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Molecules 2019, 24(4), 757; https://doi.org/10.3390/molecules24040757

Evaluation of WBSF, Color, Cooking Loss of Longissimus Lumborum Muscle with Fiber Optic Near-Infrared Spectroscopy (FT-NIR), Depending on Aging Time

1
Division of Engineering in Nutrition, Department of Technique and Food Development, Warsaw University of Life Sciences (WULS-SGGW) 159c Nowoursynowska, 02-776 Warsaw, Poland
2
Institute of Genetics and Animal Breeding of the Polish Academy of Sciences, 05-552 Jastrzebiec, Poland
3
Department of Pharmacognosy, University of Vienna, 1090 Vienna, Austria
*
Author to whom correspondence should be addressed.
Received: 12 December 2018 / Revised: 14 February 2019 / Accepted: 18 February 2019 / Published: 20 February 2019
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Abstract

Near-infrared spectroscopy is a known technique for assessing the quality of compounds found in food products. However, it is still not widely used for predicting physical properties of meat using the online system. This study aims to assess the possibility of application of a NIR equipped with fiber optic system as an online measurement system to predict Warner–Bratzler shear force (WBSF) value, cooking loss (CL), and color of longissimus lumborum muscle, depending on aging time. The prediction model satisfactorily estimated the WBSF on day 1 and day 7 of aging as well as a* color parameter on day one and CL on day 21. This could be explained by the fact that during beef aging, the physicochemical structure of meat becomes more uniform and less differentiation of raw data is observed. There is still a challenge to obtain a verifiable model for the prediction of physical properties, using NIR, by utilizing more varied raw data. View Full-Text
Keywords: FT NIR spectroscopy; beef; WBSF; quality prediction FT NIR spectroscopy; beef; WBSF; quality prediction
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Wyrwisz, J.; Moczkowska, M.; Kurek, M.A.; Karp, S.; Atanasov, A.G.; Wierzbicka, A. Evaluation of WBSF, Color, Cooking Loss of Longissimus Lumborum Muscle with Fiber Optic Near-Infrared Spectroscopy (FT-NIR), Depending on Aging Time. Molecules 2019, 24, 757.

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