Crop Disease Prediction using Machine Learning and Deep Learning: An Exploratory Study

Abstract

Crop diseases are caused by pests, insects, and pathogens, and if not promptly handled, they significantly reduce the yield. Farmers are losing money because of different crop diseases. When the cultivated area is large (in acres), it becomes tiresome for the cultivators to examine the crops regularly. The farming business needs an automatic crop disease identification and analysis. It may be used to diminish the loss of money and other resources, reduce yield losses, and enhance the effectiveness of treatment leading to healthier crop output. Many industries today have benefited from the development of new technologies, particularly artificial intelligence, Machine Learning (ML) and Deep Learning (DL). This study examined the significant advancements and issues, such as reduction in harvest yield, lower quality of produce and crop damage, using ML and DL approaches for crop disease detection and prediction in the recent studies.