光谱学与光谱分析 |
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Research on Overall Assessment of Royal Jelly Freshness by FTIR Spectroscopy |
WU Li-ming1, 2, ZHOU Qun3, ZHAO Jing1, SUN Su-qin3*, HU Fu-liang2 |
1. Institute of Apicultural Research, the Chinese Academy of Agricultural Sciences, Beijing 100081, China 2. College of Animal Science, Zhejiang University, Hangzhou 310029, China 3. Key Laboratory of Bioorganic Phosphorus Chemistry and Chemistry Biology (Ministry of Education), Department of Chemistry, Tsinghua University, Beijing 100084, China |
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Abstract Fourier transform infrared spectra (FTIR) of royal jelly (RJ) stored at different temperature and after different storage periods were measured,a series of correlation analysis among the spectra were carried out by using the spectra of new-harvested RJ as a standard. The results showed that the correlation coefficient of amide band Ⅰ and the relative intensity ratios of I1 647/I1 541, I1 647/I1 409, I1 647/I1 247 and I1 647/I1 054 of RJ samples’ spectra decreased with extension of storage time and temperature, and existed good linear correlations with the storage time, with the order of their change extent being 28 ℃>16 ℃>4 ℃>-18 ℃. According to the spectra change laws and practical experiences of RJ storage, the correlation coefficient of amide band Ⅰ and four relative intensity ratios I1 647/I1 541, I1 647/I1 409, I1 647/I1 247 and I1 647/I1 054 were selected as assessment indexes of RJ freshness. The threshold value of correlation coefficient was set to be 0.910 0, and the threshold values of the four relative intensity ratios were set to be 1.744, 2.430, 3.345 and 1.412 respectively. Once one or more indexes are lower than the corresponding threshold values, the RJ sample can be considered as a stale sample. So, FTIR spectroscopy combined with several data-processing methods would be an effective method for overall assessing the freshness of RJ.
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Received: 2008-11-10
Accepted: 2009-02-20
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Corresponding Authors:
SUN Su-qin
E-mail: sunsq@tsinghua.edu.cn
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[1] Stocker A, Rossmann A, Kettrup A, et al. Rapid Communications in Mass Spectrometry, 2006, 20(2): 181. [2] Jozef S. Apidologie, 2001, 32(1): 69. [3] Cristina M, Fiorenza M, Emanuele M. Journal of Agricultural and Food Chemistry, 2005, 53(11): 4440. [4] Yoshifumi T, Keizo K, Shinichiro I, et al. International Immunopharmacology, 2003, 3(9): 1313. [5] Jean F, Ois A, Sarah Z, et al. Food Chemistry, 2003, 80(1): 85. [6] Zuo L, Sun S, Zhou Q, et al. Journal of Pharmaeeutieal and Biomedical Analysis, 2003, 30(5): 1491. [7] SUN Su-qin, ZHOU Qun, ZHANG Xuan, et al(孙素琴,周 群,张 宣, 等). Chinese Journal of Analytical Chemistry(分析化学), 2000, 28(2): 211. [8] WU Jin-guang(吴瑾光). Techniques and Applications of Modern Fourier Transform Infrared Spectroscopy(近代傅里叶变换红外光谱技术及应用). Beijing: Science and Technology Literature Press(北京:科学技术文献出版社),1994. 156. [9] ZHAN Da-qi, ZHANG Xiao-ming, SUN Su-qin(詹达琦,张晓明,孙素琴). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2007, 27(8): 1497. [10] WU Jing-gui, ZENG Guang-bin, WANG Dong-mei, et al(吴景贵,曾广斌,汪冬梅, 等). Chinese Journal of Analytical Chemistry(分析化学), 1997, 25(12): 1395. [11] Durig D T, Esterle J S, Dickson T J, et al. Applied Spectroscopy, 1988, 42(7): 1239. [12] Inbar Y, Chen Y, Hadar Y. Soil Science, 1991, 4: 272. [13] Chinshuh C, Soe-Yen C. Food Chemistry. 1995, 54: 195. [14] Chen Y, Inbar Y, Hadar Y. Sci. Total Environ., 1989, 82: 201. [15] Kamakura M, Fukuda T, Fukushima M, et al. Bioscience, Biotechnology and Biochemistry, 2001, 65(2): 277. |
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