光谱学与光谱分析 |
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Application of ICP-MS to Identify the Botanic Source of Characteristic Honey in South Yunnan |
WEI Yue1, 2, CHEN Fang1, 2, WANG Yong1, 2, CHEN Lan-zhen1, 2, ZHANG Xue-wen3, WANG Yan-hui3, WU Li-ming1, 2*, ZHOU Qun4* |
1. Institute of Apiculture Research, Chinese Academy of Agricultural Sciences, Beijing 100093, China 2. Risk Assessment Laboratory for Bee Products Quality and Safety of Ministry of Agriculture (Beijing), Beijing 100093, China 3. Yunnan Province Academy of Agricultural Sciences, Kunming 650231, China 4. Department of Chemistry, Tsinghua University, Beijing 100084, China |
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Abstract By adopting inductively coupled plasma mass spectrometry (ICP-MS) combined with chemometric analysis technology, 23 kinds of minerals in four kinds of characteristic honey derived from Yunnan province were analyzed. The result showed that 21 kinds of mineral elements, namely Na, Mg, K, Ca, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Se, Sr, Mo, Cd, Sb, Ba, Tl and Pb, have significant differences among different varieties of honey. The results of principal component analysis (PCA) showed that the cumulative variance contribution rate of the first four main components reached 77.74%, seven kinds of elements (Mg, Ca, Mn, Co, Sr, Cd, Ba) from the first main component contained most of the honey information. Through the stepwise discriminant analysis, seven kinds of elements (Mg, K, Ca, Cr, Mn, Sr, Pb) were filtered out and used to establish the discriminant function model, and the correct classification rates of the proposed model reached 90% and 86.7%, respectively, which showed elements contents could be effectively indicators to discriminate the four kinds characteristic honey in southern Yunnan Province. In view of all the honey samples were harvested from apiaries located at south Yunnan Province where have similar climate, soil and other environment conditions, the differences of the mineral elements contents for the honey samples mainly due to their corresponding nectariferous plant. Therefore, it is feasible to identify honey botanical source through the differences of mineral elements.
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Received: 2014-08-19
Accepted: 2014-12-16
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Corresponding Authors:
WU Li-ming, ZHOU Qun
E-mail: apiswu@126.com; zhouqun@mail.tsinghua.edu.cn
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[1] The State Standard of the People’s Republic of China—Honey GB14963—2011(中华人民共和国标准—蜂蜜 GB14963—2011). Beijing: China Standard Press(北京:中国标准出版社),2011. 1. [2] Ezzel-Arab A M, Girgis M, Hegazy E M, et al. BMC Complementary and Alternative Medicine, 2006, 6(1): 6. [3] Tuzen M, Silici S, Mendil D, et al. Food Chemistry, 2007, 103(2): 325. [4] Madejczyk M, Baralkiewicz D. Analytical Chemistry Acta, 2008, 617(1-2): 11. [5] Grembecka M, Szefer P. Environment Monitor Assess, 2013, 185(5): 4033. [6] Ajtony Z, Bencs L, Haraszi R, et al. Talanta, 2007, 71(2): 683. [7] Sahan D, Barbosa F, Tomazelli A C, et al. Analytical and Bioanalytical Chemistry, 2002, 373(3): 183. [8] Kira C S, Maihara V A. Food Chemistry, 2007, 100(1): 390. [9] Pisani A, Protano S, Riccobono F, et al. Food Chemistry, 2008, 107(4): 1553. [10] Mehment M, Fahad Y, AL Juhaimi. Environment Monitor Assess, 2012, 184(4): 2373. [11] Chudzinska M, Baralkiewicz D. Food Chemistry Toxicol, 2010, 48(1): 284. [12] Ana B P L, Silmara R B, Renato L, et al. Food Analytical Methods, 2014, 7(5): 1009. [13] Sahan Y, Barbosa F, Gucer S, et al. Food Chemistry, 2007, 105(1): 395. [14] Marua C, Danuta B. Food and Chemical Toxicology, 2011, 49(11): 2742. [15] Batista B L, da Silva L R S, Rocha B A, et al. Food Research International, 2012, 49(1): 210. |
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