Classification of sugarcane varieties using visible/near infrared spectral reflectance of stalks and multivariate methods
Autor: | João Vitor Toledo, Sérgio Zolnier, Thieres George Freire da Silva, Daniela de Carvalho Lopes, A. J. Steidle Neto |
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Rok vydání: | 2018 |
Předmět: |
Multivariate statistics
business.industry Visible near infrared 010401 analytical chemistry Near-infrared spectroscopy Pattern recognition Context (language use) 04 agricultural and veterinary sciences Linear discriminant analysis 01 natural sciences Reflectivity 0104 chemical sciences Chemometrics Principal component analysis 040103 agronomy & agriculture Genetics 0401 agriculture forestry and fisheries Animal Science and Zoology Artificial intelligence business Agronomy and Crop Science Mathematics |
Zdroj: | The Journal of Agricultural Science. 156:537-546 |
ISSN: | 1469-5146 0021-8596 |
Popis: | The use of fast and non-destructive techniques for identifying sugarcane varieties enables the development of automatic sorting systems, contributing towards improving pre-processing steps in the alcohol and sugar industries. In this context, principal component analysis (PCA), factorial discriminant analysis (FDA), stepwise forward discriminant analysis (SFDA) and partial least-squares discriminant analysis (PLS-DA) were used to classify four Brazilian sugarcane varieties based on visible/near infrared (Vis/NIR) spectral reflectance measurements (450–1000 nm range) of stalks. All wavelengths contributed towards discriminating the sugarcane varieties, but the 600–750 nm range was most relevant. When evaluating PCA results considering the four sugarcane varieties, two of them overlapped and it was only possible to use classifiers of three varieties. Factorial discriminant analysis, PLS-DA and SFDA reached correct classifications of 0.81, 0.82 and 0.74, respectively, when considering the external validation data and the four sugarcane varieties evaluated. Results showed that Vis/NIR spectroscopy combined with discriminating methods is a promising tool for non-destructive and fast sugarcane variety classification, which can be used in the agro-food industry or directly in the field. |
Databáze: | OpenAIRE |
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