Machine Learning Algorithm for Detection And Classification of Tomato Plant Leaf Disease

Abstract

Agriculture is the life of a nation. Due to this crops protection from various diseases is needed. We took tomato as a sample crop for research and it is found in various forms irrespective of the cuisine. The quality of tomatoes degrades due to various types of diseases. This article presents an approach for early prediction and detection of tomato plant leaf disease using Machine Learning algorithms. Experimentally, we work on a dataset and perform various operations on it like feature extraction, perform testing, etc. with the help of different 8 machine learning algorithms.It is observed that the accuracy of classification of tomato leaf disease is between 67%-99%. Results are documented for 10 different diseases and the Random Forest algorithm results in the highest accuracy of 98%. This gives a strong foundation for our work-in-progress research of the design and development of a new approach for the prediction and early detection of tomato leaf disease.