Machine Learning Reveals Important Genes to Help Corn Grow with Less Fertilizer

A study conducted by researchers at New York University (NYU) together with their colleagues from National Taiwan University, Purdue University, and the University of Illinois has found genes, through machine learning, that help crops grow with less fertilizer and predict additional traits in plants and disease outcomes in animals.

In the Nature Communications paper, it was indicated that the research team used machine learning, a type of artificial intelligence used to detect patterns in data. As a proof-of-concept, the researchers showed that genes whose responsiveness to nitrogen is evolutionarily conserved between two diverse plant species—Arabidopsis, and varieties of corn—significantly improved the ability of machine learning models to predict genes of importance for how efficiently plants use nitrogen, a crucial nutrient for plants and the main component of fertilizer. Crops that use nitrogen more efficiently grow better and require less fertilizer, which has economic and environmental benefits.