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There is an urgent need for making fruit tree breeding more efficient while adapting methods to low-input agriculture. Our goal is to define resilient ideotypes (i.e.  type of trees which can adapt to the presence of pests and diseases) and to predict these ideotypes based on genetic information to be able to identify them quickly among breeding material. To this aim, it is crucial to screen a large genetic diversity and to measure tree health in a precise manner.

In this project we will test new phenotyping technologies (drones, smartphone) to measure the sanitary state of trees in core-collections of peach and apricot managed under low phytosanitary protection. Next, genomic prediction will be used to assess the potential of genomic selection for resilience traits by modelling the link between phenotype and genotype.