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Feasibility of near infrared transmittance spectroscopy to predict fatty acid composition of commercial processed meat
Author(s) -
De Marchi Massimo,
Manuelian Carmen L,
Ton Sofia,
Cassandro Martino,
Penasa Mauro
Publication year - 2018
Publication title -
journal of the science of food and agriculture
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.782
H-Index - 142
eISSN - 1097-0010
pISSN - 0022-5142
DOI - 10.1002/jsfa.8438
Subject(s) - transmittance , polyunsaturated fatty acid , food science , chemistry , infrared spectroscopy , fatty acid , spectroscopy , composition (language) , near infrared spectroscopy , analytical chemistry (journal) , chromatography , materials science , biochemistry , organic chemistry , biology , physics , optoelectronics , linguistics , philosophy , quantum mechanics , neuroscience
BACKGROUND The new European Regulation 1169/2011 concerning nutrition declaration of food products compels the addition of saturated fatty acids, whereas the declaration of monounsaturated and polyunsaturated fatty acids remains voluntary. Therefore, the industry is interested in a more rapid, easy and less cost‐effective analysis method for accomplishing this labelling regulation. The present study aimed to evaluate the ability of near infrared transmittance spectroscopy (wavelengths between 850 and 1050 nm) to predict the fatty acid ( FA ) composition of commercial processed meat samples ( n = 310). RESULTS Good predictions were achieved for the absolute content of saturated, unsaturated, monounsaturated and polyunsaturated FA , as well as ω‐6 groups, and also for a few individual FA ( C16 :0, C18 :0, C18 :1n9, C18 :2n6 and 18:1n7), with the coefficient of determination in cross‐validation being > 0.90 and the residual prediction deviation being > 3.15. Unsatisfactory models were obtained for the relative content of FA . CONCLUSION Near infrared transmittance spectroscopy can be considered as a reliable method for predicting the main groups of FA in processed meat products, whereas predictions of individual FA are less reliable. © 2017 Society of Chemical Industry