Study on the Relationship between Blueberry Soil and Leaf in Southern China—Based on MLR-PCA Prediction Model

Jian Li, Ming-Yue Wang, Guang Chen, Lin Wu, Min Zhang

Ekoloji, 2018, Issue 106, Pages: 395-404, Article No: e106030


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This paper selects six blueberry varieties from Miluo City as the sample, constructs MLR-Principal Component Prediction Model for Soil and Leaf Nutrients, studies deeply the correlation and predictive function between different blueberry varieties’ soil and leaf nutrient contents. Compared with several prediction methods, the principal component prediction function combined with multiple regression is more systematic and has a better effect on the prediction of blueberry nutrition status. The results show that the nutrient content of the leaves is highly correlated with the elements of the soil, the nutritional status of different blueberry varieties’ leaves can be fully expressed with predictive functions, and uses the MLR regression equation and regression prediction model to guide the technicians for matching the fertilization programs, positively guides the blueberry planting industry in practical applications.


blueberry, soil, leaf blade, prediction, correlation


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