Global agribusiness company Syngenta is at the forefront of using data analytics techniques to feed the world and help farmers overcome challenges. One way it encourages innovation to tackle these ambitious goals is with the Syngenta Crop Challenge, a global open innovation competition that invites participants to improve farm productivity. For the 2018 version of the contest, solvers were challenged to apply their analytics skills to develop models that predict how well corn hybrids will perform in untested locations.
This year’s winners hail from the International Center for Tropical Agriculture (CIAT) in Colombia, a not-for-profit dedicated to reducing poverty and hunger while protecting natural resources in developing countries. The team consisted of almost a dozen members and was headed by Dr. Daniel Jimenez an agronomist, data scientist and pioneer in the use of artificial intelligence in agriculture. He is also the Data-Driven Agronomy Community of Practice Lead at the CGIAR Platform for Big Data in Agriculture.
The team worked solidly for months on their solution, beating off stiff competition to take the USD $5,000 first prize.
Read the original article on Syngenta Crop Challenge – IdeaConnection.
