Non-Destructive Spectroscopic Techniques and Multivariate Analysis for Assessment of Fat Quality in Pork and Pork Products: A Review

被引:51
作者
Kucha, Christopher T. [1 ]
Liu, Li [1 ]
Ngadi, Michael O. [1 ]
机构
[1] McGill Univ, Dept Bioresource Engn, Macdonald Campus 21,111 Lakeshore Rd, Quebec City, PQ H9X 3V9, Canada
来源
SENSORS | 2018年 / 18卷 / 02期
关键词
hyperspectral imaging; spectroscopy; multivariate analysis; pork; fat quality; fatty acid; solid fat content; iodine value; oxidative stability; fat colour; NEAR-INFRARED SPECTROSCOPY; IBERIAN BREED SWINE; PIG ADIPOSE-TISSUE; ACID-COMPOSITION; INTRAMUSCULAR FAT; LIPID OXIDATION; MEAT-PRODUCTS; REFLECTANCE SPECTROSCOPY; SUBCUTANEOUS FAT; IODINE VALUE;
D O I
10.3390/s18020377
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Fat is one of the most important traits determining the quality of pork. The composition of the fat greatly influences the quality of pork and its processed products, and contribute to defining the overall carcass value. However, establishing an efficient method for assessing fat quality parameters such as fatty acid composition, solid fat content, oxidative stability, iodine value, and fat color, remains a challenge that must be addressed. Conventional methods such as visual inspection, mechanical methods, and chemical methods are used off the production line, which often results in an inaccurate representation of the process because the dynamics are lost due to the time required to perform the analysis. Consequently, rapid, and non-destructive alternative methods are needed. In this paper, the traditional fat quality assessment techniques are discussed with emphasis on spectroscopic techniques as an alternative. Potential spectroscopic techniques include infrared spectroscopy, nuclear magnetic resonance and Raman spectroscopy. Hyperspectral imaging as an emerging advanced spectroscopy-based technology is introduced and discussed for the recent development of assessment for fat quality attributes. All techniques are described in terms of their operating principles and the research advances involving their application for pork fat quality parameters. Future trends for the non-destructive spectroscopic techniques are also discussed.
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页数:23
相关论文
共 96 条
  • [31] On-line determination of fatty acid composition in intramuscular fat of Iberian pork loin by NIRs with a remote reflectance fibre optic probe
    González-Martín, I
    González-Pérez, C
    Alvarez-García, N
    González-Cabrera, JM
    [J]. MEAT SCIENCE, 2005, 69 (02) : 243 - 248
  • [32] Determination of fatty acids in the subcutaneous fat of Iberian breed swine by near infrared spectroscopy (NIRS) with a fibre-optic probe
    González-Martín, I
    González-Pérez, C
    Hernández-Méndez, J
    Alvarez-García, N
    [J]. MEAT SCIENCE, 2003, 65 (02) : 713 - 719
  • [33] Determination of fatty acids in the subcutaneous fat of Iberian breed swine by near infrared spectroscopy.: A comparative study of the methods for obtaining total lipids:: solvents and melting with microwaves
    González-Martín, I
    González-Pérez, C
    Hernández-Méndez, J
    Alvarez-García, N
    Lázaro, SM
    [J]. JOURNAL OF NEAR INFRARED SPECTROSCOPY, 2002, 10 (04) : 257 - 268
  • [34] Gray J. I., 1992, Trends in Food Science & Technology, V3, P315
  • [35] Hemminga M. A., 1992, Trends in Food Science & Technology, V3, P179, DOI 10.1016/0924-2244(92)90186-Z
  • [36] Heussen P., 2011, DIFFERENTIAL SCANNIN, P1
  • [37] NEAR-INFRARED SPECTRA OF FATTY ACIDS AND SOME RELATED SUBSTANCES
    HOLMAN, RT
    EDMONDSON, PR
    [J]. ANALYTICAL CHEMISTRY, 1956, 28 (10) : 1533 - 1538
  • [38] A REVIEW OF THE METHODOLOGY OF THE 2-THIOBARBITURIC ACID TEST
    HOYLAND, DV
    TAYLOR, AJ
    [J]. FOOD CHEMISTRY, 1991, 40 (03) : 271 - 291
  • [39] Rapid and non-invasive quantification of intramuscular fat content of intact pork cuts
    Huang, H.
    Liu, L.
    Ngadi, M. O.
    Gariepy, C.
    [J]. TALANTA, 2014, 119 : 385 - 395
  • [40] Assessment of intramuscular fat content of pork using NIR hyperspectral images of rib end
    Huang, Hui
    Liu, Li
    Ngadi, Michael O.
    [J]. JOURNAL OF FOOD ENGINEERING, 2017, 193 : 29 - 41