En cours (2022‑2023)
CE PROJET EST FINANCÉ DANS LE CADRE DU PROGRAMME « PROJETS ÉMERGENTS DU RQRAD »
The continuous rapid growth in global population and climate change is resulting in more conscientious decisions in consumers at the time of buying sustainably-produced food products; In this program, we will develop AI-driven computational methods to characterize architectures of chickpea (Cicer arietinum) plants in 3D space with the aim of releasing cultivars adapted to Quebec conditions. The McGill University Pulse Breeding and Genetics Laboratory has initiated the breeding activities, and a panel of 550 chickpea accessions will be used in this program. Point clouds of chickpea plants will be reconstructed at three different growing stages; the resulting data will be used to develop 3D deep learning-based methods for plant instance segmentation and architectural trait analysis. Based on the gained insights, we will conduct breeding and development of elite chickpea lines for advanced yield trials, which will be conducted at the Emile A. Lods farm of Macdonald campus of McGill University.
- Shangpeng Sun (Université McGill)
Membres de l'équipe
- Valerio Hoyos-Villegas (Université McGill)
Axes(s) de recherche
- Axe 3 - Outils numériques, agriculture de précision et données massives