Scientia Agricultura Sinica ›› 2011, Vol. 44 ›› Issue (20): 4272-4278.doi: 10.3864/j.issn.0578-1752.2011.20.015

• STORAGE·FRESH-KEEPING·PROCESSING • Previous Articles     Next Articles

Analysis on Characteristics of Near Infrared Spectra of Beef According to Regions and Feeding Periods

 CAI  Xian-Feng, GUO  Bo-Li, WEI  Yi-Min, SUN  Shu-Min, ZHAO  Duo-Yong, WEI  Shuai   

  1. 1.中国农业科学院农产品加工研究所/农业部农产品加工与质量控制重点开放实验室
  • Received:2011-01-20 Online:2011-10-15 Published:2011-07-27

Abstract: 【Objective】The feasibility of using near infrared spectroscopy(NIRS) to differentiate beef from different regions and feeding periods was discussed, and the objective was to provide analytical methods and theoretical support for geographical origin assignment and authentication of beef. 【Method】 Eighteen cattle muscle samples obtained from designed migration and feeding model experiment in Taipusiqi (Inner Mongolia Autonomous Region), Yangling Zone(Shaanxi province) and Nanyang City (Henan province) were scanned by DA7200 NIR spectrometer, and the differences of NIR spectra were analyzed. Principle component analysis was used to analyze the spatial distribution of samples. 【Result】 NIR spectra of beef samples were closely related to factors such as region, feed and feeding practice, and there were significant differences in NIR spectra of samples from different regions and feeding periods. The results indicated that samples could be differentiated according to their regions and feeding periods. 【Conclusion】NIR spectra of beef are significantly affected by regions and feeding periods, which have to be taken into account for geographical origin assignment and authentication. It is feasible to differentiate beef from different regions and feeding periods using NIRS analysis.

Key words: beef, NIRspectrum, region, feedingperiod, geographicaloriginassignment, geographicaloriginauthentication

[1]邢旺兴, 谷 娜, 郭胜才, 邹晓华, 郑筱祥. 近红外漫反射光谱聚类分析法在通光藤鉴别中的应用. 解放军药学学报, 2005, 21(5): 325-327.

Xing W X, Gu N, Guo S C, Zou X H, Zheng Y X. Identification of Marsdeniae Tenacissima with clustering analysis by near-infrared diffuse reflectance Spectrometry. Pharmaceutical Journal of Chinese People's Liberation Army, 2005, 21(5): 325-327. (in Chinese)

[2]孙丽英, 杨天鸣, 王云英. 不同产地黄柏的近红外指纹图谱鉴别分析. 计算机与应用化学, 2008, 25(3): 329-332.

Sun L Y, Yang T M, Wang Y Y. Identification of Cortex phellodendri chinensis by near infrared spectroscopy fingerprint. Computers and Applied Chemistry, 2008, 25(3): 329-332. (in Chinese)

[3]张晓慧, 刘建学. 近红外光谱技术鉴别连翘产地. 激光与红外, 2008, 38(4):342-344.

Zhang X H, Liu J X. Identification of forsythia suspense from different habitats by NIR spectra. Laser and Infrared, 2008, 38(4): 342-344. (in Chinese)

[4]刘福莉, 陈华才, 姜礼义, 胡献恩. 近红外透射光谱聚类分析快速鉴别食用油种类. 中国计量学院学报, 2008, 19(3):278-282.

Liu F L, Chen H C, Jiang L Y, Hu X E. Rapid discrimination of edible oil by near infrared transmission spectroscopy using clustering analysis. Journal of China Jiliang University, 2008, 19(3): 278-282. (in Chinese)

[5]周子立, 张 瑜, 何 勇, 李晓丽, 邵咏妮. 基于近红外光谱技术的大米品种快速鉴别方法. 农业工程学报, 2009, 25(8):131-134.

Zhou Z L, Zhang Y, He Y, Li X L, Shao Y N. Method for rapid discrimination of varieties of rice using visible NIR spectroscopy. Transactions of the Chinese Society of Agricultural Engineering, 2009, 25(8): 131-134. (in Chinese)

[6]杨红菊, 姜艳彬, 候东军, 赵丽丽. 注胶肉的近红外光谱快速判别分析. 肉类研究, 2008(11): 62-64.

Yang H J, Jiang Y B, Hou D J, Zhao L L. Fast discrimination of gel-injected meat using near infrared spectra. Meat Research, 2008(11): 62-64. (in Chinese)

[7]陈兰珍, 孙 谦, 叶志华, 赵 静, 韩东海, 薛晓锋. 基于神经网络的近红外光谱鉴别蜂蜜品种研究. 食品科技, 2009, 34(8):287-289.

Chen L Z, Sun Q, Ye Z H, Zhao J, Han D H, Xue X F. Determination of floral origin of honey by near infrared spectroscopy based on artificial netural network. Food Science and Technology, 2009, 34(8): 287-289. (in Chinese)

[8]庞艳苹, 夏立娅, 左永强, 张晓瑜, 闫军颖. 近红外光谱法快速鉴别真伪平谷大久保桃. 安徽农业科学, 2010, 38(3):1122-1123, 1140.

Pang Y P, Xia L Y, Zuo Y Q, Zhang X Y, Yan J Y. Rapid true or false identification on Pinggu Okubao peach by near-infrared spectroscopy. Journal of Anhui Agricultural Sciences, 2010, 38(3): 1122-1123, 1140. (in Chinese)

[9]李凯歌, 韩东海, 孙 明. 纯牛奶中还原奶的近红外检测判别分析. 农机化研究, 2008(8): 145-147.

Li K G, Han D H, Sun M. Identification of reconstructed milk in raw milk using near infrared spectroscopy. Journal of Agricultural Mechanization Research, 2008(8): 145-147. (in Chinese)

[10]李 亮, 王雷鸣, 丁 武. 近红外光谱技术结合人工神经网络鉴别生鲜奶和蛋白掺假奶. 食品工业, 2009(6): 67-70.

Li L, Wang L M, Ding W. Study on discrimination of raw milk and milk adulterated foreign protein based on near-infrared spectroscopy and artificial neural net work model. The Food Industry, 2009(6): 67-70. (in Chinese)

[11]占茉莉, 李 勇, 魏益民, 潘家荣, 钱 和, 姚卫蓉. 应用FT-IR光谱指纹分析和模式识别技术溯源茶叶产地的研究. 核农学报, 2008, 22(6): 829-833.

Zhan M L, Li Y, Wei Y M, Pan J R, Qian H, Yao W R. Determination of the geographical origin of tea by FT-IR spectroscopy analysis and pattern recognition technique. Journal of Nuclear Agricultural Sciences, 2008, 22(6): 829-833. (in Chinese)

[12]陈永明, 林 萍, 何 勇. 基于遗传算法的近红外光谱橄榄油产地鉴别方法研究. 光谱学与光谱分析, 2009, 29(3):671-674.

Chen Y M, Lin P, He Y. Study on discrimination of producing area of olive oil using near infrared spectra based on genetic algorithms. Spectroscopy and Spectral Analysis, 2009, 29(3): 671-674. (in Chinese)

[13]张 宁, 张德权, 李淑荣, 李庆鹏. 近红外光谱结SIMCA法溯源羊肉产地的初步研究. 农业工程学报, 2008, 24(12): 309-312.

Zhang N, Zhang D Q, Li S R, Li Q P. Preliminary study on origin traceability of mutton by near infrared reflectance spectroscopy coupled with SIMCA method. Transactions of the Chinese Society of Agricultural Engineering, 2008, 24(12): 309-312. (in Chinese)

[14]李 勇, 魏益民, 潘家荣, 郭波莉. 基于FTIR指纹光谱的牛肉产地溯源技术研究. 光谱学与光谱分析, 2009, 29(3): 647-651.

Li Y, Wei Y M, Pan J R, Guo B L. Determination of geographical origin of beef based on FTIR spectroscopy analysis. Spectroscopy and Spectral Analysis, 2009, 29(3): 647-651. (in Chinese)

[15]Prieto N, Andrés S, Giráldez F J, Mantecón A R, Lavín P. Discrimination of adult steers (oxen) and young cattle ground meat samples by near infrared re?ectance spectroscopy (NIRS). Meat Science, 2008, 79:198-201.

[16]Pla M, Hernández P, Ariño B, Ramírez J A, Isabel Dí?az. Prediction of fatty acid content in rabbit meat and discrimination between conventional and organic production systems by NIRS methodology. Food Chemistry, 2007, 100: 165-170.

[17]严衍禄, 赵龙莲, 韩东海, 杨曙明. 近红外光谱分析基础与应用. 北京: 中国轻工业出版社, 2005: 31-39.

Yan Y L, Zhao L L, Han H D, Yang S M. Analytical Basis and Application of Near Infrared Spectrometry. Beijing: China Light Industry Press, 2005: 31-39. (in Chinese)

[18]褚小立, 许育鹏, 田高友译. 近红外光谱解析实用指南. 北京: 化学工业出版社, 2009: 19-55.

Chu X L, Xun Y P, Tian G Y(translate). Practical Guide to Interpretive Near-infrared Spectroscopy. Beijing: Chemical Industry Press, 2009, 19-55. (in Chinese)

[19]Coltro W, Ferreira M, Macedo F, Macedo F, Oliveira C, Visentainer J, Souza N, Matsushita M. Correlation of animal diet and fatty acid content in young goat meat by gas chromatography and chemometrics. Meat Science, 2005, 71: 358-363.

[20]Vasta V, Nudda A, Cannas A, Lanza M, Priolo A. Alternative feed resources and their effects on the quality of meat and milk from small ruminants. Animal Feed Science and Technology, 2008, 147: 223-246.

[21]Tejerina D, López-Parra M M, García-Torres S. Potential used of near infrared re?ectance spectroscopy to predict meat physico-chemical composition of guinea fowl (Numida meleagris) reared under different production systems. Food Chemistry, 2009, 113: 1290-1296.

[22]Aurousseau B, Bauchart D, Calichon E, Micol D, Priolob A. Effect of grass or concentrate feeding systems and rate of growth on triglyceride and phospholipid and their fatty acids in the M. longissimus thoracis of lambs. Meat Science, 2004, 66: 531-541.

[23]Warren H E, Scollan N D, Enser M, Hughes S I, Wood J D. Effects of breed and a concentrate or grass silage diet on beef quality in cattle of 3 ages. I: Animal performance, carcass quality and muscle fatty acid composition. Meat Science, 2008, 78: 256-269.

[24]French P, O’riordan E G, Monahan F J, Sanudo C, Campo M M, Oliver M A, Furnols, M F, Montossi F, Julián R, Nute G R, Caneque V. Fatty acid composition of intra-muscular triacylglycerols of steers fed autumn grass and concentrates. Livestock Production Science, 2003, 81: 307-317.

[25]Eriksson S F, Pickova J. Fatty acids and tocopherol levels in M. longissimus dorsi of beef cattle in Sweden–A comparison between seasonal diets. Meat Science, 2007, 76: 746-754.
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