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The crop leaf color is tightly connected with its meteorological environment. Color gradation skewness-distribution (CGSD) parameters can describe the information of leaf color more accurately, systematically, and comprehensively from five dimensions. We took photographs of pepper growing in the greenhouse at a fixed time every day and observed the meteorological factors. The results showed that the CGSD parameters were significantly correlated with meteorological factors, especially with the accumulated temperature, which showed the strongest correlation. Since the relationship between canopy leaf color and accumulated temperature is nonlinear, the piecewise inversion models were constructed by taking the stationary point of the high-order response model of Gskewness to accumulated temperature as the point of demarcation. The rate of outliers had decreased by 57.72%; moreover, the overall inversion accuracy had increased by 3.31% compared with the linear model directly constructed by the stepwise regression. It was observed that the pepper in the greenhouse had a different response to the same meteorological environmental stimulus before and after the stationary point. This study will provide a new method for constructing crop growth models in future research. [ABSTRACT FROM AUTHOR]