Artificial Intelligence Algorithm Used to Predict Agriculture Yield

It is predicted that the precision agriculture market will reach $12.9 billion by 2027. With this increase, there is a need for sophisticated data-analysis solutions that are capable of guiding management decisions in real-time. A new methodology has been developed by an interdisciplinary group at the University of Illinois, and it aims to efficiently and accurately process precision agricultural data. Nicolas Martin is an assistant professor in the Department of Crop Sciences at Illinois and co-author of the study. "We're trying to change how people run agronomic research. Instead of establishing a small field plot, running statistics, and publishing the means, what we're trying to do involves the farmer far more directly. We are running experiments with farmers' machinery in their own fields. We can detect site-specific responses to different inputs. And we can see whether there's a response in different parts of the field," he says.