CIAT's data team reaches final stage of international agriculture data competition
If you were given datasets with genetic information and yields from trials of different experimental maize hybrids, along with information on soil conditions and recorded weather of a U.S. growing region, how will you predict the performance of these hybrids? And what if the genetic information dataset included an average of 12,000 genetic markers or unique DNA sequences to identify each hybrid? Those were the questions that the CIAT data analytics team needed to address as part of an international competition organized by agribusiness giant Syngenta in partnership with INFORMS, the largest international society of operations research, management science, and analytics practitioners.