Assignation of sweet cherry selections to 3 taste groupings based on perceived sweetness and sourness.

UNLABELLED

Providing consumers with basic taste properties of sweet cherries at point of purchase would allow consumers to make purchase decisions based on fruit's intrinsic sensory attributes. The objective of this study was to develop a model to predict taste-grouping assignation of cherries into the following categories: (1) low sweetness/high sourness, (2) balance between sweetness and sourness, and (3) high sweetness/low sourness. A sensory panel (n = 10) was trained to recognize sweetness and sourness in 5 cultivars of sweet cherries and assign a taste grouping based on the perceived balance of sweetness and sourness. Four of these same cultivars were then evaluated for sweetness and sourness by a consumer panel (n = 117) and instrumentally for titratable acidity (TA) and soluble solids concentration (SSC). Results showed that for 3 of the 4 cherry cultivars, the sweetness/sourness balance of the cherries was not significantly different as evaluated instrumentally or by the trained panel. However, the balance determined by the consumer and the trained panel was different for 3 of the 4 cherry cultivars (P < 0.05). Based on trained panel perceived sweetness and sourness, a multinomial logit model was developed to predict the assignation of cherry taste grouping. The likelihood of group assignment depended on both the perceived sweetness and sourness of the cherry, with taste groupings agreed upon for 3 of 5 sweet cherry cultivars. As previous studies have indicated a positive relationship between cherry sweetness and sourness to consumer acceptance, these groupings show promise for assisting consumers in cherry selection at the point of purchase.

PRACTICAL APPLICATIONS

The prediction models proposed in this study suggest that both sweetness and sourness are important in the cherry characterization and the ratio between the 2 attributes may be appropriate for making taste-grouping assignments. These groupings may then be used to provide additional sensory information to consumers to assist them in cherry selection at the point of purchase.