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KMID : 1024620220420020240
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Food Science of Animal Resources
2022 Volume.42 No. 2 p.240 ~ p.251
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Distinguishing Aroma Profile of Highly-Marbled Beef according to Quality Grade using Electronic Nose Sensors Data and Chemometrics Approach
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Dicky Tri Utama
Jang Ae-Ra
Kim Gur-Yoo
Kang Sun-Moon
Lee Sung-Ki
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Abstract
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Fat deposition in animal muscles differs according to the genetics and muscle anatomical locations. Moreover, different fat to lean muscle ratios (quality grade, QG) might contribute to aroma development in highly marbled beef. Scientific evidence is required to determine whether the abundance of aroma volatiles is positively correlated with the amount of fat in highly marbled beef. Therefore, this study aims to investigate the effect of QG on beef aroma profile using electronic nose data and a chemometric approach. An electronic nose with metal oxide semiconductors was used, and discrimination was performed using multivariate analysis, including principal component analysis and hierarchical clustering. The M. longissimus lumborum (striploin) of QG 1++, 1+, 1, and 2 of Hanwoo steers (n=6), finished under identical feeding systems on similar farms, were used. In contrast to the proportion of monounsaturated fatty acids (MUFAs), the abundance of volatile compounds and the proportion of polyunsaturated fatty acids (PUFAs) decreased as the QG increased. The aroma profile of striploin from carcasses of different QGs was well-discriminated. QG1++ was close to QG1+, while QG1 and QG2 were within a cluster. In conclusion, aroma development in beef is strongly influenced by fat deposition, particularly the fat-to-lean muscle ratio with regard to the proportion of PUFA. As MUFA slows down the oxidation and release of volatile compounds, leaner beef containing a higher proportion of PUFA produces more volatile compounds than beef with a higher amount of intramuscular fat.
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KEYWORD
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hierarchical clustering, lipid oxidation, marbling, multivariate analysis, principal component analysis, volatile compounds
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