102431 A Simple Maize and Soybean Phenology Model to Perform Climate Analysis and Weather-Related Risk Assessment.

Poster Number 321-613

See more from this Division: ASA Section: Climatology and Modeling
See more from this Session: Climatology and Modeling Poster

Tuesday, November 8, 2016
Phoenix Convention Center North, Exhibit Hall CDE

Diego N. L. Pequeno1, Clyde W. Fraisse1, Noemi Guindin-Garcia2 and Carol Crawford3, (1)Agricultural and Biological Engineering, University of Florida, Gainesville, FL
(2)National Agricultural Statistics Service, USDA - United States Department of Agriculture, Hyattsville, MD
(3)National Agricultural Statistics Service, United States Department of Agriculture, Washington, DC
Abstract:
Assessment of weather-related risks are becoming very important mainly as a climate change scenarios adaptation that could help agricultural producers to develop management strategies taking into account the sensitivity of specific plant developmental phases, reducing the risk of economic losses and increasing profits. The objective of this research was to study climate-related risks during maize and soybean phenological phases in Nebraska. The model was calibrated using 14 years of field experimental data at three locations in Nebraska. 30 years of historical weather data was used to calculate risk probabilities during each phenological phase of maize and soybean cultivars. The extreme weather events considered were high temperature, frost damage, excess of rain, and dry spell events during each plant phenological phase. The maize and soybean phenology data were simulated using a standalone Maize and Soybean Phenology Model, based on the CERES-Maize and CROPGRO-Soybean crop models. The phenology models were efficient in simulating maize and soybean development with good accuracy, and could be used for weather-related risks assessment based on historical analysis of weather extremes events.

See more from this Division: ASA Section: Climatology and Modeling
See more from this Session: Climatology and Modeling Poster