The ability of a portable near infrared instrument to evaluate the shelf-life of fresh and thawed goat muscles

[Display omitted] •A portable near infrared (NIR) was evaluated to monitor shelf-life of four goat muscles.•The cross-validation statistics were obtained for the prediction of days of storage in the biceps femoris muscle.•Differences in the loadings for the cross-validation models were observed due...

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Bibliographic Details
Published in:Food research international 2024-03, Vol.180, p.114047-114047, Article 114047
Main Authors: Cozzolino, D., Wu, W., Zhang, S., Beya, M., van Jaarsveld, P.F., Hoffman, L.C.
Format: Article
Language:English
Subjects:
Animals
Goat
Goats
Hamstring Muscles
Meat - analysis
Muscles
NIR
Shelf-life
Spectra
Spectroscopy, Near-Infrared
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Summary:[Display omitted] •A portable near infrared (NIR) was evaluated to monitor shelf-life of four goat muscles.•The cross-validation statistics were obtained for the prediction of days of storage in the biceps femoris muscle.•Differences in the loadings for the cross-validation models were observed due to the interactions between the different muscle samples and days of storage.•These results showed the potential of NIR spectroscopy to identify the time of storage in four different goat muscles. The objective of this study was to evaluate the use of a portable near infrared (NIR) instrument to monitor the shelf-life of four goat muscles [longissimus thoracis et lumborum (LTL), semimembranosus (SM), semitendinosus (ST) and biceps femoris (BF)] stored for up to 8 days (4 °C). The NIR spectra of the muscle samples were collected at day 0, and after 1, 4 and 8 days of storage using a MicroNIR instrument (900–1600 nm). The coefficient of determination in cross-validation (R2) and the standard error in cross validation (SECV) obtained for the prediction of days of storage ranged between 0.76 and 0.86, where the SECV ranged from 0.32 to 0.41. The best statistics in cross-validation were obtained for the prediction of days of storage in the BF samples, followed by the ST and LTL muscles. Differences in the PLS loadings for the cross-validation models were observed due to the interactions between the different muscle samples and days of storage. Overall, these results showed the potential of NIR spectroscopy to identify the time of storage in four different goat muscles. Similar data and techniques could be used to predict the remaining shelf life of meat derived from different species under storage. This information can then be used as a tool to predict and guarantee the safety of meat samples to the consumer along the meat supply and value chains.
ISSN:0963-9969
1873-7145
DOI:10.1016/j.foodres.2024.114047