Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/354567
Type: Artigo
Title: Classification of individual cotton seeds with respect to variety using near-infrared hyperspectral imaging
Author: Soares, Sófacles Figueredo Carreiro
Medeiros, Everaldo Paulo
Pasquini, Celio
Morello, Camilo de Lelis
Galvão, Roberto Kawakami Harrop
Araújo, Mário César Ugulino
Abstract: This paper proposes the use of Near Infrared Hyperspectral Imaging (NIR-HSI) as a new strategy for fast and non-destructive classification of cotton seeds with respect to variety. A total of 807 seeds of four different cotton varieties are employed in this study. For classification purposes, each seed is represented by an average spectrum obtained by coaveraging the pixel spectra of the NIR-HSI image. Conventional NIR and VIS-NIR spectra are also employed for comparison. By using Partial-Least-Squares Discriminant Analysis (PLS-DA), correct classification rates of 98.0%, 89.7% and 91.7% were achieved in the NIR-HSI, conventional NIR and conventional VIS-NIR datasets. The superiority of the NIR-HSI system can be ascribed to a more comprehensive scan of the seed area, as compared to the conventional VIS-NIR spectrometer
Subject: Algodão
Imagem hiperespectral
Country: Reino Unido
Editor: Royal Society of Chemistry
Rights: Aberto
Identifier DOI: 10.1039/c6ay02896a
Address: https://pubs.rsc.org/en/content/articlelanding/2016/AY/C6AY02896A
Date Issue: 2016
Appears in Collections:IQ - Artigos e Outros Documentos

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