IJAIEM

S. Venkateswar Rao, S. Pushpalatha

Abstract

The agricultural sector accounts for the lion's share of India's GDP. The yield of crops is affected by a variety of diseases that impact plant leaves. Problems with disease prevention and increasing crop output are ongoing issues for apple growers. Diseases and pests are common, which greatly reduce apple yields and causes the sector to lose a lot of money every year. The ability to anticipate leaf diseases is a skill that farmers could lack. To efficiently manage and reduce these problems in orchards, rapid and precise detection of apple leaf diseases (ALD) is essential. Novel approaches to computer vision based on Deep Learning (DL) have made it possible to detect and comprehend these illnesses in their earliest stages right on the leaves. To solve this problem, we suggest a DL-model-based web tool that can detect and forecast health issues such as Alternaria, Leaf Spot, Marssonina Blotch, and Powdery mildew on afflicted leaves. Information needed to make well-informed decis