Paddy Pro: A MobileNetV3-Based App to Identify Paddy Leaf Diseases

Abstract

The crop disease and the plant disease are a major issue affecting the food quality and quantity in agriculture. The lack in detecting the crop disease impacts the crop yield and the farmers’ income. Early detection of leaf diseases will prevent and control the diseases in the initial stages. The objective of the proposed work is to develop a smart phone-based plant diseases detection system using deep learning techniques. This system aims to provide information to the farmers about to the identification of the bacterial, fungal and pest diseases and provide management and control especially of the paddy plant. Paddy is indigenously grown in delta region of Tamil Nadu. Millions of hectares of paddy fields are infected annually by deadly diseases, and crop loss may be as high as 75%. The proposed work uses deep learning-based MobileNetV3 architecture to detect the leaf diseases from images to reduce the major crop losses. The performance improvement with 93.75% accuracy is achieved through the proposed model.