Volatile Compounds for Discrimination between Beef, Pork, and Their Admixture Using Solid-Phase- Microextraction-Gas Chromatography-Mass Spectrometry (SPME-GC-MS) and Chemometrics Analysisopen accessVolatile Compounds for Discrimination between Beef, Pork, and Their Admixture Using Solid-Phase- Microextraction-Gas Chromatography-Mass Spectrometry (SPME-GC-MS) and Chemometrics Analysis
- Other Titles
- Volatile Compounds for Discrimination between Beef, Pork, and Their Admixture Using Solid-Phase- Microextraction-Gas Chromatography-Mass Spectrometry (SPME-GC-MS) and Chemometrics Analysis
- Authors
- Zubayed Ahamed; 서진규; 엄정욱; 양한술
- Issue Date
- Jul-2024
- Publisher
- 한국축산식품학회
- Keywords
- solid-phase-microextraction-gas chromatography-mass spectrometry (SPMEGC- MS); adulteration; partial least square-discriminant analysis (PLS-DA); principal component analysis (PCA); cooked meat
- Citation
- 한국축산식품학회지, v.44, no.4, pp 934 - 950
- Pages
- 17
- Indexed
- SCIE
SCOPUS
KCI
- Journal Title
- 한국축산식품학회지
- Volume
- 44
- Number
- 4
- Start Page
- 934
- End Page
- 950
- URI
- https://scholarworks.gnu.ac.kr/handle/sw.gnu/71105
- DOI
- 10.5851/kosfa.2024.e32
- ISSN
- 2636-0772
2636-0780
- Abstract
- This study addresses the prevalent issue of meat species authentication and adulteration through a chemometrics-based approach, crucial for upholding public health and ensuring a fair marketplace. Volatile compounds were extracted and analyzed using headspace-solid-phase-microextraction-gas chromatography-mass spectrometry. Adulterated meat samples were effectively identified through principal component analysis (PCA) and partial least square-discriminant analysis (PLS-DA). Through variable importance in projection scores and a Random Forest test, 11 key compounds, including nonanal, octanal, hexadecanal, benzaldehyde, 1-octanol, hexanoic acid, heptanoic acid, octanoic acid, and 2-acetylpyrrole for beef, and hexanal and 1-octen-3-ol for pork, were robustly identified as biomarkers. These compounds exhibited a discernible trend in adulterated samples based on adulteration ratios, evident in a heatmap. Notably, lipid degradation compounds strongly influenced meat discrimination. PCA and PLS-DA yielded significant sample separation, with the first two components capturing 80% and 72.1% of total variance, respectively. This technique could be a reliable method for detecting meat adulteration in cooked meat.
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