New approach to improve the calibration of main fatty acids by near-infrared reflectance spectroscopy in ruminant meat
B. P. Mourot A B , D. Gruffat A C , D. Durand A , G. Chesneau B , S. Prache A , G. Mairesse B and D. Andueza AA National Institute for Agronomic Research (INRA), UMR 1213 Herbivores, Research Centre of Clermont-Ferrand/Theix, F-63122 Saint-Genès-Champanelle, France.
B Valorex, La Messayais, 35210 Combourtillé, France.
C Corresponding author. Email: dominique.gruffat@clermont.inra.fr
Animal Production Science 54(10) 1848-1852 https://doi.org/10.1071/AN14328
Submitted: 13 March 2014 Accepted: 18 June 2014 Published: 19 August 2014
Abstract
This study aims to investigate alternative near-infrared reflectance spectroscopy (NIRS) strategies for predicting beef polyunsaturated fatty acids (PUFA) composition, which have a great nutritional interest, and are actually poorly predicted by NIRS. We compared the results of NIRS models for predicting fatty acids (FA) of beef meat by using two databases: a beef database including 143 beef samples, and a ruminant database including 76 lamb and 143 beef samples. For all the FA, particularly for PUFA, the coefficient of determination of cross-validation (R2CV) and the residual predictive deviation (RPD) of models increased when the ruminant muscle samples database was used instead of the beef muscle database. The R2CV values for the linoleic acid, total conjugated linoleic acid and total PUFA increased from 0.44, 0.79 and 0.59 to 0.68, 0.9, 0.8, respectively, and RPD values for these FA increased from 1.33, 2.14, 1.54 to 1.76, 3.11 and 2.24, respectively. RPD above 2.5 indicates calibration model is considered as acceptable for analytical purposes. The use of a universal equation for ruminant meats to predict FA composition seems to be an encouraging strategy.
Additional keywords: beef quality, fatty acid calibration, NIR spectroscopy, standardisation.
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