield losses under future climate warming.
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.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Woodbury, Peter B.; Kemanian, Armen R.; Jacobson, Michael
Replacing row crops with perennial bioenergy crops may reduce nitrogen (N) loading to surface waters. We estimated the benefits, costs, and potential for replacing maize with switchgrass to meet required N loading reduction targets for the Chesapeake Bay (CB) of 26.9 Gg -1. After subtracting the potential reduction in N loading due to improved N fertilizer practices for maize, a further 22.8 Gg reduction is required. Replacing maize with fertilized switchgrass could reduce N loading to the CB by 18 kg ha -1 y -1, meeting 31% of the N reduction target. The break-even price of fertilized switchgrass to providemore » the same profit as maize in the CB is 111 $Mg -1 (oven-dry basis throughout). Growers replacing maize with switchgrass could receive an ecosystem service payment of 148 ha -1 based on the price paid in Maryland for planting a rye cover crop. For our estimated average switchgrass yield of 9.9 Mg ha -1, and the greater N loading reduction of switchgrass compared to a cover crop, this equates to 24 dollars Mg -1. The annual cost of this ecosystem service payment to induce switchgrass planting is 13.29 dollars kg -1 of N. Using the POLYSYS model to account for competition among food, feed, and biomass markets, we found that with the ecosystem service payment for switchgrass of 25 $ Mg -1 added to a farm-gate price of 111 dollars Mg -1, 11% of the N loading reduction target could be met while also producing 1.3 Tg of switchgrass, potentially yielding 420 dam 3 y -1 of ethanol.« less
Woodbury, Peter B.; Kemanian, Armen R.; Jacobson, Michael; ...
2017-02-03
Replacing row crops with perennial bioenergy crops may reduce nitrogen (N) loading to surface waters. We estimated the benefits, costs, and potential for replacing maize with switchgrass to meet required N loading reduction targets for the Chesapeake Bay (CB) of 26.9 Gg -1. After subtracting the potential reduction in N loading due to improved N fertilizer practices for maize, a further 22.8 Gg reduction is required. Replacing maize with fertilized switchgrass could reduce N loading to the CB by 18 kg ha -1 y -1, meeting 31% of the N reduction target. The break-even price of fertilized switchgrass to providemore » the same profit as maize in the CB is 111 $Mg -1 (oven-dry basis throughout). Growers replacing maize with switchgrass could receive an ecosystem service payment of 148 ha -1 based on the price paid in Maryland for planting a rye cover crop. For our estimated average switchgrass yield of 9.9 Mg ha -1, and the greater N loading reduction of switchgrass compared to a cover crop, this equates to 24 dollars Mg -1. The annual cost of this ecosystem service payment to induce switchgrass planting is 13.29 dollars kg -1 of N. Using the POLYSYS model to account for competition among food, feed, and biomass markets, we found that with the ecosystem service payment for switchgrass of 25 $ Mg -1 added to a farm-gate price of 111 dollars Mg -1, 11% of the N loading reduction target could be met while also producing 1.3 Tg of switchgrass, potentially yielding 420 dam 3 y -1 of ethanol.« less
NASA Astrophysics Data System (ADS)
Lee, K.; Leng, G.; Huang, M.; Sheffield, J.; Zhao, G.; Gao, H.
2017-12-01
Texas has the largest farm area in the U.S, and its revenue from crop production ranks third overall. With the changing climate, hydrological extremes such as droughts are becoming more frequent and intensified, causing significant yield reduction in rainfed agricultural systems. The objective of this study is to investigate the potential impacts of agricultural drought on crop yields (corn, sorghum, and wheat) under a changing climate in Texas. The Variable Infiltration Capacity (VIC) model, which is calibrated and validated over 10 major Texas river basins during the historical period, is employed in this study.The model is forced by a set of statistically downscaled climate projections from Coupled Model Intercomparison Project Phase 5 (CMIP5) model ensembles at a spatial resolution of 1/8°. The CMIP5 projections contain four Representative Concentration Pathways (RCP) that represent different greenhouse gas concentration (4.5 and 8.5 w/m2 are selected in this study). To carry out the analysis, VIC simulations from 1950 to 2099 are first analyzed to investigate how the frequency and severity of agricultural droughts will be altered in Texas (under a changing climate). Second, future crop yields are projected using a statistical crop model. Third, the effects of agricultural drought on crop yields are quantitatively analyzed. The results are expected to contribute to future water resources planning, with a goal of mitigating the negative impacts of future droughts on agricultural production in Texas.
Influence of extreme weather disasters on global crop production.
Lesk, Corey; Rowhani, Pedram; Ramankutty, Navin
2016-01-07
In recent years, several extreme weather disasters have partially or completely damaged regional crop production. While detailed regional accounts of the effects of extreme weather disasters exist, the global scale effects of droughts, floods and extreme temperature on crop production are yet to be quantified. Here we estimate for the first time, to our knowledge, national cereal production losses across the globe resulting from reported extreme weather disasters during 1964-2007. We show that droughts and extreme heat significantly reduced national cereal production by 9-10%, whereas our analysis could not identify an effect from floods and extreme cold in the national data. Analysing the underlying processes, we find that production losses due to droughts were associated with a reduction in both harvested area and yields, whereas extreme heat mainly decreased cereal yields. Furthermore, the results highlight ~7% greater production damage from more recent droughts and 8-11% more damage in developed countries than in developing ones. Our findings may help to guide agricultural priorities in international disaster risk reduction and adaptation efforts.
Impacts of biofuel cultivation on mortality and crop yields
NASA Astrophysics Data System (ADS)
Ashworth, K.; Wild, O.; Hewitt, C. N.
2013-05-01
Ground-level ozone is a priority air pollutant, causing ~ 22,000 excess deaths per year in Europe, significant reductions in crop yields and loss of biodiversity. It is produced in the troposphere through photochemical reactions involving oxides of nitrogen (NOx) and volatile organic compounds (VOCs). The biosphere is the main source of VOCs, with an estimated 1,150TgCyr-1 (~ 90% of total VOC emissions) released from vegetation globally. Isoprene (2-methyl-1,3-butadiene) is the most significant biogenic VOC in terms of mass (around 500TgCyr-1) and chemical reactivity and plays an important role in the mediation of ground-level ozone concentrations. Concerns about climate change and energy security are driving an aggressive expansion of bioenergy crop production and many of these plant species emit more isoprene than the traditional crops they are replacing. Here we quantify the increases in isoprene emission rates caused by cultivation of 72Mha of biofuel crops in Europe. We then estimate the resultant changes in ground-level ozone concentrations and the impacts on human mortality and crop yields that these could cause. Our study highlights the need to consider more than simple carbon budgets when considering the cultivation of biofuel feedstock crops for greenhouse-gas mitigation.
77 FR 6544 - Humanitarian Awards Pilot Program
Federal Register 2010, 2011, 2012, 2013, 2014
2012-02-08
..., medical diagnostics, water purification, more nutritious or higher-yield crops, pollution reduction, and... water filters, sterilization devices, and cleaner sources of energy for light, heat, cooking, or other...
Adimassu, Zenebe; Langan, Simon; Johnston, Robyn; Mekuria, Wolde; Amede, Tilahun
2017-01-01
Research results published regarding the impact of soil and water conservation practices in the highland areas of Ethiopia have been inconsistent and scattered. In this paper, a detailed review and synthesis is reported that was conducted to identify the impacts of soil and water conservation practices on crop yield, surface run-off, soil loss, nutrient loss, and the economic viability, as well as to discuss the implications for an integrated approach and ecosystem services. The review and synthesis showed that most physical soil and water conservation practices such as soil bunds and stone bunds were very effective in reducing run-off, soil erosion and nutrient depletion. Despite these positive impacts on these services, the impact of physical soil and water conservation practices on crop yield was negative mainly due to the reduction of effective cultivable area by soil/stone bunds. In contrast, most agronomic soil and water conservation practices increase crop yield and reduce run-off and soil losses. This implies that integrating physical soil and water conservation practices with agronomic soil and water conservation practices are essential to increase both provisioning and regulating ecosystem services. Additionally, effective use of unutilized land (the area occupied by bunds) by planting multipurpose grasses and trees on the bunds may offset the yield lost due to a reduction in planting area. If high value grasses and trees can be grown on this land, farmers can harvest fodder for animals or fuel wood, both in scarce supply in Ethiopia. Growing of these grasses and trees can also help the stability of the bunds and reduce maintenance cost. Economic feasibility analysis also showed that, soil and water conservation practices became economically more viable if physical and agronomic soil and water conservation practices are integrated.
NASA Astrophysics Data System (ADS)
Adimassu, Zenebe; Langan, Simon; Johnston, Robyn; Mekuria, Wolde; Amede, Tilahun
2017-01-01
Research results published regarding the impact of soil and water conservation practices in the highland areas of Ethiopia have been inconsistent and scattered. In this paper, a detailed review and synthesis is reported that was conducted to identify the impacts of soil and water conservation practices on crop yield, surface run-off, soil loss, nutrient loss, and the economic viability, as well as to discuss the implications for an integrated approach and ecosystem services. The review and synthesis showed that most physical soil and water conservation practices such as soil bunds and stone bunds were very effective in reducing run-off, soil erosion and nutrient depletion. Despite these positive impacts on these services, the impact of physical soil and water conservation practices on crop yield was negative mainly due to the reduction of effective cultivable area by soil/stone bunds. In contrast, most agronomic soil and water conservation practices increase crop yield and reduce run-off and soil losses. This implies that integrating physical soil and water conservation practices with agronomic soil and water conservation practices are essential to increase both provisioning and regulating ecosystem services. Additionally, effective use of unutilized land (the area occupied by bunds) by planting multipurpose grasses and trees on the bunds may offset the yield lost due to a reduction in planting area. If high value grasses and trees can be grown on this land, farmers can harvest fodder for animals or fuel wood, both in scarce supply in Ethiopia. Growing of these grasses and trees can also help the stability of the bunds and reduce maintenance cost. Economic feasibility analysis also showed that, soil and water conservation practices became economically more viable if physical and agronomic soil and water conservation practices are integrated.
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.
Landscape simplification reduces classical biological control and crop yield.
Grab, Heather; Danforth, Bryan; Poveda, Katja; Loeb, Greg
2018-03-01
Agricultural intensification resulting in the simplification of agricultural landscapes is known to negatively impact the delivery of key ecosystem services such as the biological control of crop pests. Both conservation and classical biological control may be influenced by the landscape context in which they are deployed; yet studies examining the role of landscape structure in the establishment and success of introduced natural enemies and their interactions with native communities are lacking. In this study, we investigated the relationship between landscape simplification, classical and conservation biological control services and importantly, the outcome of these interactions for crop yield. We showed that agricultural simplification at the landscape scale is associated with an overall reduction in parasitism rates of crop pests. Additionally, only introduced parasitoids were identified, and no native parasitoids were found in crop habitat, irrespective of agricultural landscape simplification. Pest densities in the crop were lower in landscapes with greater proportions of semi-natural habitats. Furthermore, farms with less semi-natural cover in the landscape and consequently, higher pest numbers, had lower yields than farms in less agriculturally dominated landscapes. Our study demonstrates the importance of landscape scale agricultural simplification in mediating the success of biological control programs and highlights the potential risks to native natural enemies in classical biological control programs against native insects. Our results represent an important contribution to an understanding of the landscape-mediated impacts on crop yield that will be essential to implementing effective policies that simultaneously conserve biodiversity and ecosystem services. © 2018 by the Ecological Society of America.
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.
NASA Astrophysics Data System (ADS)
Hobley, Eleanor; Honermeier, Bernd; Don, Axel; Amelung, Wulf; Kögel-Knabner, Ingrid
2017-04-01
Crop fertilization provides vital plant nutrients (e.g. NPK) to ensure yield security but is also associated with negative environmental impacts. In particular, inorganic, mineral nitrogen (Nmin) fertilization leads to emissions during its energy intensive production as well as Nmin leaching to receiving waters. Incorporating legumes into crop rotations can provide organic N to the soil and subsequent crops, reducing the need for mineral N fertilizer and its negative environmental impacts. An added bonus is the potential to enhance soil organic carbon stocks, thereby reducing atmospheric CO2 concentrations. In this study we assessed the effects of legumes in rotation and fertilization regimes on the depth distribution - down to 1 m - of total soil nitrogen (Ntot), soil organic carbon (SOC) as well as isotopic composition (δ13C, δ15N), electrical conductivity and bulk density as well as agricultural yields at a long-term field experiment in Gießen, Germany. Fertilization had significant but small impacts on the soil chemical environment, most particularly the salt content of the soil, with PK fertilization increasing electrical conductivity throughout the soil profile. Similarly, fertilization resulted in a small reduction of soil pH throughout the soil profile. N fertilization, in particular, significantly increased yields, whereas PK fertilizer had only marginal yield effects, indicating that these systems are N limited. This N limitation was confirmed by significant yield benefits with leguminous crops in rotation, even in combination with mineral N fertilizer. The soil was physically and chemically influenced by the choice of crop rotation. Adding clover as a green mulch crop once every 4 years resulted in an enrichment of total N and SOC at the surface compared with fava beans and maize, but only in combination with PK fertilization. In contrast, fava beans and to a lesser extent maize in rotation lowered bulk densities in the subsoil compared with clover. This resulted in a reduction of N density at depth, which was not mirrored in C densities, indicating that fava beans decouple C and N cycles in the deep soil profile. We then tested whether these effects are a result of plant (i.e. enhanced rooting depth associated with lowered subsoil bulk density) or microbial (i.e. N-cycling and denitrification processes) activities, by investigating the isotopic signatures of C and N down the profile. Our results indicate that the selection of crop rotation influences soil C and N cycling and depth distribution. Although mineral N fertilizer has significant benefits for yield, the choice of crop rotation has a greater influence on soil C and N cycling and specifically the addition of leguminous plants into rotation can provide additional yield benefits and stability. Incorporating legumes into crop rotations affects soil physical and chemical properties and decouples C and N cycles in the deep soil profile, indicating different nutrient and water cycling processes in the deep soil profile.
Reductions in India's crop yield due to ozone
NASA Astrophysics Data System (ADS)
Ghude, Sachin D.; Jena, Chinmay; Chate, D. M.; Beig, G.; Pfister, G. G.; Kumar, Rajesh; Ramanathan, V.
2014-08-01
This bottom-up modeling study, supported by emission inventories and crop production, simulates ozone on local to regional scales. It quantifies, for the first time, potential impact of ozone on district-wise cotton, soybeans, rice, and wheat crops in India for the first decade of the 21st century. Wheat is the most impacted crop with losses of 3.5 ± 0.8 million tons (Mt), followed by rice at 2.1 ± 0.8 Mt, with the losses concentrated in central and north India. On the national scale, this loss is about 9.2% of the cereals required every year (61.2 Mt) under the provision of the recently implemented National Food Security Bill (in 2013) by the Government of India. The nationally aggregated yield loss is sufficient to feed about 94 million people living below poverty line in India.
Drought Effects on Agricultural Yield: Comparison Across Regions and Crop Types
NASA Astrophysics Data System (ADS)
Daryanto, S.; Wang, L.; Jacinthe, P. A.
2014-12-01
Global agricultural production is dominated by rainfed agriculture, and is therefore prone to disruption from climate extreme weathers. These uncertainties become more problematic when considering the projection of increased drought frequency suggested by several climate models for various world regions. Curiously, few regional analyses of drought impact of food production have been attempted. We collated and analyzed data from the last 25 years to disentangle the effects of drought (i.e. timing, intensity and duration) on agricultural production in different eco-regions and with varying crop types. Our preliminary results suggested greater yield reduction in annual (-21.5%) than perennial plants (-16%), in C4 (-21%) compared to C3 crops (-17%), and when drought occurred during generative (i.e. flowering until maturity; -16.5%) than vegetative stage (-15.5%). Although drought caused similar amounts of yield reduction in both tropical and subtropical regions (i.e. -17%), it carries a greater food security risk in the tropics due to inherently low productivity (i.e. less than half than in the subtropical regions). Consequently, cultivating drought-resistant C3 perennial plants (e.g. sweet potato and cassava) in the tropics could prove a viable adaptive strategy to mitigate the effects of climate variability. In addition, these crops have limited input requirements, are well adapted to nutrient-poor Oxisols and Ultisols of the tropics, and generally outyield cereal crops in the region. Our analysis is ongoing and needs to take into account agronomic traits (e.g. water requirement), as well as the energy and nutritional values (e.g. protein, minerals) of alternative crops. Our results could inform the selection and development of new cultivars for the drought-prone regions of the world.
Effect of irrigation techniques and strategies on water footprint of growing crops
NASA Astrophysics Data System (ADS)
Chukalla, A. D.; Krol, M. S.; Hoekstra, A. Y. Y.
2014-12-01
Reducing the water footprint (WF) of growing crops, the largest water user and a significant contributor to the WF of many consumer products, plays a significant role in integrated and sustainable water management. The water footprint for growing crop is accounted by relating the crop yield with the corresponding consumptive water use (CWU), which both can be adjusted by measures that affect the crop growth and root-zone soil water balance. This study explored the scope for reducing the water footprint of irrigated crops by experimenting set of field level technical and managerial measures: (i) irrigation technologies (Furrow, sprinkler, drip and sub-surface drip), (ii) irrigation strategies (full and a range of sustained and controlled deficit) and (iii) field management options (zero, organic and synthetic mulching). Ranges of cases were also considered: (a) Arid and semi-arid environment (b) Loam and Sandy-loam soil types and (c) for Potato, Wheat and Maize crops; under (c) wet, normal and dry years. AquaCrop, the water driven crop growth and soil water balance model, offered the opportunity to systematically experiment these measures on water consumption and yield. Further, the green and blue water footprints of growing crop corresponding to each measure were computed by separating the root zone fluxes of the AquaCrop output into the green and blue soil water stocks and their corresponding fluxes. Results showed that in arid environment reduction in irrigation supply, CWU and WF up to 300 mm, 80 mm and 75 m3/tonne respectively can be achieved for Maize by a combination of organic mulching and drip technology with controlled deficit irrigation strategies (10-20-30-40% deficit with reference to the full irrigation requirement). These reductions come with a yield drop of 0.54 tonne/ha. In the same environment under the absence of mulching practice, the sub-surface drip perform better in reducing CWU and WF of irrigated crops followed by drip and furrow irrigation technique. This rank though changes in non-moisture limiting condition (wet year) drip performing better in reducing the WF of growing crops than sub-surface drip. It was observed that with all range of irrigation techniques, strategies and field management practices there is more room in reducing the WF of growing crops in loam than sandy-loam soil.
Impacts of Stratospheric Sulfate Geoengineering on Chinese Agricultural Production
NASA Astrophysics Data System (ADS)
Xia, L.; Robock, A.
2012-12-01
Possible food supply change is one of the most important concerns in the discussion of stratospheric sulfate geoengineering. In China, the high population density and strong summer monsoon influence on agriculture make this region sensitive to climate changes, such as reductions of precipitation, temperature, and solar radiation spurred by stratospheric sulfate injection. We used results from the Geoengineering Model Intercomparison Project G2 scenario to force the Decision Support System for Agrotechnology Transfer (DSSAT) crop model to predict crop yield changes from rice, maize, and winter wheat. We first evaluated the DSSAT model by forcing it with daily observed weather data and management practices for the period 1978-2008 for all the provinces in China, and compared the results to observations of the yields of the three major crops in China. We then created two 50-year sets of climate anomalies using the results from eight climate models, for 1%/year increase of CO2 and for G2 (1%/year increase of CO2 balanced by insolation reduction), and compared the resulting agricultural responses. Considering that geoengineering could happen in the future, we used two geoengineering starting years, 2020 and 2060. For 2020, we increased the mean temperature by 1°C and started the CO2 concentration at 410 ppm. For 2060, we increased temperature by 2°C and started the CO2 concentration at 550 ppm. Without changing agriculture technology, we find that compared to the control run, geoengineering with the G2 scenario starting in 2020 or 2060 would both moderately increase rice and winter wheat production due to the CO2 fertilization effect, but the increasing rates are different. However, as a C4 crop, without a significant CO2 fertilization effect, maize production would decrease slightly because of regional drought. Compared to the reference run, the three crops all have less heat stress in southern China and their yields increase, but in northern China cooler temperatures cause yields to decrease, especially for winter wheat. Therefore after deploying geoengineering (G2), there are positive effects from temperature reduction, but regions with precipitation reduction may be harmful for agriculture activity. In addition, the starting year of geoengineering would affect its impacts on agriculture.
Dias, Teresa; Dukes, Angela; Antunes, Pedro M
2015-02-01
There is an urgent need for novel agronomic improvements capable of boosting crop yields while alleviating environmental impacts. One such approach is the use of optimized crop rotations. However, a set of measurements that can serve as guiding principles for the design of crop rotations is lacking. Crop rotations take advantage of niche complementarity, enabling the optimization of nutrient use and the reduction of pests and specialist pathogen loads. However, despite the recognized importance of plant-soil microbial interactions and feedbacks for crop yield and soil health, this is ignored in the selection and management of crops for rotation systems. We review the literature and propose criteria for the design of crop rotations focusing on the roles of soil biota and feedback on crop productivity and soil health. We consider that identifying specific key organisms or consortia capable of influencing plant productivity is more important as a predictor of soil health and crop productivity than assessing the overall soil microbial diversity per se. As such, we propose that setting up soil feedback studies and applying genetic sequencing tools towards the development of soil biotic community databases has a strong potential to enable the establishment of improved soil health indicators for optimized crop rotations. © 2014 Society of Chemical Industry.
Impacts of climate change and inter-annual variability on cereal crops in China from 1980 to 2008.
Zhang, Tianyi; Huang, Yao
2012-06-01
Negative climate impacts on crop yield increase pressures on food security in China. In this study, climatic impacts on cereal yields (rice, wheat and maize) were investigated by analyzing climate-yield relationships from 1980 to 2008. Results indicated that warming was significant, but trends in precipitation and solar radiation were not statistically significant in most of China. In general, maize is particularly sensitive to warming. However, increase in temperature was correlated with both lower and higher yield of rice and wheat, which is inconsistent with the current view that warming results in decline in yields. Of the three cereal crops, further analysis suggested that reduction in yields with higher temperature is accompanied by lower precipitation, which mainly occurred in northern parts of China, suggesting droughts reduced yield due to lack of water resources. Similarly, a positive correlation between temperature and yield can be alternatively explained by the effect of solar radiation, mainly in the southern part of China where water resources are abundant. Overall, our study suggests that it is inter-annual variations in precipitation and solar radiation that have driven change in cereal yields in China over the last three decades. Copyright © 2011 Society of Chemical Industry.
Integrating Water Supply Constraints into Irrigated Agricultural Simulations of California
NASA Technical Reports Server (NTRS)
Winter, Jonathan M.; Young, Charles A.; Mehta, Vishal K.; Ruane, Alex C.; Azarderakhsh, Marzieh; Davitt, Aaron; McDonald, Kyle; Haden, Van R.; Rosenzweig, Cynthia E.
2017-01-01
Simulations of irrigated croplands generally lack key interactions between water demand from plants and water supply from irrigation systems. We coupled the Water Evaluation and Planning system (WEAP) and Decision Support System for Agrotechnology Transfer (DSSAT) to link regional water supplies and management with field-level water demand and crop growth. WEAP-DSSAT was deployed and evaluated over Yolo County in California for corn, rice, and wheat. WEAP-DSSAT is able to reproduce the results of DSSAT under well-watered conditions and reasonably simulate observed mean yields, but has difficulty capturing yield interannual variability. Constraining irrigation supply to surface water alone reduces yields for all three crops during the 1987-1992 drought. Corn yields are reduced proportionally with water allocation, rice yield reductions are more binary based on sufficient water for flooding, and wheat yields are least sensitive to irrigation constraints as winter wheat is grown during the wet season.
NASA Astrophysics Data System (ADS)
Valin, H.; Havlík, P.; Mosnier, A.; Herrero, M.; Schmid, E.; Obersteiner, M.
2013-09-01
In this letter, we investigate the effects of crop yield and livestock feed efficiency scenarios on greenhouse gas (GHG) emissions from agriculture and land use change in developing countries. We analyze mitigation associated with different productivity pathways using the global partial equilibrium model GLOBIOM. Our results confirm that yield increase could mitigate some agriculture-related emissions growth over the next decades. Closing yield gaps by 50% for crops and 25% for livestock by 2050 would decrease agriculture and land use change emissions by 8% overall, and by 12% per calorie produced. However, the outcome is sensitive to the technological path and which factor benefits from productivity gains: sustainable land intensification would increase GHG savings by one-third when compared with a fertilizer intensive pathway. Reaching higher yield through total factor productivity gains would be more efficient on the food supply side but halve emissions savings due to a strong rebound effect on the demand side. Improvement in the crop or livestock sector would have different implications: crop yield increase would bring the largest food provision benefits, whereas livestock productivity gains would allow the greatest reductions in GHG emission. Combining productivity increases in the two sectors appears to be the most efficient way to exploit mitigation and food security co-benefits.
Romero, Pascual; Navarro, Josefa Maria; García, Francisco; Botía Ordaz, Pablo
2004-03-01
We investigated the effects of regulated deficit irrigation (RDI) during the pre-harvest period (kernel-filling stage) on water relations, leaf development and crop yield in mature almond (Prunus dulcis (Mill.) D.A. Webb cv. Cartagenera) trees during a 2-year field experiment. Trees were either irrigated at full-crop evapotranspiration (ETc=100%) (well-irrigated control treatment) or subjected to an RDI treatment that consisted of full irrigation for the full season, except from early June to early August (kernel-filling stage), when 20% ETc was applied. The severity of water stress was characterized by measurements of soil water content, predawn leaf water potential (Psipd) and relative water content (RWC). Stomatal conductance (gs), net CO2 assimilation rate (A), transpiration rate (E), leaf abscission, leaf expansion rate and crop yield were also measured. In both years, Psipd and RWC of well-irrigated trees were maintained above -1.0 MPa and 92%, respectively, whereas the corresponding values for trees in the RDI treatment were -2.37 MPa and 82%. Long-term water stress led to a progressive decline in gs, A and E, with significant reductions after 21 days in the RDI treatment. At the time of maximum stress (48 days after commencement of RDI), A, gs and E were 64, 67 and 56% lower than control values, respectively. High correlations between A, E and gs were observed. Plant water status recovered within 15 days after the resumption of irrigation and was associated with recovery of soil water content. A relatively rapid and complete recovery of A and gs was also observed, although the recovery was slower than for Psipd and RWC. Severe water stress during the kernel-filling stage resulted in premature defoliation (caused by increased leaf abscission) and a reduction in leaf growth rate, which decreased tree leaf area. Although kernel yield was correlated with leaf water potential, RDI caused a nonsignificant 7% reduction in kernel yield and had no effect on kernel size. The RDI treatment also improved water-use efficiency because about 30% less irrigation water was applied in the RDI treatment than in the control treatment. We conclude that high-cropping almonds can be successfully grown in semiarid regions in an RDI regime provided that Psipd is maintained above a threshold value of -2 MPa.
NASA Astrophysics Data System (ADS)
King, A. W.; Absar, S. M.; Nair, S.; Preston, B. L.
2012-12-01
The vulnerability of agriculture is among the leading concerns surrounding climate change. Agricultural production is influenced by drought and other extremes in weather and climate. In regions of subsistence farming, worst case reductions in yield lead to malnutrition and famine. Reduced surplus contributes to poverty in agrarian economies. In more economically diverse and industrialized regions, variations in agricultural yield can influence the regional economy through market mechanisms. The latter grows in importance as agriculture increasingly services the energy market in addition to markets for food and fiber. Agriculture is historically a highly adaptive enterprise and will respond to future changes in climate with a variety of adaptive mechanisms. Nonetheless, the risk, if not expectation, of increases in climate extremes and hazards exceeding historical experience motivates scientifically based anticipatory assessment of the vulnerability of agriculture to climate change. We investigate the sensitivity component of that vulnerability using EPIC, a well established field-scale model of cropping systems that includes the simulation of economic yield. The core of our analysis is the relationship between simulated yield and various indices of climate change, including the CCI/CLIVAR/JCOM ETCCDI indices, calculated from weather inputs to the model. We complement this core with analysis using the DSSAT cropping system model and exploration of relationships between historical yield statistics and climate indices calculated from weather records. Our analyses are for sites in the Southeast/Gulf Coast region of the United States. We do find "tight" monotonic relationships between annual yield and climate for some indices, especially those associated with available water. More commonly, however, we find an increase in the variability of yield as the index value becomes more extreme. Our findings contribute to understanding the sensitivity of crop yield as part of vulnerability analysis. They also contribute to considerations of adaptation, focusing attention on adapting to increased variability in yield rather than just reductions in yield. For example, in the face of increased variability or reduced reliability, hedging and risk spreading strategies may be more important than technological innovations such as drought-resistant crops or other optimization strategies. Our findings also have implications for the choice and application of climate extreme indices, demands on models used to project climate change and the development of next generation integrated assessment models (IAM) that incorporate the agricultural sector, and especially adaption within that sector, in energy and broader more general markets.
Rocha, João; Roebeling, Peter; Rial-Rivas, María Ermitas
2015-12-01
The extensive use of fertilizers has become one of the most challenging environmental issues in agricultural catchment areas. In order to reduce the negative impacts from agricultural activities and to accomplish the objectives of the European Water Framework Directive we must consider the implementation of sustainable agricultural practices. In this study, we assess sustainable agricultural practices based on reductions in N-fertilizer application rates (from 100% to 0%) and N-application methods (single, split and slow-release) across key agricultural land use classes in the Vouga catchment, Portugal. The SWAT model was used to relate sustainable agricultural practices, agricultural yields and N-NO3 water pollution deliveries. Results show that crop yields as well as N-NO3 exportation rates decrease with reductions in N-application rates and single N-application methods lead to lower crop yields and higher N-NO3 exportation rates as compared to split and slow-release N-application methods. Copyright © 2015 Elsevier B.V. All rights reserved.
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.
NASA Astrophysics Data System (ADS)
Chukalla, Abebe; Krol, Maarten; Hoekstra, Arjen
2016-04-01
Reducing water footprints (WF) in irrigated crop production is an essential element in water management, particularly in water-scarce areas. To achieve this, policy and decision making need to be supported with information on marginal cost curves that rank measures to reduce the WF according to their cost-effectiveness and enable the estimation of the cost associated with a certain WF reduction target, e.g. towards a certain reasonable WF benchmark. This paper aims to develop marginal cost curves (MCC) for WF reduction. The AquaCrop model is used to explore the effect of different measures on evapotranspiration and crop yield and thus WF that is used as input in the MCC. Measures relate to three dimensions of management practices: irrigation techniques (furrow, sprinkler, drip and subsurface drip); irrigation strategies (full and deficit irrigation); and mulching practices (no mulching, organic and synthetic mulching). A WF benchmark per crop is calculated as resulting from the best-available production technology. The marginal cost curve is plotted using the ratios of the marginal cost to WF reduction of the measures as ordinate, ranking with marginal costs rise with the increase of the reduction effort. For each measure, the marginal cost to reduce WF is estimated by comparing the associated WF and net present value (NPV) to the reference case (furrow irrigation, full irrigation, no mulching). The NPV for each measure is based on its capital costs, operation and maintenances costs (O&M) and revenues. A range of cases is considered, including: different crops, soil types and different environments. Key words: marginal cost curve, water footprint benchmark, soil water balance, crop growth, AquaCrop
Food security, irrigation, climate change, and water scarcity in India
NASA Astrophysics Data System (ADS)
Hertel, T. W.; Taheripour, F.; Gopalakrishnan, B. N.; Sahin, S.; Escurra, J.
2015-12-01
This paper uses an advanced CGE model (Taheripour et al., 2013) coupled with hydrological projections of future water scarcity and biophysical data on likely crop yields under climate change to examine how water scarcity, climate change, and trade jointly alter land use changes across the Indian subcontinent. Climate shocks to rainfed and irrigated yields in 2030 are based on the p-DSSAT crop model, RCP 2.6, as reported under the AgMIP project (Rosenzweig et al., 2013), accessed through GEOSHARE (Villoria et al, 2014). Results show that, when water scarcity is ignored, irrigated areas grow in the wake of climate change as the returns to irrigation rise faster than for rainfed uses of land within a given agro-ecological zone. When non-agricultural competition for future water use, as well as anticipated supply side limitations are brought into play (Rosegrant et al., 2013), the opportunity cost of water rises across all river basins, with the increase ranging from 12% (Luni) to 44% (Brahmaputra). As a consequence, irrigated crop production is curtailed in most regions (Figure 1), with the largest reductions coming in the most water intensive crops, namely rice and wheat. By reducing irrigated area, which tends to have much higher yields, the combined effects of water scarcity and climate impacts require an increase in total cropped area, which rises by about 240,000 ha. The majority of this area expansion occurs in the Ganges, Indus, and Brahmari river basins. Overall crop output falls by about 2 billion, relative to the 2030 baseline, with imports rising by about 570 million. The combined effects of climate change and water scarcity for irrigation also have macro-economic consequences, resulting in a 0.28% reduction in GDP and an increase in the consumer price index by about 0.4% in 2030, compared the baseline. The national welfare impact on India amounts to roughly 3 billion (at 2007 prices) in 2030. Assuming a 3% social discount rate, the net present value of the annual reductions in welfare will be about 24.3 billion for 2008 to 2030. This study highlights the importance of considering the interplay between climate and water availability in assessments of food security.
NASA Astrophysics Data System (ADS)
Alfieri, Silvia Maria; De Lorenzi, Francesca; Basile, Angelo; Bonfante, Antonello; Missere, Daniele; Menenti, Massimo
2014-05-01
Climate change in Mediterranean area is likely to reduce precipitation amounts and to increase temperature thus affecting the timing of development stages and the productivity of crops. Further, extreme weather events are expected to increase in the future leading to significant increase in agricultural risk. Some strategies for effectively managing risks and adapting to climate change involve adjustments to irrigation management and use of different varieties. We quantified the risk on Peach production in an irrigated area of "Emilia Romagna" region ( Italy) taking into account the impact on crop yield due to climate change and variability and to extreme weather events as well as the ability of the agricultural system to modulate this impact (adaptive capacity) through changes in water and crop management. We have focused on climatic events causing insufficient water supply to crops, while taking into account the effect of climate on the duration and timing of phenological stages. Further, extreme maximum and minimum temperature events causing significant reduction of crop yield have been considered using phase-specific critical temperatures. In our study risk was assessed as the product of the probability of a damaging event (hazard), such as drought or extreme temperatures, and the estimated impact of such an event (vulnerability). To estimate vulnerability we took into account the possible options to reduce risk, by combining estimates of the sensitivity of the system (negative impact on crop yield) and its adaptive capacity. The latter was evaluated as the relative improvement due to alternate management options: the use of alternate varieties or the changes in irrigation management. Vulnerability was quantified using cultivar-specific thermal and hydrologic requirements of a set of cultivars determined by experimental data and from scientific literature. Critical temperatures determining a certain reduction of crop yield have been estimated and used to assess thermal hazard and vulnerability in sensitive phenological stages. Cultivar-specific yield response functions to water availability were used to assess the reduction of yield for a determinate management option. Downscaled climate scenarios have been used to calculate indicators of soil water availability and thermal times and to evaluate the variability of crop phenology in combination with critical temperatures. Two climate scenarios were considered: reference (1961-90) and future (2021-2050) climate, the former from climatic statistics on observed variables, and the latter from statistical downscaling of general circulation models (AOGCM). Management options were defined by combinations of irrigation strategies (optimal, rainfed and deficit) with use of alternate varieties. As regards hydrologic conditions, risk assessment has been done at landscape scale in all soil units within each study area. The mechanistic model SWAP (Soil-Water-Atmosphere-Plant model) of water flow in the soil-plant-atmosphere system was used to describe the hydrological conditions in response to climate and irrigation. Different farm management options were evaluated. In a moderate water shortage scenario, deficit irrigation was an effective strategy to cope with climate change risks. In a severe water shortage scenario, the study showed the potentiality of intra-specific biodiversity to reduce risk of yield losses, although costs should be evaluated against the benefits of each specific management option. The work was carried out within the Italian national project AGROSCENARI funded by the Ministry for Agricultural, Food and Forest Policies (MIPAAF, D.M. 8608/7303/2008)
USDA-ARS?s Scientific Manuscript database
Irrigation with high salinity water influences plant growth, production of photosynthetic pigments and total phenols, leading to reduction in crop yield and quality. Foliar application of macro- and/or micro-nutrients can, to some extent, mitigate negative effects of high salinity irrigation water o...
Weather based risks and insurances for agricultural production
NASA Astrophysics Data System (ADS)
Gobin, Anne
2015-04-01
Extreme weather events such as frost, drought, heat waves and rain storms can have devastating effects on cropping systems. According to both the agriculture and finance sectors, a risk assessment of extreme weather events and their impact on cropping systems is needed. The principle of return periods or frequencies of natural hazards is adopted in many countries as the basis of eligibility for the compensation of associated losses. For adequate risk management and eligibility, hazard maps for events with a 20-year return period are often used. Damages due to extreme events are strongly dependent on crop type, crop stage, soil type and soil conditions. The impact of extreme weather events particularly during the sensitive periods of the farming calendar therefore requires a modelling approach to capture the mixture of non-linear interactions between the crop, its environment and the occurrence of the meteorological event in the farming calendar. Physically based crop models such as REGCROP (Gobin, 2010) assist in understanding the links between different factors causing crop damage. Subsequent examination of the frequency, magnitude and impacts of frost, drought, heat stress and soil moisture stress in relation to the cropping season and crop sensitive stages allows for risk profiles to be confronted with yields, yield losses and insurance claims. The methodology is demonstrated for arable food crops, bio-energy crops and fruit. The perspective of rising risk-exposure is exacerbated further by limited aid received for agricultural damage, an overall reduction of direct income support to farmers and projected intensification of weather extremes with climate change. Though average yields have risen continuously due to technological advances, there is no evidence that relative tolerance to adverse weather events has improved. The research is funded by the Belgian Science Policy Organisation (Belspo) under contract nr SD/RI/03A.
Yamori, Wataru; Kondo, Eri; Sugiura, Daisuke; Terashima, Ichiro; Suzuki, Yuji; Makino, Amane
2016-01-01
Although photosynthesis is the most important source for biomass and grain yield, a lack of correlation between photosynthesis and plant yield among different genotypes of various crop species has been frequently observed. Such observations contribute to the ongoing debate whether enhancing leaf photosynthesis can improve yield potential. Here, transgenic rice plants that contain variable amounts of the Rieske FeS protein in the cytochrome (cyt) b6 /f complex between 10 and 100% of wild-type levels have been used to investigate the effect of reductions of these proteins on photosynthesis, plant growth and yield. Reductions of the cyt b6 /f complex did not affect the electron transport rates through photosystem I but decreased electron transport rates through photosystem II, leading to concomitant decreases in CO2 assimilation rates. There was a strong control of plant growth and grain yield by the rate of leaf photosynthesis, leading to the conclusion that enhancing photosynthesis at the single-leaf level would be a useful target for improving crop productivity and yield both via conventional breeding and biotechnology. The data here also suggest that changing photosynthetic electron transport rates via manipulation of the cyt b6 /f complex could be a potential target for enhancing photosynthetic capacity in higher plants. © 2015 John Wiley & Sons Ltd.
NASA Astrophysics Data System (ADS)
Konadu, D. D.; Sobral Mourao, Z.; Lupton, R.; Skelton, S.
2015-12-01
The UK Department of Energy and Climate Change has developed four low-carbon energy transition pathways - the Carbon Plan - towards achieving the legally binding 80% territorial greenhouse gas emissions reduction, stipulated in the 2008 Climate Change Act by 2050. All the pathways require increase in bioenergy deployment, of which a significant amount could be indigenously sourced from crops. But will increased domestic production of energy crops conflict with other land use and ecosystem priorities? To address this question, a coupled analysis of the four energy transition pathways and land use has been developed using an integrated resource accounting platform called ForeseerTM. The two systems are connected by the bioenergy component, and are projected forward in time to 2050, under different scenarios of energy crop composition and yield, and accounting for various constraints on land use for agriculture and ecosystem services. The results show between 7 and 61% of UK agricultural land could be required to meet bioenergy deployment projections under different combinations of crop yield and compositions for the transition pathways. This could result in competition for land for food production and other socio-economic and ecological land uses. Consequently, the potential role of bioenergy in achieving UK emissions reduction targets may face significant deployment challenges.
Ssegane, Herbert; Negri, M. Cristina
2016-09-16
Here, locating bioenergy crops on strategically selected subfield areas of marginal interest for commodity agriculture can increase environmental sustainability. Location and choice of bioenergy crops should improve environmental benefits with minimal disruption of current food production systems. We identified subfield soils of a tile-drained agricultural watershed as marginal if they had areas of low crop productivity index (CPI), were susceptible to nitrate-nitrogen (NO 3–N) leaching, or were susceptible to at least two other forms of environmental degradation (marginal areas). In the test watershed (Indian Creek watershed, IL) with annual precipitation of 852 mm, 3% of soils were CPI areas andmore » 22% were marginal areas. The Soil and Water Assessment Tool was used to forecast the impact of growing switchgrass ( Panicum virgatum L.), willow ( Salix spp.), and big bluestem ( Andropogon gerardi Vitman) in these subfield areas on annual grain yields, NO 3–N and sediment exports, and water yield. Simulated conversion of CPI areas from current land use to bioenergy crops had no significant (p ≤ 0.05) impact on grain production and reduced NO 3–N and sediment exports by 5.0 to 6.0% and 3.0%, respectively. Conversion of marginal areas from current land use to switchgrass forecasted the production of 34,000 t of biomass and reductions in NO 3–N (26.0%) and sediment (33.0%) exports. Alternatively, conversion of marginal areas from current land use to willow forecasted similar reductions as switchgrass for sediment but significantly (p ≤ 0.01) lower reductions in annual NO 3–N export (18.0 vs. 26.0%).« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ssegane, Herbert; Negri, M. Cristina
Here, locating bioenergy crops on strategically selected subfield areas of marginal interest for commodity agriculture can increase environmental sustainability. Location and choice of bioenergy crops should improve environmental benefits with minimal disruption of current food production systems. We identified subfield soils of a tile-drained agricultural watershed as marginal if they had areas of low crop productivity index (CPI), were susceptible to nitrate-nitrogen (NO 3–N) leaching, or were susceptible to at least two other forms of environmental degradation (marginal areas). In the test watershed (Indian Creek watershed, IL) with annual precipitation of 852 mm, 3% of soils were CPI areas andmore » 22% were marginal areas. The Soil and Water Assessment Tool was used to forecast the impact of growing switchgrass ( Panicum virgatum L.), willow ( Salix spp.), and big bluestem ( Andropogon gerardi Vitman) in these subfield areas on annual grain yields, NO 3–N and sediment exports, and water yield. Simulated conversion of CPI areas from current land use to bioenergy crops had no significant (p ≤ 0.05) impact on grain production and reduced NO 3–N and sediment exports by 5.0 to 6.0% and 3.0%, respectively. Conversion of marginal areas from current land use to switchgrass forecasted the production of 34,000 t of biomass and reductions in NO 3–N (26.0%) and sediment (33.0%) exports. Alternatively, conversion of marginal areas from current land use to willow forecasted similar reductions as switchgrass for sediment but significantly (p ≤ 0.01) lower reductions in annual NO 3–N export (18.0 vs. 26.0%).« less
Yao, Zhisheng; Yan, Guangxuan; Zheng, Xunhua; Wang, Rui; Liu, Chunyan; Butterbach-Bahl, Klaus
2017-12-01
High nitrogen (N) inputs in Chinese vegetable and cereal productions played key roles in increasing crop yields. However, emissions of the potent greenhouse gas nitrous oxide (N 2 O) and atmospheric pollutant nitric oxide (NO) increased too. For lowering the environmental costs of crop production, it is essential to optimize N strategies to maintain high crop productivity, while reducing the associated N losses. We performed a 2 year-round field study regarding the effect of different combinations of poultry manure and chemical N fertilizers on crop yields, N use efficiency (NUE) and N 2 O and NO fluxes from a Welsh onion-winter wheat system in the North China Plain. Annual N 2 O and NO emissions averaged 1.14-3.82 kg N ha -1 yr -1 (or 5.54-13.06 g N kg -1 N uptake) and 0.57-1.87 kg N ha -1 yr -1 (or 2.78-6.38 g N kg -1 N uptake) over all treatments, respectively. Both N 2 O and NO emissions increased linearly with increasing total N inputs, and the mean annual direct emission factors (EF d ) were 0.39% for N 2 O and 0.19% for NO. Interestingly, the EF d for chemical N fertilizers (N 2 O: 0.42-0.48%; NO: 0.07-0.11%) was significantly lower than for manure N (N 2 O: 1.35%; NO: 0.76%). Besides, a negative power relationship between yield-scaled N 2 O, NO or N 2 O + NO emissions and NUE was observed, suggesting that improving NUE in crop production is crucial for increasing crop yields while decreasing nitrogenous gas release. Compared to the current farmers' fertilization rate, alternative practices with reduced chemical N fertilizers increased NUE and decreased annual N 2 O + NO emissions substantially, while crop yields remained unaffected. As a result, annual yield-scaled N 2 O + NO emissions were reduced by > 20%. Our study shows that a reduction of current application rates of chemical N fertilizers by 30-50% does not affect crop productivity, while at the same time N 2 O and NO emissions would be reduced significantly. Copyright © 2017 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Almagro, María; de Vente, Joris; Boix-Fayós, Carolina; García-Franco, Noelia; Melgares de Aguilar, Javier; González, David; Solé-Benet, Albert; Martínez-Mena, María
2015-04-01
Little is known about the multiple impacts of sustainable land management practices on soil and water conservation, carbon sequestration, mitigation of global warming, and crop yield productivity in semiarid Mediterranean agroecosystems. We hypothesized that a shift from intensive tillage to more conservative tillage management practices (reduced tillage optionally combined with green manure) leads to an improvement in soil structure and quality and will reduce soil erosion and enhance carbon sequestration in semiarid Mediterranean rainfed agroecosystems. To test the hypothesis, we assessed the effects of different tillage treatments (conventional (CT), reduced (RT), reduced tillage combined with green manure (RTG), and no tillage (NT)) on soil structure and soil water content, runoff and erosion control, soil CO2 emissions, crop yield and carbon sequestration in two semiarid agroecosystems with organic rainfed almond in the Murcia Region southeast Spain). It was found that reduction and suppression of tillage under almonds led to an increase in soil water content in both agroecosystems. Crop yields ranged from 775 to 1766 kg ha-1 between tillage 18 treatments, but we did not find a clear relation between soil water content and crop yield. RT and RTG treatments showed lower soil erosion rates and higher crop yields of almonds than under CT treatment. Overall, higher soil organic carbon contents and aggregate stability were observed under RTG treatment than under RT or CT treatment. It is concluded that conversion from CT to RTG is suitable to increase carbon inputs without enhancing soil CO2 emissions in semiarid Mediterranean agroecosystems.
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.
Shtull-Trauring, Eliav; Aviani, Ido; Avisar, Dror; Bernstein, Nirit
2016-01-01
Addressing the global challenges to water security requires a better understanding of humanity's use of water, especially the agricultural sector that accounts for 70% of global withdrawals. This study combined high resolution-data with a GIS system to analyze the impact of agricultural practices, crop type, and spatial factors such as drainage basins, climate, and soil type on the Water Footprint (WF) of agricultural crops. The area of the study, the northern Lower Jordan Valley, covers 1121 ha in which three main plantation crops are grown: banana (cultivated in open-fields or net-houses), avocado and palm-dates. High-resolution data sources included GIS layers of the cultivated crops and a drainage pipe-system installed in the study area; meteorological data (2000–2013); and crop parameters (yield and irrigation recommendations). First, the study compared the WF of the different crops on the basis of yield and energy produced as well as a comparison to global values and local irrigation recommendations. The results showed that net-house banana has the lowest WF based on all different criteria. However, while palm-dates showed the highest WF for the yield criteria, it had the second lowest WF for energy produced, emphasizing the importance of using multiple parameters for low and high yield crop comparisons. Next, the regional WF of each drainage basin in the study area was calculated, demonstrating the strong influence of the Gray WF, an indication of the amount of freshwater required for pollution assimilation. Finally, the benefits of integrating GIS and WF were demonstrated by computing the effect of adopting net-house cultivation throughout the area of study with a result a reduction of 1.3 MCM irrigation water per year. Integrating the WF methodology and local high-resolution data using GIS can therefore promote and help quantify the benefits of adopting site-appropriate crops and agricultural practices that lower the WF by increasing yield, reducing water consumption, and minimizing negative environmental impacts. PMID:28018408
Shtull-Trauring, Eliav; Aviani, Ido; Avisar, Dror; Bernstein, Nirit
2016-01-01
Addressing the global challenges to water security requires a better understanding of humanity's use of water, especially the agricultural sector that accounts for 70% of global withdrawals. This study combined high resolution-data with a GIS system to analyze the impact of agricultural practices, crop type, and spatial factors such as drainage basins, climate, and soil type on the Water Footprint (WF) of agricultural crops. The area of the study, the northern Lower Jordan Valley, covers 1121 ha in which three main plantation crops are grown: banana (cultivated in open-fields or net-houses), avocado and palm-dates. High-resolution data sources included GIS layers of the cultivated crops and a drainage pipe-system installed in the study area; meteorological data (2000-2013); and crop parameters (yield and irrigation recommendations). First, the study compared the WF of the different crops on the basis of yield and energy produced as well as a comparison to global values and local irrigation recommendations. The results showed that net-house banana has the lowest WF based on all different criteria. However, while palm-dates showed the highest WF for the yield criteria, it had the second lowest WF for energy produced, emphasizing the importance of using multiple parameters for low and high yield crop comparisons. Next, the regional WF of each drainage basin in the study area was calculated, demonstrating the strong influence of the Gray WF, an indication of the amount of freshwater required for pollution assimilation. Finally, the benefits of integrating GIS and WF were demonstrated by computing the effect of adopting net-house cultivation throughout the area of study with a result a reduction of 1.3 MCM irrigation water per year. Integrating the WF methodology and local high-resolution data using GIS can therefore promote and help quantify the benefits of adopting site-appropriate crops and agricultural practices that lower the WF by increasing yield, reducing water consumption, and minimizing negative environmental impacts.
Li, Caihong; Song, Yanjie; Guo, Liyue; Gu, Xian; Muminov, Mahmud A; Wang, Tianzuo
2018-05-01
Accelerated industrialization has been increasing releases of chemical precursors of ozone. Ozone concentration has risen nowadays, and it's predicted that this trend will continue in the next few decades. The yield of many ozone-sensitive crops suffers seriously from ozone pollution, and there are abundant reports exploring the damage mechanisms of ozone to these crops, such as winter wheat. However, little is known on how to alleviate these negative impacts to increase grain production under elevated ozone. Nitric oxide, as a bioactive gaseous, mediates a variety of physiological processes and plays a central role in response to biotic and abiotic stresses. In the present study, the accumulation of endogenous nitric oxide in wheat leaves was found to increase in response to ozone. To study the functions of nitric oxide, its precursor sodium nitroprusside was spayed to wheat leaves under ozone pollution. Wheat leaves spayed with sodium nitroprusside accumulated less hydrogen peroxide, malondialdehyde and electrolyte leakage under ozone pollution, which can be accounted for by the higher activities of superoxide dismutase and peroxidase than in leaves treated without sodium nitroprusside. Consequently, net photosynthetic rate of wheat treated using sodium nitroprusside was much higher, and yield reduction was alleviated under ozone fumigation. These findings are important for our understanding of the potential roles of nitric oxide in responses of crops in general and wheat in particular to ozone pollution, and provide a viable method to mitigate the detrimental effects on crop production induced by ozone pollution, which is valuable for keeping food security worldwide. Copyright © 2018 Elsevier Ltd. All rights reserved.
Petit, Sandrine; Munier-Jolain, Nicolas; Bretagnolle, Vincent; Bockstaller, Christian; Gaba, Sabrina; Cordeau, Stéphane; Lechenet, Martin; Mézière, Delphine; Colbach, Nathalie
2015-11-01
Amongst the biodiversity components of agriculture, weeds are an interesting model for exploring management options relying on the principle of ecological intensification in arable farming. Weeds can cause severe crop yield losses, contribute to farmland functional biodiversity and are strongly associated with the generic issue of pesticide use. In this paper, we address the impacts of herbicide reduction following a causal framework starting with herbicide reduction and triggering changes in (i) the management options required to control weeds, (ii) the weed communities and functions they provide and (iii) the overall performance and sustainability of the implemented land management options. The three components of this framework were analysed in a multidisciplinary project that was conducted on 55 experimental and farmer's fields that included conventional, integrated and organic cropping systems. Our results indicate that the reduction of herbicide use is not antagonistic with crop production, provided that alternative practices are put into place. Herbicide reduction and associated land management modified the composition of in-field weed communities and thus the functions of weeds related to biodiversity and production. Through a long-term simulation of weed communities based on alternative (?) cropping systems, some specific management pathways were identified that delivered high biodiversity gains and limited the negative impacts of weeds on crop production. Finally, the multi-criteria assessment of the environmental, economic and societal sustainability of the 55 systems suggests that integrated weed management systems fared better than their conventional and organic counterparts. These outcomes suggest that sustainable management could possibly be achieved through changes in weed management, along a pathway starting with herbicide reduction.
NASA Astrophysics Data System (ADS)
Petit, Sandrine; Munier-Jolain, Nicolas; Bretagnolle, Vincent; Bockstaller, Christian; Gaba, Sabrina; Cordeau, Stéphane; Lechenet, Martin; Mézière, Delphine; Colbach, Nathalie
2015-11-01
Amongst the biodiversity components of agriculture, weeds are an interesting model for exploring management options relying on the principle of ecological intensification in arable farming. Weeds can cause severe crop yield losses, contribute to farmland functional biodiversity and are strongly associated with the generic issue of pesticide use. In this paper, we address the impacts of herbicide reduction following a causal framework starting with herbicide reduction and triggering changes in (i) the management options required to control weeds, (ii) the weed communities and functions they provide and (iii) the overall performance and sustainability of the implemented land management options. The three components of this framework were analysed in a multidisciplinary project that was conducted on 55 experimental and farmer's fields that included conventional, integrated and organic cropping systems. Our results indicate that the reduction of herbicide use is not antagonistic with crop production, provided that alternative practices are put into place. Herbicide reduction and associated land management modified the composition of in-field weed communities and thus the functions of weeds related to biodiversity and production. Through a long-term simulation of weed communities based on alternative (?) cropping systems, some specific management pathways were identified that delivered high biodiversity gains and limited the negative impacts of weeds on crop production. Finally, the multi-criteria assessment of the environmental, economic and societal sustainability of the 55 systems suggests that integrated weed management systems fared better than their conventional and organic counterparts. These outcomes suggest that sustainable management could possibly be achieved through changes in weed management, along a pathway starting with herbicide reduction.
Increased phytochrome B alleviates density effects on tuber yield of field potato crops.
Boccalandro, Hernán E; Ploschuk, Edmundo L; Yanovsky, Marcelo J; Sánchez, Rodolfo A; Gatz, Christiane; Casal, Jorge J
2003-12-01
The possibility that reduced photomorphogenic responses could increase field crop yield has been suggested often, but experimental support is still lacking. Here, we report that ectopic expression of the Arabidopsis PHYB (phytochrome B) gene, a photoreceptor involved in detecting red to far-red light ratio associated with plant density, can increase tuber yield in field-grown transgenic potato (Solanum tuberosum) crops. Surprisingly, this effect was larger at very high densities, despite the intense reduction in the red to far-red light ratios and the concomitant narrowed differences in active phytochrome B levels between wild type and transgenics at these densities. Increased PHYB expression not only altered the ability of plants to respond to light signals, but they also modified the light environment itself. This combination resulted in larger effects of enhanced PHYB expression on tuber number and crop photosynthesis at high planting densities. The PHYB transgenics showed higher maximum photosynthesis in leaves of all strata of the canopy, and this effect was largely due to increased leaf stomatal conductance. We propose that enhanced PHYB expression could be used in breeding programs to shift optimum planting densities to higher levels.
Chenu, Karine; Chapman, Scott C; Tardieu, François; McLean, Greg; Welcker, Claude; Hammer, Graeme L
2009-12-01
Under drought, substantial genotype-environment (G x E) interactions impede breeding progress for yield. Identifying genetic controls associated with yield response is confounded by poor genetic correlations across testing environments. Part of this problem is related to our inability to account for the interplay of genetic controls, physiological traits, and environmental conditions throughout the crop cycle. We propose a modeling approach to bridge this "gene-to-phenotype" gap. For maize under drought, we simulated the impact of quantitative trait loci (QTL) controlling two key processes (leaf and silk elongation) that influence crop growth, water use, and grain yield. Substantial G x E interaction for yield was simulated for hypothetical recombinant inbred lines (RILs) across different seasonal patterns of drought. QTL that accelerated leaf elongation caused an increase in crop leaf area and yield in well-watered or preflowering water deficit conditions, but a reduction in yield under terminal stresses (as such "leafy" genotypes prematurely exhausted the water supply). The QTL impact on yield was substantially enhanced by including pleiotropic effects of these QTL on silk elongation and on consequent grain set. The simulations obtained illustrated the difficulty of interpreting the genetic control of yield for genotypes influenced only by the additive effects of QTL associated with leaf and silk growth. The results highlight the potential of integrative simulation modeling for gene-to-phenotype prediction and for exploiting G x E interactions for complex traits such as drought tolerance.
NASA Astrophysics Data System (ADS)
Teng, W. L.; Shannon, H.
2010-12-01
The USDA World Agricultural Outlook Board (WAOB) coordinates the development of the monthly World Agricultural Supply and Demand Estimates (WASDE) for the U.S. and major foreign producing countries. Given the significant effect of weather on crop progress, conditions, and production, WAOB prepares frequent agricultural weather assessments in the Global Agricultural Decision Support Environment (GLADSE). Because the timing of the precipitation is often as important as the amount, in their effects on crop production, WAOB frequently examines precipitation time series to estimate crop productivity. An effective method for such assessment is the use of analog year comparisons, where precipitation time series, based on surface weather stations, from several historical years are compared with the time series from the current year. Once analog years are identified, crop yields can be estimated for the current season based on observed yields from the analog years, because of the similarities in the precipitation patterns. In this study, NASA satellite precipitation and soil moisture time series are used to identify analog years. Given that soil moisture often has a more direct effect than does precipitation on crop water availability, the time series of soil moisture could be more effective than that of precipitation, in identifying those years with similar crop yields. Retrospective analyses of analogs will be conducted to determine any reduction in the level of uncertainty in identifying analog years, and any reduction in false negatives or false positives. The comparison of analog years could potentially be improved by quantifying the selection of analogs, instead of the current visual inspection method. Various approaches to quantifying are currently being evaluated. This study is part of a larger effort to improve WAOB estimates by integrating NASA remote sensing soil moisture observations and research results into GLADSE, including (1) the integration of the Land Parameter Retrieval Model (LPRM) soil moisture algorithm for operational production and (2) the assimilation of LPRM soil moisture into the USDA Environmental Policy Integrated Climate (EPIC) crop model.
Identification of technology options for reducing nitrogen pollution in cropping systems of Pujiang*
Fang, Bin; Wang, Guang-huo; Van den berg, Marrit; Roetter, Reimund
2005-01-01
This work analyses the potential role of nitrogen pollution technology of crop systems of Pujiang, County in Eastern China’s Zhejiang Province, rice and vegetables are important cropping systems. We used a case study approach involving comparison of farmer practices and improved technologies. This approach allows assessing the impact of technology on pollution, is forward looking, and can yield information on the potential of on-the-shelf technology and provide opportunities for technology development. The approach particularly suits newly developed rice technologies with large potential of reducing nitrogen pollution and for future rice and vegetables technologies. The results showed that substantial reductions in nitrogen pollution are feasible for both types of crops. PMID:16187411
Identification of technology options for reducing nitrogen pollution in cropping systems of Pujiang.
Fang, Bin; Wang, Guang-Huo; Van, Den Berg Marrit; Roetter, Reimund
2005-10-01
This work analyses the potential role of nitrogen pollution technology of crop systems of Pujiang, County in Eastern China's Zhejiang Province, rice and vegetables are important cropping systems. We used a case study approach involving comparison of farmer practices and improved technologies. This approach allows assessing the impact of technology on pollution, is forward looking, and can yield information on the potential of on-the-shelf technology and provide opportunities for technology development. The approach particularly suits newly developed rice technologies with large potential of reducing nitrogen pollution and for future rice and vegetables technologies. The results showed that substantial reductions in nitrogen pollution are feasible for both types of crops.
Hamada, Yuki; Ssegane, Herbert; Negri, Maria Cristina
2015-07-31
Biofuels are important alternatives for meeting our future energy needs. Successful bioenergy crop production requires maintaining environmental sustainability and minimum impacts on current net annual food, feed, and fiber production. The objectives of this study were to: (1) determine under-productive areas within an agricultural field in a watershed using a single date; high resolution remote sensing and (2) examine impacts of growing bioenergy crops in the under-productive areas using hydrologic modeling in order to facilitate sustainable landscape design. Normalized difference indices (NDIs) were computed based on the ratio of all possible two-band combinations using the RapidEye and the National Agriculturalmore » Imagery Program images collected in summer 2011. A multiple regression analysis was performed using 10 NDIs and five RapidEye spectral bands. The regression analysis suggested that the red and near infrared bands and NDI using red-edge and near infrared that is known as the red-edge normalized difference vegetation index (RENDVI) had the highest correlation (R 2 = 0.524) with the reference yield. Although predictive yield map showed striking similarity to the reference yield map, the model had modest correlation; thus, further research is needed to improve predictive capability for absolute yields. Forecasted impact using the Soil and Water Assessment Tool model of growing switchgrass ( Panicum virgatum) on under-productive areas based on corn yield thresholds of 3.1, 4.7, and 6.3 Mg·ha -1 showed reduction of tile NO 3-N and sediment exports by 15.9%–25.9% and 25%–39%, respectively. Corresponding reductions in water yields ranged from 0.9% to 2.5%. While further research is warranted, the study demonstrated the integration of remote sensing and hydrologic modeling to quantify the multifunctional value of projected future landscape patterns in a context of sustainable bioenergy crop production.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hamada, Yuki; Ssegane, Herbert; Negri, Maria Cristina
Biofuels are important alternatives for meeting our future energy needs. Successful bioenergy crop production requires maintaining environmental sustainability and minimum impacts on current net annual food, feed, and fiber production. The objectives of this study were to: (1) determine under-productive areas within an agricultural field in a watershed using a single date; high resolution remote sensing and (2) examine impacts of growing bioenergy crops in the under-productive areas using hydrologic modeling in order to facilitate sustainable landscape design. Normalized difference indices (NDIs) were computed based on the ratio of all possible two-band combinations using the RapidEye and the National Agriculturalmore » Imagery Program images collected in summer 2011. A multiple regression analysis was performed using 10 NDIs and five RapidEye spectral bands. The regression analysis suggested that the red and near infrared bands and NDI using red-edge and near infrared that is known as the red-edge normalized difference vegetation index (RENDVI) had the highest correlation (R 2 = 0.524) with the reference yield. Although predictive yield map showed striking similarity to the reference yield map, the model had modest correlation; thus, further research is needed to improve predictive capability for absolute yields. Forecasted impact using the Soil and Water Assessment Tool model of growing switchgrass ( Panicum virgatum) on under-productive areas based on corn yield thresholds of 3.1, 4.7, and 6.3 Mg·ha -1 showed reduction of tile NO 3-N and sediment exports by 15.9%–25.9% and 25%–39%, respectively. Corresponding reductions in water yields ranged from 0.9% to 2.5%. While further research is warranted, the study demonstrated the integration of remote sensing and hydrologic modeling to quantify the multifunctional value of projected future landscape patterns in a context of sustainable bioenergy crop production.« less
Jiang, Dong; Hao, Mengmeng; Wang, Qiao; Huang, Yaohuan; Fu, Xinyu
2014-01-01
The main purpose for developing biofuel is to reduce GHG (greenhouse gas) emissions, but the comprehensive environmental impact of such fuels is not clear. Life cycle analysis (LCA), as a complete comprehensive analysis method, has been widely used in bioenergy assessment studies. Great efforts have been directed toward establishing an efficient method for comprehensively estimating the greenhouse gas (GHG) emission reduction potential from the large-scale cultivation of energy plants by combining LCA with ecosystem/biogeochemical process models. LCA presents a general framework for evaluating the energy consumption and GHG emission from energy crop planting, yield acquisition, production, product use, and postprocessing. Meanwhile, ecosystem/biogeochemical process models are adopted to simulate the fluxes and storage of energy, water, carbon, and nitrogen in the soil-plant (energy crops) soil continuum. Although clear progress has been made in recent years, some problems still exist in current studies and should be addressed. This paper reviews the state-of-the-art method for estimating GHG emission reduction through developing energy crops and introduces in detail a new approach for assessing GHG emission reduction by combining LCA with biogeochemical process models. The main achievements of this study along with the problems in current studies are described and discussed. PMID:25045736
Jin, Zhenong; Zhuang, Qianlai; Tan, Zeli; Dukes, Jeffrey S; Zheng, Bangyou; Melillo, Jerry M
2016-09-01
Stresses from heat and drought are expected to increasingly suppress crop yields, but the degree to which current models can represent these effects is uncertain. Here we evaluate the algorithms that determine impacts of heat and drought stress on maize in 16 major maize models by incorporating these algorithms into a standard model, the Agricultural Production Systems sIMulator (APSIM), and running an ensemble of simulations. Although both daily mean temperature and daylight temperature are common choice of forcing heat stress algorithms, current parameterizations in most models favor the use of daylight temperature even though the algorithm was designed for daily mean temperature. Different drought algorithms (i.e., a function of soil water content, of soil water supply to demand ratio, and of actual to potential transpiration ratio) simulated considerably different patterns of water shortage over the growing season, but nonetheless predicted similar decreases in annual yield. Using the selected combination of algorithms, our simulations show that maize yield reduction was more sensitive to drought stress than to heat stress for the US Midwest since the 1980s, and this pattern will continue under future scenarios; the influence of excessive heat will become increasingly prominent by the late 21st century. Our review of algorithms in 16 crop models suggests that the impacts of heat and drought stress on plant yield can be best described by crop models that: (i) incorporate event-based descriptions of heat and drought stress, (ii) consider the effects of nighttime warming, and (iii) coordinate the interactions among multiple stresses. Our study identifies the proficiency with which different model formulations capture the impacts of heat and drought stress on maize biomass and yield production. The framework presented here can be applied to other modeled processes and used to improve yield predictions of other crops with a wide variety of crop models. © 2016 John Wiley & Sons Ltd.
NASA Astrophysics Data System (ADS)
Moore, Demie; Kostka, Stan; McMillan, Mica; Gadd, Nick
2010-05-01
Water's ability to infiltrate and disperse in soils, and soil's ability to receive, transport, retain, filter and release water are important factors in the efficient use of water in agriculture. Deteriorating soil conditions, including development of soil water repellency, negatively impact hydrological processes and, consequently, the efficiency of rainfall and irrigation. Soil water repellency is increasingly being identified in diverse soils and cropping systems. Recently research has been conducted on the use of novel soil surfactants (co-formulations of alkyl polyglycoside and block copolymer surfactants) to avoid or overcome soil water repellency and enhance water distribution in soils. Results indicate that this is an effective and affordable approach to maintaining or restoring soil and water productivity in irrigated cropping systems. Results from studies conducted in Australia and the United States to determine how this technology modifies soil hydrological behavior and crop yields will be presented. A range of soils and various crops, including potatoes, corn, apples and grapes, were included. Several rates were compared to controls for effect on soil moisture levels, soil water distribution, and crop yield. An economic analysis was also conducted in some trials. Treatments improved rootzone water status, significantly increased crop yield and quality, and in some cases allowed significant reductions in water requirements. Where assessed, a positive economic return was generated. This technology holds promise as a strategy for increasing efficiency of water use in agriculture.
Assimilation of LAI time-series in crop production models
NASA Astrophysics Data System (ADS)
Kooistra, Lammert; Rijk, Bert; Nannes, Louis
2014-05-01
Agriculture is worldwide a large consumer of freshwater, nutrients and land. Spatial explicit agricultural management activities (e.g., fertilization, irrigation) could significantly improve efficiency in resource use. In previous studies and operational applications, remote sensing has shown to be a powerful method for spatio-temporal monitoring of actual crop status. As a next step, yield forecasting by assimilating remote sensing based plant variables in crop production models would improve agricultural decision support both at the farm and field level. In this study we investigated the potential of remote sensing based Leaf Area Index (LAI) time-series assimilated in the crop production model LINTUL to improve yield forecasting at field level. The effect of assimilation method and amount of assimilated observations was evaluated. The LINTUL-3 crop production model was calibrated and validated for a potato crop on two experimental fields in the south of the Netherlands. A range of data sources (e.g., in-situ soil moisture and weather sensors, destructive crop measurements) was used for calibration of the model for the experimental field in 2010. LAI from cropscan field radiometer measurements and actual LAI measured with the LAI-2000 instrument were used as input for the LAI time-series. The LAI time-series were assimilated in the LINTUL model and validated for a second experimental field on which potatoes were grown in 2011. Yield in 2011 was simulated with an R2 of 0.82 when compared with field measured yield. Furthermore, we analysed the potential of assimilation of LAI into the LINTUL-3 model through the 'updating' assimilation technique. The deviation between measured and simulated yield decreased from 9371 kg/ha to 8729 kg/ha when assimilating weekly LAI measurements in the LINTUL model over the season of 2011. LINTUL-3 furthermore shows the main growth reducing factors, which are useful for farm decision support. The combination of crop models and sensor techniques shows promising results for precision agriculture application and thereby for reduction of the footprint agriculture has on the world's resources.
NASA Astrophysics Data System (ADS)
Chipanshi, A.; Qi, D.; Zhang, Y.; Cherneski, P.
2017-12-01
In an attempt to understand how agriculture will adapt to the changing and variable climate, crop based agrometeorological indices including the Effective Growing Degree Days (EGDDs), Growing Season Length (GSL), Heat waves, Water Demand (Precipitation - Evapotranspiration) and the Standardized Precipitation Evapotranspiration Index (SPEI) were analyzed in terms of frequency, duration and trend over a 63-year timeframe (1950 to 2012) from the Canadian Prairies and related to crop production. The heat based indices (EGDD, GSL and Heat waves) increased over the analysis period due to an upward increase in the observed mean temperature. The change was most noticeable in the northern portion of the study area where agriculture is limited by insufficient heat units under the present climate. Heat waves became more frequent in the southern parts of the study area (there were more days above the 30oC threshold). Water availability as assessed from water demand (P-PE) and SPEI trended downward especially in Alberta and Saskatchewan. In spite of the increased severity and frequency in water deficits, there was a noticeable reduction in the variability of crop yield over time. This was attributed to the increased adaptive capacity that has been gained through the use of improved seed hybrids, fertilizer, the use of fungicides and adoption of best management practices such as zero till and direct seeding. After crop yields were de-trended to remove effects of technology, the cumulative precipitation during the growing season explained the majority of the variance in crop yield. This initial analysis has set the stage for analyzing the characteristics of agrometeorological indices under climate change scenarios and how accumulated precipitation during the growing season will affect crop yield and production.
Zhao, Wei; Song, Chun; Zhou, Pan; Wang, Jia Yu; Xui, Feng; Ye, Fang; Wang, Xiao Chun; Yang, Wen Yu
2018-04-01
In order to explore the advantage of intercropping on phosphorus (P) efficient utilization and the reduction of soil P loss, a field experiment in a maize-soybean intercropping system, which included three P application (P 2 O 5 ) rates (CP: 168 kg·hm -2 ; RP 1 : 135 kg·hm -2 ; RP 2 : 101 kg·hm -2 ) and three P application depths (D 1 : applied in 5 cm depth; D 2 : applied in 15 cm depth; D 3 : 1/2 of P fertilizer applied in 5 cm depth and another 1/2 in 15 cm depth) was carried out to analyze the effects of P application rates and depth on crop aboveground biomass, grain yield, crop P uptake, soil total and available P contents, and soil P adsorption-desorption characteristics. Compared with control treatment, the aboveground biomass, grain yield, crop P uptake, soil total P, and available P content were increased significantly by P application, regardless of P rate and application depth. Under the same application depth, RP 1 had similar grain yield but higher crop P uptake compared with CP, and thus higher P apparent utilization efficiency. Under the same P application rate, the application depth of D 2 had the highest crop aboveground biomass, grain yield, P uptake, soil total P, and available P. According to the characteristic of soil P adsorption-desorption, the treatment with the rate of RP 1 and the depth of D 2 had the strongest soil P retention capacity, which had advantage in alleviating P loss. These results suggested that reducing application rate but increasing application depth of P fertilizer could improve P use efficiency and reduce soil P loss without sacrifice in crop production in maize-soybean relay intercropping system.
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.
Spatial variability of climate change impacts on yield of rice and wheat in the Indian Ganga Basin.
Mishra, Ashok; Singh, R; Raghuwanshi, N S; Chatterjee, C; Froebrich, Jochen
2013-12-01
Indian Ganga Basin (IGB), one of the most densely populated areas in the world, is facing a significant threat to food grain production, besides increased yield gap between actual and potential production, due to climate change. We have analyzed the spatial variability of climate change impacts on rice and wheat yields at three different locations representing the upper, middle and lower IGB. The DSSAT model is used to simulate the effects of climate variability and climate change on rice and wheat yields by analyzing: (i) spatial crop yield response to current climate, and (ii) impact of a changing climate as projected by two regional climate models, REMO and HadRM3, based on SRES A1B emission scenarios for the period 2011-2040. Results for current climate demonstrate a significant gap between actual and potential yield for upper, middle and lower IGB stations. The analysis based on RCM projections shows that during 2011-2040, the largest reduction in rice and wheat yields will occur in the upper IGB (reduction of potential rice and wheat yield respectively by 43.2% and 20.9% by REMO, and 24.8% and 17.2% by HadRM3). In the lower IGB, however, contrasting results are obtained, with HadRM3 based projections showing an increase in the potential rice and wheat yields, whereas, REMO based projections show decreased potential yields. We discuss the influence of agro-climatic factors; variation in temperature, length of maturity period and leaf area index which are responsible for modeled spatial variability in crop yield response within the IGB. Copyright © 2013 Elsevier B.V. All rights reserved.
Estimating yield gaps at the cropping system level.
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.
Impact of capillary rise and recirculation on simulated crop yields
NASA Astrophysics Data System (ADS)
Kroes, Joop; Supit, Iwan; van Dam, Jos; van Walsum, Paul; Mulder, Martin
2018-05-01
Upward soil water flow is a vital supply of water to crops. The purpose of this study is to determine if upward flow and recirculated percolation water can be quantified separately, and to determine the contribution of capillary rise and recirculated water to crop yield and groundwater recharge. Therefore, we performed impact analyses of various soil water flow regimes on grass, maize and potato yields in the Dutch delta. Flow regimes are characterized by soil composition and groundwater depth and derived from a national soil database. The intermittent occurrence of upward flow and its influence on crop growth are simulated with the combined SWAP-WOFOST model using various boundary conditions. Case studies and model experiments are used to illustrate the impact of upward flow on yield and crop growth. This impact is clearly present in situations with relatively shallow groundwater levels (85 % of the Netherlands), where capillary rise is a well-known source of upward flow; but also in free-draining situations the impact of upward flow is considerable. In the latter case recirculated percolation water is the flow source. To make this impact explicit we implemented a synthetic modelling option that stops upward flow from reaching the root zone, without inhibiting percolation. Such a hypothetically moisture-stressed situation compared to a natural one in the presence of shallow groundwater shows mean yield reductions for grassland, maize and potatoes of respectively 26, 3 and 14 % or respectively about 3.7, 0.3 and 1.5 t dry matter per hectare. About half of the withheld water behind these yield effects comes from recirculated percolation water as occurs in free-drainage conditions and the other half comes from increased upward capillary rise. Soil water and crop growth modelling should consider both capillary rise from groundwater and recirculation of percolation water as this improves the accuracy of yield simulations. This also improves the accuracy of the simulated groundwater recharge: neglecting these processes causes overestimates of 17 % for grassland and 46 % for potatoes, or 63 and 34 mm yr-1, respectively.
Crops in silico: A community wide multi-scale computational modeling framework of plant canopies
NASA Astrophysics Data System (ADS)
Srinivasan, V.; Christensen, A.; Borkiewic, K.; Yiwen, X.; Ellis, A.; Panneerselvam, B.; Kannan, K.; Shrivastava, S.; Cox, D.; Hart, J.; Marshall-Colon, A.; Long, S.
2016-12-01
Current crop models predict a looming gap between supply and demand for primary foodstuffs over the next 100 years. While significant yield increases were achieved in major food crops during the early years of the green revolution, the current rates of yield increases are insufficient to meet future projected food demand. Furthermore, with projected reduction in arable land, decrease in water availability, and increasing impacts of climate change on future food production, innovative technologies are required to sustainably improve crop yield. To meet these challenges, we are developing Crops in silico (Cis), a biologically informed, multi-scale, computational modeling framework that can facilitate whole plant simulations of crop systems. The Cis framework is capable of linking models of gene networks, protein synthesis, metabolic pathways, physiology, growth, and development in order to investigate crop response to different climate scenarios and resource constraints. This modeling framework will provide the mechanistic details to generate testable hypotheses toward accelerating directed breeding and engineering efforts to increase future food security. A primary objective for building such a framework is to create synergy among an inter-connected community of biologists and modelers to create a realistic virtual plant. This framework advantageously casts the detailed mechanistic understanding of individual plant processes across various scales in a common scalable framework that makes use of current advances in high performance and parallel computing. We are currently designing a user friendly interface that will make this tool equally accessible to biologists and computer scientists. Critically, this framework will provide the community with much needed tools for guiding future crop breeding and engineering, understanding the emergent implications of discoveries at the molecular level for whole plant behavior, and improved prediction of plant and ecosystem responses to the environment.
NASA Astrophysics Data System (ADS)
Liu, X.
2014-12-01
Biochar's effects on improving soil fertility, enhancing crop productivity and reducing greenhouse gases (GHGs) emission from croplands had been well addressed in numerous short-term experiments with biochar soil amendment (BSA) mostly in a single crop season / cropping year. However, the persistence of these effects, after a single biochar application, has not yet been well known due to limited long-term field studies so far. Large scale BSA in agriculture is often commented on the high cost due to large amount of biochar in a single application. Here, we try to show the persistence of biochar effects on soil fertility and crop productivity improvement as well as GHGs emission reduction, using data from a field experiment with BSA for 5 crop seasons in central North China. A single amendment of biochar was performed at rates of 0 (C0), 20 (C20) and 40 t ha-1 (C40) before sowing of the first crop season. Emissions of CO2, CH4 and N2O were monitored with static closed chamber method throughout the crop growing season for the 1st, 2nd and 5th cropping. Crop yield was measured and topsoil samples were collected at harvest of each crop season. BSA altered most of the soil physic-chemical properties with a significant increase over control in soil organic carbon (SOC) and available potassium (K) content. The increase in SOC and available K was consistent over the 5 crop seasons after BSA. Despite a significant yield increase in the first maize season, enhancement of crop yield was not consistent over crop seasons without corresponding to the changes in soil nutrient availability. BSA did not change seasonal total CO2 efflux but greatly reduced N2O emissions throughout the five seasons. This supported a stable nature of biochar carbon in soil, which played a consistent role in reducing N2O emission, which showed inter-annual variation with changes in temperature and soil moisture conditions. The biochar effect was much more consistent under C40 than under C20 and with GHGs emission than with soil property and crop yield. Thus, our study suggested that biochar amended in dry land could sustain a low carbon production both of maize and wheat in terms of its efficient carbon sequestration, lower GHGs emission intensity and soil improvement over 5 crop seasons after a single amendment.
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.
NASA Astrophysics Data System (ADS)
Sinha, B.; Singh Sangwan, K.; Maurya, Y.; Kumar, V.; Sarkar, C.; Chandra, B. P.; Sinha, V.
2015-08-01
In this study we use a high-quality data set 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 intercompare crop yield loss estimates according to different exposure metrics, such as AOT40 (accumulated ozone exposure over a threshold of 40) and M7 (mean 7-hour ozone mixing ratio from 09:00 to 15:59), for the two major crop growing seasons of kharif (June-October) and rabi (November-April) and establish a new crop-yield-exposure relationship for southern Asian wheat, maize and rice cultivars. These are a factor of 2 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 to 41 % for wheat, 21 to 26 % for rice, 3 to 5 % for maize and 47 to 58 % for cotton. Crop production losses for wheat amounted to 20.8 ± 10.4 million t in the fiscal year of 2012-2013 and 10.3 ± 4.7 million t in the fiscal year of 2013-2014 for Punjab and Haryana taken together. Crop production losses for rice totalled 5.4 ± 1.2 million t in the fiscal year of 2012-2013 and 3.2 ± 0.8 million t in the year 2013-2014 for Punjab and Haryana taken together. The Indian National Food Security Ordinance entitles ~ 820 million of India's poor to purchase about 60 kg of rice or wheat per person annually at subsidized rates. The scheme requires 27.6 Mt of wheat and 33.6 Mt of rice per year. The 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 ± 2.2 billion in the fiscal year of 2012-2013 and USD 3.7 ± 1.2 billion in the fiscal year of 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 all of India currently amounts to 3.5-20 % of India's GDP. The mitigation of high surface ozone would require relatively little investment in comparison to the economic losses incurred presently. Therefore, ozone mitigation can yield massive benefits in terms of ensuring food security and boosting the economy. The co-benefits of ozone mitigation also include a decrease in the ozone-related mortality and morbidity and a reduction of the ozone-induced warming in the lower troposphere.
NASA Astrophysics Data System (ADS)
Vico, Giulia; Porporato, Amilcare
2013-04-01
Supplemental irrigation represents one of the main strategies to mitigate the effects of climate variability and stabilize yields. Irrigated agriculture currently provides 40% of food production and its relevance is expected to further increase in the near future, in face of the projected alterations of rainfall patterns and increase in food, fiber, and biofuel demand. Because of the significant investments and water requirements involved in irrigation, strategic choices are needed to preserve productivity and profitability, while maintaining a sustainable water management - a nontrivial task given the unpredictability of the rainfall forcing. To facilitate decision making under uncertainty, a widely applicable probabilistic framework is proposed. The occurrence of rainfall events and irrigation applications are linked probabilistically to crop development during the growing season and yields at harvest. Based on these linkages, the probability density function of yields and corresponding probability density function of required irrigation volumes, as well as the probability density function of yields under the most common case of limited water availability are obtained analytically, as a function of irrigation strategy, climate, soil and crop parameters. The full probabilistic description of the frequency of occurrence of yields and water requirements is a crucial tool for decision making under uncertainty, e.g., via expected utility analysis. Furthermore, the knowledge of the probability density function of yield allows us to quantify the yield reduction hydrologic risk. Two risk indices are defined and quantified: the long-term risk index, suitable for long-term irrigation strategy assessment and investment planning, and the real-time risk index, providing a rigorous probabilistic quantification of the emergence of drought conditions during a single growing season in an agricultural setting. Our approach employs relatively few parameters and is thus easily and broadly applicable to different crops and sites, under current and future climate scenarios. Hence, the proposed probabilistic framework provides a quantitative tool to assess the impact of irrigation strategy and water allocation on the risk of not meeting a certain target yield, thus guiding the optimal allocation of water resources for human and environmental needs.
Kaliakatsou, Evridiki; Bell, J Nigel B; Thirtle, Colin; Rose, Daniel; Power, Sally A
2010-05-01
Numerous experiments have demonstrated reductions in the yields of cereal crops due to tropospheric O(3), with losses of up to 25%. However, the only British econometric study on O(3) impacts on winter wheat yields, found that a 10% increase in AOT40 would decrease yields by only 0.23%. An attempt is made here to reconcile these observations by developing AOT40 maps for Great Britain and matching levels with a large number of standardised trial plot wheat yields from many sites over a 13-year period. Panel estimates (repeated measures on the same plots with time) show a 0.54% decrease in yields and it is hypothesised that plant breeders may have inadvertently selected for O(3) tolerance in wheat. Some support for this is provided by fumigations of cultivars of differing introduction dates. A case is made for the use of econometric as well as experimental studies in prediction of air pollution induced crop loss. Copyright 2009 Elsevier Ltd. All rights reserved.
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
Engineering photorespiration: current state and future possibilities.
Peterhansel, C; Krause, K; Braun, H-P; Espie, G S; Fernie, A R; Hanson, D T; Keech, O; Maurino, V G; Mielewczik, M; Sage, R F
2013-07-01
Reduction of flux through photorespiration has been viewed as a major way to improve crop carbon fixation and yield since the energy-consuming reactions associated with this pathway were discovered. This view has been supported by the biomasses increases observed in model species that expressed artificial bypass reactions to photorespiration. Here, we present an overview about the major current attempts to reduce photorespiratory losses in crop species and provide suggestions for future research priorities. © 2012 German Botanical Society and The Royal Botanical Society of the Netherlands.
Chenu, Karine; Chapman, Scott C.; Tardieu, François; McLean, Greg; Welcker, Claude; Hammer, Graeme L.
2009-01-01
Under drought, substantial genotype–environment (G × E) interactions impede breeding progress for yield. Identifying genetic controls associated with yield response is confounded by poor genetic correlations across testing environments. Part of this problem is related to our inability to account for the interplay of genetic controls, physiological traits, and environmental conditions throughout the crop cycle. We propose a modeling approach to bridge this “gene-to-phenotype” gap. For maize under drought, we simulated the impact of quantitative trait loci (QTL) controlling two key processes (leaf and silk elongation) that influence crop growth, water use, and grain yield. Substantial G × E interaction for yield was simulated for hypothetical recombinant inbred lines (RILs) across different seasonal patterns of drought. QTL that accelerated leaf elongation caused an increase in crop leaf area and yield in well-watered or preflowering water deficit conditions, but a reduction in yield under terminal stresses (as such “leafy” genotypes prematurely exhausted the water supply). The QTL impact on yield was substantially enhanced by including pleiotropic effects of these QTL on silk elongation and on consequent grain set. The simulations obtained illustrated the difficulty of interpreting the genetic control of yield for genotypes influenced only by the additive effects of QTL associated with leaf and silk growth. The results highlight the potential of integrative simulation modeling for gene-to-phenotype prediction and for exploiting G × E interactions for complex traits such as drought tolerance. PMID:19786622
NASA Astrophysics Data System (ADS)
Han, Xiao; Xu, Cong; Dungait, Jennifer A. J.; Bol, Roland; Wang, Xiaojie; Wu, Wenliang; Meng, Fanqiao
2018-04-01
Loss of soil organic carbon (SOC) from agricultural soils is a key indicator of soil degradation associated with reductions in net primary productivity in crop production systems worldwide. Technically simple and locally appropriate solutions are required for farmers to increase SOC and to improve cropland management. In the last 30 years, straw incorporation (SI) has gradually been implemented across China in the context of agricultural intensification and rural livelihood improvement. A meta-analysis of data published before the end of 2016 was undertaken to investigate the effects of SI on crop production and SOC sequestration. The results of 68 experimental studies throughout China in different edaphic conditions, climate regions and farming regimes were analyzed. Compared with straw removal (SR), SI significantly sequestered SOC (0-20 cm depth) at the rate of 0.35 (95 % CI, 0.31-0.40) Mg C ha-1 yr-1, increased crop grain yield by 13.4 % (9.3-18.4 %) and had a conversion efficiency of the incorporated straw C of 16 % ± 2 % across China. The combined SI at the rate of 3 Mg C ha-1 yr-1 with mineral fertilizer of 200-400 kg N ha-1 yr-1 was demonstrated to be the best farming practice, where crop yield increased by 32.7 % (17.9-56.4 %) and SOC sequestrated by the rate of 0.85 (0.54-1.15) Mg C ha-1 yr-1. SI achieved a higher SOC sequestration rate and crop yield increment when applied to clay soils under high cropping intensities, and in areas such as northeast China where the soil is being degraded. The SOC responses were highest in the initial starting phase of SI, then subsequently declined and finally became negligible after 28-62 years. However, crop yield responses were initially low and then increased, reaching their highest level at 11-15 years after SI. Overall, our study confirmed that SI created a positive feedback loop of SOC enhancement together with increased crop production, and this is of great practical importance to straw management as agriculture intensifies both in China and other regions with different climate conditions.
Assessment of impact of climate change and adaptation strategies on maize production in Uganda
NASA Astrophysics Data System (ADS)
Kikoyo, Duncan A.; Nobert, Joel
2016-06-01
Globally, various climatic studies have estimated a reduction of crop yields due to changes in surface temperature and precipitation especially for the developing countries which is heavily dependent on agriculture and lacks resources to counter the negative effects of climate change. Uganda's economy and the wellbeing of its populace depend on rain-fed agriculture which is susceptible to climate change. This study quantified the impacts of climate change and variability in Uganda and how coping strategies can enhance crop production against climate change and/or variability. The study used statistical methods to establish various climate change and variability indicators across the country, and uses the FAO AquaCrop model to simulate yields under possible future climate scenarios with and without adaptation strategies. Maize, the most widely grown crop was used for the study. Meteorological, soil and crop data were collected for various districts representing the maize growing ecological zones in the country. Based on this study, it was found that temperatures have increased by up to 1 °C across much of Uganda since the 1970s, with rates of warming around 0.3 °C per decade across the country. High altitude, low rainfall regions experience the highest level of warming, with over 0.5 °C/decade recorded in Kasese. Rainfall is variable and does not follow a specific significant increasing or decreasing trend. For both future climate scenarios, Maize yields will reduce in excess of 4.7% for the fast warming-low rainfall climates but increase on average by 3.5% for slow warming-high rainfall regions, by 2050. Improved soil fertility can improve yields by over 50% while mulching and use of surface water management practices improve yields by single digit percentages. The use of fertilizer application needs to go hand in hand with other water management strategies since more yields as a result of the improved soil fertility leads to increased water stress, especially for the dry climates.
NASA Astrophysics Data System (ADS)
Sakurai, G.; Iizumi, T.; Yokozawa, M.
2011-12-01
The actual impact of elevated [CO2] with the interaction of the other climatic factors on the crop growth is still debated. In many process-based crop models, the response of photosynthesis per single leaf to environmental factors is basically described using the biochemical model of Farquhar et al. (1980). However, the decline in photosynthetic enhancement known as down regulation has not been taken into account. On the other hand, the mechanisms causing photosynthetic down regulation is still unknown, which makes it difficult to include the effect of down regulation into process-based crop models. The current results of Free-air CO2 enrichment (FACE) experiments have reported the effect of down regulation under actual environments. One of the effective approaches to involve these results into future crop yield prediction is developing a semi process-based crop growth model, which includes the effect of photosynthetic down regulation as a statistical model, and assimilating the data obtained in FACE experiments. In this study, we statistically estimated the parameters of a semi process-based model for soybean growth ('SPM-soybean') using a hierarchical Baysian method with the FACE data on soybeans (Morgan et al. 2005). We also evaluated the effect of down regulation on the soybean yield in future climatic conditions. The model selection analysis showed that the effective correction to the overestimation of the Farquhar's biochemical C3 model was to reduce the maximum rate of carboxylation (Vcmax) under elevated [CO2]. However, interestingly, the difference in the estimated final crop yields between the corrected model and the non-corrected model was very slight (Fig.1a) for future projection under climate change scenario (Miroc-ESM). This was due to that the reduction in Vcmax also brought about the reduction of the base dark respiration rate of leaves. Because the dark respiration rate exponentially increases with temperature, the slight difference in base respiration rate becomes a large difference under high temperature under the future climate scenarios. In other words, if the temperature rise is very small or zero under elevated [CO2] condition, the effect of down regulation significantly appears (Fig.1b). This result suggest that further experimental data that considering high CO2 effect and high temperature effect in field conditions should be important and elaborate the model projection of the future crop yield through data assimilation method.
Feuerbacher, Arndt; Luckmann, Jonas; Boysen, Ole; Zikeli, Sabine; Grethe, Harald
2018-01-01
Organic agriculture (OA) is considered a strategy to make agriculture more sustainable. Bhutan has embraced the ambitious goal of becoming the world's first 100% organic nation. By analysing recent on-farm data in Bhutan, we found organic crop yields on average to be 24% lower than conventional yields. Based on these yield gaps, we assess the effects of the 100% organic conversion policy by employing an economy-wide computable general equilibrium (CGE) model with detailed representation of Bhutan's agricultural sector incorporating agroecological zones, crop nutrients, and field operations. Despite a low dependency on agrochemicals from the onset of this initiative, we find a considerable reduction in Bhutan's GDP, substantial welfare losses, particularly for non-agricultural households, and adverse impacts on food security. The yield gap is the main driver for a strong decline in domestic agricultural production, which is largely compensated by increased food imports, resulting in a weakening of the country's cereal self-sufficiency. Current organic by default farming practices in Bhutan are still underdeveloped and do not apply the systems approach of organic farming as defined in the IFOAM organic farming standards. This is reflected in the strong decline of nitrogen (N) availability to crops in our simulation and bears potential for increased yields in OA. Improvement of soil-fertility practices, e.g., the adoption of N-fixing crops, improved animal husbandry systems with increased provision of animal manure and access to markets with price premium for organic products could help to lower the economic cost of the large-scale conversion.
Luckmann, Jonas; Boysen, Ole; Zikeli, Sabine; Grethe, Harald
2018-01-01
Organic agriculture (OA) is considered a strategy to make agriculture more sustainable. Bhutan has embraced the ambitious goal of becoming the world’s first 100% organic nation. By analysing recent on-farm data in Bhutan, we found organic crop yields on average to be 24% lower than conventional yields. Based on these yield gaps, we assess the effects of the 100% organic conversion policy by employing an economy-wide computable general equilibrium (CGE) model with detailed representation of Bhutan’s agricultural sector incorporating agroecological zones, crop nutrients, and field operations. Despite a low dependency on agrochemicals from the onset of this initiative, we find a considerable reduction in Bhutan’s GDP, substantial welfare losses, particularly for non-agricultural households, and adverse impacts on food security. The yield gap is the main driver for a strong decline in domestic agricultural production, which is largely compensated by increased food imports, resulting in a weakening of the country’s cereal self-sufficiency. Current organic by default farming practices in Bhutan are still underdeveloped and do not apply the systems approach of organic farming as defined in the IFOAM organic farming standards. This is reflected in the strong decline of nitrogen (N) availability to crops in our simulation and bears potential for increased yields in OA. Improvement of soil-fertility practices, e.g., the adoption of N-fixing crops, improved animal husbandry systems with increased provision of animal manure and access to markets with price premium for organic products could help to lower the economic cost of the large-scale conversion. PMID:29897989
Consequence of climate mitigation on the risk of hunger.
Hasegawa, Tomoko; Fujimori, Shinichiro; Shin, Yonghee; Tanaka, Akemi; Takahashi, Kiyoshi; Masui, Toshihiko
2015-06-16
Climate change and mitigation measures have three major impacts on food consumption and the risk of hunger: (1) changes in crop yields caused by climate change; (2) competition for land between food crops and energy crops driven by the use of bioenergy; and (3) costs associated with mitigation measures taken to meet an emissions reduction target that keeps the global average temperature increase to 2 °C. In this study, we combined a global computable general equilibrium model and a crop model (M-GAEZ), and we quantified the three impacts on risk of hunger through 2050 based on the uncertainty range associated with 12 climate models and one economic and demographic scenario. The strong mitigation measures aimed at attaining the 2 °C target reduce the negative effects of climate change on yields but have large negative impacts on the risk of hunger due to mitigation costs in the low-income countries. We also found that in a strongly carbon-constrained world, the change in food consumption resulting from mitigation measures depends more strongly on the change in incomes than the change in food prices.
Naranjo, Steven E; Ellsworth, Peter C; Dierig, David A
2011-10-01
Lesquerella, Physaria fendleri (A. Gray) S. Watson, is a mustard native to the western United States and is currently being developed as a commercial source of valuable hydroxy fatty acids that can be used in a number of industrial applications, including biolubricants, biofuel additives, motor oils, resins, waxes, nylons, plastics, corrosion inhibitors, cosmetics, and coatings. The plant is cultivated as a winter-spring annual and in the desert southwest it harbors large populations of arthropods, several of which could be significant pests once production expands. Lygus spp. (Hemiptera: Miridae) are common in lesquerella and are known pests of a number of agronomic and horticultural crops where they feed primarily on reproductive tissues. A 4-yr replicated plot study was undertaken to evaluate the probable impact of Lygus spp. on production of this potential new crop. Plant damage and subsequent seed yield and quality were examined relative to variable and representative densities of Lygus spp. (0.3-4.9 insects per sweep net) resulting from variable frequency and timing of insecticide applications. Increasing damage to various fruiting structures (flowers [0.9-13.9%], buds [1.2-7.1%], and seed pods [19.4-42.5%]) was significantly associated with increasing pest abundance, particularly the abundance of nymphs, in all years. This damage, however, did not consistently translate into reductions in seed yield (481-1,336 kg/ha), individual seed weight (0.5-0.7 g per 1,000 seed), or seed oil content (21.8-30.4%), and pest abundance generally explained relatively little of the variation in crop yield and quality. Negative effects on yield were not sensitive to the timing of pest damage (early versus late season) but were more pronounced during years when potential yields were lower due to weed competition and other agronomic factors. Results suggest that if the crop is established and managed in a more optimal fashion, Lygus spp. may not significantly limit yield. Nonetheless, additional work will be needed once more uniform cultivars become available and yield effects can be more precisely measured. Densities of Lygus spp. in unsprayed lesquerella are on par with those in other known agroecosystem level sources of this pest (e.g., forage and seed alfalfa, Medicago sativa L.). Thus, lesquerella production may introduce new challenges to pest management in crops such as cotton.
Detection and characterization of the first North American mastrevirus in Switchgrass
USDA-ARS?s Scientific Manuscript database
Virus infections have the potential to reduce biomass yields in energy crops, including Panicum virgatum (switchgrass). As a first step towards managing virus-induced biomass reductions, deep sequencing was used to identify viruses associated with mosaic symptoms in switch grass, which detected thre...
Implications of Climate Mitigation for Future Agricultural Production
NASA Technical Reports Server (NTRS)
Mueller, Christoph; Elliott, Joshua; Chryssanthacopoulos, James; Deryng, Delphine; Folberth, Christian; Pugh, Thomas A. M.; Schmid, Erwin
2015-01-01
Climate change is projected to negatively impact biophysical agricultural productivity in much of the world. Actions taken to reduce greenhouse gas emissions and mitigate future climate changes, are thus of central importance for agricultural production. Climate impacts are, however, not unidirectional; some crops in some regions (primarily higher latitudes) are projected to benefit, particularly if increased atmospheric carbon dioxide is assumed to strongly increase crop productivity at large spatial and temporal scales. Climate mitigation measures that are implemented by reducing atmospheric carbon dioxide concentrations lead to reductions both in the strength of climate change and in the benefits of carbon dioxide fertilization. Consequently, analysis of the effects of climate mitigation on agricultural productivity must address not only regions for which mitigation is likely to reduce or even reverse climate damages. There are also regions that are likely to see increased crop yields due to climate change, which may lose these added potentials under mitigation action. Comparing data from the most comprehensive archive of crop yield projections publicly available, we find that climate mitigation leads to overall benefits from avoided damages at the global scale and especially in many regions that are already at risk of food insecurity today. Ignoring controversial carbon dioxide fertilization effects on crop productivity, we find that for the median projection aggressive mitigation could eliminate approximately 81% of the negative impacts of climate change on biophysical agricultural productivity globally by the end of the century. In this case, the benefits of mitigation typically extend well into temperate regions, but vary by crop and underlying climate model projections. Should large benefits to crop yields from carbon dioxide fertilization be realized, the effects of mitigation become much more mixed, though still positive globally and beneficial in many food insecure countries.
Commercial Crop Yields Reveal Strengths and Weaknesses for Organic Agriculture in the United States.
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
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
Effects of geoengineering on crop yields
NASA Astrophysics Data System (ADS)
Pongratz, J.; Lobell, D. B.; Cao, L.; Caldeira, K.
2011-12-01
The potential of "solar radiation management" (SRM) to reduce future climate change and associated risks has been receiving significant attention in scientific and policy circles. SRM schemes aim to reduce global warming despite increasing atmospheric CO2 concentrations by diminishing the amount of solar insolation absorbed by the Earth, for example, by injecting scattering aerosols into the atmosphere. Climate models predict that SRM could fully compensate warming at the global mean in a high-CO2 world. While reduction of global warming may offset a part of the predicted negative effects of future climate change on crop yields, SRM schemes are expected to alter regional climate and to have substantial effects on climate variables other than temperature, such as precipitation. It has therefore been warned that, overall, SRM may pose a risk to food security. Assessments of benefits and risks of geoengineering are imperative, yet such assessments are only beginning to emerge; in particular, effects on global food security have not previously been assessed. Here, for the first time, we combine climate model simulations with models of crop yield responses to climate to assess large-scale changes in yields and food production under SRM. In most crop-growing regions, we find that yield losses caused by climate changes are substantially reduced under SRM as compared with a non-geoengineered doubling of atmospheric CO2. Substantial yield losses with SRM are only found for rice in high latitudes, where the limits of low temperatures are no longer alleviated. At the same time, the beneficial effect of CO2-fertilization on plant productivity remains active. Overall therefore, SRM in our models causes global crop yields to increase. We estimate the direct effects of climate and CO2 changes on crop production, and do not quantify effects of market dynamics and management changes. We note, however, that an SRM deployment would be unlikely to maintain the economic status quo, as market shares of agricultural output may change with the different spatial pattern of climate change. More importantly, geoengineering by SRM does not address a range of other detrimental consequences of climate change, such as ocean acidification, which could also affect food security via effects on marine food webs. Finally, SRM poses substantial anticipated and unanticipated risks by interfering with complex, not fully understood systems. Therefore, despite potential positive effects of SRM on crop yields, the most certain way to reduce climate risks to global food security is to reduce emissions of greenhouse gases.
Maize ARGOS1 (ZAR1) transgenic alleles increase hybrid maize yield.
Guo, Mei; Rupe, Mary A; Wei, Jun; Winkler, Chris; Goncalves-Butruille, Marymar; Weers, Ben P; Cerwick, Sharon F; Dieter, Jo Ann; Duncan, Keith E; Howard, Richard J; Hou, Zhenglin; Löffler, Carlos M; Cooper, Mark; Simmons, Carl R
2014-01-01
Crop improvement for yield and drought tolerance is challenging due to the complex genetic nature of these traits and environmental dependencies. This study reports that transgenic over-expression of Zea mays AR GOS1 (ZAR1) enhanced maize organ growth, grain yield, and drought-stress tolerance. The ZAR1 transgene exhibited environmental interactions, with yield increase under Temperate Dry and yield reduction under Temperate Humid or High Latitude environments. Native ZAR1 allele variation associated with drought-stress tolerance. Two founder alleles identified in the mid-maturity germplasm of North America now predominate in Pioneer's modern breeding programme, and have distinct proteins, promoters and expression patterns. These two major alleles show heterotic group partitioning, with one predominant in Pioneer's female and the other in the male heterotic groups, respectively. These two alleles also associate with favourable crop performance when heterozygous. Allele-specific transgene testing showed that, of the two alleles discussed here, each allele differed in their impact on yield and environmental interactions. Moreover, when transgenically stacked together the allelic pair showed yield and environmental performance advantages over either single allele, resembling heterosis effects. This work demonstrates differences in transgenic efficacy of native alleles and the differences reflect their association with hybrid breeding performance.
Global Food Security Index Studies and Satellite Information
NASA Astrophysics Data System (ADS)
Medina, T. A.; Ganti-Agrawal, S.; Joshi, D.; Lakhankar, T.
2017-12-01
Food yield is equal to the total crop harvest per unit cultivated area. During the elapsed time of germination and frequent harvesting, both human and climate related effects determine a country's' contribution towards global food security. Each country across the globe's annual income per capita was collected to then determine nine countries for further studies. For a location to be chosen, its income per capita needed to be considered poor, uprising or wealthy. Both physical land cover and regional climate helped categorize potential parameters thought to be studied. Once selected, Normalized Difference Vegetation Index (NDVI) data was collected for Ethiopia, Liberia, Indonesia, United States, Norway, Russia, Kuwait and Saudi Arabia over the recent 16 years for approximately every 16 days starting from early in the year 2000. Software languages such as Geographic Information System (GIS), MatLab and Excel were used to determine how population size, income and deforestation directly determines agricultural yields. Because of high maintenance requirements for large harvests when forest areas are cleared, they often have a reduction in soil quality, requiring fertilizer use to produce sufficient crop yields. Total area and vegetation index of each country is to be studied, to determine crop and deforestation percentages. To determine how deforestation impacts future income and crop yield predictions of each country studied. By using NDVI results a parameter is to be potentially found that will help define an index, to create an equation that will determine a country's annual income and ability to provide for their families and themselves.
Agomoh, Ikechukwu; Hao, Xiying; Zvomuya, Francis
2018-01-02
Phytoextraction of excess nutrients by crops in soils with a long history of manure application may be a viable option for reducing the nutrient levels. This greenhouse study examined the effectiveness of six growth cycles (40 d each) of barley, canola, corn, oat, pea, soybean, and triticale at extracting nitrogen (N) and phosphorus (P) from a Dark Brown Chernozem that had received 180 Mg ha -1 (wet wt.) of beef cattle feedlot manure annually for 38 years. Moisture content during the study was maintained at either 100% or 50% soil field capacity (SFC). Repeated cropping resulted in an overall decrease in dry matter yield (DMY). The decrease in N and P uptake relative to Cycle 1 was fastest for the cereal grains and less pronounced for the two legumes. However, cumulative N uptake values were significantly greater for corn than the other crops under both moisture regimes. The reduction in soil N was greater under the 100% than the 50% SFC. These results indicate that repeated cropping can be a useful management practice for reducing N and P levels in a heavily manured soil. The extent of reduction will be greater for crops with high biomass production under adequate moisture supply.
Increasing crop diversity mitigates weather variations and improves yield stability.
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.
Impacts on Global Agriculture of Stratospheric Sulfate Injection
NASA Astrophysics Data System (ADS)
Robock, A.; Xia, L.
2014-12-01
Impacts on global food supply are one of the most important concerns in the discussion of stratospheric sulfate geoengineering. Stratospheric sulfate injection could reduce surface temperature, precipitation, and insolation, which could affect agricultural production. We use output from climate model simulations using the two most "realistic" scenarios from the Geoengineering Model Intercomparison Project, G3 and G4. G3 posits balancing the increasing radiative forcing from the RCP4.5 business-as-usual scenario with stratospheric sulfate aerosols from 2020 through 2070. The G4 scenario also uses RCP4.5, but models simulate the stratospheric injection of 5 Tg SO2 per year from 2020 to 2070. In total, there are three modeling groups which have completed G3 and four for G4. We use two crop models, the global gridded Decision Support System for Agrotechnology Transfer (gDSSAT) crop model and the crop model in the NCAR Community Land Model (CLM-crop), to predict global maize yield changes. Without changing agricultural technology, we find that compared to the reference run forced by the RCP4.5 scenario, maize yields could increase in both G3 and G4 due to both the cooling effect of stratospheric sulfate injection and the CO2 fertilization effect, with the cooling effect contributing more to the increased productivity. However, the maize yield changes are not much larger than natural variability under G3, since the temperature reduction is smaller in G3 than in G4. Both crop models show similar results.
Sandhu, Harpinder; Waterhouse, Benjamin; Boyer, Stephane; Wratten, Steve
2016-01-01
Ecosystem services (ES) such as pollination are vital for the continuous supply of food to a growing human population, but the decline in populations of insect pollinators worldwide poses a threat to food and nutritional security. Using a pollinator (honeybee) exclusion approach, we evaluated the impact of pollinator scarcity on production in four brassica fields, two producing hybrid seeds and two producing open-pollinated ones. There was a clear reduction in seed yield as pollination rates declined. Open-pollinated crops produced significantly higher yields than did the hybrid ones at all pollination rates. The hybrid crops required at least 0.50 of background pollination rates to achieve maximum yield, whereas in open-pollinated crops, 0.25 pollination rates were necessary for maximum yield. The total estimated economic value of pollination services provided by honeybees to the agricultural industry in New Zealand is NZD $1.96 billion annually. This study indicates that loss of pollination services can result in significant declines in production and have serious implications for the market economy in New Zealand. Depending on the extent of honeybee population decline, and assuming that results in declining pollination services, the estimated economic loss to New Zealand agriculture could be in the range of NZD $295-728 million annually.
Waterhouse, Benjamin; Wratten, Steve
2016-01-01
Ecosystem services (ES) such as pollination are vital for the continuous supply of food to a growing human population, but the decline in populations of insect pollinators worldwide poses a threat to food and nutritional security. Using a pollinator (honeybee) exclusion approach, we evaluated the impact of pollinator scarcity on production in four brassica fields, two producing hybrid seeds and two producing open-pollinated ones. There was a clear reduction in seed yield as pollination rates declined. Open-pollinated crops produced significantly higher yields than did the hybrid ones at all pollination rates. The hybrid crops required at least 0.50 of background pollination rates to achieve maximum yield, whereas in open-pollinated crops, 0.25 pollination rates were necessary for maximum yield. The total estimated economic value of pollination services provided by honeybees to the agricultural industry in New Zealand is NZD $1.96 billion annually. This study indicates that loss of pollination services can result in significant declines in production and have serious implications for the market economy in New Zealand. Depending on the extent of honeybee population decline, and assuming that results in declining pollination services, the estimated economic loss to New Zealand agriculture could be in the range of NZD $295–728 million annually. PMID:27441108
First report of Xiphinema rivesi (Nematoda, Longidoridae) in Washington State
USDA-ARS?s Scientific Manuscript database
The dagger nematode Xiphinema rivesi Dalmasso 1969 transmits several viruses in North America and Europe (2), causing severe yield reduction in crops. During a routine survey of cherry orchards suffering from cherry rasp leaf disease caused by Cherry rasp leaf virus (CRLV) (genus Cheravirus) in Che...
Azadirachtin powder for control of root-knot nematodes in tomato
USDA-ARS?s Scientific Manuscript database
USDA ARS Daniel K. Inouye U.S. Pacific Basin Agricultural Research Center, 64 Nowelo St., Hilo, HI 96720. Root-knot nematodes cause root galling and yield reductions in many vegetable crops, including tomato. Three organic treatments to improve root growth and reduce nematode infestation were eval...
2011 High Plains and Northern Rolling Plains Cotton Harvest-Aid Guide
USDA-ARS?s Scientific Manuscript database
Harvest-aid chemicals are generally applied to hasten harvest of a mature crop and to reduce potential preharvest losses of lint yield and fiber quality. Proper use of harvest aids can result in earlier harvest, preservation of fiber quality, and fewer seed quality reductions due to field exposure. ...
2009 High plains and northern rolling plains cotton harvest-aid guide
USDA-ARS?s Scientific Manuscript database
Harvest-aid chemicals are generally applied to hasten harvest of a mature crop, and to reduce potential preharvest losses of lint yield and fiber quality. Proper use of harvest aids can result in earlier harvest, preservation of fiber quality, and fewer seed quality reductions due to field exposure....
2012 High Plains and Northern Rolling Plains Cotton harvest aid-guide
USDA-ARS?s Scientific Manuscript database
Harvest-aid chemicals are generally applied to hasten harvest of a mature crop, and to reduce potential preharvest losses of lint yield and fiber quality. Proper use of harvest aids can result in earlier harvest, preservation of fiber quality, and fewer seed quality reductions due to field exposure....
Ozone dose-response relationships for spring oilseed rape and broccoli
NASA Astrophysics Data System (ADS)
De Bock, Maarten; Op de Beeck, Maarten; De Temmerman, Ludwig; Guisez, Yves; Ceulemans, Reinhart; Vandermeiren, Karine
2011-03-01
Tropospheric ozone is an important air pollutant with known detrimental effects for several crops. Ozone effects on seed yield, oil percentage, oil yield and 1000 seed weight were examined for spring oilseed rape ( Brassica napus cv. Ability). For broccoli ( Brassica oleracea L. cv. Italica cv. Monaco) the effects on fresh marketable weight and total dry weight were studied. Current ozone levels were compared with an increase of 20 and 40 ppb during 8 h per day, over the entire growing season. Oilseed rape seed yield was negatively correlated with ozone dose indices calculated from emergence until harvest. This resulted in an R2 of 0.24 and 0.26 ( p < 0.001) for the accumulated hourly O 3 exposure over a threshold of 40 ppb (AOT40) and the phytotoxic ozone dose above a threshold of 6 nmol m -2 s -1 (POD 6) respectively. Estimated critical levels, above which 5% yield reduction is expected, were 3.7 ppm h and 4.4 mmol m -2 respectively. Our results also confirm that a threshold value of 6 nmol s -1 m -2 projected leaf area, as recommended for agricultural crops (UNECE, Mills, 2004), can indeed be applied for spring oilseed rape. The reduction of oilseed rape yield showed the highest correlation with the ozone uptake during the vegetative growth stage: when only the first 47 days after emergence were used to calculate POD 6, R2 values increased up to 0.476 or even 0.545 when the first 23 days were excluded. The highest ozone treatments, corresponding to the future ambient level by 2100 (IPCC, Meehl et al., 2007), led to a reduction of approximately 30% in oilseed rape seed yield in comparison to the current ozone concentrations. Oil percentage was also significantly reduced in response to ozone ( p < 0.001). As a consequence oil yield was even more severely affected by elevated ozone exposure compared to seed yield: critical levels for oil yield dropped to 3.2 ppm h and 3.9 mmol m -2. For broccoli the applied ozone doses had no effect on yield.
Liu, Xiuwei; Sun, Hongyong; Feike, Til; Zhang, Xiying; Shao, Liwei; Chen, Suying
2016-01-01
The major wheat production region of China the North China Plain (NCP) is seriously affected by air pollution. In this study, yield of winter wheat (Triticum aestivum L.) was analyzed with respect to the potential impact of air pollution index under conditions of optimal crop management in the NCP from 2001 to 2012. Results showed that air pollution was especially serious at the early phase of winter wheat growth significantly influencing various weather factors. However, no significant correlations were found between final grain yield and the weather factors during the early growth phase. In contrast, significant correlations were found between grain yield and total solar radiation gap, sunshine hour gap, diurnal temperature range and relative humidity during the late growing phase. To disentangle the confounding effects of various weather factors, and test the isolated effect of air pollution induced changes in incoming global solar radiation on yield under ceteris paribus conditions, crop model based scenario-analysis was conducted. The simulation results of the calibrated Agricultural Production Systems Simulator (APSIM) model indicated that a reduction in radiation by 10% might cause a yield reduction by more than 10%. Increasing incident radiation by 10% would lead to yield increases of (only) 7%, with the effects being much stronger during the late growing phase compared to the early growing phase. However, there is evidence that APSIM overestimates the effect of air pollution induced changes on radiation, as it does not consider the changes in radiative properties of solar insulation, i.e. the relative increase of diffuse over direct radiation, which may partly alleviate the negative effects of reduced total radiation by air pollution. Concluding, the present study could not detect a significantly negative effect of air pollution on wheat yields in the NCP.
Kumar, Virender; Jat, Hanuman S; Sharma, Parbodh C; Balwinder-Singh; Gathala, Mahesh K; Malik, Ram K; Kamboj, Baldev R; Yadav, Arvind K; Ladha, Jagdish K; Raman, Anitha; Sharma, D K; McDonald, Andrew
2018-01-15
In the most productive area of the Indo-Gangetic Plains in Northwest India where high yields of rice and wheat are commonplace, a medium-term cropping system trial was conducted in Haryana State. The goal of the study was to identify integrated management options for further improving productivity and profitability while rationalizing resource use and reducing environmental externalities (i.e., "sustainable intensification", SI) by drawing on the principles of diversification, precision management, and conservation agriculture. Four scenarios were evaluated: Scenario 1 - "business-as-usual" [conventional puddled transplanted rice (PTR) followed by ( fb ) conventional-till wheat]; Scenario 2 - reduced tillage with opportunistic diversification and precision resource management [PTR fb zero-till (ZT) wheat fb ZT mungbean]; Scenario 3 - ZT for all crops with opportunistic diversification and precision resource management [ZT direct-seeded rice (ZT-DSR) fb ZT wheat fb ZT mungbean]; and Scenario 4 - ZT for all crops with strategic diversification and precision resource management [ZT maize fb ZT wheat fb ZT mungbean]. Results of this five-year study strongly suggest that, compared with business-as-usual practices, SI strategies that incorporate multi-objective yield, economic, and environmental criteria can be more productive when used in these production environments. For Scenarios 2, 3, and 4, system-level increases in productivity (10-17%) and profitability (24-50%) were observed while using less irrigation water (15-71% reduction) and energy (17-47% reduction), leading to 15-30% lower global warming potential (GWP), with the ranges reflecting the implications of specific innovations. Scenario 3, where early wheat sowing was combined with ZT along with no puddling during the rice phase, resulted in a 13% gain in wheat yield compared with Scenario 2. A similar gain in wheat yield was observed in Scenario 4 vis-à-vis Scenario 2. Compared to Scenario 1, wheat yields in Scenarios 3 and 4 were 15-17% higher, whereas, in Scenario 2, yield was either similar in normal years or higher in warmer years. During the rainy ( kharif ) season, ZT-DSR provided yields similar to or higher than those of PTR in the first three years and lower (11-30%) in Years 4 and 5, a result that provides a note of caution for interpreting technology performance through short-term trials or simply averaging results over several years. The resource use and economic and environmental advantages of DSR were more stable through time, including reductions in irrigation water (22-40%), production cost (11-17%), energy inputs (13-34%), and total GWP (14-32%). The integration of "best practices" in PTR in Scenario 2 resulted in reductions of 24% in irrigation water and 21% in GWP, with a positive impact on yield (0.9 t/ha) and profitability compared to conventional PTR, demonstrating the power of simple management changes to generate improved SI outcomes. When ZT maize was used as a diversification option instead of rice in Scenario 4, reductions in resource use jumped to 82-89% for irrigation water and 49-66% for energy inputs, with 13-40% lower GWP, similar or higher rice equivalent yield, and higher profitability (27-73%) in comparison to the rice-based scenarios. Despite these advantages, maize value chains are not robust in this part of India and public procurement is absent. Results do demonstrate that transformative opportunities exist to break the cycle of stagnating yields and inefficient resource use in the most productive cereal-based cropping systems of South Asia. However, these SI entry points need to be placed in the context of the major drivers of change in the region, including market conditions, risks, and declining labor availability, and matching with the needs and interests of different types of farmers.
Weather based risks and insurances for crop production in Belgium
NASA Astrophysics Data System (ADS)
Gobin, Anne
2014-05-01
Extreme weather events such as late frosts, droughts, heat waves and rain storms can have devastating effects on cropping systems. Damages due to extreme events are strongly dependent on crop type, crop stage, soil type and soil conditions. The perspective of rising risk-exposure is exacerbated further by limited aid received for agricultural damage, an overall reduction of direct income support to farmers and projected intensification of weather extremes with climate change. According to both the agriculture and finance sectors, a risk assessment of extreme weather events and their impact on cropping systems is needed. The impact of extreme weather events particularly during the sensitive periods of the farming calendar requires a modelling approach to capture the mixture of non-linear interactions between the crop, its environment and the occurrence of the meteorological event. The risk of soil moisture deficit increases towards harvesting, such that drought stress occurs in spring and summer. Conversely, waterlogging occurs mostly during early spring and autumn. Risks of temperature stress appear during winter and spring for chilling and during summer for heat. Since crop development is driven by thermal time and photoperiod, the regional crop model REGCROP (Gobin, 2010) enabled to examine the likely frequency, magnitude and impacts of frost, drought, heat stress and waterlogging in relation to the cropping season and crop sensitive stages. The risk profiles were subsequently confronted with yields, yield losses and insurance claims for different crops. Physically based crop models such as REGCROP assist in understanding the links between different factors causing crop damage as demonstrated for cropping systems in Belgium. Extreme weather events have already precipitated contraction of insurance coverage in some markets (e.g. hail insurance), and the process can be expected to continue if the losses or damages from such events increase in the future. Climate change will stress this further and impacts on crop growth are expected to be twofold, owing to the sensitive stages occurring earlier during the growing season and to the changes in return period of extreme weather events. Though average yields have risen continuously due to technological advances, there is no evidence that relative tolerance to adverse weather events has improved. The research is funded by the Belgian Science Policy Organisation (Belspo) under contract nr SD/RI/03A.
Sarker, Ashutosh; Fikre, Asnake; El-Moneim, Ali M Abd; Nakkoul, Hani; Singh, Murari
2018-01-01
Grasspea (Lathyrus sativus L.) is an important pulse crop for food, feed and sustainable crop production systems in Ethiopia. Despite its advantages in nutrition and adaptability to harsh climate and low fertile soil, it contains a neurotoxin, β-N-oxalyl-α,β-diamiono propionic acid (β-ODAP), which paralyses the lower limbs and is affected by genotypic and agronomic factors. To determine the effect of zinc application and planting date on yield and β-ODAP content of two genotypes, experiments were conducted in two regions of Ethiopia. The main effects of variety, sowing date and zinc and their interactions were significant (P < 0.001) for β-ODAP and seed yield, which had a linear relationship with zinc. For the improved grasspea variety, an application of 20 kg ha -1 zinc showed a reduction of β-ODAP from 0.15% to 0.088% at Debre Zeit and 0.14% to 0.08% at Sheno and increased its yield from 841 kg ha -1 to 2260 kg ha -1 at Debre Zeit and from 715 to 1835 kg ha -1 at Sheno. Early sowing showed a reduction in ODAP content in relation to the late sowing. An application of Zn beyond even 20 kg ha -1 with an early sowing is recommended for the improved variety. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.
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...
Xiao, Dengpan; Tao, Fulu
2016-07-01
The impact of climate change on crop yield is compounded by cultivar shifts and agronomic management practices. To determine the relative contributions of climate change, cultivar shift, and management practice to changes in maize (Zea mays L.) yield in the past three decades, detailed field data for 1981-2009 from four representative experimental stations in North China Plain (NCP) were analyzed via model simulation. The four representative experimental stations are geographically and climatologically different, represent the typical cropping system in the study area, and have more complete weather/crop records for the period of 1981-2009. The results showed that while the shift from traditional to modern cultivar increased yield by 23.9-40.3 %, new fertilizer management increased yield by 3.3-8.6 %. However, the trends in climate variables for 1981-2009 reduced maize yield by 15-30 % in the study area. Among the main climate variables, solar radiation had the largest effect on maize yield, followed by temperature and then precipitation. While a significant decline in solar radiation in 1981-2009 (maybe due to air pollution) reduced yield by 12-24 %, a significant increase in temperature reduced yield by 3-9 %. In contrast, a non-significant increase in precipitation during the maize growth period increased yield by 0.9-3 % at three of the four investigated stations. However, a decline in precipitation reduced yield by 3 % in the remaining station. The study revealed that although the shift from traditional to modern cultivars and agronomic management practices contributed most to the increase in maize yield, the negative impact of climate change was large enough to offset 46-67 % of the trend in the observed yields in the past three decades in NCP. The reduction in solar radiation, especially in the most critical period of maize growth, limited the process of photosynthesis and thereby further reduced maize yield.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Leng, Guoyong
The United States is responsible for 35% and 60% of global corn supply and exports. Enhanced supply stability through a reduction in the year-to-year variability of US corn yield would greatly benefit global food security. Important in this regard is to understand how corn yield variability has evolved geographically in the history and how it relates to climatic and non-climatic factors. Results showed that year-to-year variation of US corn yield has decreased significantly during 1980-2010, mainly in Midwest Corn Belt, Nebraska and western arid regions. Despite the country-scale decreasing variability, corn yield variability exhibited an increasing trend in South Dakota,more » Texas and Southeast growing regions, indicating the importance of considering spatial scales in estimating yield variability. The observed pattern is partly reproduced by process-based crop models, simulating larger areas experiencing increasing variability and underestimating the magnitude of decreasing variability. And 3 out of 11 models even produced a differing sign of change from observations. Hence, statistical model which produces closer agreement with observations is used to explore the contribution of climatic and non-climatic factors to the changes in yield variability. It is found that climate variability dominate the change trends of corn yield variability in the Midwest Corn Belt, while the ability of climate variability in controlling yield variability is low in southeastern and western arid regions. Irrigation has largely reduced the corn yield variability in regions (e.g. Nebraska) where separate estimates of irrigated and rain-fed corn yield exist, demonstrating the importance of non-climatic factors in governing the changes in corn yield variability. The results highlight the distinct spatial patterns of corn yield variability change as well as its influencing factors at the county scale. I also caution the use of process-based crop models, which have substantially underestimated the change trend of corn yield variability, in projecting its future changes.« less
NASA Astrophysics Data System (ADS)
Xiao, Dengpan; Tao, Fulu
2016-07-01
The impact of climate change on crop yield is compounded by cultivar shifts and agronomic management practices. To determine the relative contributions of climate change, cultivar shift, and management practice to changes in maize ( Zea mays L.) yield in the past three decades, detailed field data for 1981-2009 from four representative experimental stations in North China Plain (NCP) were analyzed via model simulation. The four representative experimental stations are geographically and climatologically different, represent the typical cropping system in the study area, and have more complete weather/crop records for the period of 1981-2009. The results showed that while the shift from traditional to modern cultivar increased yield by 23.9-40.3 %, new fertilizer management increased yield by 3.3-8.6 %. However, the trends in climate variables for 1981-2009 reduced maize yield by 15-30 % in the study area. Among the main climate variables, solar radiation had the largest effect on maize yield, followed by temperature and then precipitation. While a significant decline in solar radiation in 1981-2009 (maybe due to air pollution) reduced yield by 12-24 %, a significant increase in temperature reduced yield by 3-9 %. In contrast, a non-significant increase in precipitation during the maize growth period increased yield by 0.9-3 % at three of the four investigated stations. However, a decline in precipitation reduced yield by 3 % in the remaining station. The study revealed that although the shift from traditional to modern cultivars and agronomic management practices contributed most to the increase in maize yield, the negative impact of climate change was large enough to offset 46-67 % of the trend in the observed yields in the past three decades in NCP. The reduction in solar radiation, especially in the most critical period of maize growth, limited the process of photosynthesis and thereby further reduced maize yield.
Statistical emulators of maize, rice, soybean and wheat yields from global gridded crop models
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 ...
Impacts of Geoengineering and Nuclear War on Chinese Agriculture
NASA Astrophysics Data System (ADS)
Xia, L.; Robock, A.
2011-12-01
Climate is one of the most important factors determining crop yields and world food supplies. To be well prepared for possible futures, it is necessary to study yield changes of major crops under different climate scenarios. Here we consider two situations: stratospheric sulfate geoengineering and nuclear war. Although we certainly do not advocate either scenario, we cannot exclude the possibilities: if global warming is getting worse, we might have to deliberately manipulate global temperature; if nuclear weapons still exist, we might face a nuclear war catastrophe. Since in both scenarios there would be reductions of temperature, precipitation, and insolation, which are three controlling factors on crop growth, it is important to study food supply changes under the two cases. We conducted our simulations for China, because it has the highest population and crop production in the world and it is under the strong influence of the summer monsoon, which would be altered in geoengineering and nuclear war scenarios. To examine the effects of climate changes induced by geoengineering and nuclear war on Chinese agriculture, we use the DSSAT crop model. We first evaluate the model by forcing it with daily weather data and management practices for the period 1978-2008 for all the provinces in China, and compare the results to observations of the yields of major crops in China (middle season rice, winter wheat, and maize). Then we perturbed observed weather data using climate anomalies for geoengineering and nuclear war simulations using NASA GISS ModelE. For stratospheric geoengineering, we consider the injection of 5 Tg SO2 per year into the tropical lower stratosphere. For the nuclear war scenario, we consider the effects of 5 Tg of soot that could be injected into the upper troposphere by a war between India and Pakistan using only 100 Hiroshima-size atomic bombs dropped on cities. We perturbed each year of the 31-year climate record with anomalies from each year of geoengineering and nuclear war simulations for different regions in China. Without changes of agricultural technology, we found that in both climate scenarios, the national crop production decreases, but different regions responded differently, indicating that the climate under which agriculture is conducted is a key factor to determine the impacts of geoengineering and nuclear war on agriculture. In southern China, the cooling helps the rice and maize grow. In northern China, the cooling makes the temperatures so cold that it hurts crop productivity, and in western China, the reduction of precipitation causes failed crop growth. To adapt to geoengineering and nuclear war scenarios, we could substitute crops that would grow better in the perturbed climate, increase fertilizer usage, irrigate agricultural land, change planting date, or change to seeds which are tolerant of cooler and drier climates.
Bita, Craita E.; Gerats, Tom
2013-01-01
Global warming is predicted to have a general negative effect on plant growth due to the damaging effect of high temperatures on plant development. The increasing threat of climatological extremes including very high temperatures might lead to catastrophic loss of crop productivity and result in wide spread famine. In this review, we assess the impact of global climate change on the agricultural crop production. There is a differential effect of climate change both in terms of geographic location and the crops that will likely show the most extreme reductions in yield as a result of expected extreme fluctuations in temperature and global warming in general. High temperature stress has a wide range of effects on plants in terms of physiology, biochemistry and gene regulation pathways. However, strategies exist to crop improvement for heat stress tolerance. In this review, we present recent advances of research on all these levels of investigation and focus on potential leads that may help to understand more fully the mechanisms that make plants tolerant or susceptible to heat stress. Finally, we review possible procedures and methods which could lead to the generation of new varieties with sustainable yield production, in a world likely to be challenged both by increasing population, higher average temperatures and larger temperature fluctuations. PMID:23914193
Zhang, Dabin; Yao, Pengwei; Na, Zhao; Cao, Weidong; Zhang, Suiqi; Li, Yangyang; Gao, Yajun
2016-01-01
Winter wheat (Triticum aestivum L.) monoculture is conventionally cultivated followed by two to three months of summer fallow in the Loess Plateau. To develop a sustainable cropping system, we conducted a six-year field experiment to investigate the effect of leguminous green manure (LGM) instead of bare fallow on the yield and water use efficiency (WUE) of winter wheat and the soil water balance (SWB) in different precipitation years in a semi-arid region of northwest China. Results confirmed that planting LGM crop consumes soil water in the fallow season can bring varied effects to the subsequent wheat. The effect is positive or neutral when the annual precipitation is adequate, so that there is no significant reduction in the soil water supplied to wheat. If this is not the case, the effect is negative. On average, the LGM crop increased wheat yield and WUE by 13% and 28%, respectively, and had considerable potential for maintaining the SWB (0–200 cm) compared with fallow management. In conclusion, cultivation of the LGM crop is a better option than fallow to improve the productivity and WUE of the next crop and maintain the soil water balance in the normal and wet years in the Loess Plateau. PMID:27225842
Bita, Craita E; Gerats, Tom
2013-01-01
Global warming is predicted to have a general negative effect on plant growth due to the damaging effect of high temperatures on plant development. The increasing threat of climatological extremes including very high temperatures might lead to catastrophic loss of crop productivity and result in wide spread famine. In this review, we assess the impact of global climate change on the agricultural crop production. There is a differential effect of climate change both in terms of geographic location and the crops that will likely show the most extreme reductions in yield as a result of expected extreme fluctuations in temperature and global warming in general. High temperature stress has a wide range of effects on plants in terms of physiology, biochemistry and gene regulation pathways. However, strategies exist to crop improvement for heat stress tolerance. In this review, we present recent advances of research on all these levels of investigation and focus on potential leads that may help to understand more fully the mechanisms that make plants tolerant or susceptible to heat stress. Finally, we review possible procedures and methods which could lead to the generation of new varieties with sustainable yield production, in a world likely to be challenged both by increasing population, higher average temperatures and larger temperature fluctuations.
Analysis of climate signals in the crop yield record of sub-Saharan Africa.
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
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) ...
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.
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.
First report of mango malformation disease caused by Fusarium pseudocircinatum in Mexico
USDA-ARS?s Scientific Manuscript database
Mango (Mangifera indica L.) malformation disease (MMD) is one of the most important diseases affecting this crop worldwide, causing severe economic loss due to reduction of yield. Subsequent to the first report in India in 1891 (3), MMD has spread worldwide to most mango-growing regions. Several spe...
Isolation of nematode DNA from 100 grams of soil using Fe3O4 super paramagnetic nanoparticles
USDA-ARS?s Scientific Manuscript database
Soilborne plant-parasitic nematodes cause losses through yield reductions and damage to a broad range of crops worldwide. Control of plant-parasitic nematodes often relies on application of fumigants or non-fumigant nematicides without knowledge of the presence of the nematodes or population densiti...
USDA-ARS?s Scientific Manuscript database
Fusarium Head Blight (FHB) is a destructive disease of small grain cereals and a major food safety concern. Epidemics result in substantial yield losses, reduction in crop quality, and contamination of grains with trichothecenes and other mycotoxins. A number of different fusaria can cause FHB, and ...
Liu, Zhijuan; Yang, Xiaoguang; Lin, Xiaomao; Hubbard, Kenneth G; Lv, Shuo; Wang, Jing
2016-01-15
Closing the gap between current and potential yields is one means of increasing agricultural production to feed the globally increasing population. Therefore, investigation of the geographic patterns, trends and causes of crop yield gaps is essential to identifying where yields might be increased and quantifying the contributions of yield-limiting factors that may provide us potentials to enhance crop productivity. In this study, the changes in potential yields, attainable yields, potential farmers' yields, and actual farmers' yields during the past five decades in Northeast China (NEC) were investigated. Additionally the yield gaps caused by non-controllable, agronomic, and socioeconomic factors were determined. Over the period 1961 to 2010 the estimated regional area-weighted mean maize potential yield, attainable yield, and potential farmers' yield were approximately 12.3 t ha(-1), 11.5 t ha(-1), and 6.4 t ha(-1) which showed a decreasing tendency. The actual farmers' yield over NEC was 4.5 t ha(-1), and showed a tendency to increase (p<0.01) by 1.27 t ha(-1) per decade. The regional mean total yield gap (YGt), weighted by the area in each county dedicated to maize crop, was 64% of potential yield. Moreover, 8, 40, and 16% reductions in potential yields were due to non-controllable factors (YGI), agronomic factors (YGII), and socioeconomic factors (YGIII), respectively. Therefore, the exploitable yield gap, considered here as the difference between the potential yield and what one can expect considering non-controllable factors (i.e. YGt-YGI), of maize in NEC was about 56%. The regional area-weighted averages of YGt, and YGIII were found to have significant decreases of 11.0, and 10.7% per decade. At the time horizon 2010, the exploitable yield gaps were estimated to equal 36% of potential yield. This led to the conclusion that the yield gap could be deeply reduced by improving local agronomic management and controlling socioeconomic factors. Copyright © 2015 Elsevier B.V. All rights reserved.
Meeting the challenge of food and energy security.
Karp, Angela; Richter, Goetz M
2011-06-01
Growing crops for bioenergy or biofuels is increasingly viewed as conflicting with food production. However, energy use continues to rise and food production requires fuel inputs, which have increased with intensification. Focussing on the question of food or fuel is thus not helpful. The bigger, more pertinent, challenge is how the increasing demands for food and energy can be met in the future, particularly when water and land availability will be limited. Energy crop production systems differ greatly in environmental impact. The use of high-input food crops for liquid transport fuels (first-generation biofuels) needs to be phased out and replaced by the use of crop residues and low-input perennial crops (second/advanced-generation biofuels) with multiple environmental benefits. More research effort is needed to improve yields of biomass crops grown on lower grade land, and maximum value should be extracted through the exploitation of co-products and integrated biorefinery systems. Policy must continually emphasize the changes needed and tie incentives to improved greenhous gas reduction and environmental performance of biofuels.
Assessment of climate change impact on yield of major crops in the Banas River Basin, India.
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.
NASA Astrophysics Data System (ADS)
Kothari, K.; Ale, S.; Bordovsky, J.; Hoogenboom, G.; Munster, C. L.
2017-12-01
The semi-arid Texas High Plains (THP) is one of the most productive agricultural regions in the United States. However, agriculture in the THP is faced with the challenges of rapid groundwater depletion in the underlying Ogallala Aquifer, restrictions on pumping groundwater, recurring droughts, and projected warmer and drier future climatic conditions. Therefore, it is imperative to adopt strategies that enhance climate change resilience of THP agriculture to maintain a sustainable agricultural economy in this region. The overall goal of this study is to assess the impacts of climate change and potential reduction in groundwater availability on production of two major crops in the region, cotton and grain sorghum, and suggest adaptation strategies using the Decision Support System for Agrotechnology Transfer (DSSAT) Cropping System Model. The DSSAT model was calibrated and evaluated using data from the long-term cotton-sorghum rotation experiments conducted at Helms Farm near Halfway in the THP. After achieving a satisfactory calibration for crop yield (RMSE < 1.0 T ha-1 or 14%) and dates of onset of various growth stages, the model was used to simulate historic (1980-2010) and future (2040-2070) cotton and sorghum yields and water use. The Multivariate Adaptive Constructed Analogs (MACA) projected future climate datasets from nine CMIP5 global climate models (GCMs) and two representative concentration pathways (RCP 4.5 and 8.5) were used in this study. Preliminary results indicated a reduction in irrigated grain sorghum yield per hectare by 6% and 8%, and a reduction in dryland sorghum yield per hectare by 9% and 17% under RCP 4.5 and RCP 8.5 scenarios, respectively. Grain sorghum future water use declined by about 2% and 5% under RCP 4.5 and RCP 8.5, respectively. Climate change impacts on cotton production and evaluation of several adaptation strategies such as incorporating heat and drought tolerances in cultivars, early planting, shifting to short season varieties, and deficit irrigation are currently being studied.
E-precision agriculture for small scale cash crops in Tobasa regency
NASA Astrophysics Data System (ADS)
Putra Simanjuntak, Panca; Tiurniari Napitupulu, Pangeran; Pratama Silalahi, Soni; Kisno; Pasaribu, Norlina; Valešová, Libuše
2017-09-01
Cash crop is a promising sector in Tobasa regency; however, the trend showed a negative change of the cash crop production in. This research aims to develop an application which is based on Arduino for watering and fertilizing corn land. The result of using e-precision agriculture based on embedded system is 100% higher than the conventional one and the risk of harvesting failure using the embedded system decreased to 50%. Embedded system in this study acquired critical environment measurements which at last affected the yield raising and risk reduction. As the result, the use of e-precision agriculture provided a framework to be used by different stakeholders to implement e-agriculture platform that supports marketing of agricultural production since the system is proven to save the material and time which finally reduces the risk of harvesting failure and increases the yield. In other words, the system is able to economize the use of water and fertilizer on a small corn land. The system will be developed for more efficiency in material loss and the mobile-based application development to reach sustainable rural development particularly for cash-crop farmers.
Use of treated wastewater in agriculture: effects on soil environment
NASA Astrophysics Data System (ADS)
Levy, Guy J.; Lado, Marcos
2014-05-01
Disposal of treated sewage, both from industrial and domestic origin (herein referred to as treated wastewater [TWW]), is often considered as an environmental hazard. However, in areas afflicted by water scarcity, especially in semi-arid and arid regions, where the future of irrigated agriculture (which produces approximately one third of crop yield and half the return from global crop production) is threatened by existing or expected shortage of fresh water, the use of TWW offers a highly effective and sustainable strategy to exploit a water resource. However, application of TWW to the soil is not free of risks both to organisms (e.g., crops, microbiota) and to the soil. Potential risks may include reduction in biological activity (including crop yield) due to elevated salinity and specific ion toxicity, migration of pollutants towards surface- and ground-water, and deterioration of soil structure. In recent years, new evidence about the possible negative impact of long-term irrigation with TWW on soil structure and physical and chemo-physical properties has emerged, thus putting the sustainability of irrigation with TWW in question. In this presentation, some aspects of the effects of long-term irrigation with TWW on soil properties are shown.
Estimating climate change, CO2 and technology development effects on wheat yield in northeast Iran
NASA Astrophysics Data System (ADS)
Bannayan, M.; Mansoori, H.; Rezaei, E. Eyshi
2014-04-01
Wheat is the main food for the majority of Iran's population. Precise estimation of wheat yield change in future is essential for any possible revision of management strategies. The main objective of this study was to evaluate the effects of climate change, CO2 concentration, technology development and their integrated effects on wheat production under future climate change. This study was performed under two scenarios of the IPCC Special Report on Emission Scenarios (SRES): regional economic (A2) and global environmental (B1). Crop production was projected for three future time periods (2020, 2050 and 2080) in comparison with a baseline year (2005) for Khorasan province located in the northeast of Iran. Four study locations in the study area included Mashhad, Birjand, Bojnourd and Sabzevar. The effect of technology development was calculated by fitting a regression equation between the observed wheat yields against historical years considering yield potential increase and yield gap reduction as technology development. Yield relative increase per unit change of CO2 concentration (1 ppm-1) was considered 0.05 % and was used to implement the effect of elevated CO2. The HadCM3 general circulation model along with the CSM-CERES-Wheat crop model were used to project climate change effects on wheat crop yield. Our results illustrate that, among all the factors considered, technology development provided the highest impact on wheat yield change. Highest wheat yield increase across all locations and time periods was obtained under the A2 scenario. Among study locations, Mashhad showed the highest change in wheat yield. Yield change compared to baseline ranged from -28 % to 56 % when the integration of all factors was considered across all locations. It seems that achieving higher yield of wheat in future may be expected in northeast Iran assuming stable improvements in production technology.
Estimating climate change, CO2 and technology development effects on wheat yield in northeast Iran.
Bannayan, M; Mansoori, H; Rezaei, E Eyshi
2014-04-01
Wheat is the main food for the majority of Iran's population. Precise estimation of wheat yield change in future is essential for any possible revision of management strategies. The main objective of this study was to evaluate the effects of climate change, CO2 concentration, technology development and their integrated effects on wheat production under future climate change. This study was performed under two scenarios of the IPCC Special Report on Emission Scenarios (SRES): regional economic (A2) and global environmental (B1). Crop production was projected for three future time periods (2020, 2050 and 2080) in comparison with a baseline year (2005) for Khorasan province located in the northeast of Iran. Four study locations in the study area included Mashhad, Birjand, Bojnourd and Sabzevar. The effect of technology development was calculated by fitting a regression equation between the observed wheat yields against historical years considering yield potential increase and yield gap reduction as technology development. Yield relative increase per unit change of CO2 concentration (1 ppm(-1)) was considered 0.05 % and was used to implement the effect of elevated CO2. The HadCM3 general circulation model along with the CSM-CERES-Wheat crop model were used to project climate change effects on wheat crop yield. Our results illustrate that, among all the factors considered, technology development provided the highest impact on wheat yield change. Highest wheat yield increase across all locations and time periods was obtained under the A2 scenario. Among study locations, Mashhad showed the highest change in wheat yield. Yield change compared to baseline ranged from -28 % to 56 % when the integration of all factors was considered across all locations. It seems that achieving higher yield of wheat in future may be expected in northeast Iran assuming stable improvements in production technology.
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.
Fertilizing Nature: A Tragedy of Excess in the Commons
Good, Allen G.; Beatty, Perrin H.
2011-01-01
Globally, we are applying excessive nitrogen (N) fertilizers to our agricultural crops, which ultimately causes nitrogen pollution to our ecosphere. The atmosphere is polluted by N2O and NOx gases that directly and indirectly increase atmospheric warming and climate change. Nitrogen is also leached from agricultural lands as the water-soluble form NO3 −, which increases nutrient overload in rivers, lakes, and oceans, causing “dead zones”, reducing property values and the diversity of aquatic life, and damaging our drinking water and aquatic-associated industries such as fishing and tourism. Why do some countries show reductions in fertilizer use while others show increasing use? What N fertilizer application reductions could occur, without compromising crop yields? And what are the economic and environmental benefits of using directed nutrient management strategies? PMID:21857803
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.
Maize ARGOS1 (ZAR1) transgenic alleles increase hybrid maize yield
Guo, Mei
2014-01-01
Crop improvement for yield and drought tolerance is challenging due to the complex genetic nature of these traits and environmental dependencies. This study reports that transgenic over-expression of Zea mays ARGOS1 (ZAR1) enhanced maize organ growth, grain yield, and drought-stress tolerance. The ZAR1 transgene exhibited environmental interactions, with yield increase under Temperate Dry and yield reduction under Temperate Humid or High Latitude environments. Native ZAR1 allele variation associated with drought-stress tolerance. Two founder alleles identified in the mid-maturity germplasm of North America now predominate in Pioneer’s modern breeding programme, and have distinct proteins, promoters and expression patterns. These two major alleles show heterotic group partitioning, with one predominant in Pioneer’s female and the other in the male heterotic groups, respectively. These two alleles also associate with favourable crop performance when heterozygous. Allele-specific transgene testing showed that, of the two alleles discussed here, each allele differed in their impact on yield and environmental interactions. Moreover, when transgenically stacked together the allelic pair showed yield and environmental performance advantages over either single allele, resembling heterosis effects. This work demonstrates differences in transgenic efficacy of native alleles and the differences reflect their association with hybrid breeding performance. PMID:24218327
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...
Abid, Muhammad; Tian, Zhongwei; Ata-Ul-Karim, Syed Tahir; Liu, Yang; Cui, Yakun; Zahoor, Rizwan; Jiang, Dong; Dai, Tingbo
2016-09-01
Wheat crop endures a considerable penalty of yield reduction to escape the drought events during post-anthesis period. Drought priming under a pre-drought stress can enhance the crop potential to tolerate the subsequent drought stress by triggering a faster and stronger defense mechanism. Towards these understandings, a set of controlled moderate drought stress at 55-60% field capacity (FC) was developed to prime the plants of two wheat cultivars namely Luhan-7 (drought tolerant) and Yangmai-16 (drought sensitive) during tillering (Feekes 2 stage) and jointing (Feekes 6 stage), respectively. The comparative response of primed and non-primed plants, cultivars and priming stages was evaluated by applying a subsequent severe drought stress at 7 days after anthesis. The results showed that primed plants of both cultivars showed higher potential to tolerate the post-anthesis drought stress through improved leaf water potential, more chlorophyll, and ribulose-1, 5-bisphosphate carboxylase/oxygenase contents, enhanced photosynthesis, better photoprotection and efficient enzymatic antioxidant system leading to less yield reductions. The primed plants of Luhan-7 showed higher capability to adapt the drought stress events than Yangmai-16. The positive effects of drought priming to sustain higher grain yield were pronounced in plants primed at tillering than those primed at jointing. In consequence, upregulated functioning of photosynthetic apparatus and efficient enzymatic antioxidant activities in primed plants indicated their superior potential to alleviate a subsequently occurring drought stress, which contributed to lower yield reductions than non-primed plants. However, genotypic and priming stages differences in response to drought stress also contributed to affect the capability of primed plants to tolerate the post-anthesis drought stress conditions in wheat. Copyright © 2016. Published by Elsevier Masson SAS.
Cover crops impact on excess rainfall and soil erosion rates in orchards and potato fields, Israel
NASA Astrophysics Data System (ADS)
Egozi, Roey; Gil, Eshel
2015-04-01
Bare soil and high drainage densities are common characteristics of intensive agriculture land. The couplings of these characteristics lead to high runoff and eroded soil volumes leaving the field or the orchard via the local drainage system into the fluvial system. This process increase flood risk due to massive deposition of the coarse fraction of the eroded soil and therefore reduces channel capacity to discharge the increase volumes of concentrated runoff. As a result drainage basin authorities are forced to invest large amount of money in maintaining and enlarging the drainage network. However this approach is un-sustainable. On the other hand, implementing cover crops (CC) and modification to current agricultural practices over the contributing area of the watershed seems to have more benefits and provide sustainable solution. A multi-disciplinary approach applied in commercial potatoes fields and orchards that utilize the benefit of CC shows great success as means of soil and water conservation and weed disinfestation without reduction in the yield, its quality or its profitability. The results indicate that it is possible to grow potatoes and citrus trees under CC with no reduction in yield or nutrient uptake, with more than 95% reduction in soil loss and more than 60% in runoff volumes and peak discharges.
Agriculture Impacts of Regional Nuclear Conflict
NASA Astrophysics Data System (ADS)
Xia, Lili; Robock, Alan; Mills, Michael; Toon, Owen Brian
2013-04-01
One of the major consequences of nuclear war would be climate change due to massive smoke injection into the atmosphere. Smoke from burning cities can be lofted into the stratosphere where it will have an e-folding lifetime more than 5 years. The climate changes include significant cooling, reduction of solar radiation, and reduction of precipitation. Each of these changes can affect agricultural productivity. To investigate the response from a regional nuclear war between India and Pakistan, we used the Decision Support System for Agrotechnology Transfer agricultural simulation model. We first evaluated the model by forcing it with daily weather data and management practices in China and the USA for rice, maize, wheat, and soybeans. Then we perturbed observed weather data using monthly climate anomalies for a 10-year period due to a simulated 5 Tg soot injection that could result from a regional nuclear war between India and Pakistan, using a total of 100 15 kt atomic bombs, much less than 1% of the current global nuclear arsenal. We computed anomalies using the NASA Goddard Institute for Space Studies ModelE and NCAR's Whole Atmosphere Community Climate Model (WACCM). We perturbed each year of the observations with anomalies from each year of the 10-year nuclear war simulations. We found that different regions respond differently to a regional nuclear war; southern regions show slight increases of crop yields while in northern regions crop yields drop significantly. Sensitivity tests show that temperature changes due to nuclear war are more important than precipitation and solar radiation changes in affecting crop yields in the regions we studied. In total, crop production in China and the USA would decrease 15-50% averaged over the 10 years using both models' output. Simulations forced by ModelE output show smaller impacts than simulations forced by WACCM output at the end of the 10 year period because of the different temperature responses in the two models.
US major crops’ uncertain climate change risks and greenhouse gas mitigation benefits
Wing, Ian Sue; Monier, Erwan; Stern, Ari; ...
2015-10-28
In this study, we estimate the costs of climate change to US agriculture, and associated potential benefits of abating greenhouse gas emissions. Five major crops' yield responses to climatic variation are modeled empirically, and the results combined with climate projections for a no-policy, high-warming future, as well as moderate and stringent mitigation scenarios. Unabated warming reduces yields of wheat and soybeans by 2050, and cotton by 2100, but moderate warming increases yields of all crops except wheat. Yield changes are monetized using the results of economic simulations within an integrated climate-economy modeling framework. Uncontrolled warming's economic effects on major cropsmore » are slightly positive—annual benefits <$4 B. These are amplified by emission reductions, but subject to diminishing returns—by 2100 reaching $17 B under moderate mitigation, but only $7 B with stringent mitigation. Costs and benefits are sensitive to irreducible uncertainty about the fertilization effects of elevated atmospheric carbon dioxide, without which unabated warming incurs net costs of up to $18 B, generating benefits to moderate (stringent) mitigation as large as $26 B ($20 B).« less
US major crops’ uncertain climate change risks and greenhouse gas mitigation benefits
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wing, Ian Sue; Monier, Erwan; Stern, Ari
In this study, we estimate the costs of climate change to US agriculture, and associated potential benefits of abating greenhouse gas emissions. Five major crops' yield responses to climatic variation are modeled empirically, and the results combined with climate projections for a no-policy, high-warming future, as well as moderate and stringent mitigation scenarios. Unabated warming reduces yields of wheat and soybeans by 2050, and cotton by 2100, but moderate warming increases yields of all crops except wheat. Yield changes are monetized using the results of economic simulations within an integrated climate-economy modeling framework. Uncontrolled warming's economic effects on major cropsmore » are slightly positive—annual benefits <$4 B. These are amplified by emission reductions, but subject to diminishing returns—by 2100 reaching $17 B under moderate mitigation, but only $7 B with stringent mitigation. Costs and benefits are sensitive to irreducible uncertainty about the fertilization effects of elevated atmospheric carbon dioxide, without which unabated warming incurs net costs of up to $18 B, generating benefits to moderate (stringent) mitigation as large as $26 B ($20 B).« less
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.
Irrigation Trials for ET Estimation and Water Management in California Specialty Crops
NASA Astrophysics Data System (ADS)
Johnson, L.; Cahn, M.; Martin, F.; Lund, C.; Melton, F. S.
2012-12-01
Accurate estimation of crop evapotranspiration (ETc) can support efficient irrigation water management, which in turn brings benefits including surface water conservation, mitigation of groundwater depletion/degradation, energy savings, and crop quality assurance. Past research in California has revealed strong relationships between canopy fractional cover (Fc) and ETc of certain specialty crops, while additional research has shown the potential of monitoring Fc by satellite remote sensing. California's Central Coast is the leading region of cool season vegetable production in the U.S. Monterey County alone produces more than 80,000 ha of lettuce and broccoli (about half of U.S. production), valued at $1.5 billion in 2009. Under this study, we are conducting ongoing irrigation trials on these crops at the USDA Agricultural Research Station (Salinas) to compare irrigation scheduling via plant-based ETc approaches, by way of Fc, with current industry standard-practice. The following two monitoring approaches are being evaluated - 1) a remote sensing model employed by NASA's prototype Satellite Irrigation Management System, and 2) an online irrigation scheduling tool, CropManage, recently developed by U.C. Cooperative Extension. Both approaches utilize daily grass-reference ETo data as provided by the California Irrigation Management Irrigation System (CIMIS). A sensor network is deployed to monitor applied irrigation, volumetric soil water content, soil water potential, deep drainage, and standard meteorologic variables in order to derive ETc by a water balance approach. Evaluations of crop yield and crop quality are performed by the research team and by commercial growers. Initial results to-date indicate that applied water reductions based on Fc measurements are possible with little-to-no impact on yield of crisphead lettuce (Lactuca sativa). Additional results for both lettuce and broccoli trials, conducted during summer-fall 2012, are presented with respect to nutrient management and crop viability.
Global growth and stability of agricultural yield decrease with pollinator dependence
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
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.
[Predicting the impact of climate change in the next 40 years on the yield of maize in China].
Ma, Yu-ping; Sun, Lin-li; E, You-hao; Wu, Wei
2015-01-01
Climate change will significantly affect agricultural production in China. The combination of the integral regression model and the latest climate projection may well assess the impact of future climate change on crop yield. In this paper, the correlation model of maize yield and meteorological factors was firstly established for different provinces in China by using the integral regression method, then the impact of climate change in the next 40 years on China's maize production was evaluated combined the latest climate prediction with the reason be ing analyzed. The results showed that if the current speeds of maize variety improvement and science and technology development were constant, maize yield in China would be mainly in an increasing trend of reduction with time in the next 40 years in a range generally within 5%. Under A2 climate change scenario, the region with the most reduction of maize yield would be the Northeast except during 2021-2030, and the reduction would be generally in the range of 2.3%-4.2%. Maize yield reduction would be also high in the Northwest, Southwest and middle and lower reaches of Yangtze River after 2031. Under B2 scenario, the reduction of 5.3% in the Northeast in 2031-2040 would be the greatest across all regions. Other regions with considerable maize yield reduction would be mainly in the Northwest and the Southwest. Reduction in maize yield in North China would be small, generally within 2%, under any scenarios, and that in South China would be almost unchanged. The reduction of maize yield in most regions would be greater under A2 scenario than under B2 scenario except for the period of 2021-2030. The effect of the ten day precipitation on maize yield in northern China would be almost positive. However, the effect of ten day average temperature on yield of maize in all regions would be generally negative. The main reason of maize yield reduction was temperature increase in most provinces but precipitation decrease in a few provinces. Assessments of the future change of maize yield in China based on the different methods were not consistent. Further evaluation needs to consider the change of maize variety and scientific and technological progress, and to enhance the reliability of evaluation models.
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.
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.
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
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
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
NASA Astrophysics Data System (ADS)
Wang, Xiaoping; Mauzerall, Denise L.
Using an integrated assessment approach, we evaluate the impact that surface O 3 in East Asia had on agricultural production in 1990 and is projected to have in 2020. We also examine the effect that emission controls and the enforcement of environmental standards could have in increasing grain production in China. We find that given projected increases in O 3 concentrations in the region, East Asian countries are presently on the cusp of substantial reductions in grain production. Our conservative estimates, based on 7- and 12-h mean (M7 or M12) exposure indices, show that due to O 3 concentrations in 1990 China, Japan and South Korea lost 1-9% of their yield of wheat, rice and corn and 23-27% of their yield of soybeans, with an associated value of 1990US 3.5, 1.2 and 0.24 billion, respectively. In 2020, assuming no change in agricultural production practices and again using M7 and M12 exposure indices, grain loss due to increased levels of O 3 pollution is projected to increase to 2-16% for wheat, rice and corn and 28-35% for soybeans; the associated economic costs are expected to increase by 82%, 33%, and 67% in 2020 over 1990 for China, Japan and South Korea, respectively. For most crops, the yield losses in 1990 based on SUM06 or W126 exposure indices are lower than yield losses estimated using M7 or M12 exposure indices in China and Japan but higher in South Korea; in 2020, the yield losses based on SUM06 or W126 exposure indices are substantially higher for all crops in all three countries. This is primarily due to the nature of the cumulative indices which weight elevated values of O 3 more heavily than lower values. Chinese compliance with its ambient O 3 standard in 1990 would have had a limited effect in reducing the grain yield loss caused by O 3 exposure, resulting in only US 0.2 billion of additional grain revenues, but in 2020 compliance could reduce the yield loss by one third and lead to an increase of US$ 2.6 (M7 or M12) -27 (SUM06) billion in grain revenues. We conclude that East Asian countries may have tremendous losses of crop yields in the near future due to projected increases in O 3 concentrations. They likely could achieve substantial increases in future agricultural production through reduction of surface O 3 concentrations and/or use of O 3 resistant crop cultivars.
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.
Cauliflower is a new host of a subgroup 16SrVII-B phytoplasma associated with stunting disease
USDA-ARS?s Scientific Manuscript database
Cauliflower stunt has occurred with high levels of incidence and provoked significant yield reduction in Brazilian crops. Phytoplasmas belonging to the subgroups 16SrIII-J and 16SrXV-A were previously reported in association with the disease. In 2014, plants with typical symptoms of the disease were...
Liu, Wenfeng; Yang, Hong; Liu, Yu; Kummu, Matti; Hoekstra, Arjen Y; Liu, Junguo; Schulin, Rainer
2018-08-15
Global food trade entails virtual flows of agricultural resources and pollution across countries. Here we performed a global-scale assessment of impacts of international food trade on blue water use, total water use, and nitrogen (N) inputs and on N losses in maize, rice, and wheat production. We simulated baseline conditions for the year 2000 and explored the impacts of an agricultural intensification scenario, in which low-input countries increase N and irrigation inputs to a greater extent than high-input countries. We combined a crop model with the Global Trade Analysis Project model. Results show that food exports generally occurred from regions with lower water and N use intensities, defined here as water and N uses in relation to crop yields, to regions with higher resources use intensities. Globally, food trade thus conserved a large amount of water resources and N applications, and also substantially reduced N losses. The trade-related conservation in blue water use reached 85km 3 y -1 , accounting for more than half of total blue water use for producing the three crops. Food exported from the USA contributed the largest proportion of global water and N conservation as well as N loss reduction, but also led to substantial export-associated N losses in the country itself. Under the intensification scenario, the converging water and N use intensities across countries result in a more balanced world; crop trade will generally decrease, and global water resources conservation and N pollution reduction associated with the trade will reduce accordingly. The study provides useful information to understand the implications of agricultural intensification for international crop trade, crop water use and N pollution patterns in the world. Copyright © 2018 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Sahajpal, R.; Hurtt, G. C.; Fisk, J. P.; Izaurralde, R. C.; Zhang, X.
2012-12-01
While cellulosic biofuels are widely considered to be a low carbon energy source for the future, a comprehensive assessment of the environmental sustainability of existing and future biofuel systems is needed to assess their utility in meeting US energy and food needs without exacerbating environmental harm. To assess the carbon emission reduction potential of cellulosic biofuels, we need to identify lands that are initially not storing large quantities of carbon in soil and vegetation but are capable of producing abundant biomass with limited management inputs, and accurately model forest production rates and associated input requirements. Here we present modeled results for carbon emission reduction potential and cellulosic ethanol production of woody bioenergy crops replacing existing native prairie vegetation grown on marginal lands in the US Midwest. Marginal lands are selected based on soil properties describing use limitation, and are extracted from the SSURGO (Soil Survey Geographic) database. Yield estimates for existing native prairie vegetation on marginal lands modeled using the process-based field-scale model EPIC (Environmental Policy Integrated Climate) amount to ~ 6.7±2.0 Mg ha-1. To model woody bioenergy crops, the individual-based terrestrial ecosystem model ED (Ecosystem Demography) is initialized with the soil organic carbon stocks estimated at the end of the EPIC simulation. Four woody bioenergy crops: willow, southern pine, eucalyptus and poplar are parameterized in ED. Sensitivity analysis of model parameters and drivers is conducted to explore the range of carbon emission reduction possible with variation in woody bioenergy crop types, spatial and temporal resolution. We hypothesize that growing cellulosic crops on these marginal lands can provide significant water quality, biodiversity and GHG emissions mitigation benefits, without accruing additional carbon costs from the displacement of food and feed production.
NASA Astrophysics Data System (ADS)
Hack-ten Broeke, Mirjam J. D.; Kroes, Joop G.; Bartholomeus, Ruud P.; van Dam, Jos C.; de Wit, Allard J. W.; Supit, Iwan; Walvoort, Dennis J. J.; van Bakel, P. Jan T.; Ruijtenberg, Rob
2016-08-01
For calculating the effects of hydrological measures on agricultural production in the Netherlands a new comprehensive and climate proof method is being developed: WaterVision Agriculture (in Dutch: Waterwijzer Landbouw). End users have asked for a method that considers current and future climate, that can quantify the differences between years and also the effects of extreme weather events. Furthermore they would like a method that considers current farm management and that can distinguish three different causes of crop yield reduction: drought, saline conditions or too wet conditions causing oxygen shortage in the root zone. WaterVision Agriculture is based on the hydrological simulation model SWAP and the crop growth model WOFOST. SWAP simulates water transport in the unsaturated zone using meteorological data, boundary conditions (like groundwater level or drainage) and soil parameters. WOFOST simulates crop growth as a function of meteorological conditions and crop parameters. Using the combination of these process-based models we have derived a meta-model, i.e. a set of easily applicable simplified relations for assessing crop growth as a function of soil type and groundwater level. These relations are based on multiple model runs for at least 72 soil units and the possible groundwater regimes in the Netherlands. So far, we parameterized the model for the crops silage maize and grassland. For the assessment, the soil characteristics (soil water retention and hydraulic conductivity) are very important input parameters for all soil layers of these 72 soil units. These 72 soil units cover all soils in the Netherlands. This paper describes (i) the setup and examples of application of the process-based model SWAP-WOFOST, (ii) the development of the simplified relations based on this model and (iii) how WaterVision Agriculture can be used by farmers, regional government, water boards and others to assess crop yield reduction as a function of groundwater characteristics or as a function of the salt concentration in the root zone for the various soil types.
Climate Change and Projected Impacts in Agriculture: an Example on Mediterranean Crops
NASA Astrophysics Data System (ADS)
Ferrise, R.; Moriondo, M.; Bindi, M.
2009-04-01
Recently, the availability of multi-model ensemble prediction methods has permitted the assignment of likelihoods to future climate projections. This allowed moving from the scenario-based approach to the risk-based approach in assessing the effects of climate change, thus providing more useful information for decision-makers that, as reported by Schneider (2001), need probability estimates to assess the seriousness of the projected impacts. The probabilistic approach to evaluate crop response to climate change mainly consists in applying an impact model (such as crop growth model) to a very large number of climate projections so to provide a probabilistic distribution of the variable selected to evaluate the impact. By comparing the outputs of the multi-simulation with a critical threshold (such as minimum yield below which it is not admissible to fall), it is possible to evaluate the risk related to future climate conditions. Unfortunately, such an approach is a time-consuming process due to the large number of model runs needed for such a procedure. An alternative method relies on the set up of impact response surfaces (RS) with respect to key climatic variables on which a probabilistic representation of projected changes in the same climatic variables may be overlaid (Fronzek et al. 2008). This approach was exploited within the ENSEMBLES EU Project aiming at assessing climate change impact on typical Mediterranean crops. This work presents the results of the project with a particular concerning about the assessment of risk, of durum wheat (T. turgidum L. subsp. durum (Desf.) Husn) and grapevine (Vitis vinifera L.) yield falling below fixed thresholds, using probabilistic information about future climate. Methodology The simple mechanistic crop growth models, SIRIUS Quality (Jamieson et al., 1998) and VITE-model (Bindi et al., 1997a,b), were selected to respectively simulate durum wheat and grapevine yields in present and future scenarios. SIRIUS Quality is a wheat simulation model that calculates biomass production from photosynthetically active radiation and grain growth from simple partition rules. VITE-model is a model that uses a simplified mechanistic approach based on the accumulated degree days, the radiation use efficiency and the fruit biomass index to simulate the main processes regulating grapevine development, growth and yield. The selected crop growth models were adopted to create yield RSs of both crops over the suitable cultivated area in the Mediterranean Basin. Yield RSs were calculated performing a scenario sensitivity analysis by altering the baseline climate with respect to temperature and precipitation changes. The baseline climate consisted of 30 years (1975-2005) of daily minimum and maximum temperatures, rainfall and global radiation. Meteorological data were extracted from the MARS JRC Archive and are referred to a grid with a spatial resolution of 50 Km x 50 Km covering the whole European area. The sensitivity analysis was performed for precipitation changes (from -40% to 20%) and temperature changes (from 0°C to +8°C), uniformly applied across all the year. To take in account for the effect of rising CO2, the yield RSs for future periods, were produced considering CO2 air concentration level according to the A1B SRES emission scenario. For each rainfall and temperature combination the average yield over the 30-years period was calculated. The probabilistic distribution of future yields was estimated by applying a bilinear interpolative method to overlap, onto the RSs, the data from perturbed physics experiment of Hadley Centre for future scenarios (joint distribution of annual temperature and rainfall changes). Critical thresholds of impact were determined by calculating, for each grid cell, the distribution of the 30-years average yield according to the joint distribution data for present period (1990-2010) and selecting the values that correspond to the 20th percentile of the cumulative distribution. Finally, future yields were compared with yield threshold to assess the risk of yield shortfall that, in each time period, was defined as the percentage of projected yields that not overcome the selected threshold. Results Maps of durum wheat and grapevine low productivity risk were generated for the next century over the Mediterranean Basin. For durum wheat, with the exception of Portugal and Southern Spain, in the next 30 years risk of low crop productivity shows an overall reduction, due to the fertilizing effect of CO2 increase that counterbalances for the negative impact of rising temperature and reducing rainfall. Thereafter, these latter negative effects become greater and the risk progressively increases starting from lower latitudes. Maximum risk was estimated in 2060 when strong reductions in yield were accounted all over the study area. The smaller reductions in risk, estimated for the end of the next century, may be explained by the greater uncertainty in climate projections. South Portugal, South Spain and Peloponnesus resulted the most vulnerable areas showing increase in risk probability up to 50%, while risk in Galicia, Slovenia, Croatia and central-southern France always resulted lower then present time. As regard grapevine, in the great part of the case study area, the yield seems to have beneficial effect from future climate change. In Central-Western Europe and at lower latitudes the projected yields never fall below the risk threshold, indicating a prevailing effect of CO2 fertilisation. By the other hand, Central-Northern Italy and North of Greece result the most vulnerable areas. In these regions the likelihood of reduced yields quickly rises and remains very high (>50%) until the end of the century, denoting a greater negative effect of temperature and rainfall. Conclusions From these results it may be argued that the impact of future climate change on crop yields is the resultant of the contrasting effects of changes in temperature and precipitation, CO2 increase and uncertainty in climate projections. The intensity of these effects is very site and crop dependent and may vary with time, differently affecting the assessment of risk. As a consequence, the patterns of risk of low crop productivity will change depending on which of these effects will prevail. References Bindi M. et al., 1997a "A simple model for simulation of growth and development in grapevine (Vitis vinifera L.). I. Model description". Vitis 36:67-71 Bindi M. et al., 1997b "A simple model for simulation of growth and development in grapevine (Vitis vinifera L.). II. Model validation". Vitis 36:73-76 Carter T. et al., 2006 "". Fronzek S. et al 2008 "Applying probabilistic projections of climate change with impact models: a case study for sub-arctic palsa mires in Fennoscandia". Climatic Change (submitted) Jamieson et al., 1998 "Sirius: a mechanistic model of wheat response to environmental variation". Eur. J. Agron. 8:161-179. Schneider S. 2001 "What is ‘dangerous' climate change?". Nature 411:17-19
Ozga, Jocelyn A; Kaur, Harleen; Savada, Raghavendra P; Reinecke, Dennis M
2017-04-01
Legume crops are grown throughout the world and provide an excellent food source of digestible protein and starch, as well as dietary fibre, vitamins, minerals, and flavonoids. Fruit and seeds from legumes are also an important source of vegetables for a well-balanced diet. A trend in elevated temperature as a result of climate change increases the risk of a heat stress-induced reduction in legume crop yield. High temperatures during the crop reproductive development phase are particularly detrimental to fruit/seed production because the growth and development of the reproductive tissues are sensitive to small changes in temperature. Hormones are signalling molecules that play important roles in a plant's ability to integrate different environmental inputs and modify their developmental processes to optimize growth, survival, and reproduction. This review focuses on the hormonal regulation of reproductive development and heat stress-induced alteration of this regulation during (i) pollination, (ii) early fruit set, and (iii) seed development that affects fruit/seed yield in legume and other model crops. Further understanding of hormone-regulated reproductive growth under non-stress and heat-stress conditions can aid in trait selection and the development of gene modification strategies and cultural practices to improve heat tolerance in legume crops contributing to improved food security. © 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.
Detecting crop yield reduction due to irrigation-induced soil salinization in South-West Russia
NASA Astrophysics Data System (ADS)
Argaman, E.; Beets, W.; Croes, J.; Keesstra, S.; Verzandvoort, S.; Zeiliguer, A.
2012-04-01
The South-European part of the Russian Federation has experienced serious land degradation in the form of soil salinization since the 1960s. This land degradation was caused by intensive, large-scale irrigation on reclaimed land in combination with the salt-rich nature of the substrate. Alkaline soil salinity is believed to be an important factor decreasing crop yield in this area. A large research effort has been directed to the effects of soil salinity on crops, there is a need for simple, easily determinable indicators of crop health and soil salinity in irrigated systems, that can help to detect crop water stress in an early stage. The objectives of this research were to study the effects of soil salinity and vegetation water stress on the performance of alfalfa crop yield and physiological crop properties, and to study the possibility to measure soil salinity and alkalinity and the crop water stress index at plot level using a thermal gun and a regular digital camera. The study area was located in Saratov District, in the South-West part of Russia. Variables on the surface energy balance, crop properties, soil properties and visible reflectance were measured on plots with alfalfa cultures in two fields with and without signs of alkaline soil salinity, and with and without irrigation in July 2009. The research showed no clear adverse effects of soil salinity and soil alkalinity on crop yield and physiological crop properties. Soil salinity, as reflected by the electric conductivity, positively affected the root biomass of alfalfa in the range of 0.15 to 1.52 dS/m . This was a result of EC levels being below the documented threshold to negatively affect Alfalfa, as would be the case in truly saline soils. The soil pH also showed a positive correlation with root biomass within the range of pH 6.2 and 8.5 . From the literature these pH values are generally believed to be too high to exhibit a positive relationship with root biomass. No relationship was found between EC and pH on the one hand , and soil moisture content on the other. However, soil moisture content in the topsoil appeared to have a major influence on the crop water stress index, which on its turn affected the leaf area index, the fresh biomass and the mean plant height. The crop leaf color as detected by a regular digital camera appeared to be correlated with pH and EC properties of the soil. The visible light band ratios red/green and blue/green correlated well with the crop water stress index. More research is necessary to prove if this relation is applicable in different environments, and for different crops. A confirmation of these findings would offer scope to increase the spatial support of this technique using satellite images.
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...
Hu, Shi; Mo, Xing-guo; Lin, Zhong-hui
2015-04-01
Based on the multi-model datasets of three representative concentration pathway (RCP) emission scenarios from IPCC5, the response of yield and accumulative evapotranspiration (ET) of winter wheat to climate change in the future were assessed by VIP model. The results showed that if effects of CO2 enrichment were excluded, temperature rise would lead to a reduction in the length of the growing period for wheat under the three climate change scenarios, and the wheat yield and ET presented a decrease tendency. The positive effect of atmospheric CO2 enrichment could offset most negative effect introduced by temperature rising, indicating that atmospheric CO2 enrichment would be the prime reason of the wheat yield rising in future. In 2050s, wheat yield would increase 14.8% (decrease 2.5% without CO2 fertilization) , and ET would decrease 2.1% under RCP4.5. By adoption of new crop variety with enhanced requirement on accumulative temperature, the wheat yield would increase more significantly with CO2 fertilization, but the water consumption would also increase. Therefore, cultivar breeding new irrigation techniques and agronomical management should be explored under the challenges of climate change in the future.
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.
Soil Physicochemical and Biological Properties of Paddy-Upland Rotation: A Review
Lv, Teng-Fei; Chen, Yong; Westby, Anthony P.; Ren, Wan-Jun
2014-01-01
Paddy-upland rotation is an unavoidable cropping system for Asia to meet the increasing demand for food. The reduction in grain yields has increased the research interest on the soil properties of rice-based cropping systems. Paddy-upland rotation fields are unique from other wetland or upland soils, because they are associated with frequent cycling between wetting and drying under anaerobic and aerobic conditions; such rotations affect the soil C and N cycles, make the chemical speciation and biological effectiveness of soil nutrient elements varied with seasons, increase the diversity of soil organisms, and make the soil physical properties more difficult to analyze. Consequently, maintaining or improving soil quality at a desirable level has become a complicated issue. Therefore, fully understanding the soil characteristics of paddy-upland rotation is necessary for the sustainable development of the system. In this paper, we offer helpful insight into the effect of rice-upland combinations on the soil chemical, physical, and biological properties, which could provide guidance for reasonable cultivation management measures and contribute to the improvement of soil quality and crop yield. PMID:24995366
Redefining agricultural yields: from tonnes to people nourished per hectare
NASA Astrophysics Data System (ADS)
Cassidy, Emily S.; West, Paul C.; Gerber, James S.; Foley, Jonathan A.
2013-09-01
Worldwide demand for crops is increasing rapidly due to global population growth, increased biofuel production, and changing dietary preferences. Meeting these growing demands will be a substantial challenge that will tax the capability of our food system and prompt calls to dramatically boost global crop production. However, to increase food availability, we may also consider how the world’s crops are allocated to different uses and whether it is possible to feed more people with current levels of crop production. Of particular interest are the uses of crops as animal feed and as biofuel feedstocks. Currently, 36% of the calories produced by the world’s crops are being used for animal feed, and only 12% of those feed calories ultimately contribute to the human diet (as meat and other animal products). Additionally, human-edible calories used for biofuel production increased fourfold between the years 2000 and 2010, from 1% to 4%, representing a net reduction of available food globally. In this study, we re-examine agricultural productivity, going from using the standard definition of yield (in tonnes per hectare, or similar units) to using the number of people actually fed per hectare of cropland. We find that, given the current mix of crop uses, growing food exclusively for direct human consumption could, in principle, increase available food calories by as much as 70%, which could feed an additional 4 billion people (more than the projected 2-3 billion people arriving through population growth). Even small shifts in our allocation of crops to animal feed and biofuels could significantly increase global food availability, and could be an instrumental tool in meeting the challenges of ensuring global food security.
Climate Change Impacts on Crop Production in Nigeria
NASA Astrophysics Data System (ADS)
Mereu, V.; Gallo, A.; Carboni, G.; Spano, D.
2011-12-01
The agricultural sector in Nigeria is particularly important for the country's food security, natural resources, and growth agenda. The cultivable areas comprise more than 70% of the total area; however, the cultivated area is about the 35% of the total area. The most important components in the food basket of the nation are cereals and tubers, which include rice, maize, corn, millet, sorghum, yam, and cassava. These crops represent about 80% of the total agricultural product in Nigeria (from NPAFS). The major crops grown in the country can be divided into food crops (produced for consumption) and export products. Despite the importance of the export crops, the primary policy of agriculture is to make Nigeria self-sufficient in its food and fiber requirements. The projected impacts of future climate change on agriculture and water resources are expected to be adverse and extensive in these area. This implies the need for actions and measures to adapt to climate change impacts, and especially as they affect agriculture, the primary sector for Nigerian economy. In the framework of the Project Climate Risk Analysis in Nigeria (founded by World Bank Contract n.7157826), a study was made to assess the potential impact of climate change on the main crops that characterize Nigerian agriculture. The DSSAT-CSM (Decision Support System for Agrotechnology Transfer - Cropping System Model) software, version 4.5 was used for the analysis. Crop simulation models included in DSSAT are tools that simulate physiological processes of crop growth, development and production by combining genetic crop characteristics and environmental (soil and weather) conditions. For each selected crop, the models were calibrated to evaluate climate change impacts on crop production. The climate data used for the analysis are derived by the Regional Circulation Model COSMO-CLM, from 1971 to 2065, at 8 km of spatial resolution. The RCM model output was "perturbed" with 10 Global Climate Models to have a wide variety of possible climate projections for the impact analysis. Multiple combinations of soil and climate conditions and crop management and varieties were considered for each Agro-Ecological Zone (AEZ) of Nigeria. A sensitivity analysis was made to evaluate the model response to changes in precipitation and temperature. The climate impact assessment was made by comparing the yield obtained with the climate data for the present period and the yield obtainable under future climate conditions. The results were analyzed at state, AEZ and country levels. The analysis shows a general reduction in crop yields in particular in the dryer regions of northern Nigeria.
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.
Poaceae vs. Abiotic Stress: Focus on Drought and Salt Stress, Recent Insights and Perspectives
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
Economic Analysis of Nitrate Source Reductions in California Agriculture
NASA Astrophysics Data System (ADS)
Medellin-Azuara, J.; Howitt, R.; Rosenstock, T.; Harter, T.; Pettygrove, S. G.; Dzurella, K.; Lund, J. R.
2011-12-01
We present an analytical approach to assess the economic impact of improving nitrogen management practices in California agriculture. We employ positive mathematical programming to calibrate crop production to base input information. The production function representation is a nested constant elasticity of substitution with two nests: one for applied water and one for applied nitrogen. The first nest accounts for the tradeoffs between irrigation efficiency and capital investments in irrigation technology. The second nest represents the tradeoffs between nitrogen application efficiency and the marginal costs of improving nitrogen efficiency. In the production function nest, low elasticities of substitution and water and nitrogen stress constraints keep agricultural crop yields constant despite changes in nitrogen management practices. We use the Tulare Basin, and the Salinas Valley in California's Central Valley and Central Coast respectively as our case studies. Preliminary results show that initial reductions of 25% in nitrogen loads to groundwater may not impose large costs to agricultural crop production as substitution of management inputs results in only small declines in net revenue from farming and total land use. Larger reductions in the nitrogen load to groundwater of 50% imposes larger marginal costs for better nitrogen management inputs and reductions in the area of lower valued crops grown in the study areas. Despite the shortage of data on quantitative effects of improved nitrogen efficiency; our results demonstrate the potential of combining economic and agronomic data into a model that can reflect differences in cost and substitutabilty in nitrogen application methods, that can be used to reduce the quantity of nitrogen leaching into groundwater.
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 ...
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.
Integrated crop management practices for maximizing grain yield of double-season rice crop.
Wang, Depeng; Huang, Jianliang; Nie, Lixiao; Wang, Fei; Ling, Xiaoxia; Cui, Kehui; Li, Yong; Peng, Shaobing
2017-01-12
Information on maximum grain yield and its attributes are limited for double-season rice crop grown under the subtropical environment. This study was conducted to examine key characteristics associated with high yielding double-season rice crop through a comparison between an integrated crop management (ICM) and farmers' practice (FP). Field experiments were conducted in the early and late seasons in the subtropical environment of Wuxue County, Hubei Province, China in 2013 and 2014. On average, grain yield in ICM was 13.5% higher than that in FP. A maximum grain yield of 9.40 and 10.53 t ha -1 was achieved under ICM in the early- and late-season rice, respectively. Yield improvement of double-season rice with ICM was achieved with the combined effects of increased plant density and optimized nutrient management. Yield gain of ICM resulted from a combination of increases in sink size due to more panicle number per unit area and biomass production, further supported by the increased leaf area index, leaf area duration, radiation use efficiency, crop growth rate, and total nitrogen uptake compared with FP. Further enhancement in the yield potential of double-season rice should focus on increasing crop growth rate and biomass production through improved and integrated crop management practices.
How Can CO2 Help Agriculture in the Face of Climate Change?
NASA Technical Reports Server (NTRS)
Delphine, Deryng; Elliott, Joshua; Folberth, Christian; Mueller, Christoph; Pugh, Thomas A. M.; Boote, Kenneth J.; Conway, Declan; Ruane, Alexander C.; Gerten, Dieter; Jones, James W.;
2017-01-01
Humans are increasing the amount of carbon dioxide (CO2) in the air through CO2 emissions. This is changing the climate, making life harder for many plants in areas that suffer from heat and drought. However, plants need CO2 to grow, and more CO2 can make them grow better. So will plants overall benefit from increased CO2 level or suffer from it? We wanted to test if the positive effect would offset the negative ones. To do so, we used scientific models to calculate future crop production and water use of four important crops all over the world under different scenarios of CO2 emissions and climate change. Our calculations show that although there will be large reductions in crop yield due to climate change over the next century, some crops will still be able to grow well. This is also because crops can grow with less water when CO2 levels are raised.
Potts, Simon G.; Steffan-Dewenter, Ingolf; Vaissière, Bernard E.; Woyciechowski, Michal; Krewenka, Kristin M.; Tscheulin, Thomas; Roberts, Stuart P.M.; Szentgyörgyi, Hajnalka; Westphal, Catrin; Bommarco, Riccardo
2014-01-01
Background. Up to 75% of crop species benefit at least to some degree from animal pollination for fruit or seed set and yield. However, basic information on the level of pollinator dependence and pollinator contribution to yield is lacking for many crops. Even less is known about how insect pollination affects crop quality. Given that habitat loss and agricultural intensification are known to decrease pollinator richness and abundance, there is a need to assess the consequences for different components of crop production. Methods. We used pollination exclusion on flowers or inflorescences on a whole plant basis to assess the contribution of insect pollination to crop yield and quality in four flowering crops (spring oilseed rape, field bean, strawberry, and buckwheat) located in four regions of Europe. For each crop, we recorded abundance and species richness of flower visiting insects in ten fields located along a gradient from simple to heterogeneous landscapes. Results. Insect pollination enhanced average crop yield between 18 and 71% depending on the crop. Yield quality was also enhanced in most crops. For instance, oilseed rape had higher oil and lower chlorophyll contents when adequately pollinated, the proportion of empty seeds decreased in buckwheat, and strawberries’ commercial grade improved; however, we did not find higher nitrogen content in open pollinated field beans. Complex landscapes had a higher overall species richness of wild pollinators across crops, but visitation rates were only higher in complex landscapes for some crops. On the contrary, the overall yield was consistently enhanced by higher visitation rates, but not by higher pollinator richness. Discussion. For the four crops in this study, there is clear benefit delivered by pollinators on yield quantity and/or quality, but it is not maximized under current agricultural intensification. Honeybees, the most abundant pollinator, might partially compensate the loss of wild pollinators in some areas, but our results suggest the need of landscape-scale actions to enhance wild pollinator populations. PMID:24749007
Bartomeus, Ignasi; Potts, Simon G; Steffan-Dewenter, Ingolf; Vaissière, Bernard E; Woyciechowski, Michal; Krewenka, Kristin M; Tscheulin, Thomas; Roberts, Stuart P M; Szentgyörgyi, Hajnalka; Westphal, Catrin; Bommarco, Riccardo
2014-01-01
Background. Up to 75% of crop species benefit at least to some degree from animal pollination for fruit or seed set and yield. However, basic information on the level of pollinator dependence and pollinator contribution to yield is lacking for many crops. Even less is known about how insect pollination affects crop quality. Given that habitat loss and agricultural intensification are known to decrease pollinator richness and abundance, there is a need to assess the consequences for different components of crop production. Methods. We used pollination exclusion on flowers or inflorescences on a whole plant basis to assess the contribution of insect pollination to crop yield and quality in four flowering crops (spring oilseed rape, field bean, strawberry, and buckwheat) located in four regions of Europe. For each crop, we recorded abundance and species richness of flower visiting insects in ten fields located along a gradient from simple to heterogeneous landscapes. Results. Insect pollination enhanced average crop yield between 18 and 71% depending on the crop. Yield quality was also enhanced in most crops. For instance, oilseed rape had higher oil and lower chlorophyll contents when adequately pollinated, the proportion of empty seeds decreased in buckwheat, and strawberries' commercial grade improved; however, we did not find higher nitrogen content in open pollinated field beans. Complex landscapes had a higher overall species richness of wild pollinators across crops, but visitation rates were only higher in complex landscapes for some crops. On the contrary, the overall yield was consistently enhanced by higher visitation rates, but not by higher pollinator richness. Discussion. For the four crops in this study, there is clear benefit delivered by pollinators on yield quantity and/or quality, but it is not maximized under current agricultural intensification. Honeybees, the most abundant pollinator, might partially compensate the loss of wild pollinators in some areas, but our results suggest the need of landscape-scale actions to enhance wild pollinator populations.
Downscaled climate change impacts on agricultural water resources in Puerto Rico
DOE Office of Scientific and Technical Information (OSTI.GOV)
Harmsen, E.W.; Miller, N.L.; Schlegel, N.J.
2009-04-01
The purpose of this study is to estimate reference evapotranspiration (ET{sub o}), rainfall deficit (rainfall - ET{sub o}) and relative crop yield reduction for a generic crop under climate change conditions for three locations in Puerto Rico: Adjuntas, Mayaguez, and Lajas. Reference evapotranspiration is estimated by the Penman-Monteith method. Rainfall and temperature data were statistically downscaled and evaluated using the DOE/NCAR PCM global circulation model projections for the B1 (low), A2 (mid-high) and A1fi (high) emission scenarios of the Intergovernmental Panel on Climate Change Special Report on Emission Scenarios. Relative crop yield reductions were estimated from a function dependent watermore » stress factor, which is a function of soil moisture content. Average soil moisture content for the three locations was determined by means of a simple water balance approach. Results from the analysis indicate that the rainy season will become wetter and the dry season will become drier. The 20-year mean 1990-2010 September rainfall excess (i.e., rainfall - ET{sub o} > 0) increased for all scenarios and locations from 149.8 to 356.4 mm for 2080-2100. Similarly, the 20-year average February rainfall deficit (i.e., rainfall - ET{sub o} < 0) decreased from a -26.1 mm for 1990-2010 to -72.1 mm for the year 2080-2100. The results suggest that additional water could be saved during the wet months to offset increased irrigation requirements during the dry months. Relative crop yield reduction did not change significantly under the B1 projected emissions scenario, but increased by approximately 20% during the summer months under the A1fi emissions scenario. Components of the annual water balance for the three climate change scenarios are rainfall, evapotranspiration (adjusted for soil moisture), surface runoff, aquifer recharge and change in soil moisture storage. Under the A1fi scenario, for all locations, annual evapotranspiration decreased owing to lower soil moisture, surface runoff decreased, and aquifer recharge increased. Aquifer recharge increased at all three locations because the majority of recharge occurs during the wet season and the wet season became wetter. This is good news from a groundwater production standpoint. Increasing aquifer recharge also suggests that groundwater levels may increase and this may help to minimize saltwater intrusion near the coasts as sea levels increase, provided that groundwater use is not over-subscribed.« less
Zhang, Xiying; Shao, Liwei; Chen, Suying
2016-01-01
The major wheat production region of China the North China Plain (NCP) is seriously affected by air pollution. In this study, yield of winter wheat (Triticum aestivum L.) was analyzed with respect to the potential impact of air pollution index under conditions of optimal crop management in the NCP from 2001 to 2012. Results showed that air pollution was especially serious at the early phase of winter wheat growth significantly influencing various weather factors. However, no significant correlations were found between final grain yield and the weather factors during the early growth phase. In contrast, significant correlations were found between grain yield and total solar radiation gap, sunshine hour gap, diurnal temperature range and relative humidity during the late growing phase. To disentangle the confounding effects of various weather factors, and test the isolated effect of air pollution induced changes in incoming global solar radiation on yield under ceteris paribus conditions, crop model based scenario-analysis was conducted. The simulation results of the calibrated Agricultural Production Systems Simulator (APSIM) model indicated that a reduction in radiation by 10% might cause a yield reduction by more than 10%. Increasing incident radiation by 10% would lead to yield increases of (only) 7%, with the effects being much stronger during the late growing phase compared to the early growing phase. However, there is evidence that APSIM overestimates the effect of air pollution induced changes on radiation, as it does not consider the changes in radiative properties of solar insulation, i.e. the relative increase of diffuse over direct radiation, which may partly alleviate the negative effects of reduced total radiation by air pollution. Concluding, the present study could not detect a significantly negative effect of air pollution on wheat yields in the NCP. PMID:27612146
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.
African Orphan Crops under Abiotic Stresses: Challenges and Opportunities.
Tadele, Zerihun
2018-01-01
A changing climate, a growing world population, and a reduction in arable land devoted to food production are all problems facing the world food security. The development of crops that can yield under uncertain and extreme climatic and soil growing conditions can play a key role in mitigating these problems. Major crops such as maize, rice, and wheat are responsible for a large proportion of global food production but many understudied crops (commonly known as "orphan crops") including millets, cassava, and cowpea feed millions of people in Asia, Africa, and South America and are already adapted to the local environments in which they are grown. The application of modern genetic and genomic tools to the breeding of these crops can provide enormous opportunities for ensuring world food security but is only in its infancy. In this review, the diversity and types of understudied crops will be introduced, and the beneficial traits of these crops as well as their role in the socioeconomics of Africa will be discussed. In addition, the response of orphan crops to diverse types of abiotic stresses is investigated. A review of the current tools and their application to the breeding of enhanced orphan crops will also be described. Finally, few examples of global efforts on tackling major abiotic constraints in Africa are presented.
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.
Scenario analysis of fertilizer management practices for N2O mitigation from corn systems in Canada.
Abalos, Diego; Smith, Ward N; Grant, Brian B; Drury, Craig F; MacKell, Sarah; Wagner-Riddle, Claudia
2016-12-15
Effective management of nitrogen (N) fertilizer application by farmers provides great potential for reducing emissions of the potent greenhouse gas nitrous oxide (N 2 O). However, such potential is rarely achieved because our understanding of what practices (or combination of practices) lead to N 2 O reductions without compromising crop yields remains far from complete. Using scenario analysis with the process-based model DNDC, this study explored the effects of nine fertilizer practices on N 2 O emissions and crop yields from two corn production systems in Canada. The scenarios differed in: timing of fertilizer application, fertilizer rate, number of applications, fertilizer type, method of application and use of nitrification/urease inhibitors. Statistical analysis showed that during the initial calibration and validation stages the simulated results had no significant total error or bias compared to measured values, yet grain yield estimations warrant further model improvement. Sidedress fertilizer applications reduced yield-scaled N 2 O emissions by c. 60% compared to fall fertilization. Nitrification inhibitors further reduced yield-scaled N 2 O emissions by c. 10%; urease inhibitors had no effect on either N 2 O emissions or crop productivity. The combined adoption of split fertilizer application with inhibitors at a rate 10% lower than the conventional application rate (i.e. 150kgNha -1 ) was successful, but the benefits were lower than those achieved with single fertilization at sidedress. Our study provides a comprehensive assessment of fertilizer management practices that enables policy development regarding N 2 O mitigation from agricultural soils in Canada. Copyright © 2016 Elsevier B.V. All rights reserved.
Wildlife-friendly farming increases crop yield: evidence for ecological intensification.
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.
DNA damage and repair in plants – from models to crops
Manova, Vasilissa; Gruszka, Damian
2015-01-01
The genomic integrity of every organism is constantly challenged by endogenous and exogenous DNA-damaging factors. Mutagenic agents cause reduced stability of plant genome and have a deleterious effect on development, and in the case of crop species lead to yield reduction. It is crucial for all organisms, including plants, to develop efficient mechanisms for maintenance of the genome integrity. DNA repair processes have been characterized in bacterial, fungal, and mammalian model systems. The description of these processes in plants, in contrast, was initiated relatively recently and has been focused largely on the model plant Arabidopsis thaliana. Consequently, our knowledge about DNA repair in plant genomes - particularly in the genomes of crop plants - is by far more limited. However, the relatively small size of the Arabidopsis genome, its rapid life cycle and availability of various transformation methods make this species an attractive model for the study of eukaryotic DNA repair mechanisms and mutagenesis. Moreover, abnormalities in DNA repair which proved to be lethal for animal models are tolerated in plant genomes, although sensitivity to DNA damaging agents is retained. Due to the high conservation of DNA repair processes and factors mediating them among eukaryotes, genes and proteins that have been identified in model species may serve to identify homologous sequences in other species, including crop plants, in which these mechanisms are poorly understood. Crop breeding programs have provided remarkable advances in food quality and yield over the last century. Although the human population is predicted to “peak” by 2050, further advances in yield will be required to feed this population. Breeding requires genetic diversity. The biological impact of any mutagenic agent used for the creation of genetic diversity depends on the chemical nature of the induced lesions and on the efficiency and accuracy of their repair. More recent targeted mutagenesis procedures also depend on host repair processes, with different pathways yielding different products. Enhanced understanding of DNA repair processes in plants will inform and accelerate the engineering of crop genomes via both traditional and targeted approaches. PMID:26557130
Freitag, Sabine; Verrall, Susan R; Pont, Simon D A; McRae, Diane; Sungurtas, Julia A; Palau, Raphaëlle; Hawes, Cathy; Alexander, Colin J; Allwood, J William; Foito, Alexandre; Stewart, Derek; Shepherd, Louise V T
2018-01-31
The reduction of the environmental footprint of crop production without compromising crop yield and their nutritional value is a key goal for improving the sustainability of agriculture. In 2009, the Balruddery Farm Platform was established at The James Hutton Institute as a long-term experimental platform for cross-disciplinary research of crops using two agricultural ecosystems. Crops representative of UK agriculture were grown under conventional and integrated management systems and analyzed for their water-soluble vitamin content. Integrated management, when compared with the conventional system, had only minor effects on water-soluble vitamin content, where significantly higher differences were seen for the conventional management practice on the levels of thiamine in field beans (p < 0.01), Spring barley (p < 0.05), and Winter wheat (p < 0.05), and for nicotinic acid in Spring barley (p < 0.05). However, for all crops, variety and year differences were of greater importance. These results indicate that the integrated management system described in this study does not significantly affect the water-soluble vitamin content of the crops analyzed here.
NASA Astrophysics Data System (ADS)
Molina Herrera, Saul; Haas, Edwin; Klatt, Steffen; Kraus, David; Kiese, Ralf; Butterbach-Bahl, Klaus
2014-05-01
The use of mineral nitrogen (N) fertilizers increase crop yields but cause the biggest anthropogenic source of nitrous oxide (N2O) emissions and strongly contribute to surface water eutrophication (e.g. nitrate leaching). The necessity to identify affordable strategies that improve crop production while improving ecosystem services are in continuous debate between policy decision makers and farmers. In this line, a lack commitment from farmers to enforce laws might result in the reduction of benefits. For this reason, farmers should aim to increase crop production and to reduce environmental harm by the adoption of precision climate smart agriculture tools applied to management practices for instance. In this study we present optimized strategies for 8 sites (agricultural and grassland ecosystems) with long term field observation across Europe to show the mitigation potential to reduce reactive nitrogen losses under the constrain of keeping yields at observed levels. LandscapeDNDC simulations of crop yields and associated nitrogen losses (N2O emissions and NO3 leaching) were evaluated against long term field measurements. The sites presented different management regimes including the main commodity crops (maize, wheat, barley, rape seeds, etc) and fertilization amendments (synthetic and organic fertilizers) in Europe. The simulations reproduced the observed yields, captured N2O emissions and NO3 leaching losses with high statistical presicion (r2), acurrency (ME) and agreement (RMSPEn). The mitigation potentials to reduce N losses while keeping yields at observed levels for all 8 sites were assesed by Monte Carlo optimizations of the individual underlying multi year agricultural management options (timings of planting and harvest, fertilization & manure applications and rates, residues management). In this study we present for all 8 agricultural observations sites their individual mitigation potentials to reduce N losses for multi year rotations. The conclusions for each side could result in management strategies to minimize environmental impact when such a model is used to predict best management practice on the site scale.
USDA-ARS?s Scientific Manuscript database
Impaired root development caused by aluminum (Al) toxicity is a major cause for grain yield reduction for crops cultivated on acid soils which are widespread worldwide. In sorghum, the major Al tolerance locus, AltSB, is due to the function of SbMATE, which is an Al-activated root citrate transporte...
Ultraviolet-B radiation in a row-crop canopy: an extended 1-D model
Wei Gao; Richard H. Grant; Gordon M. Heisler; James R. Slusser
2003-01-01
A decrease in stratospheric ozone may result in a serious threat to plants, since biologically active short-wavelength ultraviolet-B (UV-B 280-320 nm) radiation will increase even with a relatively small decrease in ozone. Numerous investigations have demonstrated that the effect of UV-B enhancements on plants includes reduction in grain yield, alteration in species...
Climate variation explains a third of global crop yield variability
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
Breeding implications of drought stress under future climate for upland rice in Brazil.
Ramirez-Villegas, Julian; Heinemann, Alexandre B; Pereira de Castro, Adriano; Breseghello, Flávio; Navarro-Racines, Carlos; Li, Tao; Rebolledo, Maria C; Challinor, Andrew J
2018-05-01
Rice is the most important food crop in the developing world. For rice production systems to address the challenges of increasing demand and climate change, potential and on-farm yield increases must be increased. Breeding is one of the main strategies toward such aim. Here, we hypothesize that climatic and atmospheric changes for the upland rice growing period in central Brazil are likely to alter environment groupings and drought stress patterns by 2050, leading to changing breeding targets during the 21st century. As a result of changes in drought stress frequency and intensity, we found reductions in productivity in the range of 200-600 kg/ha (up to 20%) and reductions in yield stability throughout virtually the entire upland rice growing area (except for the southeast). In the face of these changes, our crop simulation analysis suggests that the current strategy of the breeding program, which aims at achieving wide adaptation, should be adjusted. Based on the results for current and future climates, a weighted selection strategy for the three environmental groups that characterize the region is suggested. For the highly favorable environment (HFE, 36%-41% growing area, depending on RCP), selection should be done under both stress-free and terminal stress conditions; for the favorable environment (FE, 27%-40%), selection should aim at testing under reproductive and terminal stress, and for the least favorable environment (LFE, 23%-27%), selection should be conducted for response to reproductive stress only and for the joint occurrence of reproductive and terminal stress. Even though there are differences in timing, it is noteworthy that stress levels are similar across environments, with 40%-60% of crop water demand unsatisfied. Efficient crop improvement targeted toward adaptive traits for drought tolerance will enhance upland rice crop system resilience under climate change. © 2018 John Wiley & Sons Ltd.
Quantifying the impacts of climatic trend and fluctuation on crop yields in northern China.
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.
Nutrient mass balance and trends, Mobile River Basin, Alabama, Georgia, and Mississippi
Harned, D.A.; Atkins, J.B.; Harvill, J.S.
2004-01-01
A nutrient mass balance - accounting for nutrient inputs from atmospheric deposition, fertilizer, crop nitrogen fixation, and point source effluents; and nutrient outputs, including crop harvest and storage - was calculated for 18 subbasins in the Mobile River Basin, and trends (1970 to 1997) were evaluated as part of the U.S. Geological Survey National Water Quality Assessment (NAWQA) Program. Agricultural nonpoint nitrogen and phosphorus sources and urban nonpoint nitrogen sources are the most important factors associated with nutrients in this system. More than 30 percent of nitrogen yield in two basins and phosphorus yield in eight basins can be attributed to urban point source nutrient inputs. The total nitrogen yield (1.3 tons per square mile per year) for the Tombigbee River, which drains a greater percentage of agricultural (row crop) land use, was larger than the total nitrogen yield (0.99 tons per square mile per year) for the Alabama River. Decreasing trends of total nitrogen concentrations in the Tombigbee and Alabama Rivers indicate that a reduction occurred from 1975 to 1997 in the nitrogen contributions to Mobile Bay from the Mobile River. Nitrogen concentrations also decreased (1980 to 1995) in the Black Warrior River, one of the major tributaries to the Tombigbee River. Total phosphorus concentrations increased from 1970 to 1996 at three urban influenced sites on the Etowah River in Georgia. Multiple regression analysis indicates a distinct association between water quality in the streams of the Mobile River drainage basin and agricultural activities in the basin.
Effects of biochar addition to soil on nitrogen fluxes in a winter wheat lysimeter experiment
NASA Astrophysics Data System (ADS)
Hüppi, Roman; Leifeld, Jens; Neftel, Albrecht; Conen, Franz; Six, Johan
2014-05-01
Biochar is a carbon-rich, porous residue from pyrolysis of biomass that potentially increases crop yields by reducing losses of nitrogen from soils and/or enhancing the uptake of applied fertiliser by the crops. Previous research is scarce about biochar's ability to increase wheat yields in temperate soils or how it changes nitrogen dynamics in the field. In a lysimeter system with two different soils (sandy/silt loam) nitrogen fluxes were traced by isotopic 15N enriched fertiliser to identify changes in nitrous oxide emissions, leaching and plant uptake after biochar addition. 20t/ha woodchip-waste biochar (pH=13) was applied to these soils in four lysimeters per soil type; the same number of lysimeters served as a control. The soils were cropped with winter wheat during the season 2012/2013. 170 kg-N/ha ammonium nitrate fertiliser with 10% 15N was applied in 3 events during the growing season and 15N concentrations where measured at different points in time in plant, soil, leachate and emitted nitrous oxide. After one year the lysimeter system showed no difference between biochar and control treatment in grain- and straw yield or nitrogen uptake. However biochar did reduce nitrous oxide emissions in the silt loam and losses of nitrate leaching in sandy loam. This study indicates potential reduction of nitrogen loss from cropland soil by biochar application but could not confirm increased yields in an intensive wheat production system.
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;
2015-01-01
Many studies have been carried out during the last decade to study the effect of climate change on crop yields and other key crop characteristics. In these studies, one or several crop models were used to simulate crop growth and development for different climate scenarios that correspond to different projections of atmospheric CO2 concentration, temperature, and rainfall changes (Semenov et al., 1996; Tubiello and Ewert, 2002; White et al., 2011). The Agricultural Model Intercomparison and Improvement Project (AgMIP; Rosenzweig et al., 2013) builds on these studies with the goal of using an ensemble of multiple crop models in order to assess effects of climate change scenarios for several crops in contrasting environments. These studies generate large datasets, including thousands of simulated crop yield data. They include series of yield values obtained by combining several crop models with different climate scenarios that are defined by several climatic variables (temperature, CO2, rainfall, etc.). Such datasets potentially provide useful information on the possible effects of different climate change scenarios on crop yields. However, it is sometimes difficult to analyze these datasets and to summarize them in a useful way due to their structural complexity; simulated yield data can differ among contrasting climate scenarios, sites, and crop models. Another issue is that it is not straightforward to extrapolate the results obtained for the scenarios to alternative climate change scenarios not initially included in the simulation protocols. Additional dynamic crop model simulations for new climate change scenarios are an option but this approach is costly, especially when a large number of crop models are used to generate the simulated data, as in AgMIP. Statistical models have been used to analyze responses of measured yield data to climate variables in past studies (Lobell et al., 2011), but the use of a statistical model to analyze yields simulated by complex process-based crop models is a rather new idea. We demonstrate herewith that statistical methods can play an important role in analyzing simulated yield data sets obtained from the ensembles of process-based crop models. Formal statistical analysis is helpful to estimate the effects of different climatic variables on yield, and to describe the between-model variability of these effects.
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;
2016-01-01
The aggregation of simulated gridded crop yields to national or regional scale requires information on temporal and spatial patterns of crop-specific harvested areas. This analysis estimates the uncertainty of simulated gridded yield time series related to the aggregation with four different harvested area data sets. We compare aggregated yield time series from the Global Gridded Crop Model Inter-comparison project for four crop types from 14 models at global, national, and regional scale to determine aggregation-driven differences in mean yields and temporal patterns as measures of uncertainty. The quantity and spatial patterns of harvested areas differ for individual crops among the four datasets applied for the aggregation. Also simulated spatial yield patterns differ among the 14 models. These differences in harvested areas and simulated yield patterns lead to differences in aggregated productivity estimates, both in mean yield and in the temporal dynamics. Among the four investigated crops, wheat yield (17% relative difference) is most affected by the uncertainty introduced by the aggregation at the global scale. The correlation of temporal patterns of global aggregated yield time series can be as low as for soybean (r = 0.28).For the majority of countries, mean relative differences of nationally aggregated yields account for10% or less. The spatial and temporal difference can be substantial higher for individual countries. Of the top-10 crop producers, aggregated national multi-annual mean relative difference of yields can be up to 67% (maize, South Africa), 43% (wheat, Pakistan), 51% (rice, Japan), and 427% (soybean, Bolivia).Correlations of differently aggregated yield time series can be as low as r = 0.56 (maize, India), r = 0.05*Corresponding (wheat, Russia), r = 0.13 (rice, Vietnam), and r = -0.01 (soybean, Uruguay). The aggregation to sub-national scale in comparison to country scale shows that spatial uncertainties can cancel out in countries with large harvested areas per crop type. We conclude that the aggregation uncertainty can be substantial for crop productivity and production estimations in the context of food security, impact assessment, and model evaluation exercises.
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.
E Birch, A Nicholas; Begg, Graham S; Squire, Geoffrey R
2011-06-01
Drivers behind food security and crop protection issues are discussed in relation to food losses caused by pests. Pests globally consume food estimated to feed an additional one billion people. Key drivers include rapid human population increase, climate change, loss of beneficial on-farm biodiversity, reduction in per capita cropped land, water shortages, and EU pesticide withdrawals under policies relating to 91/414 EEC. IPM (Integrated Pest Management) will be compulsory for all EU agriculture by 2014 and is also being widely adopted globally. IPM offers a 'toolbox' of complementary crop- and region-specific crop protection solutions to address these rising pressures. IPM aims for more sustainable solutions by using complementary technologies. The applied research challenge now is to reduce selection pressure on single solution strategies, by creating additive/synergistic interactions between IPM components. IPM is compatible with organic, conventional, and GM cropping systems and is flexible, allowing regional fine-tuning. It reduces pests below economic thresholds utilizing key 'ecological services', particularly biocontrol. A recent global review demonstrates that IPM can reduce pesticide use and increase yields of most of the major crops studied. Landscape scale 'ecological engineering', together with genetic improvement of new crop varieties, will enhance the durability of pest-resistant cultivars (conventional and GM). IPM will also promote compatibility with semiochemicals, biopesticides, precision pest monitoring tools, and rapid diagnostics. These combined strategies are urgently needed and are best achieved via multi-disciplinary research, including complex spatio-temporal modelling at farm and landscape scales. Integrative and synergistic use of existing and new IPM technologies will help meet future food production needs more sustainably in developed and developing countries, in an era of reduced pesticide availability. Current IPM research gaps are identified and discussed.
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.
NASA Astrophysics Data System (ADS)
Wen, Y.
2017-12-01
Combining mulch and irrigation scheduling may lead to an increase of crop yield and water use efficiency (WUE = crop yield/evapotranspiration) with limited irrigation water, especially in arid regions. Based on 2 years' field experiments with ten irrigation-mulching treatments of spring wheat (Triticum aestivum L.) in the Shiyang River Basin Experiment Station in Gansu Province of Northwest China, a simulation-based optimization model for deficit irrigation scheduling of plastic mulching spring wheat was used to analyze an optimal irrigation scheduling for different deficit irrigation scenarios. Results revealed that mulching may increase maximum grain yield without water stress by 0.4-0.6 t ha-1 in different years and WUE by 0.2-0.3 kg m-3 for different irrigation amounts compared with no mulching. Yield of plastic mulching spring wheat was more sensitive to water stress in the early and development growth stages with an increase of cumulative crop water sensitive index (CCWSI) by 42%, and less sensitive to water stress in the mid and late growth stages with a reduction of CCWSI by 24%. For a relative wet year, when irrigation water is only applied once it should be at the mid to end of booting growth stage. Two irrigations should be applied at the beginning of booting and heading growth stages. The irrigation date can be extended to the beginning of jointing and grain formation growth stages with more water available for irrigation. For a normal or a dry year, the first irrigation should be applied 5-8 days earlier than the wet year. The highest WUE of 3.6 kg m-3 was achieved with 180 mm of irrigation applied twice for mulching in a wet year. Combining mulch and an optimal deficit irrigation scheduling is an effective way to increase crop yield and WUE in arid regions.
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.
Wu, Chao; Cui, Kehui; Wang, Wencheng; Li, Qian; Fahad, Shah; Hu, Qiuqian; Huang, Jianliang; Nie, Lixiao; Peng, Shaobing
2016-01-01
Heat stress causes morphological and physiological changes and reduces crop yield in rice (Oryza sativa). To investigate changes in phytohormones and their relationships with yield and other attributes under heat stress, four rice varieties (Nagina22, Huanghuazhan, Liangyoupeijiu, and Shanyou 63) were grown in pots and subjected to three high temperature treatments plus control in temperature-controlled greenhouses for 15 d during the early reproductive phase. Yield reductions in Nagina22, Huanghuazhan, and Liangyoupeijiu were attributed to reductions in spikelet fertility, spikelets per panicle, and grain weight. The adverse effects of high temperature were alleviated by application of exogenous 6-benzylaminopurine (6-BA) in the heat-susceptible Liangyoupeijiu. High temperature stress reduced active cytokinins, gibberellin A1 (GA1), and indole-3-acetic acid (IAA), but increased abscisic acid (ABA) and bound cytokinins in young panicles. Correlation analyses and application of exogenous 6-BA revealed that high temperature-induced cytokinin changes may regulate yield components by modulating the differentiation and degradation of branches and spikelets, panicle exsertion, pollen vigor, anther dehiscence, and grain size. Heat-tolerant Shanyou 63 displayed minor changes in phytohormones, panicle formation, and grain yield under high temperature compared with those of the other three varieties. These results suggest that phytohormone changes are closely associated with yield formation, and a small reduction or stability in phytohormone content is required to avoid large yield losses under heat stress. PMID:27713528
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.
African Orphan Crops under Abiotic Stresses: Challenges and Opportunities
2018-01-01
A changing climate, a growing world population, and a reduction in arable land devoted to food production are all problems facing the world food security. The development of crops that can yield under uncertain and extreme climatic and soil growing conditions can play a key role in mitigating these problems. Major crops such as maize, rice, and wheat are responsible for a large proportion of global food production but many understudied crops (commonly known as “orphan crops”) including millets, cassava, and cowpea feed millions of people in Asia, Africa, and South America and are already adapted to the local environments in which they are grown. The application of modern genetic and genomic tools to the breeding of these crops can provide enormous opportunities for ensuring world food security but is only in its infancy. In this review, the diversity and types of understudied crops will be introduced, and the beneficial traits of these crops as well as their role in the socioeconomics of Africa will be discussed. In addition, the response of orphan crops to diverse types of abiotic stresses is investigated. A review of the current tools and their application to the breeding of enhanced orphan crops will also be described. Finally, few examples of global efforts on tackling major abiotic constraints in Africa are presented. PMID:29623231
Reducing nitrate loss in tile drainage water with cover crops and water-table management systems.
Drury, C F; Tan, C S; Welacky, T W; Reynolds, W D; Zhang, T Q; Oloya, T O; McLaughlin, N B; Gaynor, J D
2014-03-01
Nitrate lost from agricultural soils is an economic cost to producers, an environmental concern when it enters rivers and lakes, and a health risk when it enters wells and aquifers used for drinking water. Planting a winter wheat cover crop (CC) and/or use of controlled tile drainage-subirrigation (CDS) may reduce losses of nitrate (NO) relative to no cover crop (NCC) and/or traditional unrestricted tile drainage (UTD). A 6-yr (1999-2005) corn-soybean study was conducted to determine the effectiveness of CC+CDS, CC+UTD, NCC+CDS, and NCC+UTD treatments for reducing NO loss. Flow volume and NO concentration in surface runoff and tile drainage were measured continuously, and CC reduced the 5-yr flow-weighted mean (FWM) NO concentration in tile drainage water by 21 to 38% and cumulative NO loss by 14 to 16% relative to NCC. Controlled tile drainage-subirrigation reduced FWM NO concentration by 15 to 33% and cumulative NO loss by 38 to 39% relative to UTD. When CC and CDS were combined, 5-yr cumulative FWM NO concentrations and loss in tile drainage were decreased by 47% (from 9.45 to 4.99 mg N L and from 102 to 53.6 kg N ha) relative to NCC+UTD. The reductions in runoff and concomitant increases in tile drainage under CC occurred primarily because of increases in near-surface soil hydraulic conductivity. Cover crops increased corn grain yields by 4 to 7% in 2004 increased 3-yr average soybean yields by 8 to 15%, whereas CDS did not affect corn or soybean yields over the 6 yr. The combined use of a cover crop and water-table management system was highly effective for reducing NO loss from cool, humid agricultural soils. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.
Regional crop yield forecasting: a probabilistic approach
NASA Astrophysics Data System (ADS)
de Wit, A.; van Diepen, K.; Boogaard, H.
2009-04-01
Information on the outlook on yield and production of crops over large regions is essential for government services dealing with import and export of food crops, for agencies with a role in food relief, for international organizations with a mandate in monitoring the world food production and trade, and for commodity traders. Process-based mechanistic crop models are an important tool for providing such information, because they can integrate the effect of crop management, weather and soil on crop growth. When properly integrated in a yield forecasting system, the aggregated model output can be used to predict crop yield and production at regional, national and continental scales. Nevertheless, given the scales at which these models operate, the results are subject to large uncertainties due to poorly known weather conditions and crop management. Current yield forecasting systems are generally deterministic in nature and provide no information about the uncertainty bounds on their output. To improve on this situation we present an ensemble-based approach where uncertainty bounds can be derived from the dispersion of results in the ensemble. The probabilistic information provided by this ensemble-based system can be used to quantify uncertainties (risk) on regional crop yield forecasts and can therefore be an important support to quantitative risk analysis in a decision making process.
NASA Technical Reports Server (NTRS)
Bugbee, B.; Monje, O.
1992-01-01
Plant scientists have sought to maximize the yield of food crops since the beginning of agriculture. There are numerous reports of record food and biomass yields (per unit area) in all major crop plants, but many of the record yield reports are in error because they exceed the maximal theoretical rates of the component processes. In this article, we review the component processes that govern yield limits and describe how each process can be individually measured. This procedure has helped us validate theoretical estimates and determine what factors limit yields in optimal environments.
Spatial Sampling of Weather Data for Regional Crop Yield Simulations
NASA Technical Reports Server (NTRS)
Van Bussel, Lenny G. J.; Ewert, Frank; Zhao, Gang; Hoffmann, Holger; Enders, Andreas; Wallach, Daniel; Asseng, Senthold; Baigorria, Guillermo A.; Basso, Bruno; Biernath, Christian;
2016-01-01
Field-scale crop models are increasingly applied at spatio-temporal scales that range from regions to the globe and from decades up to 100 years. Sufficiently detailed data to capture the prevailing spatio-temporal heterogeneity in weather, soil, and management conditions as needed by crop models are rarely available. Effective sampling may overcome the problem of missing data but has rarely been investigated. In this study the effect of sampling weather data has been evaluated for simulating yields of winter wheat in a region in Germany over a 30-year period (1982-2011) using 12 process-based crop models. A stratified sampling was applied to compare the effect of different sizes of spatially sampled weather data (10, 30, 50, 100, 500, 1000 and full coverage of 34,078 sampling points) on simulated wheat yields. Stratified sampling was further compared with random sampling. Possible interactions between sample size and crop model were evaluated. The results showed differences in simulated yields among crop models but all models reproduced well the pattern of the stratification. Importantly, the regional mean of simulated yields based on full coverage could already be reproduced by a small sample of 10 points. This was also true for reproducing the temporal variability in simulated yields but more sampling points (about 100) were required to accurately reproduce spatial yield variability. The number of sampling points can be smaller when a stratified sampling is applied as compared to a random sampling. However, differences between crop models were observed including some interaction between the effect of sampling on simulated yields and the model used. We concluded that stratified sampling can considerably reduce the number of required simulations. But, differences between crop models must be considered as the choice for a specific model can have larger effects on simulated yields than the sampling strategy. Assessing the impact of sampling soil and crop management data for regional simulations of crop yields is still needed.
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).
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.
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
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...
Historical and simulated ecosystem carbon dynamics in Ghana: Land use, management, and climate
Tan, Z.; Tieszen, L.L.; Tachie-Obeng, E.; Liu, S.; Dieye, A.M.
2009-01-01
We used the General Ensemble biogeochemical Modeling System (GEMS) to simulate responses of natural and managed ecosystems to changes in land use and land cover, management, and climate for a forest/savanna transitional zone in central Ghana. Model results show that deforestation for crop production during the 20th century resulted in a substantial reduction in ecosystem carbon (C) stock from 135.4 Mg C ha−1 in 1900 to 77.0 Mg C ha−1 in 2000, and in soil organic C stock within the top 20 cm of soil from 26.6 Mg C ha−1 to 21.2 Mg C ha−1. If no land use change takes place from 2000 through 2100, low and high climate change scenarios (increase in temperature and decrease in precipitation over time) will result in losses of soil organic C stock by 16% and 20%, respectively. A low nitrogen (N) fertilization rate is the principal constraint on current crop production. An increase in N fertilization under the low climate change scenario would lead to an increase in the average crop yield by 21% with 30 kg N ha−1 and by 42% with 60 kg N ha−1 (varying with crop species), accordingly, the average soil C stock would decrease by 2% and increase by 17%, in all cropping systems by 2100. The results suggest that a reasonable N fertilization rate is critical to achieve food security and agricultural sustainability in the study area through the 21st century. Adaptation strategies for climate change in this study area require national plans to support policies and practices that provide adequate N fertilizers to sustain soil C and crop yields and to consider high temperature tolerant crop species if these temperature projections are exceeded.
Rueda-Ayala, Victor; Weis, Martin; Keller, Martina; Andújar, Dionisio; Gerhards, Roland
2013-01-01
Harrowing is often used to reduce weed competition, generally using a constant intensity across a whole field. The efficacy of weed harrowing in wheat and barley can be optimized, if site-specific conditions of soil, weed infestation and crop growth stage are taken into account. This study aimed to develop and test an algorithm to automatically adjust the harrowing intensity by varying the tine angle and number of passes. The field variability of crop leaf cover, weed density and soil density was acquired with geo-referenced sensors to investigate the harrowing selectivity and crop recovery. Crop leaf cover and weed density were assessed using bispectral cameras through differential images analysis. The draught force of the soil opposite to the direction of travel was measured with electronic load cell sensor connected to a rigid tine mounted in front of the harrow. Optimal harrowing intensity levels were derived in previously implemented experiments, based on the weed control efficacy and yield gain. The assessments of crop leaf cover, weed density and soil density were combined via rules with the aforementioned optimal intensities, in a linguistic fuzzy inference system (LFIS). The system was evaluated in two field experiments that compared constant intensities with variable intensities inferred by the system. A higher weed density reduction could be achieved when the harrowing intensity was not kept constant along the cultivated plot. Varying the intensity tended to reduce the crop leaf cover, though slightly improving crop yield. A real-time intensity adjustment with this system is achievable, if the cameras are attached in the front and at the rear or sides of the harrow. PMID:23669712
Historical and simulated ecosystem carbon dynamics in Ghana: land use, management, and climate
NASA Astrophysics Data System (ADS)
Tan, Z.; Tieszen, L. L.; Tachie-Obeng, E.; Liu, S.; Dieye, A. M.
2009-01-01
We used the General Ensemble biogeochemical Modeling System (GEMS) to simulate responses of natural and managed ecosystems to changes in land use and land cover, management, and climate for a forest/savanna transitional zone in central Ghana. Model results show that deforestation for crop production during the 20th century resulted in a substantial reduction in ecosystem carbon (C) stock from 135.4 Mg C ha-1 in 1900 to 77.0 Mg C ha-1 in 2000, and in soil organic C stock within the top 20 cm of soil from 26.6 Mg C ha-1 to 21.2 Mg C ha-1. If no land use change takes place from 2000 through 2100, low and high climate change scenarios (increase in temperature and decrease in precipitation over time) will result in losses of soil organic C stock by 16% and 20%, respectively. A low nitrogen (N) fertilization rate is the principal constraint on current crop production. An increase in N fertilization under the low climate change scenario would lead to an increase in the average crop yield by 21% with 30 kg N ha-1 and by 42% with 60 kg N ha-1 (varying with crop species), accordingly, the average soil C stock would decrease by 2% and increase by 17%, in all cropping systems by 2100. The results suggest that a reasonable N fertilization rate is critical to achieve food security and agricultural sustainability in the study area through the 21st century. Adaptation strategies for climate change in this study area require national plans to support policies and practices that provide adequate N fertilizers to sustain soil C and crop yields and to consider high temperature tolerant crop species if these temperature projections are exceeded.
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.
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.
Chen, Zhongdu; Chen, Fu; Zhang, Hailin; Liu, Shengli
2016-12-01
The net global warming potential (NGWP) and net greenhouse gas intensity (NGHGI) of double-rice cropping systems are not well documented. We measured the NGWP and NGHGI including soil organic carbon (SOC) change and indirect emissions (IE) from double-crop rice fields with fertilizing systems in Southern China. These experiments with three different nitrogen (N) application rates since 2012 are as follows: 165 kgN ha -1 for early rice and 225 kgN ha -1 for late rice (N1), which was the local N application rates as the control; 135 kgN ha -1 for early rice and 180 kgN ha -1 for late rice (N2, 20 % reduction); and 105 kgN ha -1 for early rice and 135 kgN ha -1 for late rice (N3, 40 % reduction). Results showed that yields increased with the increase of N application rate, but without significant difference between N1 and N2 plots. Annual SOC sequestration rate under N1 was estimated to be 1.15 MgC ha -1 year -1 , which was higher than those under other fertilizing systems. Higher N application tended to increase CH 4 emissions during the flooded rice season and significantly increased N 2 O emissions from drained soils during the nonrice season, ranking as N1 > N2 > N3 with significant difference (P < 0.05). Two-year average IE has a huge contribution to GHG emissions mainly coming from the higher N inputs in the double-rice cropping system. Reducing N fertilizer usage can effectively decrease the NGWP and NGHGI in the double-rice cropping system, with the lowest NGHGI obtained in the N2 plot (0.99 kg CO 2 -eq kg -1 yield year -1 ). The results suggested that agricultural economic viability and GHG mitigation can be simultaneously achieved by properly reducing N fertilizer application in double-rice cropping systems.
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.
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
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.
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.
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.
Climate change effects on agriculture: Economic responses to biophysical shocks
DOE Office of Scientific and Technical Information (OSTI.GOV)
Nelson, Gerald; Valin, Hugo; Sands, Ronald
Agricultural production is sensitive to weather and will thus be directly affected by climate change. Plausible estimates of these climate change impacts require combined use of climate, crop, and economic models. Results from previous studies vary substantially due to differences in models, scenarios, and data. This paper is part of a collective effort to systematically integrate these three types of models. We focus on the economic component of the assessment, investigating how nine global economic models of agriculture represent endogenous responses to seven standardized climate change scenarios produced by two climate and five crop models. These responses include adjustments inmore » yields, area, consumption, and international trade. We apply biophysical shocks derived from the IPCC’s Representative Concentration Pathway that result in end-of-century radiative forcing of 8.5 watts per square meter. The mean biophysical impact on crop yield with no incremental CO2 fertilization is a 17 percent reduction globally by 2050 relative to a scenario with unchanging climate. Endogenous economic responses reduce yield loss to 11 percent, increase area of major crops by 12 percent, and reduce consumption by 2 percent. Agricultural production, cropland area, trade, and prices show the greatest degree of variability in response to climate change, and consumption the lowest. The sources of these differences includes model structure and specification; in particular, model assumptions about ease of land use conversion, intensification, and trade. This study identifies where models disagree on the relative responses to climate shocks and highlights research activities needed to improve the representation of agricultural adaptation responses to climate change.« less
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.
Tripathi, Ruchika; Agrawal, S B
2012-11-01
Tropospheric ozone (O(3)) has become a serious threat to growth and yield of important agricultural crops over Asian regions including India. Effect of elevated O(3) (ambient+10ppb) was studied on Brassica campestris L. (cv. Sanjukta and Vardan) in open top chambers under natural field conditions. Eight hourly mean ambient O(3) concentration varied from 26.3ppb to 69.5ppb during the growth period. Plants under O(3) exposure showed reductions in photosynthetic rate, reproductive parameters, yield as well as seed and oil quality. Cultivar Sanjukta showed more reduction in photosynthetic characteristics, reproductive structures and seed and oil quality. However, total yield was more affected in Vardan. Exposure of O(3) increased the degree of unsaturation and level of PUFA, ω-6fatty acid, linolenic acid and erucic acid in oil indicating the deterioration of its quality. The study further confirmed that there is a correspondence between O(3) induced change in photosynthetic processes, reproductive development and yield and did not find any compensatory response in the final yield. Copyright © 2012 Elsevier Inc. All rights reserved.
The uncertainty of crop yield projections is reduced by improved temperature response functions.
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.;
2017-01-01
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 is greater than 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.
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.
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
Peña-Haro, Salvador; García-Prats, Alberto; Pulido-Velazquez, Manuel
2014-11-15
Economic instruments can be used to control groundwater nitrate pollution due to the intensive use of fertilizers in agriculture. In order to test their efficiency on the reduction of nitrate leaching, we propose an approach based on the combined use of production and pollution functions to derive the impacts on the expected farmer response of these instruments. Some of the most important factors influencing nitrate leaching and crop yield are the type of soil and the climatic conditions. Crop yield and nitrate leaching responses to different soil and climatic conditions were classified by means of a cluster analysis, and crops located in different areas but with similar response were grouped for the analysis. We use a spatial economic optimization model to evaluate the potential of taxes on nitrogen fertilizers, water prices, and taxes on nitrate emissions to reduce nitrate pollution, as well as their economic impact in terms of social welfare and farmers' net benefits. The method was applied to the Mancha Oriental System (MOS) in Spain, a large area with different soil types and climatic conditions. We divided the study area into zones of homogeneous crop production and nitrate leaching properties. Results show spatially different responses of crop growth and nitrate leaching, proving how the cost-effectiveness of pollution control instruments is contingent upon the spatial heterogeneities of the problem. Copyright © 2014 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Tarnavsky, E.
2016-12-01
The water resources satisfaction index (WRSI) model is widely used in drought early warning and food security analyses, as well as in agro-meteorological risk management through weather index-based insurance. Key driving data for the model is provided from satellite-based rainfall estimates such as ARC2 and TAMSAT over Africa and CHIRPS globally. We evaluate the performance of these rainfall datasets for detecting onset and cessation of rainfall and estimating crop production conditions for the WRSI model. We also examine the sensitivity of the WRSI model to different satellite-based rainfall products over maize growing regions in Tanzania. Our study considers planting scenarios for short-, medium-, and long-growing cycle maize, and we apply these for 'regular' and drought-resistant maize, as well as with two different methods for defining the start of season (SOS). Simulated maize production estimates are compared against available reported production figures at the national and sub-national (province) levels. Strengths and weaknesses of the driving rainfall data, insights into the role of the SOS definition method, and phenology-based crop yield coefficient and crop yield reduction functions are discussed in the context of space-time drought characteristics. We propose a way forward for selecting skilled rainfall datasets and discuss their implication for crop production monitoring and the design and structure of weather index-based insurance products as risk transfer mechanisms implemented across scales for smallholder farmers to national programmes.
Quantifying yield gaps in wheat production in Russia
NASA Astrophysics Data System (ADS)
Schierhorn, Florian; Faramarzi, Monireh; Prishchepov, Alexander V.; Koch, Friedrich J.; Müller, Daniel
2014-08-01
Crop yields must increase substantially to meet the increasing demands for agricultural products. Crop yield increases are particularly important for Russia because low crop yields prevail across Russia’s widespread and fertile land resources. However, reliable data are lacking regarding the spatial distribution of potential yields in Russia, which can be used to determine yield gaps. We used a crop growth model to determine the yield potentials and yield gaps of winter and spring wheat at the provincial level across European Russia. We modeled the annual yield potentials from 1995 to 2006 with optimal nitrogen supplies for both rainfed and irrigated conditions. Overall, the results suggest yield gaps of 1.51-2.10 t ha-1, or 44-52% of the yield potential under rainfed conditions. Under irrigated conditions, yield gaps of 3.14-3.30 t ha-1, or 62-63% of the yield potential, were observed. However, recurring droughts cause large fluctuations in yield potentials under rainfed conditions, even when the nitrogen supply is optimal, particularly in the highly fertile black soil areas of southern European Russia. The highest yield gaps (up to 4 t ha-1) under irrigated conditions were detected in the steppe areas in southeastern European Russia along the border of Kazakhstan. Improving the nutrient and water supply and using crop breeds that are adapted to the frequent drought conditions are important for reducing yield gaps in European Russia. Our regional assessment helps inform policy and agricultural investors and prioritize research that aims to increase crop production in this important region for global agricultural markets.
Monitoring Crop Yield in USA Using a Satellite-Based Climate-Variability Impact Index
NASA Technical Reports Server (NTRS)
Zhang, Ping; Anderson, Bruce; Tan, Bin; Barlow, Mathew; Myneni, Ranga
2011-01-01
A quantitative index is applied to monitor crop growth and predict agricultural yield in continental USA. The Climate-Variability Impact Index (CVII), defined as the monthly contribution to overall anomalies in growth during a given year, is derived from 1-km MODIS Leaf Area Index. The growing-season integrated CVII can provide an estimate of the fractional change in overall growth during a given year. In turn these estimates can provide fine-scale and aggregated information on yield for various crops. Trained from historical records of crop production, a statistical model is used to produce crop yield during the growing season based upon the strong positive relationship between crop yield and the CVII. By examining the model prediction as a function of time, it is possible to determine when the in-season predictive capability plateaus and which months provide the greatest predictive capacity.
The impact of Global Warming on global crop yields due to changes in pest pressure
NASA Astrophysics Data System (ADS)
Battisti, D. S.; Tewksbury, J. J.; Deutsch, C. A.
2011-12-01
A billion people currently lack reliable access to sufficient food and almost half of the calories feeding these people come from just three crops: rice, maize, wheat. Insect pests are among the largest factors affecting the yield of these three crops, but models assessing the effects of global warming on crops rarely consider changes in insect pest pressure on crop yields. We use well-established relationships between temperature and insect physiology to project climate-driven changes in pest pressure, defined as integrated population metabolism, for the three major crops. By the middle of this century, under most scenarios, insect pest pressure is projected to increase by more than 50% in temperate areas, while increases in tropical regions will be more modest. Yield relationships indicate that the largest increases in insect pest pressure are likely to occur in areas where yield is greatest, suggesting increased strain on global food markets.
The important but weakening maize yield benefit of grain filling prolongation in the US Midwest.
Zhu, Peng; Jin, Zhenong; Zhuang, Qianlai; Ciais, Philippe; Bernacchi, Carl; Wang, Xuhui; Makowski, David; Lobell, David
2018-06-14
A better understanding of recent crop yield trends is necessary for improving the yield and maintaining food security. Several possible mechanisms have been investigated recently in order to explain the steady growth in maize yield over the US Corn-Belt, but a substantial fraction of the increasing trend remains elusive. In this study, trends in grain filling period (GFP) were identified and their relations with maize yield increase were further analyzed. By using satellite data from 2000 to 2015, an average lengthening of GFP of 0.37 days per year was found over the region, which probably results from variety renewal. Statistical analysis suggests that longer GFP accounted for roughly one-quarter (23%) of the yield increase trend by promoting kernel dry matter accumulation, yet had less yield benefit in hotter counties. Both official survey data and crop model simulations estimated a similar contribution of GFP trend to yield. If growing degree days that determines the GFP continues to prolong at the current rate for the next 50 years, yield reduction will be lessened with 25% and 18% longer GFP under Representative Concentration Pathway 2.6 (RCP 2.6) and RCP 6.0, respectively. However, this level of progress is insufficient to offset yield losses in future climates, because drought and heat stress during the GFP will become more prevalent and severe. This study highlights the need to devise multiple effective adaptation strategies to withstand the upcoming challenges in food security. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.
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...
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.
PERSPECTIVE: Climate change, biofuels, and global food security
NASA Astrophysics Data System (ADS)
Cassman, Kenneth G.
2007-03-01
There is a new urgency to improve the accuracy of predicting climate change impact on crop yields because the balance between food supply and demand is shifting abruptly from surplus to deficit. This reversal is being driven by a rapid rise in petroleum prices and, in response, a massive global expansion of biofuel production from maize, oilseed, and sugar crops. Soon the price of these commodities will be determined by their value as feedstock for biofuel rather than their importance as human food or livestock feed [1]. The expectation that petroleum prices will remain high and supportive government policies in several major crop producing countries are providing strong momentum for continued expansion of biofuel production capacity and the associated pressures on global food supply. Farmers in countries that account for a majority of the world's biofuel crop production will enjoy the promise of markedly higher commodity prices and incomesNote1. In contrast, urban and rural poor in food-importing countries will pay much higher prices for basic food staples and there will be less grain available for humanitarian aid. For example, the developing countries of Africa import about 10 MMt of maize each year; another 3 5 MMt of cereal grains are provided as humanitarian aid (figure 1). In a world where more than 800 million are already undernourished and the demand for crop commodities may soon exceed supply, alleviating hunger will no longer be solely a matter of poverty alleviation and more equitable food distribution, which has been the situation for the past thirty years. Instead, food security will also depend on accelerating the rate of gain in crop yields and food production capacity at both local and global scales. Maize imports and cereal donations as humanitarian aid to the developing countries of Africa Figure 1. Maize imports (yellow bar) and cereal donations as humanitarian aid to the developing countries of Africa, 2001 2003. MMT = million metric tons. Data source: faostat.fao.org/site/395/default.aspx. Given this situation, the question of whether global climate change will have a net positive, negative, or negligible impact on crop yields takes on a larger significance because additional hundreds of millions of people could be at risk of hunger and the window of opportunity for mounting an effective response is closing. To answer this question, Lobell and Field use an innovative empirical/geostatistical approach to estimate the impact of increased temperature since 1980 on crop yields—a period when global mean temperature increased ~0.4 °C [2]. For three major crops—maize, wheat, and barley—there was a significant negative response to increased temperature. For all six crops evaluated (also including rice, soybean, and sorghum), the net impact of climate trends on yield since 1980 was negative. While the approach used by Lobell and Field can be questioned on several pointsNote2, the body of their work represents an ambitious global assessment of recent climate impact on crop yields. Most noteworthy is their conclusion that: the combined effects of increased atmospheric CO2 concentration and climate trends have largely cancelled each other over the past two decades. They contrast their finding with the conclusion of the International Panel on Climate Change (IPCC) that CO2 benefits will exceed temperature-related yield reductions up to a 2 °C increase in mean temperature [3]. It should be noted, however, that the IPCC is coming out with a new assessment to be released in April 2007 (www.ipcc.ch/), and it remains to be seen if this conclusion still holds. The purpose here is not to support or challenge the conclusions of either Lobell and Field or the IPCC, but rather to highlight the fact that there are substantive differences between results obtained from geostatistical assessments based on recent climate trends and actual crop yields versus assessments based on results from controlled experiments in growth chambers, greenhouses, and field enclosures and crop modeling. And while there appears to be good agreement on the predicted impact of atmospheric CO2 enrichment on crop yields across a wide range of studies conducted using different approaches [4], there is less convincing evidence on the impact of warming temperatures. There are three reasons for greater uncertainty about temperature effects. First, it is logistically more difficult to control temperature at elevated levels in studies that allow crops to grow in an 'open-air' environment comparable to field-grown plants. The 'free-air carbon dioxide enrichment' (FACE) systems were specifically designed to avoid such problems for study of CO2 effects and appear to have been largely successful [4]. In contrast, growth chamber, greenhouse, and small-enclosure studies used for temperature-effect experiments have confounding effects associated with differences in humidity, air turbulence, and reduced light intensity that result from the need to more fully enclose experimental units with a transparent barrier to achieve adequate temperature control. Second, unlike CO2 effects, yield response to temperature is often discontinuous. In many crops, pollination fails if temperatures rise above a critical threshold, which can result in dramatic yield reductions due to very small changes in temperature. Also, because climate change is predicted to increase both average temperature and temperature variability, changes in both factors must be evaluated in experiments with realistic growth conditions to fully understand climate change impact on crop yields. Such experiments would require expensive infrastructure with creative new designs—studies that have yet to be conducted, in part due to lack of adequate funding. A third factor is the interactive effect of temperature and plant nitrogen (protein) content on respiration, which is poorly understood. In the absence of such studies, it is sobering to note that one long-term field study in which the effect of temperature on rice yield could be isolated from other factors documented a 15% decrease in yield for every 1 °C increase in mean temperature [5]. The magnitude of this decrease is considerably larger than predictions of yield decreases from higher temperature obtained from crop simulation models. Like the results of Lobell and Field [2], we see a discrepancy between estimates of the effects of warmer temperatures on crop yields based on the relationship between crop yields and temperature under field conditions versus those derived from modeling and experiments conducted under controlled conditions. As we make the historic transition from an extended period of surplus food production to one in which demand for staple crop commodities exceeds supply, there is a vital need to better understand the impact of warming temperatures on current and future crop yields. References [1] Council for Agricultural Science and Technology 2006 Convergence of agriculture and energy: Implications for Research and Policy CAST Commentary QTA 2006-3 (Ames, Iowa: CAST) (www.cast-science.org) [2] Lobell D B and Field C B 2007 Global scale climate-crop yield relationships and the impacts of recent warming Environ. Res. Lett. 2 014002 [3] Intergovernmental Panel on Climate Change, Working Group 2 Climate Change 2001 Impacts, Adaptation and Vulnerability IPCC Working Group 2, Third Assessment (New York: Cambridge University Press) [4] Tubiello F N et al 2006 Crop response to elevated CO2 and world food supply: A comment on 'Food for Thought...' by Long et al, Science 312:1918-1921, 2006 Eur. J. Agron. 26 215 23 [5] Peng S, Huang J, Sheehy J E, Laza R, Visperas R M, Zhong X, Centeno G S, Khush G and Cassman K G 2004 Rice yields decline with higher night temperature from global warming Proc. Natl Acad. Sci. 101 9971 5 Notes Note1 USA (40% of global maize, 56% of global maize exports), Brazil (33% of global sugar, 36% of global sugar exports), Indonesia and Malaysia (81% of global palm oil, 88% of global palm oil exports)—2005 data from FAOSTAT: faostat.fao.org/site/395/default.aspx. Note2 For example, the use of a 'global season' for calculating temperatures is problematic. In the case of soybean, a substantial portion of global soybean production occurs in the southern hemisphere, mostly in Brazil and Argentina, yet the global season for temperature was July August—a time when soybean is not grown in these countries. Likewise the global season for rice was January October, a period in which two consecutive rice crops are grown in tropical and subtropical irrigated systems of Asia—systems that account for a large portion of global rice production. Photo of Kenneth G Cassman Dr Cassman is Director of the Nebraska Center for Energy Science Research at the University of Nebraska and the Heuermann Professor of Agronomy. His work focuses on ensuring local and global food security while improving environmental quality in many of the world's most productive cropping systems. Previous positions include: research agronomist in Brazil, Egypt and the Philippines; faculty member at the University of California-Davis; division/department head at the International Rice Research Institute and the University of Nebraska. He received a PhD from the University of Hawaii's College of Tropical Agriculture (1979) and a BS in Biology from the University of California, San Diego (1975).
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.
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.
NASA Technical Reports Server (NTRS)
Cacas, Joseph; Glaser, John; Copenhaver, Kenneth; May, George; Stephens, Karen
2008-01-01
The United States Environmental Protection Agency (EPA) has declared that "significant benefits accrue to growers, the public, and the environment" from the use of transgenic pesticidal crops due to reductions in pesticide usage for crop pest management. Large increases in the global use of transgenic pesticidal crops has reduced the amounts of broad spectrum pesticides used to manage pest populations, improved yield and reduced the environmental impact of crop management. A significant threat to the continued use of this technology is the evolution of resistance in insect pest populations to the insecticidal Bt toxins expressed by the plants. Management of transgenic pesticidal crops with an emphasis on conservation of Bt toxicity in field populations of insect pests is important to the future of sustainable agriculture. A vital component of this transgenic pesticidal crop management is establishing the proof of concept basic understanding, situational awareness, and monitoring and decision support system tools for more than 133650 square kilometers (33 million acres) of bio-engineered corn and cotton for development of insect resistance . Early and recent joint NASA, US EPA and ITD remote imagery flights and ground based field experiments have provided very promising research results that will potentially address future requirements for crop management capabilities.
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
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
Remotely sensed vegetation indices for seasonal crop yields predictions in the Czech Republic
NASA Astrophysics Data System (ADS)
Hlavinka, Petr; Semerádová, Daniela; Balek, Jan; Bohovic, Roman; Žalud, Zdeněk; Trnka, Miroslav
2015-04-01
Remotely sensed vegetation indices by satellites are valuable tool for vegetation conditions assessment also in the case of field crops. This study is based on the use of NDVI (Normalized Difference Vegetation Index) and EVI (Enhanced Vegetation Index) derived from MODIS (Moderate Resolution Imaging Spectroradiometer) aboard Terra satellite. Data available from the year 2000 were analyzed and tested for seasonal yields predictions within selected districts of the Czech Republic (Central Europe). Namely the yields of spring barley, winter wheat and oilseed winter rape during the period from 2000 to 2014 were assessed. Observed yields from 14 districts (NUTS 4) were collected and thus 210 seasons were included. Selected districts differ considerably in their soil fertility and terrain configuration and represent transect across various agroclimatic conditions (from warm and dry to relative cool and wet regions). Two approaches were tested: 1) using of composite remotely sensed data (available in 16 day time step) provided by the USGS (https://lpdaac.usgs.gov/); 2) using daily remotely sensed data in combination with originally developed smoothing method. The yields were successfully predicted based on established regression models (remotely sensed data used as independent parameter). Besides others the impact of severe drought episodes within vegetation were identified and yield reductions at district level predicted (even before harvest). As a result the periods with the best relationship between remotely sensed data and yields were identified. The impact of drought conditions as well as normal or above normal yields of field crops could be predicted by proposed method within study region up to 30 days prior to the harvest. It could be concluded that remotely sensed vegetation conditions assessment should be important part of early warning systems focused on drought. Such information should be widely available for various users (decision makers, farmers, etc.) in order to improve planning, business strategies but also to target the drought relief in case of major drought event. This study was funded by project "Building up a multidisciplinary scientific team focused on drought" No. CZ.1.07/2.3.00/20.0248, project supported by Czech National Agency of Agricultural Research No. QJ1310123 "Crop modelling as a tool for increasing the production potential and food security of the Czech Republic under Climate Change".
NASA Astrophysics Data System (ADS)
Bartholomeus, Ruud; van den Eertwegh, Gé; Simons, Gijs
2015-04-01
Agricultural crop yields depend largely on the soil moisture conditions in the root zone. Drought but especially an excess of water in the root zone and herewith limited availability of soil oxygen reduces crop yield. With ongoing climate change, more prolonged dry periods alternate with more intensive rainfall events, which changes soil moisture dynamics. With unaltered water management practices, reduced crop yield due to both drought stress and waterlogging will increase. Therefore, both farmers and water management authorities need to be provided with opportunities to reduce risks of decreasing crop yields. In The Netherlands, agricultural production of crops represents a market exceeding 2 billion euros annually. Given the increased variability in meteorological conditions and the resulting larger variations in soil moisture contents, it is of large economic importance to provide farmers and water management authorities with tools to mitigate risks of reduced crop yield by anticipatory water management, both at field and at regional scale. We provide the development and the field application of a decision support system (DSS), which allows to optimize crop yield by timely anticipation on drought and waterlogging situations. By using this DSS, we will minimize plant water stress through automated drainage and irrigation management. In order to optimize soil moisture conditions for crop growth, the interacting processes in the soil-plant-atmosphere system need to be considered explicitly. Our study comprises both the set-up and application of the DSS on a pilot plot in The Netherlands, in order to evaluate its implementation into daily agricultural practice. The DSS focusses on anticipatory water management at the field scale, i.e. the unit scale of interest to a farmer. We combine parallel field measurements ('observe'), process-based model simulations ('predict'), and the novel Climate Adaptive Drainage (CAD) system ('adjust') to optimize soil moisture conditions. CAD is used both for controlled drainage practices and for sub-irrigation. The DSS has a core of the plot-scale SWAP model (soil-water-atmosphere-plant), extended with a process-based module for the simulation of oxygen stress for plant roots. This module involves macro-scale and micro-scale gas diffusion, as well as the plant physiological demand of oxygen, to simulate transpiration reduction due to limited oxygen availability. Continuous measurements of soil moisture content, groundwater level, and drainage level are used to calibrate the SWAP model each day. This leads to an optimal reproduction of the actual soil moisture conditions by data assimilation in the first step in the DSS process. During the next step, near-future (+10 days) soil moisture conditions and drought and oxygen stress are predicted using weather forecasts. Finally, optimal drainage levels to minimize stress are simulated, which can be established by CAD. Linkage to a grid-based hydrological simulation model (SPHY) facilitates studying the spatial dynamics of soil moisture and associated implications for management at the regional scale. Thus, by using local-scale measurements, process-based models and weather forecasts to anticipate on near-future conditions, not only field-scale water management but also regional surface water management can be optimized both in space and time.
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...
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...
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...
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...
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...
Grab, Heather; Blitzer, Eleanor J.; Danforth, Bryan; Loeb, Greg; Poveda, Katja
2017-01-01
One of the greatest challenges in sustainable agricultural production is managing ecosystem services, such as pollination, in ways that maximize crop yields. Most efforts to increase services by wild pollinators focus on management of natural habitats surrounding farms or non-crop habitats within farms. However, mass flowering crops create resource pulses that may be important determinants of pollinator dynamics. Mass bloom attracts pollinators and it is unclear how this affects the pollination and yields of other co-blooming crops. We investigated the effects of mass flowering apple on the pollinator community and yield of co-blooming strawberry on farms spanning a gradient in cover of apple orchards in the landscape. The effect of mass flowering apple on strawberry was dependent on the stage of apple bloom. During early and peak apple bloom, pollinator abundance and yield were reduced in landscapes with high cover of apple orchards. Following peak apple bloom, pollinator abundance was greater on farms with high apple cover and corresponded with increased yields on these farms. Spatial and temporal overlap between mass flowering and co-blooming crops alters the strength and direction of these dynamics and suggests that yields can be optimized by designing agricultural systems that avoid competition while maximizing facilitation. PMID:28345653
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.
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.
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.
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.
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...
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
LaMondia, J.A.
2006-01-01
Soil-incorporated rotation/green manure crops were evaluated for management of potato early dying caused by Verticillium dahliae and Pratylenchus penetrans. After two years of rotation/green manure and a subsequent potato crop, P. penetrans numbers were less after ‘Saia’ oat/‘Polynema’ marigold, ‘Triple S’ sorghum-sudangrass, or ‘Garry’ oat than ‘Superior’ potato or ‘Humus’ rapeseed. The area under the disease progress curve (AUDPC) for early dying was lowest after Saia oat/marigold, and tuber yields were greater than continuous potato after all crops except sorghum-sudangrass. Saia oat/marigold crops resulted in the greatest tuber yields. After one year of rotation/green manure, a marigold crop increased tuber yields and reduced AUDPC and P. penetrans. In the second potato crop after a single year of rotation, plots previously planted to marigolds had reduced P. penetrans densities and AUDPC and increased tuber yield. Rapeseed supported more P. penetrans than potato, but had greater yields. After two years of rotation/green manure crops and a subsequent potato crop, continuous potato had the highest AUDPC and lowest tuber weight. Rotation with Saia oats (2 yr) and Rudbeckia hirta (1 yr) reduced P. penetrans and increased tuber yields. AUDPC was lowest after R. hirta. Two years of sorghum-sudangrass did not affect P. penetrans, tuber yield or AUDPC. These results demonstrate that P. penetrans may be reduced by one or two years of rotation to non-host or antagonistic plants such as Saia oat, Polynema marigold, or R. hirta and that nematode control may reduce the severity of potato early dying. PMID:19259461
Crop yield response to climate change varies with crop spatial distribution pattern
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
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.
Reducing greenhouse gas emissions, water use, and grain arsenic levels in rice systems.
Linquist, Bruce A; Anders, Merle M; Adviento-Borbe, Maria Arlene A; Chaney, Rufus L; Nalley, L Lanier; da Rosa, Eliete F F; van Kessel, Chris
2015-01-01
Agriculture is faced with the challenge of providing healthy food for a growing population at minimal environmental cost. Rice (Oryza sativa), the staple crop for the largest number of people on earth, is grown under flooded soil conditions and uses more water and has higher greenhouse gas (GHG) emissions than most crops. The objective of this study was to test the hypothesis that alternate wetting and drying (AWD--flooding the soil and then allowing to dry down before being reflooded) water management practices will maintain grain yields and concurrently reduce water use, greenhouse gas emissions and arsenic (As) levels in rice. Various treatments ranging in frequency and duration of AWD practices were evaluated at three locations over 2 years. Relative to the flooded control treatment and depending on the AWD treatment, yields were reduced by <1-13%; water-use efficiency was improved by 18-63%, global warming potential (GWP of CH4 and N2 O emissions) reduced by 45-90%, and grain As concentrations reduced by up to 64%. In general, as the severity of AWD increased by allowing the soil to dry out more between flood events, yields declined while the other benefits increased. The reduction in GWP was mostly attributed to a reduction in CH4 emissions as changes in N2 O emissions were minimal among treatments. When AWD was practiced early in the growing season followed by flooding for remainder of season, similar yields as the flooded control were obtained but reduced water use (18%), GWP (45%) and yield-scaled GWP (45%); although grain As concentrations were similar or higher. This highlights that multiple environmental benefits can be realized without sacrificing yield but there may be trade-offs to consider. Importantly, adoption of these practices will require that they are economically attractive and can be adapted to field scales. © 2014 John Wiley & Sons Ltd.
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 ...
NASA Astrophysics Data System (ADS)
Arunachalam, M. S.; Obili, Manjula; Srimurali, M.
2016-07-01
Long-term variation of Surface Ozone, NO2, Temperature, Relative humidity and crop yield datasets over thirteen districts of Andhra Pradesh(AP) has been studied with the help of OMI, MODIS, AIRS, ERA-Interim re-analysis and Directorate of Economics and Statistics (DES) of AP. Inter comparison of crop yield loss estimates according to exposure metrics such as AOT40 (accumulated ozone exposure over a threshold of 40) and non-linear variation of surface temperature for twenty and eighteen varieties of two major crop growing seasons namely, kharif (April-September) and rabi (October-March), respectively has been made. Study is carried to establish a new crop-yield-exposure relationship for different crop cultivars of AP. Both ozone and temperature are showing a correlation coefficient of 0.66 and 0.87 with relative humidity; and 0.72 and 0.80 with NO2. Alleviation of high surface ozone results in high food security and improves the economy thereby reduces the induced warming of the troposphere caused by ozone. Keywords: Surface Ozone, NO2, Temperature, Relative humidity, Crop yield, AOT 40.
Mapping Crop Yield and Sow Date Using High Resolution Imagery
NASA Astrophysics Data System (ADS)
Royal, K.
2015-12-01
Keitasha Royal, Meha Jain, Ph.D., David Lobell, Ph.D Mapping Crop Yield and Sow Date Using High Resolution ImageryThe use of satellite imagery in agriculture is becoming increasingly more significant and valuable. Due to the emergence of new satellites, such as Skybox, these satellites provide higher resolution imagery (e.g 1m) therefore improving the ability to map smallholder agriculture. For the smallholder farm dominated area of northern India, Skybox high-resolution satellite imagery can aid in understanding how to improve farm yields. In particular, we are interested in mapping winter wheat in India, as this region produces approximately 80% of the country's wheat crop, which is important given that wheat is a staple crop that provides approximately 20% of household calories. In northeast India, the combination of increased heat stress, limited irrigation access, and the difficulty for farmers to access advanced farming technologies results in farmers only producing about 50% of their potential crop yield. The use of satellite imagery can aid in understanding wheat yields through time and help identify ways to increase crop yields in the wheat belt of India. To translate Skybox satellite data into meaningful information about wheat fields, we examine vegetation indices, such as the normalized difference vegetation index (NDVI), to measure the "greenness" of plants to help determine the health of the crops. We test our ability to predict crop characteristics, like sow date and yield, using vegetation indices of 59 fields for which we have field data in Bihar, India.
Tropical rotation crops influence nematode densities and vegetable yields.
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 = 0.05) following sorghum-sudangrass than after any of the other treatments except fallow. Yield of eggplant was greater (P = 0.05) following castor, sesame, or American jointvetch than following okra or fallow. Several of the rotation crops evaluated here may be useful for managing nematodes in the field and for improving yields of subsequent vegetable crops.
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.
Ozone phytotoxicity evaluation and prediction of crops production in tropical regions
NASA Astrophysics Data System (ADS)
Mohammed, Nurul Izma; Ramli, Nor Azam; Yahya, Ahmad Shukri
2013-04-01
Increasing ozone concentration in the atmosphere can threaten food security due to its effects on crop production. Since the 1980s, ozone has been believed to be the most damaging air pollutant to crops. In Malaysia, there is no index to indicate the reduction of crops due to the exposure of ozone. Therefore, this study aimed to identify the accumulated exposure over a threshold of X ppb (AOTX) indexes in assessing crop reduction in Malaysia. In European countries, crop response to ozone exposure is mostly expressed as AOT40. This study was designed to evaluate and predict crop reduction in tropical regions and in particular, the Malaysian climate, by adopting the AOT40 index method and modifying it based on Malaysian air quality and crop data. Nine AOTX indexes (AOT0, AOT5, AOT10, AOT15, AOT20, AOT25, AOT30, AOT40, and AOT50) were analyzed, crop responses tested and reduction in crops predicted. The results showed that the AOT50 resulted in the highest reduction in crops and the highest R2 value between the AOT50 and the crops reduction from the linear regression analysis. Hence, this study suggests that the AOT50 index is the most suitable index to estimate the potential ozone impact on crops in tropical regions. The result showed that the critical level for AOT50 index if the estimated crop reduction is 5% was 1336 ppb h. Additionally, the results indicated that the AOT40 index in Malaysia gave a minimum percentage of 6% crop reduction; as contrasted with the European guideline of 5% (due to differences in the climate e.g., average amount of sunshine).
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.
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.
Briefing Materials for Technical Presentations, Volume B: The LACIE Symposium
NASA Technical Reports Server (NTRS)
1978-01-01
Tables, charts, and LACIE segments are used to demonstrate the accuracy of estimated crop conditions and yield from 1974 to 1976, and to demonstrate the benefits of meteorological and LANDSAT data. Developments in data acquisition, sampling, and reduction are reviewed. The USDA application test system is highlighted with emphasis on user requirements, technology transfer, data base design, and cost data models for data base operation and management.
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;
2017-01-01
Crop models are increasingly used to simulate crop yields at the global scale, but so far there is no general framework on how to assess model performance. Here we evaluate the simulation results of 14 global gridded crop modeling groups that have contributed historic crop yield simulations for maize, wheat, rice and soybean to the Global Gridded Crop Model Intercomparison (GGCMI) of the Agricultural Model Intercomparison and Improvement Project (AgMIP). Simulation results are compared to reference data at global, national and grid cell scales and we evaluate model performance with respect to time series correlation, spatial correlation and mean bias. We find that global gridded crop models (GGCMs) show mixed skill in reproducing time series correlations or spatial patterns at the different spatial scales. Generally, maize, wheat and soybean simulations of many GGCMs are capable of reproducing larger parts of observed temporal variability (time series correlation coefficients (r) of up to 0.888 for maize, 0.673 for wheat and 0.643 for soybean at the global scale) but rice yield variability cannot be well reproduced by most models. Yield variability can be well reproduced for most major producing countries by many GGCMs and for all countries by at least some. A comparison with gridded yield data and a statistical analysis of the effects of weather variability on yield variability shows that the ensemble of GGCMs can explain more of the yield variability than an ensemble of regression models for maize and soybean, but not for wheat and rice. We identify future research needs in global gridded crop modeling and for all individual crop modeling groups. In the absence of a purely observation-based benchmark for model evaluation, we propose that the best performing crop model per crop and region establishes the benchmark for all others, and modelers are encouraged to investigate how crop model performance can be increased. We make our evaluation system accessible to all crop modelers so that other modeling groups can also test their model performance against the reference data and the GGCMI benchmark.
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
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
NASA Technical Reports Server (NTRS)
Gruener, J. E.; Ming, Douglas W.; Galindo, C., Jr.; Henderson, K. E.; Golden, D. C.
2007-01-01
The National Aeronautics and Space Administration (NASA) has developed a zeolite-based synthetic substrate, termed zeoponics. The zeoponic substrate (consisting of NH4(-) and K-exchanged clinoptilolite, synthetic apatite, and dolomite) provides all of the plant-essential nutrients through mineral dissolution and ion exchange, with only the addition of water. Previous studies have shown high productivity of wheat in zeoponic substrates; however, no experiments have been conducted on other crops. The objective of this study was to determine the productivity and nutrient uptake of radish (Raphanus sativus L.) grown in zeoponic substrates with three successive crops in the same substrate. Radish was chosen because of its sensitivities to NH4(+). Average fresh weights of edible roots were similar for radish grown in zeoponic substrates watered with deionized H2O (10.97 g/plant) and in potting mix control substrate irrigated with nutrient solution (10.92 g/plant). Average fresh weight production of edible roots for radish grown in same zeoponic substrate increased in yield over time with the lowest yield in the first crop (7.10 g/plant) and highest in the third crop (13.90 g/plant). The Ca plant tissue levels in radishes (1.8-2.9 wt. %) grown in zeoponic substrates are lower than the suggested sufficient range of 3.0-4.5 wt. % Ca; however, the Ca level is highest (2.9 wt. %) in radishes grown in the third crop in the same zeoponic substrates. The higher radish yield in the third crop was attributed to a reduction in an NH4(-) induced Ca deficiency that has been previously described for wheat grown in zeoponic substrates. The P levels in plant tissues of radish grown in the zeoponic substrates ranged from 0.94-1.15 wt. %; which is slightly higher than the sufficient levels of 0.3-0.7 wt. %. With the exception of Ca and P, other macronutrient and micronutrient levels in radish grown in zeoponic substrates were well within the recommended sufficient ranges. After three successive crops of radish growth, the zeoponic substrates had 52% of the original NH4(-)N and 78% of the original K remaining on zeolite exchange sites. Zeoponic substrates are capable of long-term productivity of radishes for space.
Haviland, David R; Beede, Robert H; Daane, Kent M
2015-12-01
Ferrisia gilli Gullan (Hemiptera: Pseudococcidae) is a new pest in California pistachios, Pistacea vera L. We conducted a 3-yr field study to determine the type and amount of damage caused by F. gilli. Using pesticides, we established gradients of F. gilli densities in a commercial pistachio orchard near Tipton, CA, from 2005 to 2007. Each year, mealybug densities on pistachio clusters were recorded from May through September and cumulative mealybug-days were determined. At harvest time, nut yield per tree (5% dried weight) was determined, and subsamples of nuts were evaluated for market quality. Linear regression analysis of cumulative mealybug-days against fruit yield and nut quality measurements showed no relationships in 2005 and 2006, when mealybug densities were moderate. However, in 2007, when mealybug densities were very high, there was a negative correlation with yield (for every 1,000 mealybug-days, there was a decrease in total dry weight per tree of 0.105 kg) and percentage of split unstained nuts (for every 1,000 mealybug-days, there was a decrease in the percentage of split unstained of 0.560%), and a positive correlation between the percentage of closed kernel and closed blank nuts (for every 1,000 mealybug-days, there is an increase in the percentage of closed kernel and closed blank of 0.176 and 0.283%, respectively). The data were used to determine economic injury levels, showing that for each mealybug per cluster in May there was a 4.73% reduction in crop value associated with quality and a 0.866 kg reduction in yield per tree (4.75%). © The Authors 2015. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Harsant, Jeffrey; Pavlovic, Lazar; Chiu, Greta; Sultmanis, Stefanie; Sage, Tammy L.
2013-01-01
The effect of high temperatures on harvest index (HI) and morphological components that contribute to HI was investigated in two lines (Bd21 and Bd21-3) of Brachypodium distachyon, a C3 grass recognized as a tractable plant, to address critical issues associated with enhancing cereal crop yields in the presence of global climate change. The results demonstrated that temperatures ≥32 °C eliminated HI. Reductions in yield at 32 °C were due primarily to declines in pollen viability, retention of pollen in anthers, and pollen germination, while abortion of microspores by the uninucleate stage that was correlated with abnormal tapetal development resulted in yield failure at 36 °C. Increasing temperatures from 24 to 32 °C resulted in reductions in tiller numbers but had no impact on axillary branch numbers per tiller. Grain developed at 24 and 28 °C primarily in tiller spikes, although spikes on axillary branches also formed grain. Grain quantity decreased in tiller spikes but increased in axillary branch spikes as temperatures rose from 24 to 28 °C. Differential patterns of axillary branching and floret development within spikelets between Bd21 and Bd21-3 resulted in higher grain yield in axillary branches of Bd21-3 at 28 °C. The response of male reproductive development and tiller branching patterns in B. distachyon to increasing temperatures mirrors that in other cereal crops, providing support for the use of this C3 grass in assessing the molecular control of HI in the presence of global warming. PMID:23771979
Ozone and sulfur dioxide effects on three tall fescue cultivars
DOE Office of Scientific and Technical Information (OSTI.GOV)
Flagler, R.B.; Youngner, V.B.
Although many reports have been published concerning differential susceptibility of various crops and/or cultivars to air pollutants, most have used foliar injury instead of the marketable yield as the factor that determined susceptibility for the crop. In an examination of screening in terms of marketable yield, three cultivars of tall fescue (Festuca arundinacea Schreb.), 'Alta,' 'Fawn,' and 'Kentucky 31,' were exposed to 0-0.40 ppm O/sub 3/ or 0-0.50 ppm SO/sub 2/ 6 h/d, once a week, for 7 and 9 weeks, respectively. Experimental design was a randomized complete block with three replications. Statistical analysis was by standard analysis of variancemore » and regression techniques. Three variables were analyzed: top dry weight (yield), tiller number, and weight per tiller. Ozone had a significant effect on all three variables. Significant linear decreases in yield and weight per tiller occurred with increasing O/sub 3/ concentrations. Linear regressions of these variables on O/sub 3/ concentration produced significantly different regression coefficients. The coefficient for Kentucky 31 was significantly greater than Alta or Fawn, which did not differ from each other. This indicated that Kentucky 31 was more susceptible to O/sub 3/ than either of the other cultivars. Percent reductions in dry weight for the three cultivars at highest O/sub 3/ level were 35, 44, and 53%, respectively, for Fawn, Alta, and Kentucky 31. For weight per tiller, Kentucky 31 had a higher percent reduction than the other cultivars (59 vs. 46 and 44%). Tiller number was generally increased by O/sub 3/, but this variable was not useful for determining differential susceptibility to the pollutant. Sulfur dioxide treatments produced no significant effects on any of the variables analyzed.« less
Abid, Muhammad; Tian, Zhongwei; Ata-Ul-Karim, Syed Tahir; Cui, Yakun; Liu, Yang; Zahoor, Rizwan; Jiang, Dong; Dai, Tingbo
2016-01-01
Efficient nitrogen (N) nutrition has the potential to alleviate drought stress in crops by maintaining metabolic activities even at low tissue water potential. This study was aimed to understand the potential of N to minimize the effects of drought stress applied/occur during tillering (Feekes stage 2) and jointing (Feekes stage 6) growth stages of wheat by observing the regulations and limitations of physiological activities, crop growth rate during drought periods as well as final grain yields at maturity. In present study, pot cultured plants of a wheat cultivar Yangmai-16 were exposed to three water levels [severe stress at 35-40% field capacity (FC), moderate stress at 55-60% FC and well-watered at 75-80% FC] under two N rates (0.24 g and 0.16 g/kg soil). The results showed that the plants under severe drought stress accompanied by low N exhibited highly downregulated photosynthesis, and chlorophyll (Chl) fluorescence during the drought stress periods, and showed an accelerated grain filling rate with shortened grain filling duration (GFD) at post-anthesis, and reduced grain yields. Severe drought-stressed plants especially at jointing, exhibited lower Chl and Rubisco contents, lower efficiency of photosystem II and greater grain yield reductions. In contrast, drought-stressed plants under higher N showed tolerance to drought stress by maintaining higher leaf water potential, Chl and Rubisco content; lower lipid peroxidation associated with higher superoxide dismutase and ascorbate peroxidase activities during drought periods. The plants under higher N showed delayed senescence, increased GFD and lower grain yield reductions. The results of the study suggested that higher N nutrition contributed to drought tolerance in wheat by maintaining higher photosynthetic activities and antioxidative defense system during vegetative growth periods.
Irrigation offsets wheat yield reductions from warming temperatures
NASA Astrophysics Data System (ADS)
Tack, Jesse; Barkley, Andrew; Hendricks, Nathan
2017-11-01
Temperature increases due to climate change are expected to cause substantial reductions in global wheat yields. However, uncertainty remains regarding the potential role for irrigation as an adaptation strategy to offset heat impacts. Here we utilize over 7000 observations spanning eleven Kansas field-trial locations, 180 varieties, and 29 years to show that irrigation significantly reduces the negative impact of warming temperatures on winter wheat yields. Dryland wheat yields are estimated to decrease about eight percent for every one-degree Celsius increase in temperature, yet irrigation completely offsets this negative impact in our sample. As in previous studies, we find that important interactions exist between heat stress and precipitation for dryland production. Here, uniquely, we observe both dryland and irrigated trials side-by-side at the same locations and find that precipitation does not provide the same reduction in heat stress as irrigation. This is likely to be because the timing, intensity, and volume of water applications influence wheat yields, so the ability to irrigate—rather than relying on rainfall alone—has a stronger influence on heat stress. We find evidence of extensive differences of water-deficit stress impacts across varieties. This provides some evidence of the potential for adapting to hotter and drier climate conditions using optimal variety selection. Overall, our results highlight the critical role of water management for future global food security. Water scarcity not only reduces crop yields through water-deficit stress, but also amplifies the negative effects of warming temperatures.
Assessment of potential greenhouse gas mitigation from changes to crop root mass and architecture
DOE Office of Scientific and Technical Information (OSTI.GOV)
Paustian, Keith; Campbell, Nell; Dorich, Chris
Reducing (and eventually reversing) the increase in greenhouse gases (GHGs) in the atmosphere due to human activities, and thus reducing the extent and severity of anthropogenic climate change, is one of the great challenges facing humanity. While most of the man-caused increase in GHGs has been due to fossil fuel use, land use (including agriculture) currently accounts for about 25% of total GHG emissions and thus there is a need to include emission reductions from the land use sector as part of an effective climate change mitigation strategy. In addition, analyses included in the recent IPCC 5th Climate Change Assessmentmore » report suggests that it may not be possible to achieve large enough emissions reductions in the energy, transport and industrial sectors alone to stabilize GHG concentrations at a level commensurate with a less than 2°C global average temperature increase, without the help of a substantial CO 2 sink (i.e., atmospheric CO 2 removal) from the land use sector. One of the potential carbon sinks that could contribute to this goal is increasing C storage in soil organic matter on managed lands. This report details a preliminary scoping analysis, to assess the potential agricultural area in the US – where appropriate soil, climate and land use conditions exist – to determine the land area on which ‘improved root phenotype’ crops could be deployed and to evaluate the potential long-term soil C storage, given a set of ‘bounding scenarios’ of increased crop root input and/or rooting depth for major crop species (e.g., row crops (corn, sorghum, soybeans), small grains (wheat, barley, oats), and hay and pasture perennial forages). The enhanced root phenotype scenarios assumed 25, 50 and 100% increase in total root C inputs, in combination with five levels of modifying crop root distributions (i.e., no change and four scenarios with increasing downward shift in root distributions). We also analyzed impacts of greater root production on the soil-crop nitrogen balance, from the standpoint of increased need for additional N inputs and consequences for increased N 2O flux, as well as potential impacts if more and deeper roots contributed to reduced N leaching. In the enhanced root phenotype scenarios, the implicit assumption was that increases in overall plant production could be achieved (e.g., through increased CO 2 assimilation, greater growth efficiency) without reducing the harvested yield – that is, we did not include potential leakage and land substitution effects from potential decreased crop yield in the analysis.« less
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.
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
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.
Jaggard, Keith W; Qi, Aiming; Ober, Eric S
2010-09-27
By 2050, the world population is likely to be 9.1 billion, the CO(2) concentration 550 ppm, the ozone concentration 60 ppb and the climate warmer by ca 2 degrees C. In these conditions, what contribution can increased crop yield make to feeding the world? CO(2) enrichment is likely to increase yields of most crops by approximately 13 per cent but leave yields of C4 crops unchanged. It will tend to reduce water consumption by all crops, but this effect will be approximately cancelled out by the effect of the increased temperature on evaporation rates. In many places increased temperature will provide opportunities to manipulate agronomy to improve crop performance. Ozone concentration increases will decrease yields by 5 per cent or more. Plant breeders will probably be able to increase yields considerably in the CO(2)-enriched environment of the future, and most weeds and airborne pests and diseases should remain controllable, so long as policy changes do not remove too many types of crop-protection chemicals. However, soil-borne pathogens are likely to be an increasing problem when warmer weather will increase their multiplication rates; control is likely to need a transgenic approach to breeding for resistance. There is a large gap between achievable yields and those delivered by farmers, even in the most efficient agricultural systems. A gap is inevitable, but there are large differences between farmers, even between those who have used the same resources. If this gap is closed and accompanied by improvements in potential yields then there is a good prospect that crop production will increase by approximately 50 per cent or more by 2050 without extra land. However, the demands for land to produce bio-energy have not been factored into these calculations.
Drought effects on US maize and soybean production: spatiotemporal patterns and historical changes
NASA Astrophysics Data System (ADS)
Zipper, Samuel C.; Qiu, Jiangxiao; Kucharik, Christopher J.
2016-09-01
Maximizing agricultural production on existing cropland is one pillar of meeting future global food security needs. To close crop yield gaps, it is critical to understand how climate extremes such as drought impact yield. Here, we use gridded, daily meteorological data and county-level annual yield data to quantify meteorological drought sensitivity of US maize and soybean production from 1958 to 2007. Meteorological drought negatively affects crop yield over most US crop-producing areas, and yield is most sensitive to short-term (1-3 month) droughts during critical development periods from July to August. While meteorological drought is associated with 13% of overall yield variability, substantial spatial variability in drought effects and sensitivity exists, with central and southeastern US becoming increasingly sensitive to drought over time. Our study illustrates fine-scale spatiotemporal patterns of drought effects, highlighting where variability in crop production is most strongly associated with drought, and suggests that management strategies that buffer against short-term water stress may be most effective at sustaining long-term crop productivity.
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.
'Omics' techniques for identifying flooding-response mechanisms in soybean.
Komatsu, Setsuko; Shirasaka, Naoki; Sakata, Katsumi
2013-11-20
Plant growth and productivity are adversely influenced by various environmental stresses, which often lead to reduced seedling growth and decreased crop yields. Plants respond to stressful conditions through changes in 'omics' profiles, including transcriptomics, proteomics, and metabolomics. Linking plant phenotype to gene expression patterns, protein abundance, and metabolite accumulation is one of the main challenges for improving agricultural production. 'Omics' approaches may shed insight into the mechanisms that function in soybean in response to environmental stresses, particularly flooding by frequent rain, which occurs worldwide due to changes in global climate. Flooding causes significant reductions in the growth and yield of several crops, especially soybean. The application of 'omics' techniques may facilitate the development of flood-tolerant cultivars of soybean. In this review, the use of 'omics' techniques towards understanding the flooding-responsive mechanisms of soybeans is discussed, as the findings from these studies are expected to have applications in both breeding and agronomy. This article is part of a Special Issue entitled: Translational Plant Proteomics. Copyright © 2012 Elsevier B.V. All rights reserved.
Testing the responses of four wheat crop models to heat stress at anthesis and grain filling.
Liu, Bing; Asseng, Senthold; Liu, Leilei; Tang, Liang; Cao, Weixing; Zhu, Yan
2016-05-01
Higher temperatures caused by future climate change will bring more frequent heat stress events and pose an increasing risk to global wheat production. Crop models have been widely used to simulate future crop productivity but are rarely tested with observed heat stress experimental datasets. Four wheat models (DSSAT-CERES-Wheat, DSSAT-Nwheat, APSIM-Wheat, and WheatGrow) were evaluated with 4 years of environment-controlled phytotron experimental datasets with two wheat cultivars under heat stress at anthesis and grain filling stages. Heat stress at anthesis reduced observed grain numbers per unit area and individual grain size, while heat stress during grain filling mainly decreased the size of the individual grains. The observed impact of heat stress on grain filling duration, total aboveground biomass, grain yield, and grain protein concentration (GPC) varied depending on cultivar and accumulated heat stress. For every unit increase of heat degree days (HDD, degree days over 30 °C), grain filling duration was reduced by 0.30-0.60%, total aboveground biomass was reduced by 0.37-0.43%, and grain yield was reduced by 1.0-1.6%, but GPC was increased by 0.50% for cv Yangmai16 and 0.80% for cv Xumai30. The tested crop simulation models could reproduce some of the observed reductions in grain filling duration, final total aboveground biomass, and grain yield, as well as the observed increase in GPC due to heat stress. Most of the crop models tended to reproduce heat stress impacts better during grain filling than at anthesis. Some of the tested models require improvements in the response to heat stress during grain filling, but all models need improvements in simulating heat stress effects on grain set during anthesis. The observed significant genetic variability in the response of wheat to heat stress needs to be considered through cultivar parameters in future simulation studies. © 2016 John Wiley & Sons Ltd.
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...
Efficient Management of Fruit Pests by Pheromone Nanogels
Bhagat, Deepa; Samanta, Suman K.; Bhattacharya, Santanu
2013-01-01
Environment-friendly management of fruit flies involving pheromones is useful in reducing the undesirable pest populations responsible for decreasing the yield and the crop quality. A nanogel has been prepared from a pheromone, methyl eugenol (ME) using a low-molecular mass gelator. This was very stable at open ambient conditions and slowed down the evaporation of pheromone significantly. This enabled its easy handling and transportation without refrigeration, and reduction in the frequency of pheromone recharging in the orchard. Notably the involvement of the nano-gelled pheromone brought about an effective management of Bactrocera dorsalis, a prevalent harmful pest for a number of fruits including guava. Thus a simple, practical and low cost green chemical approach is developed that has a significant potential for crop protection, long lasting residual activity, excellent efficacy and favorable safety profiles. This makes the present invention well-suited for pest management in a variety of crops. PMID:23416455
NASA Astrophysics Data System (ADS)
Saidaliyeva, Zarina; Davenport, Ian; Nobakht, Mohamad; White, Kevin; Shahgedanova, Maria
2017-04-01
Kazakhstan is a major producer of grain. Large scale grain production dominates in the north, making Kazakhstan one of the largest exporters of grain in the world. Agricultural production accounts for 9% of the national GDP, providing 25% of national employment. The south relies on grain production from household farms for subsistence, and has low resilience, so is vulnerable to reductions in output. Yields in the south depend on snowmelt and glacier runoff. The major limit to production is water supply, which is affected by glacier retreat and frequent droughts. Climate change is likely to impact all climate drivers negatively, leading to a decrease in crop yield, which will impact Kazakhstan and countries dependent on importing its produce. This work makes initial steps in modelling the impact of climate change on crop yield, by identifying the links between snowfall, soil moisture and agricultural productivity. Several remotely-sensed data sources are being used. The availability of snowmelt water over the period 2010-2014 is estimated by extracting the annual maximum snow water equivalent (SWE) from the Globsnow dataset, which assimilates satellite microwave observations with field observations to produce a spatial map. Soil moisture over the period 2010-2016 is provided by the ESA Soil Moisture and Ocean Salinity (SMOS) mission. Vegetation density is approximated by the Normalised Difference Vegetation Index (NDVI) produced from NASA's MODIS instruments. Statistical information on crop yields is provided by the Ministry of National Economy of the Republic of Kazakhstan Committee on Statistics. Demonstrating the link between snowmelt yield and agricultural productivity depends on showing the impact of snow mass during winter on remotely-sensed soil moisture, the link between soil moisture and vegetation density, and finally the link between vegetation density and crop yield. Soil moisture maps were extracted from SMOS observations, and resampled onto a 40km x 40km grid, and analysed to produce monthly averages. The monthly maximum snow water equivalent estimates for March were resampled onto the same grid, to approximate the total snow contributing to snowmelt. The MODIS MOD13A2 1km 16-day NDVI product was resampled onto the same 40km grid, and aggregated into 32-day averages. Annual crop yield is available in terms of kg of yield per hectare for each region in Kazakhstan between 2004 and 2015. To show the connection between the snowmelt and soil moisture, the cells within the snow and soil moisture grids were compared to calculate correlation. Data were aggregated per region. Regions in northern Kazakhstan showed the strongest correlations, because more of the soil water supply is derived from snowmelt than rain, and the southern regions showed poor correlation because of the greater influence of rainfall and irrigation. Correlations between soil moisture and vegetation density, and crop yield are ongoing, and results will be presented. It is envisaged that this research will assist the Kazakh farming community, providing real-time soil moisture data from SMOS.
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 = 0.05) numbers of M. arenaria juveniles on most sampling dates. Soybean, horsebean, and sesame rotations were less effective in suppressing nematodes. Yield of squash was greater (P = 0.05) following castor, cotton, velvetbean, and crotalaria than following peanut. Compared to the peanut rotation, yield of eggplant was enhanced (P = 0.10) following castor, crotalaria, hairy indigo, American jointvetch, and sorghum-sudangrass. Several of these rotation crops may provide a means for depressing M. arenaria population densities on a short-term basis to enhance yields in a subsequent susceptible vegetable crop.
Manipulating microRNAs for improved biomass and biofuels from plant feedstocks.
Trumbo, Jennifer Lynn; Zhang, Baohong; Stewart, Charles Neal
2015-04-01
Petroleum-based fuels are nonrenewable and unsustainable. Renewable sources of energy, such as lignocellulosic biofuels and plant metabolite-based drop-in fuels, can offset fossil fuel use and reverse environmental degradation through carbon sequestration. Despite these benefits, the lignocellulosic biofuels industry still faces many challenges, including the availability of economically viable crop plants. Cell wall recalcitrance is a major economic barrier for lignocellulosic biofuels production from biomass crops. Sustainability and biomass yield are two additional, yet interrelated, foci for biomass crop improvement. Many scientists are searching for solutions to these problems within biomass crop genomes. MicroRNAs (miRNAs) are involved in almost all biological and metabolic process in plants including plant development, cell wall biosynthesis and plant stress responses. Because of the broad functions of their targets (e.g. auxin response factors), the alteration of plant miRNA expression often results in pleiotropic effects. A specific miRNA usually regulates a biologically relevant bioenergy trait. For example, relatively low miR156 overexpression leads to a transgenic feedstock with enhanced biomass and decreased recalcitrance. miRNAs have been overexpressed in dedicated bioenergy feedstocks such as poplar and switchgrass yielding promising results for lignin reduction, increased plant biomass, the timing of flowering and response to harsh environments. In this review, we present the status of miRNA-related research in several major biofuel crops and relevant model plants. We critically assess published research and suggest next steps for miRNA manipulation in feedstocks for increased biomass and sustainability for biofuels and bioproducts. © 2015 Society for Experimental Biology, Association of Applied Biologists and John Wiley & Sons Ltd.
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
NASA Astrophysics Data System (ADS)
Karer, Jasmin; Zehetner, Franz; Kloss, Stefanie; Wimmer, Bernhard; Soja, Gerhard
2013-04-01
The use of biochar as soil amendment is considered as a promising agricultural soil management technique, combining carbon sequestration and soil fertility improvements. These expectations are largely founded on positive experiences with biochar applications to impoverished or degraded tropical soils. The validity of these results for soils in temperate climates needs confirmation from field experiments with typical soils representative for intensive agricultural production areas. Frequently biochar is mixed with other organic additives like compost. As these two materials interact with each other and each one may vary considerably in its basic characteristics, it is difficult to attribute the effects of the combined additive to one of its components and to a specific physico-chemical parameter. Therefore investigations of the amendment efficacy require the study of the pure components to characterize their specific behavior in soil. This is especially important for adsorption behavior of biochar for macro- and micronutrients because in soil there are multiple nutrient sinks that compete with plant roots for vital elements. Therefore this contribution presents results from a field amendment study with pure biochar that had the objective to characterize the macro- and microelement uptake of crops from different soils in two typical Austrian areas of agricultural production. At two locations in North and South-East Austria, two identical field experiments on different soils (Chernozem and Cambisol) were installed in 2011 with varying biochar additions (0, 30 and 90 t/ha) and two nitrogen levels. The biochar was a product from slow pyrolysis of wood (SC Romchar SRL). During the installation of the experiments, the biochar fraction of <2 mm was mixed with surface soil to a depth of 15 cm in plots of 33 m2 each (n=4). Barley (at the Chernozem soil) and maize (at the Cambisol) were cultivated according to standard agricultural practices. The highest crop yields at both study sites were observed after a biochar application rate of 90 t/ha and an abundant nitrogen supply (mineral N fertilizer rates: 120 kg/ha for barley, 150 kg/ha for corn). An omission of biochar addition at the same nitrogen addition rate resulted in a yield decrease of 10 % for barley although the total N uptake was 11 % higher but P and K uptake decreased by 14 and 6 %. This indicates that the higher yields with biochar were accompanied by increased availability of P and K but not N. The N deficiency treatment (with biochar amendment) resulted in yield decreases of 23 %, which were similar as the reductions of N uptake while reductions of P and K uptake were less pronounced. For corn, the omission of biochar caused only marginal yield effects (6%) and no significant changes in the N, P, and K uptake rates. Deficient N supply, however, resulted in severe yield reductions (46%) in spite of the high biochar application rate. The reductions of macronutrient uptake were in the same range for N (44%) but lower for P, K, Ca and Mg (19 to 33%). In summary, N and Cu were the elements that were least available for plant uptake at high biochar application rates.
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;
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. Multi-method 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.
Development of transgenic crops based on photo-biotechnology.
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
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.
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.
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)
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.
Societal resilience to hydroclimatic change in the Roman World
NASA Astrophysics Data System (ADS)
Dermody, Brian; van Beek, Rens; Bierkens, Marc; Dekker, Stefan
2016-04-01
The Romans were masters of water resource management. They employed sophisticated irrigation techniques alongside a highly integrated food redistribution system that provided stable food supplies under the variable hydroclimatic regime within the Roman World. However, a number of paleoclimate studies have demonstrated hydroclimatic changes during the Roman Period that exceeded the amplitude and persistence of normal climate variability. In particular, there was a shift from warmer and more stable hydroclimatic conditions in the Roman Warm Period (c.250 BC - 250 AD) to cooler and more variable conditions in Late Roman Period (after c.250 AD). In this study we use a socio-hydrological model of the Roman world to explore the impact of hydroclimatic changes between the Roman Warm Period and Late Roman Period on the Roman food production and redistribution system. We calculate crop yields based on temperature and water resource availability using PC Raster Global Water Balance model (PCR-GLOBWB). PCR-GLOBWB is forced with reanalysis climate fields reflecting reconstructions of Roman Warm Period to the Late Roman climate patterns. Cropland areas and settlement patterns are derived from a database of 14,700 Roman settlement sites and crop suitability maps. We simulate food redistribution using a multi-agent food redistribution network with link weights based on Orbis: The Stanford Geospatial Network of the Roman World. Our analysis indicates a reduction in crop yields during the Late Roman Period compared with the Roman Warm Period owing to cooler temperatures. In addition, our simulations indicate that increased hydroclimatic variability decreased the stability of yields in the Late Roman period. Crop yields in the Western Empire are simulated to have been impacted most by the change in climate owing to cooler average temperatures and greater hydroclimatic variability compared with the Eastern part of the Empire. The food redistribution network was essential to buffer against lower and less stable yields in the Late Roman Period. However, the Late Roman Period coincided with a breakdown in the food redistribution network, making the Western Roman Empire particularly vulnerable to changing climate conditions. Our analysis demonstrates a number of important processes that have general implications for water resource management in food production and redistribution systems.
Climate Change Effects on Agriculture: Economic Responses to Biophysical Shocks
NASA Technical Reports Server (NTRS)
Nelson, Gerald C.; Valin, Hugo; Sands, Ronald D.; Havlik, Petr; Ahammad, Helal; Deryng, Delphine; Elliott, Joshua; Fujimori, Shinichiro; Hasegawa, Tomoko; Heyhoe, Edwina
2014-01-01
Agricultural production is sensitive to weather and thus directly affected by climate change. Plausible estimates of these climate change impacts require combined use of climate, crop, and economic models. Results from previous studies vary substantially due to differences in models, scenarios, and data. This paper is part of a collective effort to systematically integrate these three types of models. We focus on the economic component of the assessment, investigating how nine global economic models of agriculture represent endogenous responses to seven standardized climate change scenarios produced by two climate and five crop models. These responses include adjustments in yields, area, consumption, and international trade. We apply biophysical shocks derived from the Intergovernmental Panel on Climate Change's representative concentration pathway with end-of-century radiative forcing of 8.5 W/m(sup 2). The mean biophysical yield effect with no incremental CO2 fertilization is a 17% reduction globally by 2050 relative to a scenario with unchanging climate. Endogenous economic responses reduce yield loss to 11%, increase area of major crops by 11%, and reduce consumption by 3%. Agricultural production, cropland area, trade, and prices show the greatest degree of variability in response to climate change, and consumption the lowest. The sources of these differences include model structure and specification; in particular, model assumptions about ease of land use conversion, intensification, and trade. This study identifies where models disagree on the relative responses to climate shocks and highlights research activities needed to improve the representation of agricultural adaptation responses to climate change.
Climate change effects on agriculture: Economic responses to biophysical shocks
Nelson, Gerald C.; Valin, Hugo; Sands, Ronald D.; Havlík, Petr; Ahammad, Helal; Deryng, Delphine; Elliott, Joshua; Fujimori, Shinichiro; Hasegawa, Tomoko; Heyhoe, Edwina; Kyle, Page; Von Lampe, Martin; Lotze-Campen, Hermann; Mason d’Croz, Daniel; van Meijl, Hans; van der Mensbrugghe, Dominique; Müller, Christoph; Popp, Alexander; Robertson, Richard; Robinson, Sherman; Schmid, Erwin; Schmitz, Christoph; Tabeau, Andrzej; Willenbockel, Dirk
2014-01-01
Agricultural production is sensitive to weather and thus directly affected by climate change. Plausible estimates of these climate change impacts require combined use of climate, crop, and economic models. Results from previous studies vary substantially due to differences in models, scenarios, and data. This paper is part of a collective effort to systematically integrate these three types of models. We focus on the economic component of the assessment, investigating how nine global economic models of agriculture represent endogenous responses to seven standardized climate change scenarios produced by two climate and five crop models. These responses include adjustments in yields, area, consumption, and international trade. We apply biophysical shocks derived from the Intergovernmental Panel on Climate Change’s representative concentration pathway with end-of-century radiative forcing of 8.5 W/m2. The mean biophysical yield effect with no incremental CO2 fertilization is a 17% reduction globally by 2050 relative to a scenario with unchanging climate. Endogenous economic responses reduce yield loss to 11%, increase area of major crops by 11%, and reduce consumption by 3%. Agricultural production, cropland area, trade, and prices show the greatest degree of variability in response to climate change, and consumption the lowest. The sources of these differences include model structure and specification; in particular, model assumptions about ease of land use conversion, intensification, and trade. This study identifies where models disagree on the relative responses to climate shocks and highlights research activities needed to improve the representation of agricultural adaptation responses to climate change. PMID:24344285
Climate change effects on agriculture: economic responses to biophysical shocks.
Nelson, Gerald C; Valin, Hugo; Sands, Ronald D; Havlík, Petr; Ahammad, Helal; Deryng, Delphine; Elliott, Joshua; Fujimori, Shinichiro; Hasegawa, Tomoko; Heyhoe, Edwina; Kyle, Page; Von Lampe, Martin; Lotze-Campen, Hermann; Mason d'Croz, Daniel; van Meijl, Hans; van der Mensbrugghe, Dominique; Müller, Christoph; Popp, Alexander; Robertson, Richard; Robinson, Sherman; Schmid, Erwin; Schmitz, Christoph; Tabeau, Andrzej; Willenbockel, Dirk
2014-03-04
Agricultural production is sensitive to weather and thus directly affected by climate change. Plausible estimates of these climate change impacts require combined use of climate, crop, and economic models. Results from previous studies vary substantially due to differences in models, scenarios, and data. This paper is part of a collective effort to systematically integrate these three types of models. We focus on the economic component of the assessment, investigating how nine global economic models of agriculture represent endogenous responses to seven standardized climate change scenarios produced by two climate and five crop models. These responses include adjustments in yields, area, consumption, and international trade. We apply biophysical shocks derived from the Intergovernmental Panel on Climate Change's representative concentration pathway with end-of-century radiative forcing of 8.5 W/m(2). The mean biophysical yield effect with no incremental CO2 fertilization is a 17% reduction globally by 2050 relative to a scenario with unchanging climate. Endogenous economic responses reduce yield loss to 11%, increase area of major crops by 11%, and reduce consumption by 3%. Agricultural production, cropland area, trade, and prices show the greatest degree of variability in response to climate change, and consumption the lowest. The sources of these differences include model structure and specification; in particular, model assumptions about ease of land use conversion, intensification, and trade. This study identifies where models disagree on the relative responses to climate shocks and highlights research activities needed to improve the representation of agricultural adaptation responses to climate change.
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.
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.
The impact exploration of agricultural drought on winter wheat yield in the North China Plain
NASA Astrophysics Data System (ADS)
Yang, Jianhua; Wu, Jianjun; Han, Xinyi; Zhou, Hongkui
2017-04-01
Drought is one of the most serious agro-climatic disasters in the North China Plain, which has a great influence on winter wheat yield. Global warming exacerbates the drought trend of this region, so it is important to study the effect of drought on winter wheat yield. In order to assess the drought-induced winter wheat yield losses, SPEI (standardized precipitation evapotranspiration index), the widely used drought index, was selected to quantify the drought from 1981 to 2013. Additionally, the EPIC (Environmental Policy Integrated Climate) crop model was used to simulate winter wheat yield at 47 stations in this region from 1981 to 2013. We analyzed the relationship between winter wheat yield and the SPEI at different time scales in each month during the growing season. The trends of the SPEI and the trends of winter wheat yield at 47 stations over the past 32 years were compared with each other. To further quantify the effect of drought on winter wheat yield, we defined the year that SPEI varied from -0.5 to 0.5 as the normal year, and calculated the average winter wheat yield of the normal years as a reference yield, then calculated the reduction ratios of winter wheat based on the yields mentioned above in severe drought years. As a reference, we compared the results with the reduction ratios calculated from the statistical yield data. The results showed that the 9 to 12-month scales' SPEI in April, May and June had a high correlation with winter wheat yield. The trends of the SPEI and the trends of winter wheat yield over the past 32 years showed a positive correlation (p<0.01) and have similar spatial distributions. The proportion of the stations with the same change trend between the SPEI and winter wheat yield was 70%, indicating that drought was the main factor leading to a decline in winter wheat yield in this region. The reduction ratios based on the simulated yield and the reduction ratios calculated from the statistical yield data have a high positive correlation (p<0.01), which may provide a way to quantitatively evaluate the winter wheat yield losses caused by drought. Key words: drought, winter wheat yield, SPEI, EPIC, the North China Plain
NASA Astrophysics Data System (ADS)
Darzi-Naftchali, Abdullah; Karandish, Fatemeh
2017-12-01
Sustainable utilization of blue water resources under climate change is of great significance especially for producing high water-consuming crops in water-scarce regions. Based on the virtual water concept, we carried out a comprehensive field-modeling research to find the optimal agricultural practices regarding rice blue water consumption under prospective climate change. The DSSAT-CERES-Rice model was used in combination with 20 GCMs under three Representative Concentration Pathways of low (RCP2.6), intermediate (RCP4.6), and very high (RCP8.5) greenhouse concentrations to predict rice yield and water requirement and related virtual water and economic return for the base and future periods. The crop model was calibrated and validated based on the 2-year field data obtained from consolidated paddy fields of the Sari Agricultural Sciences and Natural Resources University during 2011 and 2012 rice cropping cycles. Climate change imposes an increase of 0.02-0.04 °C in air temperature which consequently shifts rice growing seasons to winter season, and shorten the length of rice physiological maturity period by 2-15 days. While rice virtual water reduces by 0.1-20.6% during 2011-2070, reduced rice yield by 3.8-22.6% over the late twenty-first century results in a considerable increase in rice virtual water. By increasing the contribution of green water in supplying crop water requirement, earlier cropping could diminish blue water consumption for rice production in the region while cultivation postponement increases irrigation water requirement by 2-195 m3 ha-1. Forty days delay in rice cultivation in future will result in 29.9-40.6% yield reduction and 43.9-60% increase in rice virtual water under different scenarios. Earlier cropping during the 2011-2040 and 2041-2070 periods would increase water productivity, unit value of water, and economic value of blue water compared to the base period. Based on the results, management of rice cultivation calendar is a suitable strategy for sustainable blue water consumption for producing rice under future climate.
Design and analysis of mixed cropping experiments for indigenous Pacific Islands
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...
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.
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.
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.
Trading carbon for food: global comparison of carbon stocks vs. crop yields on agricultural land.
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
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.
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.
Blackleg (Leptosphaeria maculans) Severity and Yield Loss in Canola in Alberta, Canada
Hwang, Sheau-Fang; Strelkov, Stephen E.; Peng, Gary; Ahmed, Hafiz; Zhou, Qixing; Turnbull, George
2016-01-01
Blackleg, caused by Leptosphaeria maculans, is an important disease of oilseed rape (Brassica napus L.) in Canada and throughout the world. Severe epidemics of blackleg can result in significant yield losses. Understanding disease-yield relationships is a prerequisite for measuring the agronomic efficacy and economic benefits of control methods. Field experiments were conducted in 2013, 2014, and 2015 to determine the relationship between blackleg disease severity and yield in a susceptible cultivar and in moderately resistant to resistant canola hybrids. Disease severity was lower, and seed yield was 120%–128% greater, in the moderately resistant to resistant hybrids compared with the susceptible cultivar. Regression analysis showed that pod number and seed yield declined linearly as blackleg severity increased. Seed yield per plant decreased by 1.8 g for each unit increase in disease severity, corresponding to a decline in yield of 17.2% for each unit increase in disease severity. Pyraclostrobin fungicide reduced disease severity in all site-years and increased yield. These results show that the reduction of blackleg in canola crops substantially improves yields. PMID:27447676
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.
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.
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.
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.
Zhuo, La; Mekonnen, Mesfin M; Hoekstra, Arjen Y
2016-09-01
The study assesses green and blue water footprints (WFs) and virtual water (VW) trade in China under alternative scenarios for 2030 and 2050, with a focus on crop production, consumption and trade. We consider five driving factors of change: climate, harvested crop area, technology, diet, and population. Four scenarios (S1-S4) are constructed by making use of three of IPCC's shared socio-economic pathways (SSP1-SSP3) and two of IPCC's representative concentration pathways (RCP 2.6 and RCP 8.5) and taking 2005 as the baseline year. Results show that, across the four scenarios and for most crops, the green and blue WFs per tonne will decrease compared to the baseline year, due to the projected crop yield increase, which is driven by the higher precipitation and CO2 concentration under the two RCPs and the foreseen uptake of better technology. The WF per capita related to food consumption decreases in all scenarios. Changing to the less-meat diet can generate a reduction in the WF of food consumption of 44% by 2050. In all scenarios, as a result of the projected increase in crop yields and thus overall growth in crop production, China will reverse its role from net VW importer to net VW exporter. However, China will remain a big net VW importer related to soybean, which accounts for 5% of the WF of Chinese food consumption (in S1) by 2050. All scenarios show that China could attain a high degree of food self-sufficiency while simultaneously reducing water consumption in agriculture. However, the premise of realizing the presented scenarios is smart water and cropland management, effective and coherent policies on water, agriculture and infrastructure, and, as in scenario S1, a shift to a diet containing less meat. Copyright © 2016 Elsevier Ltd. All rights reserved.
Sripanomtanakorn, S; Polprasert, C
2002-04-01
Agricultural land is an attractive alternative for the disposal of biosolids since it utilises the recyclable nutrients in the production of crops. In Thailand and other tropical regions, limited field-study information exists on the effect of biosolids management strategies on crop N utilisation and plant available N (PAN) of biosolids. A field study was conducted to quantify the PAN of the applied biosolids, and to evaluate the N uptake rates of some tropical crops. Sunflower (Helianthus annuus) and tomato (Lycopersicon esculentum) were chosen in this study. Two types of biosolids used were: anaerobically digested sludge and septic tank sludge. The soil is acid sulfate and is classified as Sulfic Tropaquepts with heavy clay in texture. The anaerobically digested sludge applied rates were: 0, 156 and 312 kg N ha(-1) for the sunflower plots, and 0, 586, and 1172 kg N ha(-1) for the tomato plots. The septic tank sludge applied rates were: 0, 95 and 190 kg N ha(-1) for the sunflower plots, and 0, 354 and 708 kg N ha(-1) for the tomato plots, respectively. The results indicated the feasibility of applying biosolids to grow tropical crops. The applications of the anaerobically digested sludge and the septic tank sludge resulted in the yields of sunflower seeds and tomato fruits and the plant N uptakes comparable or better than that applied with only the chemical fertiliser. The estimated PAN of the anaerobically digested sludge was about 27-42% of the sludge organic N during the growing season. For the septic tank sludge, the PAN was about 15-58% of the sludge organic N. It is interesting to observe that an increase of the rate of septic tank sludge incorporated into this heavy clay soil under the cropping system resulted in the decrease of N mineralisation rate. This situation could cause the reduction of yield and N uptake of crops.
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.
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.
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.
NASA Technical Reports Server (NTRS)
Estes, Lyndon D.; Beukes, Hein; Bradley, Bethany A.; Debats, Stephanie R.; Oppenheimer, Michael; Ruane, Alex C.; Schulze, Roland; Tadross, Mark
2013-01-01
Crop model-specific biases are a key uncertainty affecting our understanding of climate change impacts to agriculture. There is increasing research focus on intermodel variation, but comparisons between mechanistic (MMs) and empirical models (EMs) are rare despite both being used widely in this field. We combined MMs and EMs to project future (2055) changes in the potential distribution (suitability) and productivity of maize and spring wheat in South Africa under 18 downscaled climate scenarios (9 models run under 2 emissions scenarios). EMs projected larger yield losses or smaller gains than MMs. The EMs' median-projected maize and wheat yield changes were 3.6% and 6.2%, respectively, compared to 6.5% and 15.2% for the MM. The EM projected a 10% reduction in the potential maize growing area, where the MM projected a 9% gain. Both models showed increases in the potential spring wheat production region (EM = 48%, MM = 20%), but these results were more equivocal because both models (particularly the EM) substantially overestimated the extent of current suitability. The substantial water-use efficiency gains simulated by the MMs under elevated CO2 accounted for much of the EMMM difference, but EMs may have more accurately represented crop temperature sensitivities. Our results align with earlier studies showing that EMs may show larger climate change losses than MMs. Crop forecasting efforts should expand to include EMMM comparisons to provide a fuller picture of crop-climate response uncertainties.
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.
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;
2014-01-01
Predicting rice (Oryza sativa) productivity under future climates is important for global food security. Ecophysiological crop models in combination with climate model outputs are commonly used in yield prediction, but uncertainties associated with crop models remain largely unquantified. We evaluated 13 rice models against multi-year experimental yield data at four sites with diverse climatic conditions in Asia and examined whether different modeling approaches on major physiological processes attribute to the uncertainties of prediction to field measured yields and to the uncertainties of sensitivity to changes in temperature and CO2 concentration [CO2]. We also examined whether a use of an ensemble of crop models can reduce the uncertainties. Individual models did not consistently reproduce both experimental and regional yields well, and uncertainty was larger at the warmest and coolest sites. The variation in yield projections was larger among crop models than variation resulting from 16 global climate model-based scenarios. However, the mean of predictions of all crop models reproduced experimental data, with an uncertainty of less than 10 percent of measured yields. Using an ensemble of eight models calibrated only for phenology or five models calibrated in detail resulted in the uncertainty equivalent to that of the measured yield in well-controlled agronomic field experiments. Sensitivity analysis indicates the necessity to improve the accuracy in predicting both biomass and harvest index in response to increasing [CO2] and temperature.
Improving the monitoring of crop productivity using spaceborne solar-induced fluorescence.
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.
Environmental impact assessment of alfalfa (Medicago sativa L.) hay production.
Bacenetti, Jacopo; Lovarelli, Daniela; Tedesco, Doriana; Pretolani, Roberto; Ferrante, Valentina
2018-09-01
On-farm production of hay and high-protein-content feed has several advantages such as diversification of on-farm cultivated crops, reduction of off-farm feed concentrates transported over long distances and a reduction in runoff during the winter season if grown crops are perennial. Among those crops cultivated for high-protein-content feed, alfalfa (Medicago sativa L.) is one of the most important in the Italian context. Nevertheless, up to now, only a few studies have assessed the environmental performance of alfalfa hay production. In this study, using the Life Cycle Assessment approach, the environmental impact of alfalfa hay production in Northern Italy was analyzed. More in detail, two production practices (without and with irrigation) were compared. The results show that alfalfa hay production in irrigated fields has a better environmental performance compared to non-irrigated production, mainly because of the yield increase achieved with irrigation. In particular, for the Climate Change impact category, the impact is equal to 84.54 and 80.21kgCO 2 /t of hay for the scenario without and with irrigation, respectively. However, for two impact categories (Ozone Depletion and Human Toxicity-No Cancer Effect), the impact of irrigation completely offsets the yield increase, and the cultivation practice without irrigation shows the best environmental performance. For both scenarios, the mechanization of harvest is the main environmental hotspot, mostly due to fuel consumption and related combustion emissions. Wide differences were highlighted by comparing the two scenarios with the Ecoinvent process of alfalfa hay production; these differences are mostly due to the cultivation practice and, in particular, to the more intensive fertilization in Swiss production. Copyright © 2018 Elsevier B.V. All rights reserved.
Crop responses to climatic variation
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
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.
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.
Transgenic Strategies for Enhancement of Nematode Resistance in Plants
Ali, Muhammad A.; Azeem, Farrukh; Abbas, Amjad; Joyia, Faiz A.; Li, Hongjie; Dababat, Abdelfattah A.
2017-01-01
Plant parasitic nematodes (PPNs) are obligate biotrophic parasites causing serious damage and reduction in crop yields. Several economically important genera parasitize various crop plants. The root-knot, root lesion, and cyst nematodes are the three most economically damaging genera of PPNs on crops within the family Heteroderidae. It is very important to devise various management strategies against PPNs in economically important crop plants. Genetic engineering has proven a promising tool for the development of biotic and abiotic stress tolerance in crop plants. Additionally, the genetic engineering leading to transgenic plants harboring nematode resistance genes has demonstrated its significance in the field of plant nematology. Here, we have discussed the use of genetic engineering for the development of nematode resistance in plants. This review article also provides a detailed account of transgenic strategies for the resistance against PPNs. The strategies include natural resistance genes, cloning of proteinase inhibitor coding genes, anti-nematodal proteins and use of RNA interference to suppress nematode effectors. Furthermore, the manipulation of expression levels of genes induced and suppressed by nematodes has also been suggested as an innovative approach for inducing nematode resistance in plants. The information in this article will provide an array of possibilities to engineer resistance against PPNs in different crop plants. PMID:28536595
Transgenic Strategies for Enhancement of Nematode Resistance in Plants.
Ali, Muhammad A; Azeem, Farrukh; Abbas, Amjad; Joyia, Faiz A; Li, Hongjie; Dababat, Abdelfattah A
2017-01-01
Plant parasitic nematodes (PPNs) are obligate biotrophic parasites causing serious damage and reduction in crop yields. Several economically important genera parasitize various crop plants. The root-knot, root lesion, and cyst nematodes are the three most economically damaging genera of PPNs on crops within the family Heteroderidae. It is very important to devise various management strategies against PPNs in economically important crop plants. Genetic engineering has proven a promising tool for the development of biotic and abiotic stress tolerance in crop plants. Additionally, the genetic engineering leading to transgenic plants harboring nematode resistance genes has demonstrated its significance in the field of plant nematology. Here, we have discussed the use of genetic engineering for the development of nematode resistance in plants. This review article also provides a detailed account of transgenic strategies for the resistance against PPNs. The strategies include natural resistance genes, cloning of proteinase inhibitor coding genes, anti-nematodal proteins and use of RNA interference to suppress nematode effectors. Furthermore, the manipulation of expression levels of genes induced and suppressed by nematodes has also been suggested as an innovative approach for inducing nematode resistance in plants. The information in this article will provide an array of possibilities to engineer resistance against PPNs in different crop plants.
NASA Astrophysics Data System (ADS)
Hernandez-Santana, V.; Zhou, X.; Helmers, M. J.; Asbjornsen, H.; Kolka, R.; Tomer, M.
2013-01-01
SummaryIntensively managed annual cropping systems have produced high crop yields but have often produced significant ecosystem services alteration, in particular hydrologic regulation loss. Reconversion of annual agricultural systems to perennial vegetation can lead to hydrologic function restoration, but its effect is still not well understood. Therefore, our objective was to assess the effects of strategic introduction of different amounts and location of native prairie vegetation (NPV) within agricultural landscapes on hydrological regulation. The study was conducted in Iowa (USA), and consisted of a fully balanced, replicated, incomplete block design whereby 12 zero-order ephemeral flow watersheds received four treatments consisting of varying proportions (0%, 10%, and 20%) of prairie vegetation located in different watershed positions (footslope vs. contour strips). Runoff volume and rate were measured from 2008 to 2010 (April-October) with an H-Flume installed in each catchment, and automated ISCO samplers. Over the entire study period, we observed a total of 129 runoff events with an average runoff volume reduction of 37% based on the three treatments with NPV compared to watersheds with row crops. We observed a progressively greater reduction across the 3 years of the study as the perennial strips became established with the greatest differences among treatments occurring in 2010. The differences among the watersheds were attributed mainly to NPV amount and position, with the 10% NPV at footslope treatment having the greatest runoff reduction probably because the portion of NPV filter strip that actually contacted watershed runoff was greater with the 10% NPV at footslope. We observed greater reductions in runoff in spring and fall likely because perennial prairie plants were active and crops were absent or not fully established. High antecedent soil moisture sometimes led to little benefit of the NPV treatments but in general the NPV treatments were effective during both small and large events. We conclude that, small amounts of NPV strategically incorporated into corn-soybean watersheds in the Midwest US can be used to effectively reduce runoff.
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.
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.
Opposing effects of different soil organic matter fractions on crop yields.
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.
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.
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.
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.
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.
Robson, Paul R.H.; Farrar, Kerrie; Gay, Alan P.; Jensen, Elaine F.; Clifton-Brown, John C.; Donnison, Iain S.
2013-01-01
Energy crops can provide a sustainable source of power and fuels, and mitigate the negative effects of CO2 emissions associated with fossil fuel use. Miscanthus is a perennial C4 energy crop capable of producing large biomass yields whilst requiring low levels of input. Miscanthus is largely unimproved and therefore there could be significant opportunities to increase yield. Further increases in yield will improve the economics, energy balance, and carbon mitigation of the crop, as well as reducing land-take. One strategy to increase yield in Miscanthus is to maximize the light captured through an extension of canopy duration. In this study, canopy duration was compared among a diverse collection of 244 Miscanthus genotypes. Canopy duration was determined by calculating the number of days between canopy establishment and senescence. Yield was positively correlated with canopy duration. Earlier establishment and later senescence were also both separately correlated with higher yield. However, although genotypes with short canopy durations were low yielding, not all genotypes with long canopy durations were high yielding. Differences of yield between genotypes with long canopy durations were associated with variation in stem and leaf traits. Different methodologies to assess canopy duration traits were investigated, including visual assessment, image analysis, light interception, and different trait thresholds. The highest correlation coefficients were associated with later assessments of traits and the use of quantum sensors for canopy establishment. A model for trait optimization to enable yield improvement in Miscanthus and other bioenergy crops is discussed. PMID:23599277
Assessment of energy crops alternative to maize for biogas production in the Greater Region.
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.
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.
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.
Almendinger, James E; Murphy, Marylee S; Ulrich, Jason S
2014-01-01
For two watersheds in the northern Midwest United States, we show that landscape depressions have a significant impact on watershed hydrology and sediment yields and that the Soil and Water Assessment Tool (SWAT) has appropriate features to simulate these depressions. In our SWAT models of the Willow River in Wisconsin and the Sunrise River in Minnesota, we used Pond and Wetland features to capture runoff from about 40% of the area in each watershed. These depressions trapped considerable sediment, yet further reductions in sediment yield were required for calibration and achieved by reducing the Universal Soil Loss Equation (USLE) cropping-practice (P) factor to 0.40 to 0.45. We suggest terminology to describe annual sediment yields at different conceptual spatial scales and show how SWAT output can be partitioned to extract data at each of these scales. These scales range from plot-scale yields calculated with the USLE to watershed-scale yields measured at the outlet. Intermediate scales include field, upland, pre-riverine, and riverine scales, in descending order along the conceptual flow path from plot to outlet. Sediment delivery ratios, when defined as watershed-scale yields as a percentage of plot-scale yields, ranged from 1% for the Willow watershed (717 km) to 7% for the Sunrise watershed (991 km). Sediment delivery ratios calculated from published relations based on watershed area alone were about 5 to 6%, closer to pre-riverine-scale yields in our watersheds. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.
Importance of food-demand management for climate mitigation
NASA Astrophysics Data System (ADS)
Bajželj, Bojana; Richards, Keith S.; Allwood, Julian M.; Smith, Pete; Dennis, John S.; Curmi, Elizabeth; Gilligan, Christopher A.
2014-10-01
Recent studies show that current trends in yield improvement will not be sufficient to meet projected global food demand in 2050, and suggest that a further expansion of agricultural area will be required. However, agriculture is the main driver of losses of biodiversity and a major contributor to climate change and pollution, and so further expansion is undesirable. The usual proposed alternative--intensification with increased resource use--also has negative effects. It is therefore imperative to find ways to achieve global food security without expanding crop or pastureland and without increasing greenhouse gas emissions. Some authors have emphasized a role for sustainable intensification in closing global `yield gaps' between the currently realized and potentially achievable yields. However, in this paper we use a transparent, data-driven model, to show that even if yield gaps are closed, the projected demand will drive further agricultural expansion. There are, however, options for reduction on the demand side that are rarely considered. In the second part of this paper we quantify the potential for demand-side mitigation options, and show that improved diets and decreases in food waste are essential to deliver emissions reductions, and to provide global food security in 2050.
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...
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...
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.
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.
Higo, Masao; Takahashi, Yuichi; Gunji, Kento; Isobe, Katsunori
2018-03-01
Better cover crop management options aiming to maximize the benefits of arbuscular mycorrhizal fungi (AMF) to subsequent crops are largely unknown. We investigated the impact of cover crop management methods on maize growth performance and assemblages of AMF colonizing maize roots in a field trial. The cover crop treatments comprised Italian ryegrass, wheat, brown mustard and fallow in rotation with maize. The diversity of AMF communities among cover crops used for maize management was significantly influenced by the cover crop and time course. Cover crops did not affect grain yield and aboveground biomass of subsequent maize but affected early growth. A structural equation model indicated that the root colonization, AMF diversity and maize phosphorus uptake had direct strong positive effects on yield performance. AMF variables and maize performance were related directly or indirectly to maize grain yield, whereas root colonization had a positive effect on maize performance. AMF may be an essential factor that determines the success of cover crop rotational systems. Encouraging AMF associations can potentially benefit cover cropping systems. Therefore, it is imperative to consider AMF associations and crop phenology when making management decisions. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.
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.
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.
2013-02-01
areas of JB CHS-WS. However, loblolly pine (Pinus taeda) will be planted where soil conditions are not conducive to sustain longleaf pine populations...more subject to soil erosion. Once forested areas have been planted with seedlings, further reduction of competitive vegetation through mechanical...uses. The soil qualities, growing season, and moisture supply are needed for a well-managed soil to produce a sustained high yield of crops in an
Sustainability analysis of bioenergy based land use change under climate change and variability
NASA Astrophysics Data System (ADS)
Raj, C.; Chaubey, I.; Brouder, S. M.; Bowling, L. C.; Cherkauer, K. A.; Frankenberger, J.; Goforth, R. R.; Gramig, B. M.; Volenec, J. J.
2014-12-01
Sustainability analyses of futuristic plausible land use and climate change scenarios are critical in making watershed-scale decisions for simultaneous improvement of food, energy and water management. Bioenergy production targets for the US are anticipated to impact farming practices through the introduction of fast growing and high yielding perennial grasses/trees, and use of crop residues as bioenergy feedstocks. These land use/land management changes raise concern over potential environmental impacts of bioenergy crop production scenarios, both in terms of water availability and water quality; impacts that may be exacerbated by climate variability and change. The objective of the study was to assess environmental, economic and biodiversity sustainability of plausible bioenergy scenarios for two watersheds in Midwest US under changing climate scenarios. The study considers fourteen sustainability indicators under nine climate change scenarios from World Climate Research Programme's (WCRP's) Coupled Model Intercomparison Project phase 3 (CMIP3). The distributed hydrological model SWAT (Soil and Water Assessment Tool) was used to simulate perennial bioenergy crops such as Miscanthus and switchgrass, and corn stover removal at various removal rates and their impacts on hydrology and water quality. Species Distribution Models (SDMs) developed to evaluate stream fish response to hydrology and water quality changes associated with land use change were used to quantify biodiversity sustainability of various bioenergy scenarios. The watershed-scale sustainability analysis was done in the St. Joseph River watershed located in Indiana, Michigan, and Ohio; and the Wildcat Creek watershed, located in Indiana. The results indicate streamflow reduction at watershed outlet with increased evapotranspiration demands for high-yielding perennial grasses. Bioenergy crops in general improved in-stream water quality compared to conventional cropping systems (maize-soybean). Water quality benefits due to land use change were generally greater than the effects of climate change variability.
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
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...
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...
Multigene Engineering of Triacylglycerol Metabolism Boosts Seed Oil Content in Arabidopsis1[W][OPEN
van Erp, Harrie; Kelly, Amélie A.; Menard, Guillaume; Eastmond, Peter J.
2014-01-01
Increasing the yield of oilseed crops is an important objective for biotechnologists. A number of individual genes involved in triacylglycerol metabolism have previously been reported to enhance the oil content of seeds when their expression is altered. However, it has yet to be established whether specific combinations of these genes can be used to achieve an additive effect and whether this leads to enhanced yield. Using Arabidopsis (Arabidopsis thaliana) as an experimental system, we show that seed-specific overexpression of WRINKLED1 (a transcriptional regulator of glycolysis and fatty acid synthesis) and DIACYLGLYCEROL ACYLTRANSFERASE1 (a triacylglycerol biosynthetic enzyme) combined with suppression of the triacylglycerol lipase SUGAR-DEPENDENT1 results in a higher percentage seed oil content and greater seed mass than manipulation of each gene individually. Analysis of total seed yield per plant suggests that, despite a reduction in seed number, the total yield of oil is also increased. PMID:24696520
Genetic variations in ARE1 mediate grain yield by modulating nitrogen utilization in rice.
Wang, Qing; Nian, Jinqiang; Xie, Xianzhi; Yu, Hong; Zhang, Jian; Bai, Jiaoteng; Dong, Guojun; Hu, Jiang; Bai, Bo; Chen, Lichao; Xie, Qingjun; Feng, Jian; Yang, Xiaolu; Peng, Juli; Chen, Fan; Qian, Qian; Li, Jiayang; Zuo, Jianru
2018-02-21
In crops, nitrogen directly determines productivity and biomass. However, the improvement of nitrogen utilization efficiency (NUE) is still a major challenge in modern agriculture. Here, we report the characterization of are1, a genetic suppressor of a rice fd-gogat mutant defective in nitrogen assimilation. ARE1 is a highly conserved gene, encoding a chloroplast-localized protein. Loss-of-function mutations in ARE1 cause delayed senescence and result in 10-20% grain yield increases, hence enhance NUE under nitrogen-limiting conditions. Analysis of a panel of 2155 rice varieties reveals that 18% indica and 48% aus accessions carry small insertions in the ARE1 promoter, which result in a reduction in ARE1 expression and an increase in grain yield under nitrogen-limiting conditions. We propose that ARE1 is a key mediator of NUE and represents a promising target for breeding high-yield cultivars under nitrogen-limiting condition.
NASA Astrophysics Data System (ADS)
Hansen, K.; Shukla, S.; Holt, N.; Hendricks, G.; Sishodia, R. P.
2017-12-01
Fresh fruits and vegetables are conventionally grown in raised bed plasticulture (RBP), a high intensity, high input, and high output production system. In 2016, the fresh market plasticulture industry covered 680,000 ha in the US, producing crops (e.g. tomato, peppers, melons, and strawberries) valued at ten billion dollars. To meet the increasing future demand for fresh fruits and vegetables and sustain the production potential of croplands, a transformation of the conventional food-water-energy nexus is essential. A novel agricultural conservation system, compact bed geometry, has been proposed to shift the paradigm in RBP, sustaining yield and decreasing inputs (e.g. water, nutrients, energy, and carbon). Compact bed geometries fit the shape of the wetting front created when water is applied through drip irrigation on the production soil, creating a taller (23-30 cm) and thinner bed (66-41 cm). Two seasons of tomato (single row) and pepper (double row) production, in the environmentally fragile watershed of the Florida Everglades, highlight the potential impact of compact bed geometry on environmental sustainability in agricultural production. No difference in plant growth or yield was detected, with a reduction of 5-50% in irrigation water, up to 20% less N application, 12% less P, 20% less K, and 5-15% less carbon dioxide emissions. The hydrologic benefits of compact bed geometry include 26% less runoff generation, decreased need for active drainage pumping, and increased residence time for irrigation water within the bed, overall decreasing instances of nutrient leaching. A water related co-benefit observed was a reduction in the occurrences of Phytophthora capsici in pepper, which has the potential to reduce yield by as much as 70%. Non-water co-benefits include up to a 250/ ha reduction in production cost, with the potential to save the industry 200 million dollars annually. This economic benefit has led to rapid industry adoption, with more than 20,000 acres already converted to compact bed geometries, up and down the east coast of the US. The adoption of compact bed geometries achieves "More Crop, per Drop" and is revolutionizing the food-water-energy nexus as it relates to fruit and vegetable production.
Femeena, P V; Sudheer, K P; Cibin, R; Chaubey, I
2018-04-15
Biofuel has emerged as a substantial source of energy in many countries. In order to avoid the 'food versus fuel competition', arising from grain-based ethanol production, the United States has passed regulations that require second generation or cellulosic biofeedstocks to be used for majority of the biofuel production by 2022. Agricultural residue, such as corn stover, is currently the largest source of cellulosic feedstock. However, increased harvesting of crops residue may lead to increased application of fertilizers in order to recover the soil nutrients lost from the residue removal. Alternatively, introduction of less-fertilizer intensive perennial grasses such as switchgrass (Panicum virgatum L.) and Miscanthus (Miscanthus x giganteus Greef et Deu.) can be a viable source for biofuel production. Even though these grasses are shown to reduce nutrient loads to a great extent, high production cost have constrained their wide adoptability to be used as a viable feedstock. Nonetheless, there is an opportunity to optimize feedstock production to meet bioenergy demand while improving water quality. This study presents a multi-objective simulation optimization framework using Soil and Water Assessment Tool (SWAT) and Multi Algorithm Genetically Adaptive Method (AMALGAM) to develop optimal cropping pattern with minimum nutrient delivery and minimum biomass production cost. Computational time required for optimization was significantly reduced by loose coupling SWAT with an external in-stream solute transport model. Optimization was constrained by food security and biofuel production targets that ensured not more than 10% reduction in grain yield and at least 100 million gallons of ethanol production. A case study was carried out in St. Joseph River Watershed that covers 280,000 ha area in the Midwest U.S. Results of the study indicated that introduction of corn stover removal and perennial grass production reduce nitrate and total phosphorus loads without compromising on food and biofuel production. Optimization runs yielded an optimal cropping pattern with 32% of watershed area in stover removal, 15% in switchgrass and 2% in Miscanthus. The optimal scenario resulted in 14% reduction in nitrate and 22% reduction in total phosphorus from the baseline. This framework can be used as an effective tool to take decisions regarding environmentally and economically sustainable strategies to minimize the nutrient delivery at minimal biomass production cost, while simultaneously meeting food and biofuel production targets. Copyright © 2018 Elsevier Ltd. All rights reserved.
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.
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.
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.
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
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.
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.
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.
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.
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.
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.
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?
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
Global change impacts on wheat production along an environmental gradient in south Australia.
Reyenga, P J; Howden, S M; Meinke, H; Hall, W B
2001-09-01
Crop production is likely to change in the future as a result of global changes in CO2 levels in the atmosphere and climate. APSIM, a cropping system model, was used to investigate the potential impact of these changes on the distribution of cropping along an environmental transect in south Australia. The effects of several global change scenarios were studied, including: (1) historical climate and CO2 levels, (2) historic climate with elevated CO2 (700 ppm), (3) warmer climate (+2.4 degrees C) +700 ppm CO2, (4) drier climate (-15% summer, -20% winter rainfall) +2.4 degrees C +700 ppm CO2, (5) wetter climate (+10% summer rainfall) +2.4 degrees C +700 ppm CO2 and (6) most likely climate changes (+1.8 degrees C, -8% annual rainfall) +700 ppm CO2. Based on an analysis of the current cropping boundary, a criterion of 1 t/ha was used to assess potential changes in the boundary under global change. Under most scenarios, the cropping boundary moved northwards with a further 240,000 ha potentially being available for cropping. The exception was the reduced rainfall scenario (4), which resulted in a small retreat of cropping from its current extent. However, the impact of this scenario may only be small (in the order of 10,000-20,000 ha reduction in cropping area). Increases in CO2 levels over the current climate record have resulted in small but significant increases in simulated yields. Model limitations are discussed.
Particulate matter air pollution may offset ozone damage to global crop production
NASA Astrophysics Data System (ADS)
Schiferl, Luke D.; Heald, Colette L.
2018-04-01
Ensuring global food security requires a comprehensive understanding of environmental pressures on food production, including the impacts of air quality. Surface ozone damages plants and decreases crop production; this effect has been extensively studied. In contrast, the presence of particulate matter (PM) in the atmosphere can be beneficial to crops given that enhanced light scattering leads to a more even and efficient distribution of photons which can outweigh total incoming radiation loss. This study quantifies the impacts of ozone and PM on the global production of maize, rice, and wheat in 2010 and 2050. We show that accounting for the growing season of these crops is an important factor in determining their air pollution exposure. We find that the effect of PM can offset much, if not all, of the reduction in yield associated with ozone damage. Assuming maximum sensitivity to PM, the current (2010) global net impact of air quality on crop production varies by crop (+5.6, -3.7, and +4.5 % for maize, wheat, and rice, respectively). Future emissions scenarios indicate that attempts to improve air quality can result in a net negative effect on crop production in areas dominated by the PM effect. However, we caution that the uncertainty in this assessment is large, due to the uncertainty associated with crop response to changes in diffuse radiation; this highlights that a more detailed physiological study of this response for common cultivars is crucial.
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
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.
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.
Sugarcane for bioenergy production: an assessment of yield and regulation of sucrose content.
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.
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.