Comparison and Verification of Methods for Multivariate Statistical Analysis and Regression in Crop Modelling

Abstract

-In crop modelling, factor analysis and regression type have direct influence on the accuracy of model, but the application of these methods usually depends on the experience. In this paper, the performance of some common methods of statistical analysis and regression model was compared and verified, in order to avoid the blindness in crop modelling. The monitoring data of growth environment and photosynthesis of tomato, pumpkin and cucumber was obtained by PTM-48A, for the object variable of CO 2 exchange rate, selectivity on the main environmental factors by correlation analysis and path analysis were quantify compared, the performance of four kinds of multivariate binomial regression equations was compared in respects of complexity and accuracy, then the effectiveness of modelling was verified with the selected optimized multivariate statistical analysis and regression equation. Results showed that path analysis was more comprehensive than correlation to discrimination the variables, and the pure quadratic was more suitable to crop modelling because of its simple structure and high accuracy. The conclusion of the paper has general applicability, and offers a useful reference and guide for the other crops' modelling.