Agriculture

Dynamic geospatial modeling of mycotoxin contamination of corn in Illinois: unveiling critical factors and predictive insights with machine learning
Mycotoxin contamination of corn is a pervasive problem that negatively impacts human and animal health and causes economic losses to …
Lina Castano-Duque, Edwin Winzeler, Joshua M. Blackstock, Cheng Liu, Noemi Vergopolan, Marlous Focker, Kristin Barnett, Phillip Ray Owens, H. J. van der Fels-Klerx, Martha M. Vaughan, Kanniah Rajasekaran
PDF DOI
Dynamic geospatial modeling of mycotoxin contamination of corn in Illinois: unveiling critical factors and predictive insights with machine learning
How Much Control do Smallholder Maize Farmers Have Over Yield?
Smallholder agriculture is critical for current and future food security, yet quantifying the sources of smallholder yield variance …
Michael Cecil, Allan Chilenga, Charles Chisanga, Nicolas Gatti, Natasha Krell, Noemi Vergopolan, Kathy Baylis, Kelly Caylor, Tom Evans, Megan Konar, Justin Sheffield, Lyndon Estes
PDF DOI
How Much Control do Smallholder Maize Farmers Have Over Yield?
Is Closing the Agricultural Yield Gap a “Risky” Endeavor?
Sub-Saharan Africa (SSA) has the climatic and biophysical potential to grow the crops it needs to meet rapidly growing food demand; …
Nicolas Gatti, Michael Cecil, Kathy Baylis, Lyndon Estes, Jordan Blekking, Thomas Heckelei, Noemi Vergopolan, Tom Evans
PDF DOI
Is Closing the Agricultural Yield Gap a “Risky” Endeavor?
A comprehensive assessment of in situ and remote sensing soil moisture data assimilation in the APSIM model for improving agricultural forecasting across the U.S. Midwest
This study provides a framework for direct integration of soil moisture observations collected from soil sensors and satellite imagery into process-based crop models for improving the representation of agricultral systems. The performance of this framework was evaluated across 19 site-years for crop yield, NDVI, soil moisture, tile flow drainage and nitrate leaching.
Marissa Kivi, Noemi Vergopolan, Hamze Dokoohaki
PDF DOI
A comprehensive assessment of in situ and remote sensing soil moisture data assimilation in the APSIM model for improving agricultural forecasting across the U.S. Midwest
Field-scale Crop Yield Prediction
Satellite observations, physical models, and machine learning combined can enable crop yield prediction at high spatial resolution at data-scarse regions. Learn more about it here.
Last updated on Sep 11, 2023
Field-scale Crop Yield Prediction
From Hydroclimate Data to Science-Informed Decisions
Integrating computational models and hydroclimate data for actionable agriculture decision-making. Towards resilience and adaptability in a changing climate.
Last updated on Sep 11, 2023
From Hydroclimate Data to Science-Informed Decisions
A global near-real-time soil moisture index monitor for food security using integrated SMOS and SMAP
Soil Moisture (SM) is a direct measure of agricultural drought. While there are several global SM indices, none of them directly use SM …
Sara Sadri, Ming Pan, Yoshihide Wada, Noemi Vergopolan, Justin Sheffield, James S. Famiglietti, Yann Kerr, Eric F. Wood
PDF Cite DOI
A global near-real-time soil moisture index monitor for food security using integrated SMOS and SMAP
Cognitive Biases about Climate Variability in Smallholder Farming Systems in Zambia
Given the varying manifestations of climate change over time and the influence of climate perceptions on adaptation, it is important to …
Kurt B. Waldman, Noemi Vergopolan, Shahzeen Z. Attari, Justin Sheffield, Lyndon D. Estes, Kelly K. Caylor, Tom P. Evans
PDF Cite DOI
Cognitive Biases about Climate Variability in Smallholder Farming Systems in Zambia
Comparing empirical and survey-based yield forecasts in a dryland agro-ecosystem
Accurate crop yield forecasts before harvest are crucial for providing early warning of agricultural losses, so that policy-makers can …
Yi Zhao, Noemi Vergopolan, Kathy Baylis, Jordan Blekking, Kelly Caylor, Tom Evans, Stacey Giroux, Justin Sheffield, Lyndon Estes
PDF Cite DOI