Characterisation and Identification of Individual Intact Goat Muscle Samples (

carcass chemometrics classification goat meat infrared

Journal

Foods (Basel, Switzerland)
ISSN: 2304-8158
Titre abrégé: Foods
Pays: Switzerland
ID NLM: 101670569

Informations de publication

Date de publication:
18 Sep 2022
Historique:
received: 04 09 2022
revised: 07 09 2022
accepted: 13 09 2022
entrez: 23 9 2022
pubmed: 24 9 2022
medline: 24 9 2022
Statut: epublish

Résumé

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

Identifiants

pubmed: 36141022
pii: foods11182894
doi: 10.3390/foods11182894
pmc: PMC9498649
pii:
doi:

Types de publication

Journal Article

Langues

eng

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Auteurs

Louwrens C Hoffman (LC)

Queensland Alliance for Agriculture and Food Innovation (QAAFI), Centre for Nutrition and Food Sciences (CNAFS), The University of Queensland, Brisbane, QLD 4072, Australia.

Prasheek Ingle (P)

Queensland Alliance for Agriculture and Food Innovation (QAAFI), Centre for Nutrition and Food Sciences (CNAFS), The University of Queensland, Brisbane, QLD 4072, Australia.
School of Agriculture and Food Sciences, The University of Queensland, Brisbane, QLD 4072, Australia.

Ankita Hemant Khole (AH)

Queensland Alliance for Agriculture and Food Innovation (QAAFI), Centre for Nutrition and Food Sciences (CNAFS), The University of Queensland, Brisbane, QLD 4072, Australia.
School of Agriculture and Food Sciences, The University of Queensland, Brisbane, QLD 4072, Australia.

Shuxin Zhang (S)

Queensland Alliance for Agriculture and Food Innovation (QAAFI), Centre for Nutrition and Food Sciences (CNAFS), The University of Queensland, Brisbane, QLD 4072, Australia.
School of Agriculture and Food Sciences, The University of Queensland, Brisbane, QLD 4072, Australia.

Zhiyin Yang (Z)

Queensland Alliance for Agriculture and Food Innovation (QAAFI), Centre for Nutrition and Food Sciences (CNAFS), The University of Queensland, Brisbane, QLD 4072, Australia.
School of Agriculture and Food Sciences, The University of Queensland, Brisbane, QLD 4072, Australia.

Michel Beya (M)

Queensland Alliance for Agriculture and Food Innovation (QAAFI), Centre for Nutrition and Food Sciences (CNAFS), The University of Queensland, Brisbane, QLD 4072, Australia.

Daniel Bureš (D)

Institute of Animal Science, Přátelství 815, 104 00 Prague, Czech Republic.
Department of Food Science, Faculty of Agrobiology, Food and Natural Resources, Czech University of Life Sciences Prague, 165 00 Prague, Czech Republic.

Daniel Cozzolino (D)

Queensland Alliance for Agriculture and Food Innovation (QAAFI), Centre for Nutrition and Food Sciences (CNAFS), The University of Queensland, Brisbane, QLD 4072, Australia.

Classifications MeSH