| 光谱学与光谱分析 |
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| Study Physicochemical Characteristics of Spring Honeys from Yunnan with the Application of HPLC-RI and FAAS |
| ZHANG Zheng1,2,3, CHEN Chao2, CAO Hong-gang2, CAI Sheng-bao2, ZHAO Feng-yun1,2* |
| 1. College of Food Science and Engineering, Gansu Agricultural University, Lanzhou 730070, China2. Food Safety Institute, Kunming University of Science and Technology, Kunming 650500, China3. College of Food Science, South China Agricultural University, Guangzhou 510641, China |
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Abstract Many special honeys are produced in Yunnan province due to abundant nectar plants and minerals resources provided by the unique natural environment in this area. In this work, the physicochemical property of three honeys (Viciacracca honey, Hevea brasiliensis honey and Punica granatum honey) from Yunnan was studied. The results showed that in different honeys the moisture content, electrical conductivity and dynamic viscosity were different. The sugar contents of each honey were determined with HPLC-RI. The results showed that P. granatum honey had the most abundant glucose [35.62 g·(100 g)-1], and H. brasiliensis honey had the most abundant fructose [41.03 g·(100 g)-1]. Thirteen different mineral elements in three honey species were determined with FAAS. It was found that the mineral level was from 167.24 mg·kg-1 in P. granatum honey to 437.34 mg·kg-1 in H. brasiliensis. Based on the mineral content the three honey species were classified following the principal component analysis (PCA) method. The result showed that Cu, Zn and Na could act as the elemental markers for V. cracca honey, while Mg, K, Ca, As and Cd act as the elemental markers for H. brasiliensis honey, and Fe, Mn, Ni, and Cr act as the elemental markers for P. granatum honey. This study reported the physicochemical property of three special Yunnan honeys, which could help the further study and utilization of these honeys.
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Received: 2015-07-18
Accepted: 2015-11-22
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Corresponding Authors:
ZHAO Feng-yun
E-mail: zhaofy@kmust.edu.cn
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[1] White J W. Composition of Honey, in Honey: A Comprehensive Survey London. Heinemann Press, 1979. 157.
[2] Alvarez-Suarez J, Gasparrini M, Forbes-Hernández T Y, et al. Foods, 2014, 3(3): 420.
[3] Alvarez-Suarez J M, Giampieri F, Battino M. Curr. Med. Chem., 2013, 20(5): 621.
[4] YU Ya-li(于亚丽). Apiculture of China(中国蜂业), 2012, 63(9): 47.
[5] DONG Xia，LIN Zun-cheng(董 霞，林尊诚). Journal of Bee(蜜蜂杂志), 2002, (8): 31.
[6] Moar N T. New Zeal J. Agr Res., 1985, 28(1): 39.
[7] Silva L R, Videira R, Monteiro A P, et al. Microchem J., 2009, 93(1): 73.
[8] Terrab A, Recamales A F, Hernanz D, et al. Food Chem., 2004, 88(4): 537.
[9] ZHAO Ya-zhou, TIAN Wen-li, GUO Zhan-bao, et al(赵亚周，田文礼，国占宝，等). Journal of Agricultural Scienceand Technology(中国农业科技导报), 2010, 12(3): 50.
[10] de Alda-Garcilope C, Gallego-Picó A, Bravo-Yagüe J C, et al. Food Chem., 2012, 135(3): 1785.
[11] GU Yun，LI Hai-sheng(顾 云，李海生). Tianjin Pharmacy(天津药学), 2001, 13(2): 49.
[12] Chen H, Fan C, Chang Q, et al. J. Agr. Food Chem., 2014, 62(11): 2443.
[13] Terrab A, Díez M J, Heredia F. J. Food Chem., 2002, 79(3): 373.
[14] Bonvehí J S, Tarrés E G. Apidologie, 1993, 24(6): 586.
[15] Downey G, Hussey K, Kelly J D, et al. Food Chem., 2005, 91(2): 347.
[16] Anklam E. Food Chem., 1998, 63(4): 549. |
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