Tropical Fruit Leaf Disease Detection Dataset: Jujube, Star Fruit, and Guava

This dataset comprises original 1602 images & augmentation 7885 images of jujube, star fruit, and guava leaves, categorized into healthy and diseased labels. It is specifically designed for the development and training of machine learning models aimed at early disease detection in tropical fruit crops. The dataset includes various types of leaf diseases, making it a valuable resource for researchers in plant pathology and agricultural technology. It offers a solid foundation for advancing automated systems to aid in crop management and improve sustainable farming practices. Jujube Leaf: Jujube Original data: Defect Jujube leaf:124 Healthy Jujube Leaf:227 Insect Feeding:177 Leaf Curl:33 Jujube Augmentation data: Defect Jujube leaf:620 Healthy Jujube Leaf:1010 Insect Feeding:885 Leaf Curl:165 Star Fruit Leaf: Star Fruit Original data: Defect Star Fruit Leaf:183 Healthy Star Fruit Leaf:298 Insect Feeding:95 Star Fruit old yellow leaf:68 Star Fruit Augmentation data: Defect Star Fruit Leaf:915 Healthy Star Fruit Leaf:1490 Insect Feeding:475 Star Fruit old yellow leaf:340 Guava Leaf: Guava Original data: Defect Guava leaf:158 Fungal leaf: 39 spot disease on Guava leafHealthy Guava leaf:200 Guava Augmentation data: Defect Guava leaf:790 Fungal leaf: 195 Spot disease on Guava leafHealthy Guava leaf:1000 Purpose: The purpose of this research is to develop an efficient and accurate system for detecting diseases in jujube, star fruit, and guava leaves using advanced image processing and machine learning techniques. By identifying diseases early, this study aims to enhance crop management, minimize agricultural losses, and promote sustainable farming practices.本数据集涵盖枣（Jujube）、杨桃（Star Fruit）与番石榴（Guava）叶片的原始图像1602张，增强图像7885张，所有图像均标注为健康与染病两类标签。本数据集专为开发训练热带作物早期病害检测的机器学习模型而打造，涵盖多种叶片病害类型，可为植物病理学与农业技术领域的研究人员提供宝贵的研究资源，为推进助力作物管理、优化可持续农业实践的自动化系统奠定坚实基础。 枣（Jujube）叶： 枣（Jujube）叶原始数据： 染病（Defect）枣叶：124 健康枣叶：227 虫害（Insect Feeding）：177 卷叶病（Leaf Curl）：33 枣（Jujube）叶增强数据： 染病（Defect）枣叶：620 健康枣叶：1010 虫害（Insect Feeding）：885 卷叶病（Leaf Curl）：165 杨桃（Star Fruit）叶： 杨桃（Star Fruit）叶原始数据： 染病（Defect）杨桃叶：183 健康杨桃叶：298 虫害（Insect Feeding）：95 杨桃老黄叶病（Star Fruit old yellow leaf）：68 杨桃（Star Fruit）叶增强数据： 染病（Defect）杨桃叶：915 健康杨桃叶：1490 虫害（Insect Feeding）：475 杨桃老黄叶病（Star Fruit old yellow leaf）：340 番石榴（Guava）叶： 番石榴（Guava）叶原始数据： 染病（Defect）番石榴叶：158 真菌性叶病（Fungal leaf）：39 番石榴叶斑点病（Spot disease on Guava leaf）： 健康番石榴叶：200 番石榴（Guava）叶增强数据： 染病（Defect）番石榴叶：790 真菌性叶病（Fungal leaf）：195 番石榴叶斑点病（Spot disease on Guava leaf）： 健康番石榴叶：1000 研究目的： 本研究旨在利用先进图像处理与机器学习技术，开发一套高效精准的枣、杨桃及番石榴叶片病害检测系统。通过早期病害识别，本研究以期优化作物管理、降低农业损失，并推动可持续农业实践的发展。