Novel process harnesses machine learning to reveal groups of genes that determine how efficiently plants use nitrogen.
Novel process harnesses machine learning to reveal groups of genes that determine how efficiently plants use nitrogen.
New York University scientists are using artificial intelligence to determine which genes collectively govern nitrogen use efficiency in plants such as corn, with the goal of helping farmers improve their crop yields and minimize the cost of nitrogen fertilizers.
“By identifying genes-of-importance to nitrogen utilization, we can select for or even modify certain genes to enhance nitrogen use efficiency in major US crops like corn,” said Gloria Coruzzi, the Carroll & Milton Petrie Professor in NYU’s Department of Biology and Center for Genomics and Systems Biology and the senior author of the study, which appears in the journal The Plant Cell.
In the last 50 years, farmers have been able to grow larger crop yields thanks to major improvements in plant breeding and fertilizers, including how efficiently crops uptake and use nitrogen, the key component of fertilizers.
Read more at New York University
Image: Corn growing in the Irene Rose Sohn Zegar Memorial Greenhouse on the top floor of NYU’s Center for Genomics and Systems Biology. (Credit: Tracey Friedman/NYU)
