{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,22]],"date-time":"2026-01-22T10:21:41Z","timestamp":1769077301643,"version":"3.49.0"},"reference-count":103,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2021,1,6]],"date-time":"2021-01-06T00:00:00Z","timestamp":1609891200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003593","name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico","doi-asserted-by":"publisher","award":["140167\/2017-0"],"award-info":[{"award-number":["140167\/2017-0"]}],"id":[{"id":"10.13039\/501100003593","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Innovation Project of Chinese Academy of Agricultural Sciences","award":["960-3"],"award-info":[{"award-number":["960-3"]}]},{"name":"Fundamental Research Funds for the Chinese Academy of Agricultural Sciences","award":["Y2020GH14"],"award-info":[{"award-number":["Y2020GH14"]}]},{"name":"Talented Young Scientist Program \u2013 China Science and Technology Exchange Center","award":["Brazil \u2013 19-004"],"award-info":[{"award-number":["Brazil \u2013 19-004"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Monitoring of soybean genotypes is important because of intellectual property over seed technology, better management over seed genetics, and more efficient strategies for its agricultural production process. This paper aims at spectrally classifying soybean genotypes submitted to diverse water availability levels at different phenological stages using leaf-based hyperspectral reflectance. Leaf reflectance spectra were collected using a hyperspectral proximal sensor. Two experiments were conducted as field trials: one experiment was at Embrapa Soja in the 2016\/2017, 2017\/2018, and 2018\/2019 cropping seasons, where ten soybean genotypes were grown under four water conditions; and another experiment was in the experimental farm of Unoeste University in the 2018\/2019 cropping season, where nine soybean genotypes were evaluated. The spectral data collected was divided into nine spectral datasets, comprising single and multiple cropping seasons (from 2016 to 2019), and two contrasting crop-growing environments. Principal component analysis, applied as an indicator of the explained variance of the reflectance spectra among genotypes within each spectral dataset, explained over 94% of the spectral variance in the first three principal components. Linear discriminant analysis, used to obtain a model of classification of each reflectance spectra of soybean leaves into each soybean genotype, achieved accuracy between 61% and 100% in the calibration procedure and between 50% and 100% in the validation procedure. Misclassification was observed only between genotypes from the same genetic background. The results demonstrated the great potential of the spectral classification of soybean genotypes at leaf-scale, regardless of the phenological stages or water status to which plants were submitted.<\/jats:p>","DOI":"10.3390\/rs13020172","type":"journal-article","created":{"date-parts":[[2021,1,6]],"date-time":"2021-01-06T20:45:42Z","timestamp":1609965942000},"page":"172","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":24,"title":["Classification of Soybean Genotypes Assessed Under Different Water Availability and at Different Phenological Stages Using Leaf-Based Hyperspectral Reflectance"],"prefix":"10.3390","volume":"13","author":[{"given":"\u00a0Luis Guilherme Teixeira","family":"Crusiol","sequence":"first","affiliation":[{"name":"Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences\/Key Laboratory of Agricultural Remote Sensing, Ministry of Agriculture, Beijing 100081, China"},{"name":"Department of Agronomy, State University of Maring\u00e1, Maring\u00e1, PR 87020-900, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4854-2661","authenticated-orcid":false,"given":"Marcos Rafael","family":"Nanni","sequence":"additional","affiliation":[{"name":"Department of Agronomy, State University of Maring\u00e1, Maring\u00e1, PR 87020-900, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Renato Herrig","family":"Furlanetto","sequence":"additional","affiliation":[{"name":"Department of Agronomy, State University of Maring\u00e1, Maring\u00e1, PR 87020-900, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8711-438X","authenticated-orcid":false,"given":"Rubson Natal Ribeiro","family":"Sibaldelli","sequence":"additional","affiliation":[{"name":"Londrina, Londrina, PR 86000-000, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Everson","family":"Cezar","sequence":"additional","affiliation":[{"name":"Department of Agronomy, State University of Maring\u00e1, Maring\u00e1, PR 87020-900, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Liang","family":"Sun","sequence":"additional","affiliation":[{"name":"Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences\/Key Laboratory of Agricultural Remote Sensing, Ministry of Agriculture, Beijing 100081, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jos\u00e9 Salvador Simonetto","family":"Foloni","sequence":"additional","affiliation":[{"name":"Embrapa Soja (National Soybean Research Centre\u2013Brazilian Agricultural Research Corporation), Londrina, PR 86001-970, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7622-0649","authenticated-orcid":false,"given":"Liliane Marcia","family":"Mertz-Henning","sequence":"additional","affiliation":[{"name":"Embrapa Soja (National Soybean Research Centre\u2013Brazilian Agricultural Research Corporation), Londrina, PR 86001-970, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alexandre Lima","family":"Nepomuceno","sequence":"additional","affiliation":[{"name":"Embrapa Soja (National Soybean Research Centre\u2013Brazilian Agricultural Research Corporation), Londrina, PR 86001-970, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Norman","family":"Neumaier","sequence":"additional","affiliation":[{"name":"Embrapa Soja (National Soybean Research Centre\u2013Brazilian Agricultural Research Corporation), Londrina, PR 86001-970, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jos\u00e9 Renato Bou\u00e7as","family":"Farias","sequence":"additional","affiliation":[{"name":"Embrapa Soja (National Soybean Research Centre\u2013Brazilian Agricultural Research Corporation), Londrina, PR 86001-970, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,1,6]]},"reference":[{"key":"ref_1","unstructured":"CONAB (National Company of Food Supply) (2020, March 25). 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