Adulterated, poor-quality, and unsafe foods, including meat, are still major issues for both the food industry and consumers, 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 chemometrics, to identify and classify individual-intact fresh goat muscle samples. Fresh goat carcasses (n = 35; 19 to 21.7 Kg LW) from different animals (age, breeds, sex) were used and separated into different commercial cuts. Thus, the longissimus thoracis et lumborum, biceps femoris, semimembranosus, semitendinosus, supraspinatus, and infraspinatus muscles were removed and scanned (900-1600 nm) using a portable NIR instrument. Differences in the NIR spectra of the muscles were observed at wavelengths of around 976 nm, 1180 nm, and 1430 nm, associated with water and fat content (e.g., intramuscular fat). The classification of individual muscle samples was achieved by linear discriminant analysis (LDA) with acceptable accuracies (68-94%) using the second-derivative NIR spectra. The results indicated that NIR spectroscopy could be used to identify individual goat muscles.

Department of Food Science Faculty of Agrobiology Food and Natural Resources Czech University of Life Sciences Prague 165 00 Prague Czech Republic

Institute of Animal Science Přátelství 815 104 00 Prague Czech Republic

Queensland Alliance for Agriculture and Food Innovation The University of Queensland Brisbane QLD 4072 Australia

School of Agriculture and Food Sciences The University of Queensland Brisbane QLD 4072 Australia

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Identification of individual goat animals by means of near infrared spectroscopy and chemometrics analysis of commercial meat cuts