AI boosts strawberry farming with disease detection tech

AI model designed by Western researchers offers nearly 99% accuracy in predicting strawberry ripeness and detecting diseases.
Researchers at Western University have developed AI that detects strawberry diseases and predicts ripeness, helping farmers reduce waste and improve crop quality.

Researchers at Western University have developed an AI model that detects strawberry diseases and predicts ripeness with nearly 99% accuracy. The system, designed by Joshua Pearce and Soodeh Nikan, could significantly enhance crop quality and reduce waste. Tested in a controlled hydroponic environment, the technology aims to extend Canada’s strawberry growing season while improving fruit quality.

The model is free and open-source, enabling farmers to tailor it to their needs. It can notify them via email or phone when diseases are detected or fruit is ripe. This adaptable AI system could prove crucial for increasing agricultural efficiency.

By minimising food waste and lowering production costs, the AI model has the potential to reduce grocery prices for consumers. Researchers hope the technology will support food security and help farmers meet growing demands for fresh produce.

Future plans involve testing the AI outdoors, possibly with drones monitoring larger fields. The innovation could bring smarter, more sustainable farming to outdoor environments, further boosting efficiency in agriculture.