Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/338252
Type: Artigo
Title: Identification of fiber added to semolina by near infrared (NIR) spectral techniques
Author: Badaro, Amanda Teixeira
Morimitsu, Fernanda Lie
Ferreira, Amanda Rios
Pedrosa Silva Clerici, Maria Teresa
Barbin, Douglas Fernandes
Abstract: Ingredients added in food products can increase the nutritional value, but also affect their functional properties. After processing, determination of added ingredients is difficult, thus it is important to develop rapid techniques for quantification of food ingredients. In the current work, near infrared spectroscopy (NIRS) and hyperspectral imaging (NIR-HSI) were investigated to quantify the amount of fiber added to semolina and its distribution. NIR spectra were acquired to compare the accuracy in the classification, quantification and distribution of fibers added to semolina. Principal Component Analyses (PCA) and Soft Independent Modeling of Class Analogy (SIMCA) were used for classification. Partial Least Squares Regression (PLSR) models applied to NIR-HSI spectra showed R-p(2), between 0.85 and 0.98, and RMSEP between 0.5 and 1%, and were used for prediction map of the samples. These results showed that NIR-HSI technique can be used for the identification and quantification of fiber added to semolina
Subject: Espectroscopia de infravermelho próximo
Country: Países Baixos
Editor: Elsevier
Rights: Fechado
Identifier DOI: 10.1016/j.foodchem.2019.03.057
Address: https://www.sciencedirect.com/science/article/pii/S0308814619305345
Date Issue: 2019
Appears in Collections:FEA - Artigos e Outros Documentos

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