Sugarcane Leaf Disease Classification Using Convolutional Neural Network

Indian sugarcane is of good quality, and the country exports significant quantities of sugar and sugarcane-based products to various countries worldwide. However, the quality of the sugarcane can vary depending on the specific variety and growing conditions, and exporters need to ensure that the product meets the quality standards of the importing country. To maintain the quality of sugarcane during transportation, it is crucial to ensure that it is harvested at the right time and handled carefully during loading and unloading. However, the farmers cultivating the sugarcane face a significant issue dealing with bacterial infection in the plants. In order to stop the disease from spreading further, we use Convolutional Neural Networks in our article to extract information from sugarcane leaves and construct an algorithm that accurately classifies bacterial leaves. Using an image dataset that includes pictures of both healthy and ill plants, identifying the image's key characteristics, and using the image to help the classifier provide a reliable result are all included in the total process. Our study will save farmers time and effort by identifying the decaying plants by looking for bacterial patches on the leaves.