Characterisation and identification of individual intact goat muscle samples (Capra sp.) using a portable near-infrared spectrometer and chemometrics
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00027014%3A_____%2F22%3AN0000128" target="_blank" >RIV/00027014:_____/22:N0000128 - isvavai.cz</a>
Alternative codes found
RIV/60460709:41210/22:92256
Result on the web
<a href="http://mdpi.com" target="_blank" >http://mdpi.com</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3390/foods11182894" target="_blank" >10.3390/foods11182894</a>
Alternative languages
Result language
angličtina
Original language name
Characterisation and identification of individual intact goat muscle samples (Capra sp.) using a portable near-infrared spectrometer and chemometrics
Original language description
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.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
21101 - Food and beverages
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Foods
ISSN
2304-8158
e-ISSN
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Volume of the periodical
11
Issue of the periodical within the volume
18
Country of publishing house
CH - SWITZERLAND
Number of pages
8
Pages from-to
Article number: 2894
UT code for WoS article
000860107700001
EID of the result in the Scopus database
2-s2.0-85138646786