The ability to single out healthy fruits/plants from those with problems and to selectively start the harvesting or apply a remedy without wasting resources or contaminating the environment is critical for precision farming. This project develops a unifying framework to combine different sensor modalities that include standard (e.g., RGB-D cameras) with novel sensors (e.g., gas sensors), methods for creating accurate maps to facilitate operations on a narrow scale with a smaller environment footprint, artificial intelligence algorithms for data processing and decision support, and applications to make relevant information easily visible to the farmer.