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Abstract
Genomic selection (GS), which uses estimated genetic potential based on genome-wide
genotype data for a breeding selection, is now widely accepted as an efficient method
to improve genetically complex traits. We assessed the potential of GS for increasing
soluble solids content and total fruit weight of tomato. A collection of big-fruited
F1 varieties was used to construct the GS models, and the progeny from crosses was
used to validate the models. The present study includes two experiments: a prediction
of a parental combination that generates superior progeny and the prediction of progeny
phenotypes. The GS models successfully predicted a better parent even if the phenotypic
value did not vary substantially between candidates. The GS models also predicted
phenotypes of progeny, although their efficiency varied depending on the parental
cross combinations and the selected traits. Although further analyses are required
to apply GS in an actual breeding situation, our results indicated that GS is a promising
strategy for future tomato breeding design.