scholarly journals Maize yield loss risk under droughts in observations and crop models in the United States

2020 ◽  
Author(s):  
Guoyong Leng
Keyword(s):  
United States ◽  
Yield Loss ◽  
Maize Yield ◽  
The United States ◽  
Crop Models

scholarly journals Divergent responses of maize yield to precipitation in the United States

2021 ◽  
Author(s):  
Ru Xu ◽  
Yan Li ◽  
Kaiyu Guan ◽  
Lei Zhao ◽  
Bin Peng ◽  
...  
Keyword(s):  
United States ◽  
Spatial Heterogeneity ◽  
Temperature Response ◽  
Maize Yield ◽  
The United States ◽  
Security Assessment ◽  
Crop Modeling ◽  
Crop Models ◽  
Precipitation Response ◽  
Precipitation Threshold

Abstract How maize yield responds to precipitation variability in space and time over broader scales is largely unknown compared with the well-understood temperature response, even though precipitation change is more erratic with greater spatial heterogeneity. Here, we develop a method to quantify the spatially explicit precipitation response of maize yield using statistical data and crop models in the contiguous United States. We find the precipitation responses are highly heterogeneous with inverted-U (40.3%) being the leading response type, followed by unresponsive (30.39 %), and linear increase (28.6%). The optimal precipitation threshold derived from inverted-U response exhibits considerable spatial variations, which is higher under wetter, hotter, and well-drainage conditions but lower under drier and poor-drainage conditions. Irrigation alters precipitation response by making yield either unresponsive to precipitation or having lower optimal thresholds than rainfed conditions. We further find that the observed precipitation responses of maize yield are misrepresented in crop models, with a too high percentage of increase type (59.0% versus 29.6%) and an overestimation in optimal precipitation threshold by ~90 mm. These two factors explain about 30% and 85% of the inter-model yield overestimation biases under extreme rainfall conditions. Our study highlights the large spatial heterogeneity and the key role of human management in the precipitation responses of maize yield, which need to be better characterized in crop modeling and food security assessment under climate change.

Potential yield loss in grain sorghum (Sorghum bicolor) with weed interference in the United States

2020 ◽  
Vol 34 (4) ◽  
pp. 624-629 ◽  
Author(s):  
J. Anita Dille ◽  
Phillip W. Stahlman ◽  
Curtis R. Thompson ◽  
Brent W. Bean ◽  
Nader Soltani ◽  
...  
Keyword(s):  
United States ◽  
Weed Control ◽  
Weed Management ◽  
Yield Loss ◽  
Science Research ◽  
The United States ◽  
Grain Sorghum ◽  
Control Cost ◽  
Potential Yield ◽  
Weed Interference

AbstractPotential yield losses in grain sorghum due to weed interference based on quantitative data from the major grain sorghum-growing areas of the United States are reported by the WSSA Weed Loss Committee. Weed scientists and extension specialists who researched weed control in grain sorghum provided data on grain sorghum yield loss due to weed interference in their region. Data were requested from up to 10 individual experiments per calendar year over 10 yr between 2007 and 2016. Based on the summarized information, farmers in Arkansas, Kansas, Missouri, Nebraska, South Dakota, and Texas would potentially lose an average of 37%, 38%, 30%, 56%, 61%, and 60% of their grain sorghum yield with no weed control, and have a corresponding annual monetary loss of US $19 million, 302 million, 7 million, 32 million, 25 million, and 314 million, respectively. The overall average yield loss due to weed interference was estimated to be 47% for this grain sorghum-growing region. Thus, US farmers would lose approximately 5,700 million kg of grain sorghum valued at approximately US $953 million annually if weeds are not controlled. With each dollar invested in weed management (based on estimated weed control cost of US $100 ha−1), there would be a return of US $3.80, highlighting the return on investment in weed management and the importance of continued weed science research for sustaining high grain sorghum yield and profitability in the United States.

Global contribution of climate variability and trends to maize yield change in observations and crop models during 1980-2010

2020 ◽  
Author(s):  
Xiaomeng Yin ◽  
Guoyong Leng
Keyword(s):  
Climate Change ◽  
Climate Variability ◽  
Statistical Model ◽  
Yield Loss ◽  
Climate Change Impacts ◽  
Maize Yield ◽  
Climate Impacts ◽  
Future Climate Change ◽  
Crop Models ◽  
Process Based Models

<p>Understanding historical crop yield response to climate change is critical for projecting future climate change impacts on yields. Previous assessments rely on statistical or process-based crop models, but each has its own strength and weakness. A comprehensive comparison of climate impacts on yield between the two approaches allows for evaluation of the uncertainties in future yield projections. Here we assess the impacts of historical climate change on global maize yield for the period 1980-2010 using both statistical and process-based models, with a focus on comparing the performances between the two approaches. To allow for reasonable comparability, we develop an emulator which shares the same structure with the statistical model to mimic the behaviors of process-based models. Results show that the simulated maize yields in most of the top 10 producing countries are overestimated, when compared against FAO observations. Overall, GEPIC, EPIC-IIASA and EPIC-Boku show better performance than other models in reproducing the observed yield variations at the global scale. Climate variability explains 42.00% of yield variations in observation-based statistical model, while large discrepancy is found in crop models. Regionally, climate variability is associated with 55.0% and 52.20% of yield variations in Argentina and USA, respectively. Further analysis based on process-based model emulator shows that climate change has led to a yield loss by 1.51%-3.80% during the period 1980-1990, consistent with the estimations using the observation-based statistical model. As for the period 1991-2000, however, the observed yield loss induced by climate change is only captured by GEPIC and pDSSAT. In contrast to the observed positive climate impact for the period 2001-2010, CLM-Crop, EPIC-IIASA, GEPIC, pAPSIM, pDSSAT and PEGASUS simulated negative climate effects. The results point to the discrepancy between process-based and statistical crop models in simulating climate change impacts on maize yield, which depends on not only the regions, but also the specific time period. We suggest that more targeted efforts are required for constraining the uncertainties of both statistical and process-based crop models for future yield predictions. </p>

scholarly journals Phenotypic Diversity of Puccinia helianthi (Sunflower Rust) in the United States from 2011 and 2012

Plant Disease ◽  
2015 ◽  
Vol 99 (11) ◽  
pp. 1604-1609 ◽  
Author(s):  
Andrew J. Friskop ◽  
Thomas J. Gulya ◽  
Robert M. Harveson ◽  
Ryan M. Humann ◽  
Maricelis Acevedo ◽  
...  
Keyword(s):  
United States ◽  
Resistance Genes ◽  
Yield Loss ◽  
Phenotypic Diversity ◽  
The United States ◽  
Puccinia Helianthi ◽  
Differential Set ◽  
Hybrid Selection ◽  
First Time

Puccinia helianthi, causal agent of sunflower rust, is a macrocyclic and autoecious pathogen. Widespread sexual reproduction of P. helianthi was documented in North Dakota and Nebraska for the first time in 2008 and has since frequently occurred. Concurrently, an increase in sunflower rust incidence, severity, and subsequent yield loss on sunflower has occurred since 2008. Rust can be managed with resistance genes but determination of virulence phenotypes is important for effective gene deployment and hybrid selection. However, the only P. helianthi virulence data available in the United States was generated prior to 2009 and consisted of aggregate virulence phenotypes determined on bulk field collections. The objective of this study was to determine the phenotypic diversity of P. helianthi in the United States. P. helianthi collections were made from cultivated, volunteer, and wild Helianthus spp. at 104 locations across seven U.S. states and one Canadian province in 2011 and 2012. Virulence phenotypes of 238 single-pustule isolates were determined on the internationally accepted differential set. In total, 29 races were identified, with races 300 and 304 occurring most frequently in 2011 and races 304 and 324 occurring most frequently in 2012. Differences in race prevalence occurred between survey years and across geography but were similar among host types. Four isolates virulent to all genes in the differential set (race 777) were identified. The resistance genes found in differential lines HA-R3 (R4b), MC29 (R2 and R10), and HA-R2 (R5) conferred resistance to 96.6, 83.6, and 78.6% of the isolates tested, respectively.

scholarly journals Soybean Yield Loss Estimates Due to Diseases in the United States and Ontario, Canada, from 2010 to 2014

2017 ◽  
Vol 18 (1) ◽  
pp. 19-27 ◽  
Author(s):  
Tom W. Allen ◽  
Carl A. Bradley ◽  
Adam J. Sisson ◽  
Emmanuel Byamukama ◽  
Martin I. Chilvers ◽  
...  
Keyword(s):  
United States ◽  
Soybean Cyst Nematode ◽  
Yield Loss ◽  
Research Policy ◽  
Economic Loss ◽  
Macrophomina Phaseolina ◽  
The United States ◽  
Yield Losses ◽  
Soybean Yield ◽  
Soybean Diseases

Annual decreases in soybean (Glycine max L. Merrill) yield caused by diseases were estimated by surveying university-affiliated plant pathologists in 28 soybean-producing states in the United States and in Ontario, Canada, from 2010 through 2014. Estimated yield losses from each disease varied greatly by state or province and year. Over the duration of this survey, soybean cyst nematode (SCN) (Heterodera glycines Ichinohe) was estimated to have caused more than twice as much yield loss than any other disease. Seedling diseases (caused by various pathogens), charcoal rot (caused by Macrophomina phaseolina (Tassi) Goid), and sudden death syndrome (SDS) (caused by Fusarium virguliforme O’Donnell & T. Aoki) caused the next greatest estimated yield losses, in descending order. The estimated mean economic loss due to all soybean diseases, averaged across U.S. states and Ontario from 2010 to 2014, was $60.66 USD per acre. Results from this survey will provide scientists, breeders, governments, and educators with soybean yield-loss estimates to help inform and prioritize research, policy, and educational efforts in soybean pathology and disease management.

scholarly journals Emergence of a Novel Population of Puccinia striiformis f. sp. tritici in Eastern United States

2008 ◽  
Vol 98 (6) ◽  
pp. 632-639 ◽  
Author(s):  
S. G. Markell ◽  
E. A. Milus
Keyword(s):  
United States ◽  
Yield Loss ◽  
Fragment Length Polymorphism ◽  
Puccinia Striiformis ◽  
Genotypic Variation ◽  
Sampling Strategy ◽  
The United States ◽  
Aflp Markers ◽  
Eastern United States ◽  
Virulence Phenotype

The geographic range of stripe rust of wheat, caused by Puccinia striiformis f. sp. tritici, has increased dramatically since 2000 in the United States. Yield losses to the disease have been most severe in the eastern United States, where measurable yield loss had been rare prior to 2000. The objective of this study was to examine the phenotypic and genotypic variation among isolates of P. striiformis f. sp. tritici collected from populations in the eastern United States before and since 2000. Virulence phenotype and amplified fragment length polymorphism (AFLP) markers were used to examine 42 isolates collected between 1960 and 2004. In addition, the genetic structure of 59 isolates collected in 2005 using a hierarchical sampling strategy was examined. The data indicated that the contemporary isolates (collected since 2000) were very distinct from older isolates (collected before 2000) based on virulence and AFLP markers, and that the old population prevalent before 2000 may have been replaced by the contemporary population. The old and new populations appear to be genetically distinct and may represent an exotic introduction rather than a mutation in isolates of the old population.

Potential Corn Yield Losses from Weeds in North America

2016 ◽  
Vol 30 (4) ◽  
pp. 979-984 ◽  
Author(s):  
Nader Soltani ◽  
J. Anita Dille ◽  
Ian C. Burke ◽  
Wesley J. Everman ◽  
Mark J. VanGessel ◽  
...  
Keyword(s):  
United States ◽  
Yield Loss ◽  
Commodity Price ◽  
The United States ◽  
Corn Yield ◽  
Yield Losses ◽  
Weed Interference ◽  
Net Returns ◽  
Small Plot ◽  
Statistics Canada

Crop losses from weed interference have a significant effect on net returns for producers. Herein, potential corn yield loss because of weed interference across the primary corn-producing regions of the United States and Canada are documented. Yield-loss estimates were determined from comparative, quantitative observations of corn yields between nontreated and treatments providing greater than 95% weed control in studies conducted from 2007 to 2013. Researchers from each state and province provided data from replicated, small-plot studies from at least 3 and up to 10 individual comparisons per year, which were then averaged within a year, and then averaged over the seven years. The resulting percent yield-loss values were used to determine potential total corn yield loss in t ha−1 and bu acre−1 based on average corn yield for each state or province, as well as corn commodity price for each year as summarized by USDA-NASS (2014) and Statistics Canada (2015). Averaged across the seven years, weed interference in corn in the United States and Canada caused an average of 50% yield loss, which equates to a loss of 148 million tonnes of corn valued at over U.S.$26.7 billion annually.

scholarly journals An analysis of ozone damage to historical maize and soybean yields in the United States

2015 ◽  
Vol 112 (46) ◽  
pp. 14390-14395 ◽  
Author(s):  
Justin M. McGrath ◽  
Amy M. Betzelberger ◽  
Shaowen Wang ◽  
Eric Shook ◽  
Xin-Guang Zhu ◽  
...  
Keyword(s):  
United States ◽  
Food Production ◽  
Yield Loss ◽  
Cost Benefit ◽  
Ground Level ◽  
The United States ◽  
Yield Losses ◽  
Ground Level Ozone ◽  
Food And Feed ◽  
Actual Yield

Numerous controlled experiments find that elevated ground-level ozone concentrations ([O3]) damage crops and reduce yield. There have been no estimates of the actual yield losses in the field in the United States from [O3], even though such estimates would be valuable for projections of future food production and for cost–benefit analyses of reducing ground-level [O3]. Regression analysis of historical yield, climate, and [O3] data for the United States were used to determine the loss of production due to O3 for maize (Zea mays) and soybean (Glycine max) from 1980 to 2011, showing that over that period production of rain-fed fields of soybean and maize were reduced by roughly 5% and 10%, respectively, costing approximately $9 billion annually. Maize, thought to be inherently resistant to O3, was at least as sensitive as soybean to O3 damage. Overcoming this yield loss with improved emission controls or more tolerant germplasm could substantially increase world food and feed supply at a time when a global yield jump is urgently needed.

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