Atmosphere (May 2022)
Response of Population Canopy Color Gradation Skewed Distribution Parameters of the RGB Model to Micrometeorology Environment in <i>Begonia Fimbristipula Hance</i>
Abstract
The high quality and efficient production of greenhouse vegetation depend on micrometeorology environmental adjusting such as system warming and 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 the greenhouse environment and reduce the running costs. The parameters from the color information of the plant canopy reflect the internal physiological conditions, thus, the RGB model has been widely used in the color analysis of digital pictures of leaves. We take photographs of Begonia Fimbristipula Hance (BFH) growing in the greenhouse at a fixed time every day and measure the meteorological factors. The results showed that the color scale for the single leaf, single plant, and the populated canopy of the BFH photographs all have 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 the 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. The models 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.
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