Genetic dissection, genomic prediction, and temporal dynamics of major fruit quality traits in cold-hardy berry crops

Abstract

Berry crops such as grapes (Vitis spp.) and haskap (Lonicera caerulea L.) are valuable horticultural commodities; however, the genetic basis of fruit quality traits in cold-hardy hybrid grapes remains largely unexplored, while substantial knowledge gaps exist in understanding fruit ripening dynamics in haskap. This dissertation applies genomic tools and time-series phenotyping to enhance the understanding of key fruit quality traits in these crops. The first study employs genome-wide association studies (GWAS) to identify genetic loci associated with fruit chemistry traits in a cold-hardy hybrid grape population. Multi-year and multi-harvest phenotyping revealed stable quantitative trait loci (QTLs) linked to sugars, acids, and berry mass, with functional annotations highlighting candidate genes involved in sugar transport and organic acid metabolism. The second study explores the efficiency of genomic selection (GS) models in predicting fruit quality traits in grapes. Using univariate and multivariate GS approaches, the study evaluates different cross-validation strategies, demonstrating that incorporating multi-trait and multi- environment data improves predictive accuracy and selection efficiency for grape breeding. The final study focuses on haskap, a relatively new berry crop in North America, where fruit ripening dynamics are not well characterized. By analyzing repeated measurements across developmental stages, this study tracks changes in sugar accumulation, acid degradation, and berry mass across 14 commercially relevant haskap cultivars and one unreleased breeding line, providing insights into cultivar-specific ripening patterns and optimal harvest timing. Collectively, these projects explored previously unstudied or under-researched aspects of fruit quality in these berry crops, contributing valuable knowledge to the field and establishing a foundation for future research.