| 光谱学与光谱分析 |
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| Progress in Quality Analysis of Honey by Infrared Spectroscopy |
| TU Zhen-hua1, ZHU Da-zhou2, JI Bao-ping1, MENG Chao-ying3, WANG Lin-ge1, QING Zhao-shen1* |
1. College of Food Science and Nutritional Engineering, China Agricultural University, Beijing 100083, China
2. National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China
3. College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China |
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Abstract The detection of the quality of honey and the differentiation of adulteration are very important for quality and safety assurance. Traditionally used chemical methods were expensive and complicated, therefore they are not suitable for the requirement of wide-scale detection. In the past decade, the detection technology of honey developed with a trend of fast and high throughput detection. Spectroscopy has the fast and non-contact characteristic, and was widely used in petrifaction. This technology also has the potential for application in honey analysis. In the present study, the progress in quantitative and qualitative analysis of honey by near infrared spectroscopy (NIR) and mid infrared spectroscopy (MIR) is reviewed. The application of this two spectroscopy methods to honey detection refers to several aspects, such as quality control analysis, determination of botanical origin, determination of geographical origin and detection of adulteration. The detailed information of the detection of honey by NIR and MIR spectroscopy was analyzed, containing detection principle, technology path, accuracy, influence factors, and the development trend.
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Received: 2010-01-18
Accepted: 2010-04-22
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Corresponding Authors:
QING Zhao-shen
E-mail: qingzhaoshen@cau.edu.cn
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[1] White J W, Riethof M L, Subers M H et al. Technical Bulletin, 1962, 1261: 1.
[2] GB 18796—2005 Honey(蜂蜜). National Standards of the People’s Republic of China(中华人民共和国国家标准).
[3] Ha J, Koo M, Ok H. J. Near-Infrared Spectrosc., 1998, 6(5): A367.
[4] Cho H J, Hong S H. J. Near-Infrared Spectrosc., 1998, 6: A329.
[5] Qiu P Y, Ding H B, Tang Y K, et al. J. Agric. Food Chem., 1999, 47(7): 2760.
[6] Garcia-Alvarez M, Huidobro J F, Hermida M, et al. J. Agric. Food Chem., 2000, 48(11): 5154.
[7] Cozzolino D, Corbella E. Journal of Apicultural Research, 2003, 42(1-2): 16.
[8] Cho H J, Ha Y L. Korean Journal of Food Science and Technology, 2002, 34(3): 356.
[9] Kaspar R, Werner L, Stefan B, et al. Eur. Food Res. Technol., 2007, 225(3-4): 415.
[10] HOU Rui-li, CHENG Yu-lai, CHONGTENG He-ming(侯瑞丽, 程玉来, 重腾和明). The Food Industry(食品工业), 2007, (2): 57.
[11] CHEN Lan-zhen, SUN Qian, ZHAO Jing, et al(陈兰珍, 孙 谦, 赵 静, 等). Apiculture of China(中国蜂业), 2008, 59(12): 17.
[12] Downey G, Fouratier V, Kelly J D. J. Near-Infrared Spectrosc., 2003, 11: 447.
[13] ZHANG Ping, YAN Ji-hong, ZHU Zhi-hua, et al(张 萍, 闫继红, 朱志华, 等). Modern Scientific Instruments(现代科学仪器), 2006, (1): 60.
[14] Daviesa M C, Radovic B, Fearn T, et al. J. Near-Infrared Spectrosc., 2002, 10(2)：121.
[15] Corbella E, Cozzolino D. J. Near-Infrared Spectrosc., 2005, 13: 63.
[16] Ruoff K, Luginbuhl W, Bogdanov S, et al. J. Agric. Food Chem., 2006, 54(18): 6867.
[17] SHAO Yong-ni, HE Yong, BAO Yi-dan(邵咏妮, 何 勇, 鲍一丹). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2008, 28(3): 602.
[18] CHEN Lan-zhen, SUN Qian, YE Zhi-hua, et al(陈兰珍, 孙 谦, 叶志华, 等). Food Science and Technology(食品科技), 2009, 34(8): 287.
[19] Sivakesava S, Irudayaraj J. Journal of Food Science, 2001, 66(6): 787.
[20] Sivakesava S, Irudayaraj J. International Journal of Food Science and Technology, 2002, 37: 351.
[21] Irudayaraj J, Xu F, Tewar J. Journal of Food Science, 2003, 68(6): 2040.
[22] LIANG Qi-feng, PENG Meng-xia, LIN Juan(梁奇峰, 彭梦侠, 林 鹃). Journal of Anhui Agricultural Sciences(安徽农业科学), 2009, 37(1): 34.
[23] Bertelli D, Plessi M, Sabatini A G, et al. Food Chemistry, 2007, 101: 1565.
[24] Ruoff K, Iglesias M T, Luginbuhl W, et al. Eur. Food Res. Technol., 2006, 223: 22.
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