Digital Phenotyping with Soybean Imagery

This project will mine several different types of soybean imagery collected internally at Inari. The data sets comprise thousands of images across hundreds of plant lines with unique genetics. Sub-data sets focus on different parts of soybean anatomy collected at various growth stages. Images are labelled or segmented based on phenotype to facilitate supervised and unsupervised machine learning algorithms to further enrich the imagery data with new phenotypes and related features.