Monica’s PhD project focusses on the application of deep learning to analyse plant stress and disease detection. Deep learning refers to statistical models to identify patterns within large and complex data, and then classify and make predictions about data using the patterns identified.
The trained algorithm can be used to spot diseased areas in crop fields, enabling farmers to act fast to protect their production. The information from the algorithm can be sent directly to field machines, which will have instructions for dealing with each specific threat to production. The creation of improved crop disease and stress recognition models are crucial to preventing yield loss.