Principal component and cluster analysis of fruit quality indexes of wild mulberry in Guizhou province

Abstract:【Objective】Mulberry(Morus alba Linn.) fruits has become popular due to its rich nutrition and high medicinal value in recent years. Wild mulberry resources in Guizhou are widely distributed,and have many ecological types. Some of them have good fruit- bearing properties, good taste and strong disease resistance. In this study, the fruit quality of 15 wild mulberry germplasm resources was evaluated comprehensively to provide reference for the selection of high-quality varieties.【Methods】A total of 15 wild mulberry resources were collected from the mulberry germplasm collection of Guizhou Sericulture Research Institute. Seven indexes of sensory and pH value, juice yield and soluble solids were determined. The fruit quality of different resources was analyzed in the single factor analysis, prin-cipal component analysis, cluster analysis and comprehensive grading were conducted using the tech-nology of spss 23 and excel software.【Results】There were significant differences in fruit quality traits among 15 germplasm resources, indicating great potential for selection. In principal component analy-sis, 5 principal components were extracted, the cumulative contribution rate was 87.998%, which re-flected most of the quality characteristics of mulberry fruits. The contribution rate of the first principal component was 34.706%, including soluble solid, total acid, total sugar and longitudinal diameter. The second principal component was highly correlated with Color L* and Color b*, which could explain 20.009% of the character information. The third principal component explained 12.768% of the trait in-formation highly related to juice yield. The fourth principal component was single fruit weight, the con-tribution rate was 11.169%.The fifth principal component was mainly Color a*, and the contribution rate was 9.347%. According to the principal component analysis, the comprehensive scores of each resource were obtained, and the order was as follows: Guo2 > Guo11 > Guo24 > Guo 33 > Guo1 > Guo31 >Guo5 > Guo19 > Guo6 > Guo16 > Guo12> Guo3 > Guo23 > Guo34 > Guo4. The results of data cluster analysis showed that in the condition of European distance at 10, 15 mulberry germplasm resources could be clustered into 2 categories, Guo12, Guo24, Guo33, Guo23, Guo1, Guo11, Guo19, Guo31,Guo2 and Guo5 were classified as I; Guo34, Guo4, Guo3, Guo6 and Guo16 were classified as class II.The results of classification were highly consistent with the principal component scores.【Conclusion】It is reliable to use principal component analysis and data clustering to evaluate the quality of mulberry fruits. The comprehensive quality evaluation model established in this experiment can be used to evalu-ate the fruit quality of wild mulberry germplasm resources in Guizhou. Guo2, Guo11, Guo24, and Guo33 can be used as excellent fruit mulberry germplasm resources in Guizhou.