Screening of fermentation resources of wine based on principal component analysis combined with a fuzzy mathematical sensory evaluation method.

is a nutritious fruit with several health benefits. Recently, wine has gained popularity among consumers. However, limited research is available on the effect of different cultivars and yeast strains on fruit wine quality. Therefore, in this study, we aimed to analyze the physicochemical indicators and ester aroma compositions of 16 wines derived from four cultivars and fermented using four yeast strains to identify the most favorable combinations. The results showed significant differences in nutritional composition and flavor among the 16 wines. Principal component analysis (PCA) indicated that wines produced from the Changjiang No. 1 (CJ No. 1) and Liaofeng No. 1 (LF No. 1) cultivars, as well as those fermented with the LA-FR and LA-BA yeast strains, received higher scores. Furthermore, a fuzzy mathematical sensory evaluation (fuzzy logic model) confirmed the reliability of the PCA results, with the highest comprehensive sensory score (1.812) being awarded to CJ No. 1 wine fermented with LA-BA yeast. In this study, we identified the optimal combination of cultivars and yeast strains to provide a theoretical reference for the quality control and development of wine production.