Bormon Sajib, Ahmad Md Hasan, Sohag Sohanur Rahman, Akhi Amatul Bushra
Department of Computer Science and Engineering, Daffodil International University, Dhaka, Bangladesh.
Data Brief. 2025 Feb 12;59:111379. doi: 10.1016/j.dib.2025.111379. eCollection 2025 Apr.
The economic development of many countries largely depends on tea plantations that suffer from diseases adversely affecting their productivity and quality. This study presents a high-resolution dataset aimed at advancing precision agriculture for managing tea garden diseases. The size of the dataset is 3960 images and pixel dimension is (1024 × 1024) of the images were collected by using smartphones. This dataset contains detailed images of Tea Leaf Blight, Tea Red Leaf Spot and Tea Red Scab maladies inflicted on tea leaves as well as environmental statistics and plant health. The images were captured and stored in JPG format. The main aim of this dataset is to provide tool for detection and classification of different types of tea garden disease. Applying this dataset will enable the development of early detection systems, best-practice care regimens, and enhanced general garden upkeep. A range of images presenting the most prevalent diseases afflicting tea plants are paired with images of healthy leaves to provide a comprehensive overview of all the circumstances that can arise in a tea plantation. Therefore, it can be used to automate diseases tracking, targeted pesticide spraying, and even the making of smart farm tools with development of smart agricultural tools hence enhancing sustainability and efficiency in tea production. This dataset not only provides a strong foundation for applying precision techniques in tea cultivation in agriculture, but also can become an invaluable asset to scientists studying the issues of tea production.
许多国家的经济发展在很大程度上依赖于茶园，但这些茶园正遭受着疾病的困扰，对其生产力和品质产生了不利影响。本研究提出了一个高分辨率数据集，旨在推动茶园疾病管理的精准农业发展。该数据集包含3960张图像，图像的像素尺寸为(1024×1024)，是通过智能手机收集的。此数据集包含茶叶上患茶云纹叶枯病、茶赤叶斑病和茶红痂病的详细图像以及环境统计数据和植株健康状况。图像以JPG格式捕获和存储。该数据集的主要目的是提供用于检测和分类不同类型茶园疾病的工具。应用此数据集将有助于开发早期检测系统、最佳护理方案，并加强茶园的整体维护。一系列展示茶树最常见病害的图像与健康叶片的图像配对，以全面呈现茶园中可能出现的所有情况。因此，它可用于自动化病害跟踪、精准农药喷洒，甚至随着智能农业工具的发展制作智能农场工具，从而提高茶叶生产的可持续性和效率。该数据集不仅为在农业茶叶种植中应用精准技术提供了坚实基础，也可为研究茶叶生产问题的科学家们提供宝贵资产。
