What if farmers could see a pest outbreak coming before the insect ever had a chance to damage their crop?
New research from Texas A&M AgriLife Research indicates that artificial intelligence, AI, can predict outbreaks much more accurately than traditional methods. The tool could dramatically improve how and when insect pest risks are identified and controlled.
In a study recently published in Ecological Informatics, scientists in the Texas A&M College of Agriculture and Life Sciences Department of Entomology used machine learning models to forecast populations of western flower thrips with notable accuracy, offering producers an early warning when pest pressure is building.
