Anand kumar Jain, Neeta Nain, Anadi Jain
Contributors: Dr. Neeta Nain Research Scholars: Anand Kumar Jain Institute: Malaviya National Institute of Technology Jaipur Anadi Jain Institute: Government women engineering College Ajmer ( Bikaner Technical University, Bikaner) Domain Expert: Kota Agriculture University, Kota and Rajsthan Government Agriculture Department Published: December 2025 Version: 1.0 Crops: Chilli, Papaya & Tomato Chilli Diseases: Leaf Curl, Cercospora, Bacterial Spot, White Spot, Nutrition Deficiency. Healthy., Healthy Chilli Fruit, Disease Chilli Fruit Papaya Disease: Anthracnose, Bacterial Spot, Curl, Ring Spot. Healthy. Healthy Papaya Fruit, Disease Papaya Fruit. Tomato Disease: Healthy Tomato Fruit, Disease Tomato Fruit, Tomato healthy leaf, Tomato septoria leaf spot, Tomato verticulium wilt. Expert Ground-truth annotations, includ.ing soil health, humidity, nutrient deficiency, and pathological reports. Validated: Chilli, papaya, and tomato are economically important crops that are highly vulnerable to various diseases affecting leaves and fruits, leading to significant yield losses. Recent advances in artificial intelligence and deep learning have enabled automated plant disease detection; however, the performance of these models strongly depends on the availability of diverse and well-annotated datasets. To address this need, a three-crop disease image dataset comprising chilli, papaya, and tomato is presented. The dataset includes healthy and diseased samples captured under real-field conditions, covering variations in illumination, background, and disease severity. This dataset aims to support the development of robust multi-crop and multi-disease classification models and contribute to precision agriculture and intelligent plant health monitoring systems. Related Paper: Jain, A. K., Jain, A., & Nain, N. (2026). A Novel Multi Class Real World Fruit and Leaf Disease Image Dataset for Crop Health Analysis. DOI: https://doi.org/10.21203/rs.3.rs-8819059/v1