Big Data Helps Farmers Adapt to Climate Variability
The study, published in Scientific Reports, is the first to precisely quantify soil and landscape features and spatial and temporal yield variations in response to climate variability. It is also the first to use big data to identify areas within individual fields where yield is unstable.
Between 2007 and 2016, the U.S. economy took an estimated $536 million economic hit because of yield variation in unstable farmland caused by climate variability across the Midwest. More than one-quarter of corn and soybean cropland in the region is unstable. Yields fluctuate between over-performing and underperforming on an annual basis.
Bruno Basso, MSU Foundation professor of earth and environmental sciences, and his postdoctoral research fellow, Rafael Martinez-Feria, set out to address the key pillars of the National Institute for Food and Agriculture’s Coordinated Agricultural Project that Basso has led since 2015.
“NIFA’s collaboration with the Michigan State University team has led to various papers with students and postdoctoral fellows. It supports one of its critical mandates to fund innovative agricultural science and develop the next generation of scientists,” said Scott Angle, NIFA director.
The study was funded by USDA NIFA (awards 2015-68007-23133, 2018- 67003-27406) and AgBioResearch.
Read the full MSU article.