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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Fast determination of beef quality parameters with time-domain nuclear magnetic resonance spectroscopy and chemometrics

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Author(s):
Verbi Pereira, Fabiola Manhas [1] ; Pflanzer, Sergio Bertelli [2] ; Gomig, Thaisa [2] ; Gomes, Carolina Lugnani [2] ; de Felicio, Pedro Eduardo [2] ; Colnago, Luiz Alberto [1]
Total Authors: 6
Affiliation:
[1] Embrapa Instrumentacao, BR-13561206 Sao Carlos, SP - Brazil
[2] Univ Estadual Campinas, UNICAMP, Fac Engn Alimentos, Dept Tecnol Alimentos, BR-13083193 Campinas, SP - Brazil
Total Affiliations: 2
Document type: Journal article
Source: Talanta; v. 108, p. 88-91, APR 15 2013.
Web of Science Citations: 18
Abstract

The noteworthy of this study is to predict seven quality parameters for beef samples using time-domain nuclear magnetic resonance (TD-NMR) relaxometry data and multivariate models. Samples from 61 Bonsmara heifers were separated into five groups based on genetic (breeding composition) and feed system (grain and grass feed). Seven sample parameters were analyzed by reference methods; among them, three sensorial parameters, flavor, juiciness and tenderness and four physicochemical parameters, cooking loss, fat and moisture content and instrumental tenderness using Warner Bratzler shear force (WBSF). The raw beef samples of the same animals were analyzed by TD-NMR relaxometry using Carr-Purcell-Meiboom-Gill (CPMG) and Continuous Wave-Free Precession (CWFP) sequences. Regression models computed by partial least squares (PLS) chemometric technique using CPMG and CWFP data and the results of the classical analysis were constructed. The results allowed for the prediction of aforementioned seven properties. The predictive ability of the method was evaluated using the root mean square error (RMSE) for the calibration (RMSEC) and validation (RMSEP) data sets. The reference and predicted values showed no significant differences at a 95% confidence level. (c) 2013 Elsevier B.V. All rights reserved. (AU)

FAPESP's process: 10/19576-1 - Evaluation of low-field nuclear magnetic resonance for the development of analytical methods for quality control of meat products
Grantee:Fabiola Manhas Verbi Pereira
Support Opportunities: Scholarships in Brazil - Post-Doctoral