Morphological Marker-Assisted Breeding and Selection (MoMABS) in Peach

AI for Peach Breeding – This project harnesses artificial intelligence for data-driven breeding, aiming to develop innovative analytics and selection strategies.

Key data

Description

This project, focused on the breeding of Swiss peach specialties, aims to engage in cutting-edge technologies through interdisciplinary collaboration.

Morphological markers associated with resistance to the five most significant peach pathogens (Podosphaera pannosa var. persicae, Leucostoma persoonii, Taphrina deformans, Monilia/Monilinia sp., Myzus persicae) are to be identified through a combination of established and emerging technologies, including field studies, marker-assisted selection, and artificial intelligence.

The objectives are twofold:

To enable faster and more reliable selection of crossing partners based on morphological markers;
To streamline the selection of seedlings resulting from these crosses.

Our subproject focuses on aspects of data analytics using AI.