Revolutionizing harvesting, Israeli researchers harnessed artificial intelligence and technology to offer a cost-effective and non-invasive way to predict the quality parameters of tomatoes.

Led by Dr. David Helman of Hebrew University in collaboration with Bar-Ilan University and the Volcani Institute – Agricultural Research Organization, the researchers used a handheld hyperspectral camera to get detailed insights into tomatoes, then used machine learning algorithms to process the data. The team found the results were remarkably accurate.

“Our research aims to bridge the gap between advanced imaging technology, AI, and practical agricultural applications,” said Helman. “This work has the potential to revolutionize quality monitoring not only in tomatoes but also in other crops. Our next step is to build a low-cost device, ToMAI-SENS, for use across the fruit value chain, from farms to consumers.”