Detection of the yellow-leaf disease of rubber trees using low-altitude digital imagery from UAV

Efficient and non-destructive detection of rubber tree diseases is of great significance for optimizing disease control measures for pesticide application and fertilization. In this study, the feasibility of rubber yellow-leaf disease monitoring based on a low-altitude unmanned aerial vehicle (UAV) remote sensing platform was explored, and a low-cost method for detecting yellow-leaf disease based on visible light sensors was proposed. We compared the difference between the spectral response of each band of the visible light sensor in the diseased area and the healthy area, and then decorrelated and stretched the image in the RGB color space, thereby enhancing the color separation between highly correlated channels and enhancing the color difference of the image. Then we converted the image to the HSV color space, comparing the detection effect of different morphological parameters on yellow-leaf diseases and optimizing the extraction of the diseased area. The experimental results showed that this study provides the distribution information of yellow-leaf disease of rubber trees, and the R² of the regression model of rubber trees was greater than 0.8. This study holds significance for optimizing disease control and sustainable development of the rubber industry.