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http://hdl.handle.net/1843/39605
Type: | Artigo de Periódico |
Title: | Variable selection for multivariate classification aiming to detect individual adulterants and their blends in grape nectars |
Authors: | Carolina Sheng Whei Miaw Marcelo Martins Sena Scheilla Vitorino Carvalho de Souza Itziar Ruisanchez Maria Pilar Callao |
Abstract: | During the quality inspection control of fruit beverages, some types of adulterations can be detected, such as the addition or substitution with less expensive fruits. To determine whether grape nectars were adulterated by substitution with apple or cashew juice or by a mixture of both, a methodology based on attenuated total reflectance Fourier transform mid infrared spectroscopy (ATR-FTIR) and multivariate classification methods was proposed. Partial least squares discriminant analysis (PLS-DA) and soft independent modeling of class analogy (SIMCA) models were developed as multi-class methods (classes unadulterated, adulterated with cashew and adulterated with apple) with the full-spectra. PLS-DA presented better performance parameters than SIMCA in the classification of samples with just one adulterant, while poor results were achieved for samples with blends of two adulterants when using both classification methods. Three variable selection methods were tested in order to improve the effectiveness of the classification models: interval partial least squares (iPLS), variable importance in projection scores (VIP scores) and a genetic algorithm (GA). Variable selection methods improved the performance parameters for the SIMCA and PLS-DA methods when they were used to predict samples with only one adulterant. Only PLS-DA coupled with iPLS was able to classify samples with blends of two adulterants, providing sensitivity values between 100% and 83% at 100% specificity for the three studied classes. |
Subject: | Tecnologia de alimentos Sucos |
language: | eng |
metadata.dc.publisher.country: | Brasil |
Publisher: | Universidade Federal de Minas Gerais |
Publisher Initials: | UFMG |
metadata.dc.publisher.department: | FAR - DEPARTAMENTO DE ALIMENTOS ICX - DEPARTAMENTO DE QUÍMICA |
Rights: | Acesso Restrito |
metadata.dc.identifier.doi: | 10.1016/j.talanta.2018.07.078 |
URI: | http://hdl.handle.net/1843/39605 |
Issue Date: | 2018 |
metadata.dc.url.externa: | http://https://www.sciencedirect.com/science/article/pii/S0039914018307859 |
metadata.dc.relation.ispartof: | Talanta |
Appears in Collections: | Artigo de Periódico |
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