Quality analysis and comprehensive evaluation of cherry wine fermented from different cultivars

Abstract:【Objective】Sweet cherry (Prunus avium L.) is one of the most popular fruits because it has anexotic flavor and is a nutrient-rich fruit, with abundant sugars, vitamins, amino acids, organic acids andpolyphenols. However, it is a highly perishable fruit with difficulty in storage and transportation and thusoften processed into juices and wines. The physicochemical properties and nutritional compounds of fruitwines are directly related to the genetic background of the fruits. Nutritional quality analysis and evaluation of cherry wine are important for cherry breeding and comprehensive utilization. This study was con⁃ducted to analyze the nutrient quality of cherry wine made from different cultivars, establish an effectivemethod for cherry wine evaluation, find out the key factors influencing the nutrient quality of cherry wine,and select suitable cherry cultivars for wine processing.【Methods】Cherry wines made from 11 cultivars‘(Brooks’‘Chunxiu’‘Bigarreau Moreau’‘Hongdeng’‘Hongyan’‘Huangmi’‘Sunburst’‘Summit’‘Zaodaguo’‘Zaohongzhu’and‘23-24’) were used as materials for detecting 19 processing physico⁃chemical characteristics by conventional descriptive statistics, principal component analysis (PCA) andcluster analysis. The differences among cherry wines were analyzed to screen suitable cherry varieties forprocessing high quality wine.【Results】The results showed great differences in wine quality charactersamong different cherry cultivars. Coefficients of variation (CV) of pH and alcohol content were lower than10%, but higher CV values were found in other qualities.‘Zaodaguo’cherry wine was dark-fuchsia andpossessed significantly higher contents of total phenols, flavonoids and anthocyannis, with the highest radi⁃cal scavenging ability (DPPH and ABTs) and ferric reducing antioxidant power (FRAP). PCA is a mathe⁃matical method to perform a reduction in data dimensionality and allow visualization of underlying struc⁃ture in experimental data. Based on the major physical and chemical properties of the wines from 11 culti⁃vars, 3 principal components with eigen value >1.000 were extracted to account for the 17 quality parame⁃ters after data conversion, and the cumulative variance contribution rate of the 3 principal factors was85.74%. The variance rate of the first component factor was 57.1% and was related to h value, polypheno⁃lic compounds and antioxidant activities, and was thus considered to be the antioxidant factor. The secondprincipal component was the acidity factor, which was related to vitamin C, volatile acids and total titrat⁃able acidity. The third principal component was related to a* value. According to weight index and synthet⁃ic evaluation function of the 3 principal factors, the comprehensive evaluation of quality showed signifi⁃cant difference among wines from different cultivars. Wine from‘Zaodaguo’had the highest compositescore of 3.792, followed by wines from‘Hongdeng’‘23-24’and‘Zaohongzhu’with score value rangingfrom 1.039 to 1.650. The higher scores in the wine fermented from these varieties were attributed mainlyto richer polyphenols and higher antioxidant capacities. The lowest score was found in the wine from‘Brooks’, which had the minimum contents of total phenolics and flavonoids. Polyphenols and antioxidantactivities can be used as important indexes for comprehensive evaluation of cherry wine quality. In addi⁃tion, samples could be grouped on the basis of similarities by cluster analysis based on Euclidean distance. The results displayed 4 well-defined clusters at a Euclidean distance of 5.0, which was consistentwith the results of PCA composite score results. Cluster analysis proposed less information than PCA andneeded PCA results to assist the evaluation of the advantages and disadvantages of the clusters. In thisstudy,‘Zaodaguo’cherry wine formed one group, possessing the highest antioxidant capacities and mostabundant phenolics, flavonoids and anthocyannis, and was thus an excellent cherry cultivar for wine pro⁃cessing.‘Hongdeng’,‘23-24’and‘Zaohongzhu’cherry wine could be classified as above-average andwere clustered in one group. Wines from‘Chunxiu’‘Bigarreau Moreau’‘Sunburst’‘Summit’‘Hong⁃yan’and‘Huangmi’formed one group, which was considered to be of medium quality.‘Brooks’cherrywine formed the forth group with poor quality.【Conclusion】There were some differences in quality properties of wines among different cultivars. The key factors affecting nutrient quality were the antioxidant ability, hue angle (h), and contents of total phenolics, flavonoids and anthocyannis. These indicators represented the comprehensive cherry wine quality combining appearance, nutrient properties and functional char⁃acteristics. The comprehensive evaluation score of‘Zaodaguo’cherry wine was higher than wines fromthe other cultivars.‘Zaodaguo’‘Hongdeng’‘23-24’and‘Zaohongzhu’could be also be good choicesfor wine fermentation. However,‘Brooks’was not suitable for wine processing. These results can be usedto determine cherry cultivars appropriate for wine processing, and can be used as a guide for cherry breeding.