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Flavor is among the most important traits valued by consumers of fresh fruits. Human perception of flavor occurs primarily through two main sensory inputs, taste and aroma. Through retronasal olfaction, volatile organic compounds (VOCs) emitted by the fruit are able to produce the sensation of aroma which when combined with gustatory inputs from the tongue together underly our perception of the thousands of flavors we experience throughout our lives. In blueberry, breeders have observed that some genotypes possess berries with unique 'floral' and 'sweet' flavor and aroma notes. The potential impact these characteristics might have on consumer acceptability is largely unknown and represents an opportunity to better understand how aroma attributes affect the perception of blueberry flavor. In this study, we dissected the main components of blueberry aroma and associated it with consumer predilections by pairing metabolomics with sensory analysis. Our contribution in this study is four-fold: (i) first, we differentiated genotypes with floral and sweet aroma notes and confirmed that such characteristics are preferred by consumers; (ii) at the chemical level, we showed that a group of eight terpenoid volatiles (p-cymene, myrtenal, linalool, L-carvenol, geranyl acetone, geranyl acetate, D-limonene and β-myrcene) constitute the primary metabolic group associated with these aroma sensations; (iii) we demonstrated that aromatic genotypes can be classified using metabolomics; and finally, (iv) we combined pedigree and metabolomic information and showed the importance of metabolomic data for flavor-assisted selection. Our findings open new avenues to explore the phenomenon of flavor in blueberries and also allow us to present an emerging view about flavor and provide a detailed blueprint of how this targeted trait could be addressed in fruit and vegetable breeding., (Copyright © 2022. Published by Elsevier Ltd.)

Although they are staple foods in cuisines globally, many commercial fruit varieties have become progressively less flavorful over time. Due to the cost and difficulty associated with flavor phenotyping, breeding programs have long been challenged in selecting for this complex trait. To address this issue, we leveraged targeted metabolomics of diverse tomato and blueberry accessions and their corresponding consumer panel ratings to create statistical and machine learning models that can predict sensory perceptions of fruit flavor. Using these models, a breeding program can assess flavor ratings for a large number of genotypes, previously limited by the low throughput of consumer sensory panels. The ability to predict consumer ratings of liking, sweet, sour, umami, and flavor intensity was evaluated by a 10-fold cross-validation, and the accuracies of 18 different models were assessed. The prediction accuracies were high for most attributes and ranged from 0.87 for sourness intensity in blueberry using XGBoost to 0.46 for overall liking in tomato using linear regression. Further, the best-performing models were used to infer the flavor compounds (sugars, acids, and volatiles) that contribute most to each flavor attribute. We found that the variance decomposition of overall liking score estimates that 42% and 56% of the variance was explained by volatile organic compounds in tomato and blueberry, respectively. We expect that these models will enable an earlier incorporation of flavor as breeding targets and encourage selection and release of more flavorful fruit varieties., Competing Interests: The authors declare no competing interest., (Copyright © 2022 the Author(s). Published by PNAS.)

Variations in volatile organic compound (VOC) type and content can result in noticeable differences in fruit aroma. The genus Vaccinium encompasses over 500 distinct species of berry-producing plants, several of which are important to commercial horticulture. Understanding which VOCs are produced by different members of this genus could greatly aid efforts to improve the aroma of multiple Vaccinium crops by breeding for desirable fruit volatiles. This review summarizes the published research available on this topic, examining prior work done to characterize the volatile profiles of blueberries, cranberries, bilberries, lingonberries, whortleberries, and other Vaccinium berries. In addition, analytical methodologies used to obtain Vaccinium berry volatile profiles are discussed. Possible future directions for Vaccinium berry volatile research are also examined.