Establishment of quality evaluation model of fruit mulberry based on principal component analysis
To explore the quality characteristics of fruit mulberry in Huzhou district of Zhejiang Province,and construct its quality evaluation model.'Yueshenda 10'were used as materials and determined 12 fruit quality indices.The methods of descriptive statistical analysis,correlation analysis,principal component analysis and regression analysis were conducted,and then the quality evaluation model was established.The results showed that there were differences in fruit quality among different samples,and the degree of dispersion between 12 indicators was different.The coefficient of variation was from 2.28％ to 35.56％.Correlation analysis showed that there were different degrees of correlation among the 12 indicators.Three principal components were obtained with a cumulative contribution rate of 89.723％after principal component analysis.The first principal component was health factor with variance contribution approached to 53.172％.The second principal component was flavor factor with variance contribution approached to 25.205％.The third principal component was fruit weight factor with variance contribution approached to 11.346％.The comprehensive scores could well distinguish the quality differences between different samples.Finally,we established the quality evaluation prediction model of'Yueshenda 10'by the stepwise regression analysis,and screened 6 effective indexes such as anthocyanins,etc.The quality evaluation model of'Yueshenda 10'is as follows:Y=-9.791+0.356X12+0.653X9+3.027X2+0.051X7+0.468X10+0.011X8,in which anthocyanins,vitamin C,single fruit dry weight,solid acid ratio,flavonoids and total sugar are important indicators for evaluating its quality.The principal component analysis method can be used to evaluate the fruit quality of'Yueshenda 10'.This study provide a theoretical basis for the construction of quality evaluation system of'Yueshenda 10'.
fruit mulberry'Yueshenda 10'principal component analysisquality evaluationregression analysis
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