Plant Diseases Diagnosis with Artificial Intelligence (AI)

India’s agriculture is significant because of the country’s expanding population and rising food demands. Therefore, it is necessary to increase crop productivity. One of these significant factors contributing to reduced agricultural yields is the prevalence of bacterial, fungal, and viral illnesses. Applying techniques for plant disease identification helps stop and manage this. Machine learning techniques will be used in the process of identifying plant illnesses since they apply information most frequently and provide excellent methods for disease diagnosis. Machine learning-based techniques can be used to identify diseases because they focus mostly on data superiority outcomes for a certain goal. In this method, machine learning and deep learning based on artificial intelligence (AI) have been used to conduct a thorough assessment of the numerous methodologies used in plant disease diagnosis. In the realm of computer vision, deep learning has also become increasingly important for providing improved performance results for identifying plant diseases. There has been significant progress in the machine learning and computer vision fields as a result of the application of deep learning improvements to a variety of disciplines. In order to demonstrate the superiority of the deep learning model over the machine learning model, a comparison of the two techniques’ performances and applications in numerous research articles has been made. The deep learning technology can be used to identify leaf diseases from collected photos in order to prevent significant crop losses.