Estimating light interception using the color attributes of digital images of cotton canopies

来源 :Journal of Integrative Agriculture | 被引量 : 0次 | 上传用户:ontheroad2005
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Crop growth and yield depend on canopy light interception(LI). To identify a low-cost and relatively efficient index for measuring LI, several color attributes of red-green-blue(RGB), hue-saturation-intensity(HSI), hue-saturation-value(HSV) color models and the component values of color attributes in the RGB color model were investigated using digital images at six cotton plant population densities in 2012–2014. The results showed that the LI values followed downward quadratic curves after planting. The red(R), green(G) and blue(B) values varied greatly over the years, in accordance with Cai’s research demonstrating that the RGB model is affected by outside light. Quadratic curves were fit to these color attributes at six plant population densities. Additionally, linear regressions of LI on every color attribute revealed that the hue(H) values in HSI and HSV were significantly linearly correlated with LI with a determination coefficient(R2)≥0.89 and a root mean square error(RMSE)=0.05. Thus, the H values in the HSI and HSV models could be used to measure LI, and this hypothesis was validated. The H values are new indexes for quantitatively estimating the LI of heterogeneous crop canopies, which will provide a theoretical basis for optimizing the crop canopy structure. However, further research should be conducted in other crops and under other growing and environmental conditions to verify this finding. Crop growth and yield depend on canopy light interception (LI). To identify a low-cost and relatively efficient index for measuring LI, several color attributes of red-green-blue (RGB), hue-saturation-intensity -saturation-value (HSV) color models and the component values ​​of color attributes in the RGB color model were investigated using digital images at six cotton plant population densities in 2012-2014. The results showed that the LI values ​​followed quadratic curves after planting The red (R), green (G) and blue (B) values ​​varied greatly over the years, in accordance with Cai’s research demonstrating that the RGB model is affected by outside light. Quadratic curves were fit to these color attributes at six plant population densities. Additionally, linear regressions of LI on every color attribute revealed that the hue (H) values ​​in HSI and HSV were significantly linearly correlated with LI with a determination coefficient (R2) ≥ 0.89 and a root mean square error (RMSE) = 0 .05, Thus, the H values ​​in the HSI and HSV models could be used to measure LI, and this hypothesis was validated. The H values ​​are new indexes for quantitatively estimating the LI of heterogeneous crop canopies, which will provide a theoretical basis for优化 the crop canopy structure. However, further research should be conducted in other crops and under other growing and environmental conditions to verify this finding.
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