Low-cost vision machine for high-throughput automated monitoring of heterotrophic seedling growth on wet paper support

In this communication, we propose a fully automated vision system to monitor the germination and elongation of seedlings positioned in a petri dish. While most existing systems use agar gel as transparent nutritive medium imaged in backlight, we demonstrate that although it provides a reduced contrast, not fully opaque paper can serve as efficient lower-cost medium preventing the well-known problem of seedling joining during elongation. Automatic tracking of elongating seedlings is realized with a minimal pathalgorithm. The three organs (radicle, hypocotyl, and cotyledon) are then segmented. Validation of the accuracy of the system is provided on sugar beet seedling by comparison with the expert-based ground truth

A computer vision tool for a high-throughput phenotyping of seedlings during elongation - Application to sugar beet

A computer vision tool for a high-throughput phenotyping of seedlings during elongation - Application to sugar bee

Imaging the early development of seeds

Imaging the early development of seeds