Finalists for the 2021 Syngenta Crop Challenge in Analytics

Embodying the intersection of mathematics, big data and agriculture, the 2021 Syngenta Crop Challenge in Analytics competition focused on optimizing year-round corn hybrid breeding processes.

The finalists, listed in no particular order, are:

• Optimal Schedules for Corn Planting and Storage — Reena Kapoor and Rodolfo García-Flores affiliated with CSIRO Data61 (Australia).
• Scheduling Planting Time Through Developing an Optimization Model and Analysis of Time Series Growing Degree Units — Javad Ansarifar, Faezeh Akhavizadegan and Lizhi Wang from Iowa State University (U.S.).
• Optimizing Crop Planting Schedule Considering Planting Window & Harvesting Capacity — Saiara Samira Sajid and Guiping Hu from Iowa State University (U.S.).
• A Multiobjective, Soft Constraint Solution to the 2021 Syngenta Crop Challenge — Mingshi Cui, Kunting Qi and Byran Smucker from Miami University (U.S.).

For more information about the Syngenta Crop Challenge in Analytics, visit  ideaconnection.com/syngenta-crop-challenge.