Abstract: 【Objective】There are various trait differences among different grape germplasms, which are valuable materials for cultivating excellent new varieties. The assessment of fruit characteristics plays a vital role in the assessment of grape genetic resources, and also serves as a crucial foundation for identifying superior genetic material. Therefore, this study aimed to comprehensively evaluate the fruit quality traits of 101 table grapes in the northern Zhejiang Plain using correlation analysis, cluster analysis and principal component analysis, characterize their representative qualities, and provide technical guidance for grape fruit quality evaluation and excellent germplasm screening. 【Methods】A total of 101 table grape germplasm resources were used as test materials to investigate and analyze the fruit quality traits. In order to explore the fruit quality traits, this study measured 26 parameters including vetotal organic acidsticity, cohesion, elastic index, chewiness, pericarp puncture strength, total phenols content, flavonoid content, proanthocyanidin, sucrose content, fructose content, glucose content, oxalic acid content, tartaric acid content, malic acid content, citric acid content, total sugar content, total organic acid content, the ratio of total sugar to total organic acid, fruit cracking rate and fruit cracking index. SPSS 27.0 was used to conduct correlation analysis, cluster analysis, and principal component analysis on the above indicators, and to analyze and evaluate the quality of grape fruits through comprehensive scoring ranking. 【Results】The 26 quality indicators showed varying degrees of variation, with coefficients of variation ranging from 7.03% to 159.48%. Among all indicators, the proanthocyanidin had the largest variation and the elastic index had the smallest. According to cluster analysis, 101 grape germplasm resources were divided into 5 categories (Ⅰ, Ⅱ, Ⅲ, Ⅳ, Ⅴ) when the Euclidean distance was 11.5. The Ⅰ category could be divided into 3 groups when the Euclidean distance was 8.5, among which the majority of grape germplasm is a hybrid population, the Ⅱ category could be divided into into into 4 groups when the Euclidean distance was 8.5, among which the majority of grape germplasm is Eurasian population. After eliminating the fruit quality indexes with less variation, 14 traits of 101 grape germplasm resources were standardized by principal component analysis and then reduced in dimension. In the principal component analysis, five principal components were extracted with a total cumulative contribution of 82.178%. The contribution rate of principal component 1 was 26.008%, mainly representing soluble solids, total sugar content, and cohesion, reflecting the quality of fruit sugar content. The contribution rate of principal component 2 was 19.293%, mainly representing total phenols and flavonoids, reflecting fruit nutrients. The contribution rate of principal component 3 was 14.750%, mainly representing single fruit cracking rate, fruit cracking index, and sugar-acid ratio, reflecting the ability of fruit to resist cracking. The contribution rate of the fourth principal component was 13.420 %, and the main factors determining it were elasticity and cohesion, which reflected the fruit texture. The contribution rate of the principal component 5 was 8.707 %, and the main factors determining it were total acid and sugar-acid ratio, which reflected the fruit flavor.【Conclusion】In this study, 26 agronomic traits of 101 grape germplasm resources were analyzed and could be divided into 5 categories based on diversity analysis, cluster analysis and principal component analysis. Through the comprehensive analysis of the fruit quality, soluble solid, elasticity, cohesion, chewiness, total phenols content, flavonoid content, total sugar content, sugar-acid ratio, fruit cracking rate and fruit cracking index elements were selected as the core indicators for the evaluation of fruit quality traits. By principal component analysis, ‘Miguang’, ‘Pearl Noir’, ‘Zhengyan Wuhe’, ‘Jingshouzhi’, ‘09-42’, ‘Black Beet’, ‘13-653’ and ‘15-115’ get high scores. It could be used as an important indicator reference for the evaluation of fresh grape germplasm resources and variety selection and identification in Zhejiang Province.
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