Primary metabolite-based predictive modeling of fruit quality traits across six strawberry (Fragaria × ananassa Duch.) F1 populations.

This study investigated parental influences on primary metabolite composition and metabolic features consistently associated with fruit quality traits using 289 samples from six strawberry F1 populations. Primary metabolite profiling revealed substantial metabolic variation among populations and its relationships with total soluble solids (TSS), titratable acidity (TA), and the TSS/TA ratio. Malic acid and asparagine were positively correlated with mid-parent values, consistent with additive parental contributions across populations. Metabolite-based predictive models, Elastic Net and PLSR, achieved moderate to relatively high predictive performance, demonstrating robust applicability across populations. Quinic, citric, and malic acids, together with myo-inositol and xylose, were identified as key predictors for quality traits. Furthermore, TSS was more strongly associated with the ratio of major sugars to pentoses than with total sugar content, suggesting the relevance of sugar composition to TSS variation. These findings demonstrate that specific metabolic signatures enable robust evaluation of fruit quality traits across diverse strawberry populations.