Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/241596
Type: Artigo de periódico
Title: Vis-nir Spectroscopy As A Process Analytical Technology For Compositional Characterization Of Film Biopolymers And Correlation With Their Mechanical Properties
Author: Barbin
Douglas Fernandes; Valous
Nektarios A.; Dias
Adriana Passos; Camisa
Jaqueline; Hirooka
Elisa Yoko; Yamashita
Fabio
Abstract: There is an increasing interest in the use of polysaccharides and proteins for the production of biodegradable films. Visible and near-infrared (VIS-NIR) spectroscopy is a reliable analytical tool for objective analyses of biological sample attributes. The objective is to investigate the potential of VIS-NIR spectroscopy as a process analytical technology for compositional characterization of biodegradable materials and correlation to their mechanical properties. Biofilms were produced by single-screw extrusion with different combinations of polybutylene adipate-co-terephthalate, whole oat flour, glycerol, magnesium stearate, and citric acid. Spectral data were recorded in the range of 400-2498 nm at 2 nm intervals. Partial least square regression was used to investigate the correlation between spectral information and mechanical properties. Results show that spectral information is influenced by the major constituent components, as they are clustered according to polybutylene adipate-co-terephthalate content. Results for regression models using the spectral information as predictor of tensile properties achieved satisfactory results, with coefficients of prediction (R-c(2)) of 0.83, 0.88 and 0.92 (calibration models) for elongation, tensile strength, and Young's modulus, respectively. Results corroborate the correlation of NIR spectra with tensile properties, showing that NIR spectroscopy has potential as a rapid analytical technology for non-destructive assessment of the mechanical properties of the films. (C) 2015 Elsevier B.V. All rights reserved.
Subject: Infrared-spectroscopy
Multivariate Calibration
Prediction
Regression
Spectra
Starch
Flour
Country: AMSTERDAM
Editor: ELSEVIER SCIENCE BV
Rights: embargo
Identifier DOI: 10.1016/j.msec.2015.06.029
Address: http://www.sciencedirect.com/science/article/pii/S0928493115301648
Date Issue: 2015
Appears in Collections:Unicamp - Artigos e Outros Documentos

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