{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T16:45:59Z","timestamp":1783010759979,"version":"3.54.6"},"reference-count":42,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2020,11,2]],"date-time":"2020-11-02T00:00:00Z","timestamp":1604275200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Sheath blight (ShB), caused by Rhizoctonia solani AG1-I, is one of the most important diseases in rice worldwide. The symptoms of ShB primarily develop on leaf sheaths and leaf blades. Hyperspectral remote sensing technology has the potential of rapid, efficient and accurate detection and monitoring of the occurrence and development of rice ShB and other crop diseases. This study evaluated the spectral responses of leaf blade fractions with different development stages of ShB symptoms to construct the spectral feature library of rice ShB based on \u201cthree-edge\u201d parameters and narrow-band vegetation indices to identify the disease on the leaves. The spectral curves of leaf blade lesions have significant changes in the blue edge, green peak, yellow edge, red valley, red edge and near-infrared regions. The variables of the normalized index between green peak amplitude and red valley amplitude (Rg \u2212 Ro)\/(Rg + Ro), the normalized index between the yellow edge area and blue edge area (SDy \u2212 SDb)\/(SDy + SDb), the ratio index of green peak amplitude and red valley amplitude (Rg\/Ro) and the nitrogen reflectance index (NRI) had high relevance to the disease. At the leaf scale, the importance weights of all attributes decreased with the effect of non-infected areas in a leaf by the ReliefF algorithm, with Rg\/Ro being the indicator having the highest importance weight. Estimation rate of 95.5% was achieved in the decision tree classifier with the parameter of Rg\/Ro. In addition, it was found that the variety degree of absorptive valley, reflection peak and reflecting steep slope was different in the blue edge, green and red edge regions, although there were similar spectral curve shapes between leaf sheath lesions and leaf blade lesions. The significant difference characteristic was the ratio index of the red edge area and green peak area (SDr\/SDg) between them. These results can provide the basis for the development of a specific sensor or sensors system for detecting the ShB disease in rice.<\/jats:p>","DOI":"10.3390\/s20216243","type":"journal-article","created":{"date-parts":[[2020,11,2]],"date-time":"2020-11-02T09:04:46Z","timestamp":1604307886000},"page":"6243","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":29,"title":["Identification of Rice Sheath Blight through Spectral Responses Using Hyperspectral Images"],"prefix":"10.3390","volume":"20","author":[{"given":"Fenfang","family":"Lin","sequence":"first","affiliation":[{"name":"School of Remote Sensing &amp; Geomatics Engineering, Nanjing University of Information Science &amp; Technology, Nanjing 210044, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sen","family":"Guo","sequence":"additional","affiliation":[{"name":"National Engineering Research Center for Agro-Ecological Big Data Analysis &amp; Application, Anhui University, Hefei 230601, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Changwei","family":"Tan","sequence":"additional","affiliation":[{"name":"Jiangsu Key Laboratory of Crop Genetics and Physiology, Yangzhou University, Yangzhou 225000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xingen","family":"Zhou","sequence":"additional","affiliation":[{"name":"Plant Pathology Lab, Texas A&amp;M AgriLife Research Center, 1509 Aggie Drive, Beaumont, TX 77713, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3509-7482","authenticated-orcid":false,"given":"Dongyan","family":"Zhang","sequence":"additional","affiliation":[{"name":"National Engineering Research Center for Agro-Ecological Big Data Analysis &amp; Application, Anhui University, Hefei 230601, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2020,11,2]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1387","DOI":"10.1007\/s00425-019-03246-8","article-title":"Sheath blight of rice: A review and identification of priorities for future research","volume":"250","author":"Singh","year":"2019","journal-title":"Planta"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"72","DOI":"10.1016\/j.cropro.2017.10.017","article-title":"Field efficacy of fungicides for management of sheath blight and narrow brown leaf spot of rice","volume":"104","author":"Uppala","year":"2018","journal-title":"Crop. 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