Identification of Plant Leaf Diseases using Machine Learning Algorithms

Abstract

A country's innovation growth depends on its agriculture or agribusiness. Agriculture, mother of all the cultures, which provides food and raw materials.It is essential to living beings as a source of nutrition. Plant diseases are therefore becoming a major problem for humans. Plant diseases can happen at any time, It may be happen between harvesting and sowing. It is a great loss of economic value in the market. Therefore, the detection of leaf diseases plays an important role in agriculture. Therefore, disease detection has been carried out using traditional methods. However, the traditional method of detecting leaf diseases is empty-eye observation by agricultural experts or plant pathologists.Detecting diseases of the leaves of plants using this method, which can be subjective, time consuming, and profitable, requires a large amount of manpower and an extensive knowledge of plant diseases. With the help of an experimental evaluation software solution, plant leaf diseases can be automatically recognized and classified. Machine learning is being used for a new development. Machine learning is used to detect diseases in plants. Machine learning is one of the subsections of artificial intelligence to work automatically or to give instructions for a specific task. The main goal of machine learning is to grasp the training data and incorporate it into models that will be useful to humans. As a result, we can use machine learning to detect plant diseases. It helped make good decisions and predict the large amount of data. The color of the leaves, the extent of damage to the leaves, the leaf area of ​​the unhealthy plant is used in the classification. In this regard, various machine learning algorithms are reviewed to identify various diseases of the leaves of plants and identify the best precision.