A New Image Processing System to Diagnose the Orange Fruit Disease

Citrus fruits are among the most important food components. Orange is one of the most important citrus fruits because of its vitamin C content and delicious taste, and it is planted and harvested in most countries. Aphids, pests, and fungi cause the destruction of orange fruits. Therefore, it is very important to quickly identify diseases. Several factors are important to improve the ripening of the orange fruit, so that it does not suffer from viruses or fungi. First, several important viruses and fungi and their causes in oranges should be investigated, and ways to improve orange ripening should be made easy; here, we used an image processing system and Red, Green, Blue (RGB) to Hue, Saturation, Lightness (HSL) conversion to identify several important viruses and fungi from the color of orange peel. In addition, the proposed algorithm detects both healthy and diseased oranges. The accuracy of the present study was 93.6%. In this study, an algorithm for diagnosing orange-fruit diseases was proposed. This algorithm is performed using Python programming and executed by the Raspberry Pi. Therefore, oranges with Melanosis, Canker, and Black Spot disease were detected. The defective part of the orange fruit is shown in the form of mask and HSL images as well as the integration of the mask and HSL images in the output. After running the program, the severity of the disease is shown through the number of pixels of the defective part of the orange, and guidance for the prevention and treatment of the disease is described.