Pairing genomics and weather data to make crop predictions more powerful
AMES, Iowa – All farming is, in a sense, a prediction business. Crops are planted in anticipation they’ll grow and produce a bountiful harvest. Research led by Iowa State University agronomy professor Jianming Yu aims to give a major boost to agricultural predictions with powerful modeling tools that would benefit both breeders and farmers.
In a recent study, Yu’s team built a model to predict the flowering time and height of sorghum plants based on genomic analysis and early-season weather data. In blind tests of sorghum fields that weren’t included in the modeling data, Yu and his colleagues predicted flowering time with up to 74% accuracy and plant height up to 96%.
Similar models integrating genomics and environmental conditions could be used in other crops and to predict equally complex traits such as yield, said Yu, the Pioneer Hi-Bred Distinguished Chair in Maize Breeding and director of Raymond F. Baker Center for Plant Breeding.
“Getting information about what’s likely to happen ahead of time has tremendous value,” he said.
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Originally published by Iowa State University in August 2025.