Alexis Comar 'Phenomic Prediction as a Tool for Enhancing Functional Modeling of Plants'

Описание: Phenomic Prediction as a Tool for Enhancing Functional Modeling of Plants in a Breeding Context
Alexis Comar, Jérémy Labrosse, Jocelyn Gillet
HIPHEN SAS, Avignon, France

For the past decade, HIPHEN has established itself as a leader in high-throughput phenotyping, utilizing a range of technologies including drones, satellites, ground vehicles, and handheld systems to capture detailed plant traits. These traits, defined as the physical and measurable characteristics of plants, have been central to our work. In this presentation, we introduce a novel pipeline that not only estimates these traits but also leverages latent data spaces derived from images and videos to enhance predictive capabilities. This approach, known as phenomic selection, represents a significant advancement in plant breeding. We will showcase several concrete use cases, focusing on strawberries, corn, and sunflower, to demonstrate the practical applications and benefits of this innovative method in accelerating breeding programs.