Abstract:
Agriculture can be considered as backbone of India. It is not only a matter of food, but agricultural crop production has an impact on the entire economy of the country, as all enterprises rely on agricultural results, whether directly or indirectly. Crop pests and diseases are the leading causes of crop loss in India. In order to control disease and pests in agriculture, early disease identification is critical. Technology can be quite useful in completing this work. Machine learning has shown to be an important technique in the prediction of crop diseases in recent years. It solves many of the challenges associated with manual crop disease diagnosis while also providing high accuracy. We compare and contrast various machine learning algorithms for disease prediction in agriculture crops in this research.
