CitrusUAT: A Dataset of Orange Citrus sinensis Leaves for Abnormality Detection Using Image Analysis Techniques
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This dataset provides a collection of color images taken from the orange leaves of Citrus sinensis (L.) Osbeck species with diseases, nutritional deficiencies, and pest symptoms, proper to develop abnormality detection algorithms based on digital image analysis techniques. The dataset comprises 953 color images divided into 12 classes of orange leaves: Healthy, Huanglongbing (HLB), Greasy spot, Iron deficiency, Magnesium deficiency, Manganese deficiency, Nitrogen deficiency, Zinc deficiency, Texas citrus mite, Red scale, Red scale sequelae, and Citrus leafminer. Each color image was segmented by a thresholding method to obtain a binary mask of the leaf region. Samples were analyzed by the quantitative real-time polymerase chain reaction (qPCR) diagnostic test to detect the Ca. L. asiaticus bacterium that causes HLB disease.
本数据集收录了取自感染病害、存在营养缺乏或表现虫害症状的甜橙（Citrus sinensis (L.) Osbeck）物种的橙色叶片彩色图像，适用于开发基于数字图像分析技术的异常检测算法。本数据集共包含953张彩色图像，分为12类橙叶样本：健康叶片、黄龙病（Huanglongbing, HLB）、脂点黄斑病（Greasy spot）、缺铁、缺镁、缺锰、缺氮、缺锌、得克萨斯柑橘螨（Texas citrus mite）、红介壳虫（Red scale）、红介壳虫后遗症（Red scale sequelae）以及柑橘潜叶蛾（Citrus leafminer）。每张彩色图像均通过阈值分割法进行分割，以获取叶片区域的二值掩码。所有样本均通过实时荧光定量聚合酶链式反应（quantitative real-time polymerase chain reaction, qPCR）诊断试验进行检测，以鉴定引发HLB病害的亚洲韧皮部杆菌（Candidatus Liberibacter asiaticus, Ca. L. asiaticus）。
