近红外光谱技术在肉品检测中的应用和研究进展

doi:10.3964/j.issn.1000-0593(2009)07-1876-05

Abstract
References
Related Citation (15)

Download: PDF (1072 KB)
Export: BibTeX | EndNote (RIS)

Abstract As one of new optical detection methods, near-infrared spectroscopy (NIRS) technique has been widely used in food industry in recent years. NIRS technique is also promising for quality evaluation of meat and meat products and is characterized by its quickness, online operation and nondestructive detection. The present paper reviews the main application and recent development of research on near-infrared spectroscopy in meat industry, including components analysis, sensory quality evaluation as well as discrimination of production. It’s necessary to determine the content of main chemical components in a variety of meat such as protein, fat, water etc as they exert important influence on meat quality. Sensory quality including tenderness, water holding capacity, color, and freshness is commonly evaluated by human sensory system. Thus there is an obvious potential profit to achieve online determination industrialization for meat quality. Additionally the utilization of NIRS in quality detection of common meat products is particularized in this paper. Most study of near-infrared spectroscopy technique for meat quality evaluation lays emphasis on component analysis that especially has shown a progress in the determination of protein, fat, water and part of fatty acid, which has been investigated much recently. Not any kind of sensory quality can be well predicted by NIRS as it depends on the species of meat and the limitation of this optical technique. Therein beef is the mostly used object with many reports on the evaluation of tenderness compared to other types. There is a lot of investigation for sensory quality detection of pork on water holding capacity etc. Meanwhile this review also tries to come up with some perspectives on meat quality detection with near-infrared spectroscopy according to current development trend: on the basis of deeply improving the meat detection precision, near-infrared spectroscopy technique combined with other non-detection techniques like machine vision will be investigated in order to realize overall evaluation of meat quality.

Key words：Near-infrared spectroscopy;Meat;Chemical components;Sensory quality;Discrimination

Received: 2008-05-12 Accepted: 2008-08-16

ZTFLH:

O657.3

Corresponding Authors: CHENG Fang E-mail: fcheng@zju.edu.cn

Cite this article:

XU Xia,CHENG Fang,YING Yi-bin. Application and Recent Development of Research on Near-Infrared Spectroscopy for Meat Quality Evaluation[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2009, 29(07): 1876-1880.

URL:

https://www.gpxygpfx.com/EN/10.3964/j.issn.1000-0593(2009)07-1876-05 OR https://www.gpxygpfx.com/EN/Y2009/V29/I07/1876

[1] Monin G. Meat Science, 1998, 49(2): 231.
[2] Xiccato G, Trocino A, Tulli F, et al. Food Chemistry, 2004, 86(2):275.
[3] Togersen G, Isaksson T, Nilsen B N, et al. Meat Science, 1999, 51(1): 97.
[4] Gonzalez-Martin I, Gonzalez-Perez C, Hernandez-Mendez J, et al. Analytica Chimica Acta, 2002, 453(2): 281.
[5] Gonzalez-Martin I, Gonzalez-Perez C, Hernandez-Mendez J, et al. Analytica Chimica Acta, 2002, 468(2): 293.
[6] Ripoche A, Guillard A S. Meat Science, 2001, 58(3): 299.
[7] Prieto N, Andres S, Giraldez F J, et al. Meat Science, 2006, 74(3): 487.
[8] Pla M, Hernandez P, Arino B, et al. Food Chemistry, 2007, 100(1): 165.
[9] Viljoen M, Hoffman L C, Brand T S. Small Ruminant Research, 2007, 69(1-3): 88.
[10] Kadim I T, Mahgoub O, Al-Marzooqi W, et al. Asian-Australasian Journal of Animal Sciences, 2005, 18(7): 1036.
[11] Byrne C E, Downey G, Troy D J, et al. Meat Science, 1998, 49(4): 399.
[12] Park B, Chen W R, Hruschka S D, et al. Transactions of the ASAE, 2001, 44(3): 609.
[13] ZHAO Jie-wen, ZHAI Jian-mei, LIU Mu-hua, et al(赵杰文, 翟剑妹，刘木华，等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2006, 26(4): 640.
[14] Forrest J C, Morgan M T, Borggaard C, et al. Meat Science, 2000, 55(1): 115.
[15] Geesink G H, Schreutelkamp F H, Frankhuizen R, et al. Meat Science, 2003, 65(1): 661.
[16] Sante V S, Lebert A, Le Pottier G, et al. Meat Science, 1996, 43(3-4): 283.
[17] Cozzolino D, Barlocco N, Vadell A, et al. Lebensmittel-Wissenschaft und-Technologie, 2003, 36(2): 195.
[18] Leroy B, Lambotte S, Dotreppe O, et al. Meat Science, 2004, 66(1): 45.
[19] HOU Rui-feng, HUANG Lan, WANG Zhong-yi, et al(侯瑞锋, 黄岚, 王忠义, 等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2006, 26(12): 2193.
[20] Alomar D, Gallo C, Castaneda M, et al. Meat Science, 2003, 63(4): 441.
[21] Cozzolino D, Murray I. Swiss Society of Food Science and Technology, 2004, 37(4): 447.
[22] Javier Gayo, Scott A. Hale, Journal of Agricultural and Food Chemistry, 2007, 55(3): 585.
[23] Ortiz-Somovilla V, Espana-Espana F, Gaitan-Jurado A J, et al. Food Chemistry, 2007, 101(3): 1031.
[24] ZHAO Li-li, ZHANG Lu-da, SONG Zhong-xiang, et al(赵丽丽, 张录达, 宋忠祥, 等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2007, 27(1): 46.
[25] Ding H B, Xu R J. Journal of Agricultural and Food Chemistry, 2000, 48(6): 2193.
[26] TU Kang(屠康). Journal of Northwest Science-Technique University of Agriculture and Forrest.(Nat. Sci. Ed.)(西北农林科技大学学报·自然科学版)，2005, 33(1): 25.