Strawberry sweetness and consumer preference are enhanced by specific volatile compounds

Abstract

Breeding crops for improved flavor is challenging due to the high cost of sensory evaluation and the difficulty of connecting sensory experience to chemical composition. The main goal of this study was to identify the chemical drivers of sweetness and consumer liking for fresh strawberries (Fragaria × ananassa). Fruit of 148 strawberry samples from cultivars and breeding selections were grown and harvested over seven years and were subjected to both sensory and chemical analyses. Each panel consisted of at least 100 consumers, resulting in more than 15,000 sensory data points per descriptor. Three sugars, two acids and 113 volatile compounds were quantified. Consumer liking was highly associated with sweetness intensity, texture liking, and flavor intensity, but not sourness intensity. Partial least square analyses revealed 20 volatile compounds that increased sweetness perception independently of sugars; 18 volatiles that increased liking independently of sugars; and 15 volatile compounds that had positive effects on both. Machine learning-based predictive models including sugars, acids, and volatiles explained at least 25% more variation in sweetness and liking than models accounting for sugars and acids only. Volatile compounds such as γ-dodecalactone; 5-hepten-2-one, 6-methyl; and multiple medium-chain fatty acid esters may serve as targets for breeding or quality control attributes for strawberry products. A genetic association study identified two loci controlling ester production, both on linkage group 6 A. Co-segregating makers in these regions can be used for increasing multiple esters simultaneously. This study demonstrates a paradigm for improvement of fruit sweetness and flavor in which consumers drive the identification of the most important chemical targets, which in turn drives the discovery of genetic targets for marker-assisted breeding.

Profiles of Volatile and Phenolic Compounds as Markers of Ripening Stage in Candonga Strawberries

“…Regarding the 12 esters directly correlated to the Red-H3 strawberries ( Figure 3 B), methyl butyrate (E2), ethyl butyrate (E4), ethyl pentanoate (E8) and ethyl hexanoate (E11) have been reported as prominent components in several strawberry cultivars and historically recognized as crucial to the characteristic fruity notes of mature strawberries [ 41 , 42 ].…”

“…Recent studies have established that specific VOCs can enhance both the flavor and the sweetness perception in fresh strawberries, evaluating the overall acceptance of strawberry fruit by the statistical correlations among sensory attributes, such as ‘sweet’ and ‘aromatic’, assessed by a consumers’ panel, and analytical data, including the VOCs profile [ 38 , 42 ]. Regardless of the sugar-acid balance, VOCs with a positive impact on the consumers’ acceptance generally are some esters, including E10, E11 and E13, some aldehydes, such as Ald3, terpenes and lactones, which in our study were positively associated with the Red-H1 and Red-H2 strawberries, while negative coefficients related to liking occur with branched esters, including E5 and E12, and mesifurane (F1), which are directly correlated to the Red-H3 samples ( Figure 3 B) [ 38 , 42 ]. According to these findings, the Red-H1 and Red-H2 harvesting times could be preferred by the consumers compared to the Red-H3 fruit.…”

Consumer Perception of Milk and Plant-Based Alternatives Added to Coffee

“…The coffee with the milk addition was associated with the sweet attribute (Figure 1A) and had the highest overall liking scores (Table 3). Sweetness increases consumers' liking of many food products [48,49], including coffee and coffee-flavoured dairy beverages [10,50,51]. All the sensory properties that detracted from consumer liking were associated with the PBAs (Figure 1A).…”

Images carried before the fire: The power, promise, and responsibility of latent phenotyping in plants

“…These conventional traits capture only a limited slice of true variability yet represent the traits of primary interest to plant breeders because of their commercial and economic value. However, other traits that are also key selection targets, such as quality (e.g., taste, smell, texture), root and shoot system architectures (e.g., leaf and root angle, branching complexity, compactness), and organ form (e.g., size and shape), are more challenging to define with a single variable (Fan et al, 2021;Farneti et al, 2017;Klee & Tieman, 2013;Larsen et al, 2019;Li et al, 2020;Migicovsky et al, 2016;Migicovsky, Sawler, et al, 2017;Oh et al, 2021;Schwieterman et al, 2014;Tieman et al, 2017;Verma et al, 2017;Yano et al, 2019;Zhao et al, 2019). These traits, unlike yield, plant height, or time to flowering, are inherently multidimensional, resulting in a proliferation of potentially oversimplified definitions and interpretations.…”