Journal
LEBENSMITTEL-WISSENSCHAFT UND-TECHNOLOGIE-FOOD SCIENCE AND TECHNOLOGY
Volume 37, Issue 4, Pages 447-452Publisher
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.lwt.2003.10.013
Keywords
visible; near infrared spectroscopy; meat; identification; speciation; Principal Component Analysis; partial least squares
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Visible (VIS) and near infrared reflectance spectroscopy (NIRS) was used to identify and authenticate different meat muscle species. Samples from beef (n: 100), lamb (n: 140), pork (n: 44) and chicken (n: 48) muscles were homogenised and scanned in the visible (VIS) and near infrared (NIR) region (400-2500nm) in a monochromator instrument in reflectance. Both Principal Component Analysis (PCA) and dummy partial least-squares regression (PLS) models were developed to identify different meat species. The models correctly classified more than 80% of the meat sample muscles according with the muscle specie. The results showed the potential of VIS and NIR spectra as an objective and rapid method for authentication and identification of meat muscle species. (C) 2003 Swiss Society of Food Science and Technology. Published by Elsevier Ltd. All rights reserved.
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