文献类型：期刊文献

英文题名：Detection of citrus black spot symptoms using spectral reflectance

作者：Xie, Chuanqi[1];Lee, Won Suk[2]

机构：[1]East China Univ Sci & Technol, Sch Biotechnol, 130 Meilong Rd, Shanghai 200237, Peoples R China;[2]Univ Florida, Dept Agr & Biol Engn, Gainesville, FL 32611 USA

年份：2021

卷号：180

外文期刊名：POSTHARVEST BIOLOGY AND TECHNOLOGY

收录：;WOS:【SCI-EXPANDED(收录号:WOS:000677681600003)】；

基金：This work was sponsored by Shanghai Pujiang Program (19PJ1402400) , and the Florida Specialty Crop Block Grant. Also, we would like to thank Dr. Alireza Pourreza at the University of California, Davis for his support in this work.

语种：英文

外文关键词：Hyperspectral imaging; Citrus black spot (CBS); Effective wavelengths; K-nearest neighbor (KNN); Classification

摘要：Citrus black spot (CBS) disease can usually result in fruit blemish and yield loss on all citrus. Spectral reflectance was utilized to detect CBS symptoms in this study. Hyperspectral images of both healthy and diseased citrus were collected in the spectral region of 396-1010 nm. After raw image calibration, spectral reflectance of diseased (early hard spot, advanced hard spot, cracked spot, early virulent, and virulent) and healthy samples were extracted and used as independent variables for classification. Effective wavelengths were selected using regression coefficients based on partial least squares analysis. K-nearest neighbor models were established to classify the symptoms in each group (early hard spot vs. advanced hard spot, early virulent vs. virulent, hard spot vs. cracked spot, hard spot vs. virulent, cracked spot vs. virulent, diseased vs. healthy, and early stage vs. advanced stage). In diseased vs. healthy group, the models yielded the correct classification accuracies of 99.4 % (using full wavelengths) and 100.0 % (using selected wavelengths) for diseased samples. The correct classification accuracies were 92.5 % (using full wavelengths) and 93.8 % (using selected wavelengths) for early stage samples (early disease). Besides, the selected wavelengths were 549, 668, 706, and 790 nm for diseased vs. healthy group, and 675, 711, and 835 nm for early stage vs. advanced stage group. The overall results demonstrated that spectral reflectance information has the potential to classify different symptoms of CBS.