ANALYSIS S. Kopuzlu, A. Onenc, O. C. Bilgin, N. Esenbuga
1 Animal Science Dept., Agriculture Faculty, Atatürk University Erzurum, Turkey 2 Animal Science Dept. Agriculture Faculty, Namık Kemal University, Tekirdag, Turkey
In the present investigation, Principal Component Analysis (PCA) was applied to various variables to describe meat quality. Sixteen meat quality variables were examined, and the analysis showed that 60.71% of the total variation was explained by the first three principal components. L*, a*, b* as colour data; odour, tenderness, flavour, acceptability as sensorial traits; hardness and chewiness as physical traits had the highest share in the total variation.
Cite Score: 1.3
JCR Year: 2025
Web of Science (SCIE)
SCOPUS (Q3)
Journal Impact Factor: 0.5
HEC Category: W
Print ISSN: 1018-7081
Electronic ISSN: 2309-8694
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