Machine learning helps determine health of soybean fields

esearchers from The Ohio State University have developed a new tool using drones and machine learning to monitor crop health, particularly focusing on defoliation in soybeans. By analyzing over 97,000 images of soybean fields, the team used neural networks to accurately identify areas affected by defoliation due to pests, diseases, or stress. Their deep learning tool, Defonet, outperformed existing systems in accuracy, precision, and efficacy. This technology could be a game-changer in agricultural decision-making, enabling early detection of crop issues, optimizing yields, and potentially preventing large-scale crop losses.