{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,16]],"date-time":"2026-06-16T20:19:55Z","timestamp":1781641195965,"version":"3.54.5"},"reference-count":54,"publisher":"MDPI AG","issue":"20","license":[{"start":{"date-parts":[[2021,10,16]],"date-time":"2021-10-16T00:00:00Z","timestamp":1634342400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Institute of Agricultural Sciences, Rural Development Administration, Korea.","award":["Project No. PJ014943012021"],"award-info":[{"award-number":["Project No. PJ014943012021"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The feasibility of rapid and non-destructive classification of six different Amaranthus species was investigated using visible-near-infrared (Vis-NIR) spectra coupled with chemometric approaches. The focus of this research would be to use a handheld spectrometer in the field to classify six Amaranthus sp. in different geographical regions of South Korea. Spectra were obtained from the adaxial side of the leaves at 1.5 nm intervals in the Vis-NIR spectral range between 400 and 1075 nm. The obtained spectra were assessed with four different preprocessing methods in order to detect the optimum preprocessing method with high classification accuracy. Preprocessed spectra of six Amaranthus sp. were used as input for the machine learning-based chemometric analysis. All the classification results were validated using cross-validation to produce robust estimates of classification accuracies. The different combinations of preprocessing and modeling were shown to have a classification accuracy of between 71% and 99.7% after the cross-validation. The combination of Savitzky-Golay preprocessing and Support vector machine showed a maximum mean classification accuracy of 99.7% for the discrimination of Amaranthus sp. Considering the high number of spectra involved in this study, the growth stage of the plants, varying measurement locations, and the scanning position of leaves on the plant are all important. We conclude that Vis-NIR spectroscopy, in combination with appropriate preprocessing and machine learning methods, may be used in the field to effectively classify Amaranthus sp. for the effective management of the weedy species and\/or for monitoring their food applications.<\/jats:p>","DOI":"10.3390\/rs13204149","type":"journal-article","created":{"date-parts":[[2021,10,17]],"date-time":"2021-10-17T23:25:15Z","timestamp":1634513115000},"page":"4149","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":29,"title":["Identification of Amaranthus Species Using Visible-Near-Infrared (Vis-NIR) Spectroscopy and Machine Learning Methods"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8819-7247","authenticated-orcid":false,"given":"Soo-In","family":"Sohn","sequence":"first","affiliation":[{"name":"Department of Agricultural Biotechnology, National Institute of Agricultural Sciences, Rural Development Administration, Jeonju 54874, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Young-Ju","family":"Oh","sequence":"additional","affiliation":[{"name":"Institute for Future Environmental Ecology Co., Ltd., Jeonju 54883, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1445-8122","authenticated-orcid":false,"given":"Subramani","family":"Pandian","sequence":"additional","affiliation":[{"name":"Department of Agricultural Biotechnology, National Institute of Agricultural Sciences, Rural Development Administration, Jeonju 54874, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yong-Ho","family":"Lee","sequence":"additional","affiliation":[{"name":"Institute of Ecological Phytochemistry, Hankyong National University, Anseong 17579, Korea"},{"name":"OJeong Resilience Institute, Korea University, Seoul 02841, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2058-4416","authenticated-orcid":false,"given":"John-Lewis Zinia","family":"Zaukuu","sequence":"additional","affiliation":[{"name":"Department of Food Science and Technology, Kwame Nkrumah University of Science and Technology (KNUST), Kumasi 0233, Ghana"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hyeon-Jung","family":"Kang","sequence":"additional","affiliation":[{"name":"Department of Agricultural Biotechnology, National Institute of Agricultural Sciences, Rural Development Administration, Jeonju 54874, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tae-Hun","family":"Ryu","sequence":"additional","affiliation":[{"name":"Department of Agricultural Biotechnology, National Institute of Agricultural Sciences, Rural Development Administration, Jeonju 54874, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Woo-Suk","family":"Cho","sequence":"additional","affiliation":[{"name":"Department of Agricultural Biotechnology, National Institute of Agricultural Sciences, Rural Development Administration, Jeonju 54874, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Youn-Sung","family":"Cho","sequence":"additional","affiliation":[{"name":"Department of Agricultural Biotechnology, National Institute of Agricultural Sciences, Rural Development Administration, Jeonju 54874, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Eun-Kyoung","family":"Shin","sequence":"additional","affiliation":[{"name":"Department of Agricultural Biotechnology, National Institute of Agricultural Sciences, Rural Development Administration, Jeonju 54874, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,10,16]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"132","DOI":"10.11110\/kjpt.2014.44.2.132","article-title":"A newly naturalized species in Korea: Amaranthus powellii S. 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