Enhancing grapevine breeding efficiency through genomic prediction and selection index

Grapevine (Vitis vinifera) breeding reaches a critical point. New cultivars are released every year with resistance to powdery and downy mildews. However, the traditional process remains time-consuming, taking 20-25 years, and demands the evaluation of new traits to enhance grapevine adaptation to climate change. Until now, the selection process has relied on phenotypic data and a limited number of molecular markers for simple genetic traits such as resistance to pathogens, without a clearly defined ideotype, and was carried out on a large scale. To accelerate the breeding process and address these challenges, we investigated the use of genomic prediction, a methodology using molecular markers to predict genotypic values. In our study, we focused on 2 existing grapevine breeding programs: Rosé wine and Cognac production. In these programs, several families were created through crosses of emblematic and interspecific resistant varieties to powdery and downy mildews. Thirty traits were evaluated for each program, using 2 genomic prediction methods: Genomic Best Linear Unbiased Predictor and Least Absolute Shrinkage Selection Operator. The results revealed substantial variability in predictive abilities across traits, ranging from 0 to 0.9. These discrepancies could be attributed to factors such as trait heritability and trait characteristics. Moreover, we explored the potential of across-population genomic prediction by leveraging other grapevine populations as training sets. Integrating genomic prediction allowed us to identify superior individuals for each program, using multivariate selection index method. The ideotype for each breeding program was defined collaboratively with representatives from the wine-growing sector.

Investigating caloric values and consumers' perceptions of Nova Scotia rosé wines

In Nova Scotia, Canada, wine production has been increasing, yet little research has been done to identify and classify the sensory properties of Nova Scotia (NS) rosé wines. The first objective of this study was to identify the attributes consumers use to describe NS rosé wines. The second aim was to identify if presenting caloric labels on wine bottles would impact consumers' sensory perception. The first trial asked consumers (n = 85) to use projective mapping (PM) and ultra-flash profiling (UFP) to describe NS rosé wines (n = 8). In the second trial, consumers (n = 260) were asked to complete a check-all-that-apply (CATA) questionnaire, using the most frequently cited attributes from the PM and UFP trial, and to score their liking on 9-point hedonic scales (n = 4). Each wine was evaluated without a label and with each of the four fabricated caloric values, low (15 Calories), normal (100 Calories), high (180 Calories), and highest (240 Calories) per one serving. The projective mapping trial found that there were two main categories of rosé wines identified by consumers, those with fruit flavour and those lacking in fruit flavour. The penalty analysis from the consumer trial demonstrated that fruit attributes drove consumer liking of rosé wine. The consumer trial also displayed no significant difference between the caloric value and liking of rosé wines, even when the results were separated based on gender. Therefore, the findings support that the disclosure of caloric values on bottles will not influence consumers' sensory perceptions of wine. For future research, complete nutrition labels and not just calories alone should be used to determine their effect on consumers' perceptions.