According to the National Agricultural Statistics Service (http://www.nass.usda.gov/Statistics_by_State/Ohio/Publications/Crop_Prog...) for the week ending 7-27-14, 69% of the state’s corn was silking and 9% was in the dough stage. Questions are being asked about how this year’s weather has impacted expected yield to date, and how growing conditions during grain fill, the 8 to 9 weeks following silking, may affect final yields.
To help estimate yield and the impact of weather can impact those yields, OSU is collaborating with a team from the University of Nebraska and Robert B. Daugherty Water for Food Institute to use the Hybrid-Maize model (http://hybridmaize.unl.edu) to forecast potential corn yields across the Corn Belt. Other universities collaborating in this effort include Kansas, Iowa, Illinois and Wisconsin
The Hybrid-Maize model estimates yield based on current and historical weather parameters with the assumption that plants stands are uniform; flooding and hail did not occur; and that typical management of nutrients, insects, diseases, and weeds are not limiting (Licht, 2014). Yield estimates resulting from Hybrid-Maize become less variable as the season progresses because of less reliance on historical weather data. This helps in understanding how current season weather conditions affected corn growth up to the date of the simulation but also gives some projections of yield estimates for the remainder of the growing season.
The July 20 simulation indicate a high chance of above-average dryland yields in almost all simulated locations in the central and eastern Corn Belt (Iowa, Illinois, and Ohio). In the case of dryland corn, above-normal rainfall, coupled with low rates of daily water use due to low daytime temperature, are factors that have the largest contribution to above-average yield potential forecasts by Hybrid-Maize across the entire Corn Belt. Factors in 2014 that may result in lower yields than these forecasts even with optimal management include hail or flood damage as well as greater likelihood of foliar diseases. Also, given the large amount of rain in some areas, nitrogen leaching and/or denitrification may limit yields due to nitrogen deficiency if additional nitrogen was not applied to affected areas. Cooler than normal weather could increase the probability of an early killing frost at locations that were planted late, which would result in yields lower than currently forecast.
For more information concerning the July 20 simulation for the 25 Corn Belt locations considered, check the following “2014 Forecasted Corn Yields Based on July 20 Hybrid Maize Model Simulations” at http://cropwatch.unl.edu/archive/-/asset_publisher/VHeSpfv0Agju/content/2014-forecasted-corn-yields-based-on-hybrid-maize-model-simulations-as-of-july-20th.
In-season yield potential forecasts for the three Ohio test sites, Custar, S. Charleston, and Wooster, considered in this simulation are shown in Table 2.
Acknowledgements: The data presented here is part of larger yield forecasting project coordinated by Patricio Grassini, Haishun Yang, Roger Elmore and Kenneth Cassman from the Department of Agronomy and Horticulture, University of Nebraska-Lincolnand the Robert B. Dougherty Water for Food Institute.
Other sources: Licht, M. 2014. Corn Yield Predictions. Iowa State University Integrated Crop Management News. http://www.extension.iastate.edu/CropNews/2014/0725Licht.htm.