Crop Challenge in Analytics Award

Sponsored by Syngenta and the Analytics Society of INFORMS

Winning material: Speeding up maize hybrids breeding schemes using machine learning

Purpose of the Award

As our world population increases and arable land decreases, it becomes vital to improve the productivity of the agricultural land available. Companies like Syngenta strive to provide varieties of their crops to meet this need. 
Every year farmers have to make decisions about which soybean seeds to plant given information about different soybean varieties and knowledge about the soil and climate at their respective farms. These annual decisions are critical - after a variety is planted, the decision is irreversible. Unusual weather patterns can have disastrous impacts on crops.

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Past Awardees

2018 Second Place
Jhonathan Pedroso Rigal dos Santos, Universidade Federal de Lavras
2018 Third Place
Saeed Khaki, Iowa State University Hans Mueller, Iowa State University Lizhi Wang, Iowa State University