Characterisation and identification of individual intact goat muscle samples (Capra sp.) using a portable near-infrared spectrometer and chemometrics
|Kateg. publikace||Vědecké publikace impaktované|
Adulterated, poor quality and unsafe meat are still major challenges for the meat industry which have driven efforts to find alternative technologies to detect these challenges. This study evaluated the use of a portable near infrared (NIR) instrument combined with machine learning techniques to identify and classify individual-intact goat muscles. Fresh goat carcasses (n=35; 19 to 21.7 Kg LW) from different breeds and sex were sourced and cut in different commercial cuts. The longissimus thoracis et lumborum, biceps femoris, semimembranosus, semitendinosus, supraspinatus, and infraspinatus muscles were removed and scanned (900 – 1600 nm). Differences in the NIR spectra of the muscles were observed at wavelengths around 976 nm, 1180 nm and 1430 nm associated with water and fat content (IMF). The classification of individual muscles was achieved by linear discriminant analysis (LDA) with acceptable accuracies (68- 94%) using the second derivative NIR spectra. The results indicated that NIR spectroscopy can be used to identify individual goat muscles.
|Projekt||Dlouhodobý koncepční rozvoj výzkumné organizace|
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