The effectiveness of machine learning and image processing in detecting plant leaf disease

In our daily lives, the agricultural sector is crucial. Therefore, it is crucial to be clear about the steps taken to identify any diseases on agricultural plants’ leaves. Plant leaf disease is a significant issue or contributor to crop losses in an agricultural context. Some farmers are able to know every disease name and how to prevent them as it becomes increasingly crucial to recognize the sickness. Different plant leaf diseases appear during various seasons. This problem can be resolved using a deep learning-based approach by identifying the affected regions in plant leaf images, enabling farmers to better comprehend the disease. The primary goal of this research is to survey several image-processing methods for detecting plant diseases and to compare them. India is an agricultural nation, and the majority of its people depend on agriculture for a living. Focusing on farming with modern technology is essential to ensuring their comfort and ease of living. Crop productivity may be greatly increased by introducing new technologies. An autonomous plant disease detection method using image processing and a neural network methodology can be utilized to solve issues with plant and agricultural diseases. Plants can contract a wide range of illnesses. Different patterns are needed to detect various disorders.