Metabolomic phenotyping reveals the GxExS blind spot in berry fruit quality breeding.

Genomic selection (GS) has accelerated fruit quality improvement in strawberry, blueberry, and raspberry breeding, yet it operates under the assumption that genetic effects on quality metabolites are stable across environments and seasons. Recent metabolomics evidence challenges this assumption, revealing that Genotype × Environment × Season (GxExS) interactions can reshape metabolic profiles and reverse genotype rankings for consumer-relevant traits. In this review, (1) we evaluate the predictive capacity of GS and metabolomic phenotyping for fruit quality across the three major berry crops, (2) identify the GxExS gap as a critical barrier to the transferability of these predictions to field applications, and (3) propose multi-environment metabolomic evaluation as the missing layer to bridge this gap. Studies in blueberry have demonstrated that metabolomic and phenomic selection achieve comparable predictive accuracy to GS for quality traits, and that metabolite-based models can predict consumer liking. Yet these frameworks have been developed and validated predominantly within single environments, without systematic assessment of their stability across contrasting locations or years. Integrating metabolomic profiling into multi-environment breeding trials would enable the identification of genetically robust versus environmentally plastic metabolites, providing breeders with reliable selection targets for producing climate-resilient cultivars with consistent fruit quality.