Prediction of the Lipid Degradation and Storage Time of Chilled Beef Flank by Using Raman Spectroscopy and Chemometrics

被引:4
|
作者
Bai, Jing [1 ]
Zang, Mingwu [1 ]
Zou, Hao [1 ]
Wu, Jiajia [1 ]
Shi, Yuxuan [1 ]
Wang, Hui [1 ]
Wang, Shouwei [1 ]
Qiao, Xiaoling [1 ]
机构
[1] Beijing Acad Food Sci, China Meat Res Ctr, Beijing Key Lab Meat Proc Technol, Beijing 100068, Peoples R China
关键词
Raman spectroscopy; Beef flank; Lipid degradation; Storage time; FROZEN STORAGE; LINOLEIC-ACID; FATTY-ACIDS; MEAT; OXIDATION; ANTIOXIDANT; QUALITY; OIL;
D O I
10.1007/s12161-022-02276-5
中图分类号
TS2 [食品工业];
学科分类号
0832 ;
摘要
Raman scattering and chemometrics were used to predict the lipid degradation and storage time of chilled beef flank by using a portable Raman spectrometer. Results showed that the performance of the combination of the three indicators in terms of predicting the storage time was more accurate than that of their independent usage (R-2 = 0.92 compared with 0.88, 0.35, and 0.42). Raman spectroscopy could predict the storage time (R-cv(2) = 0.76), but it could not precisely predict acid value [Av], peroxide value [Pov], and thiobarbituric acid-reactive substances [TBARS] (R-cv(2) = 0.42-0.50, 0.18-0.40, 0.41-0.43) by using three processing methods. The prediction of Av, Pov, TBARS, and storage time based on Raman intensities at the characteristic Raman shifts were more precise (R-2 = 0.87-0.95) than based on Raman intensities at full bands. Therefore, Raman spectroscopy and chemometrics could be applied to perform nondestructive quantitation and determine the lipid degradation and storage time of chilled beef flank.
引用
收藏
页码:2213 / 2223
页数:11
相关论文
共 50 条
  • [31] Effects of Storage Time of Raw Beef on Microflora Changes and Protein Degradation in Fermented Beef Sausages
    Xu Y.
    Liu S.
    Wang Y.
    Niu S.
    Yang Y.
    Yu Q.
    Xiao Z.
    Liu S.
    He L.
    Chen S.
    Liu A.
    Yang Y.
    Shipin Kexue/Food Science, 2021, 42 (09): : 184 - 191
  • [32] Nondestructive discrimination of ivories and prediction of their specific gravity by Fourier-transform Raman spectroscopy and chemometrics
    Shimoyama, M
    Ninomiya, T
    Ozaki, Y
    ANALYST, 2003, 128 (07) : 950 - 953
  • [33] Solute concentration prediction using chemometrics and ATR-FTIR spectroscopy
    Togkalidou, T
    Fujiwara, M
    Patel, S
    Braatz, RD
    JOURNAL OF CRYSTAL GROWTH, 2001, 231 (04) : 534 - 543
  • [34] Characterization of Human Meibum Lipid using Raman Spectroscopy
    Oshima, Yusuke
    Sato, Hidetoshi
    Zaghloul, Ahmed
    Foulks, Gary N.
    Yappert, Marta C.
    Borchman, Douglas
    CURRENT EYE RESEARCH, 2009, 34 (10) : 824 - 835
  • [35] Inhibitory effects of lotus seedpod procyanidins against lipid and protein oxidation and spoilage organisms in chilled-storage beef
    Li, Xin
    Wang, Jingyi
    Gao, Xueqin
    Xie, Bijun
    Sun, Zhida
    LWT-FOOD SCIENCE AND TECHNOLOGY, 2022, 160
  • [36] Characterization of hydrogen storage materials using Raman spectroscopy
    Ward, Patrick A.
    Compton, Robert N.
    ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, 2011, 241
  • [37] Authenticating common Australian beef production systems using Raman spectroscopy
    Logan, Bridgette G.
    Hopkins, David L.
    Schmidtke, Leigh M.
    Fowler, Stephanie M.
    FOOD CONTROL, 2021, 121
  • [38] Differentiating various beef cuts using spatially offset Raman spectroscopy
    Pour, Saeideh Ostovar
    Fowler, Stephanie M.
    Hopkins, David L.
    Torley, Peter
    Gill, Harsharn
    Blanch, Ewan W.
    JOURNAL OF RAMAN SPECTROSCOPY, 2020, 51 (04) : 711 - 716
  • [39] Non-destructive prediction of texture of frozen/thaw raw beef by Raman spectroscopy
    Chen, Qingmin
    Zhang, Yichi
    Guo, Yahui
    Cheng, Yuliang
    Qian, He
    Yao, Weirong
    Xie, Yunfei
    Ozaki, Yukihiro
    JOURNAL OF FOOD ENGINEERING, 2020, 266
  • [40] Non-destructive prediction of texture of frozen/thaw raw beef by Raman spectroscopy
    Chen Q.
    Zhang Y.
    Guo Y.
    Cheng Y.
    Qian H.
    Yao W.
    Xie Y.
    Ozaki Y.
    Journal of Food Engineering, 2020, 266