Response of Population Canopy Color Gradation Skewed Distribution Parameters of the RGB model to Micrometeorology Environment in Begonia Fimbristipula Hance

Abstract

Background: The high quality and efficient production of greenhouse vegetation depend on the micrometeorology environmental adjusting such as the system warming, illumination supplement. In order to improve the quantity, quality and efficiency of greenhouse vegetation, it is necessary to figure out the relationship between the crop growth conditions and environmental meteorological factors, which could give constructive suggestions for precise control of greenhouse environment and reducing the running cost. The parameters from the color information of plant canopy reflect the internal physiological conditions, thus, RGB model has been widely used in the color analysis of digital pictures of leaves.Results: The color scale for single leaf, single plant, and the populate canopy of Begonia Fimbristipula Hance (BFH) photographs are all have a skewed cumulative distribution histograms. The color gradation skewness-distribution (CGSD) parameters of the RGB model were increased from 4 to 20 after the skewness analysis, which greatly expanded the canopy leaf color information and could simultaneously describe the depth and distribution characteristics of canopy color. The 20 CGSD parameters were sensitive to the micrometeorology factors, especially to the radiation and temperature accumulation. The multiple regression models of mean, median, mode and kurtosis parameters to microclimate factors were established, and the spatial models of skewness parameters were optimized.Conclusions: The models constructed based on the color gradation skewness-distribution (CGSD) parameters of the RGB model, can well explain the response of canopy color to microclimate factors and can be used to monitor the variation of plant canopy color under different micrometeorology.

Response and inversion of skewness parameters to meteorological factors based on RGB model of leaf color digital image

“…By skewed analysis, the RGB model parameters are expanded from the mean to the mean, median, mode, skewness and kurtosis, and the number of parameters is also expanded from 4 to 20. These color gradation skewnessdistribution (CGSD) parameters can describe leaf color information more accurately and comprehensively [37], we used (CGSD) parameters to construct a correlation model between leaf color and chlorophyll content in tobacco [37] and between leaf color and yield in soybean [38]. We found that CGSD parameters can be used directly as phenotypic parameters.…”