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Research on the Geological Sourcing of Raohe Honey by Inductively Coupled Plasma Mass Spectrometry with Primary Composite Analysis and Forecasting Models

DOI: 10.4236/ajac.2015.65046, PP. 468-479

Keywords: Raohe Honey, ICP-MS, Primary Composite Analysis, Forecasting Model

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Raohe honey (Honey in Raohe) is the only product which has obtained China’s national geographical mark for honey; however, it is always counterfeited by some producers due to its excellent quality. In this research, Raohe honey was identified by geographical sourcing, where the detection on 166 Raohe honey samples and 31 non-Raohe honey samples was conducted with Inductively Coupled Plasma Mass Spectrometry (ICP-MS). Additionally, the method of Primary Composite Analysis accomplished dimensionality reduction by transforming the abundance ratios variables of 13 isotopes to 4 primary composites, and could explain 91.17% of the total variables. There were five models: Decision Tree, Naive Bayes, Neural Network, Partial Least Square Discriminate and Support Vector Machine, built on the four new variables of primary composites with the Agilent MPP Software. The validation of the models was performed with 11 Raohe honey samples and 5 non-Raohe honey samples randomly selected. The accuracies of the Decision Tree and Support Vector Machine models were both 93.97%, and those of the Naive Bayes and Neural Network models were both 87.5%, while the contribution rate of the Partial Least Square Discriminate model was only 75%. It was concluded that the Decision Tree and Support Vector Machine models could be used for indentifying Raohe honey, and the Naive Bayes and Neural Network models could work as references, while the Partial Least Square Discriminate model was not suitable for identifying Raohe honey.


[1]  Ankalm, E.A. (1998) Review of the Analytical Methods to Determine the Geographical and Botanical Origin of Honey. Food Chemistry, 63, 549-562.
[2]  Bogdanov, S., Ruoff, K. and Oddo, L.P. (2004) Physico-Chemical Methods for the Characterisation of Unifloral Honeys: A Review. Apidologie, 35, S4-S17.
[3]  Arvanitoyannis, I.S., Chalhoub, C., Gotsiou, P., et al. (2005) Novel Quality Control Methods in Conjunction with Chemometrics (Multivariate Analysis) for Detecting Honey Authenticity. Critical Reviews in Food Science and Nutrition, 45, 193-203.
[4]  Cuevas-Glory, L.F., Pino, J.A., Santiago, L.S., et al. (2007) A Review of Volatile Analytical Methods for Determining the Botanical Origin of Honey. Food Chemistry, 103, 1032-1043.
[5]  Pohl, P. (2009) Determination of Metal Content in Honey by Atomic Absorption and Emission Spectrometries. Trends in Analytical Chemistry, 28, 117-128.
[6]  Wang, H.W. and Yang, S.M. (2007) The Application of Stable Isotope Technique in Agro-Product Traceability System. Science and Technology of Food Industry, 28, 200-203.
[7]  Vogel, J.C., Eglington, B. and Auret, J.M. (1990) Isotope Fingerprints in Elephant Bone and Ivory. Nature, 23, 747-749.
[8]  Kelly, S., Heaton, K. and Hoogewerff, J. (2005) Tracing the Geographical Origin of Food: the Application of Multi-Element and Multi-Isotope Analysis. Trends in Food Science and Technology, 16, 555-567.
[9]  Coetzee, P.P. and Vanhaecke, F. (2005) Classifying Wine According to Geographical Origin via Quadrupole-Based ICP-Mass Spectrometry Measurement of Boron Isotope Rations. Analytical and Bioanalytical Chemistry, 383, 977-984.
[10]  Wang, W., Liu, X.D., Lu, Y.Q., et al. (2002) Determination of Isotope Abundance Ratio of Lead in Beijing Atmospheric Aerosol and Lead Source Study. Journal of Chinese Mass Spectrometry Society, 23, 21-29.
[11]  Latorre, M.J., Pena, R., Garcia, S., et al. (2000) Authentication of Galician (N.W. Spain) Honeys by Multivariate Techniques Based on Metal Content Data. Analyst, 125, 307-312.
[12]  Jarvis, K.E., Gray, A.L. and Houk, R.S. (1997) Handbook of Inductively Coupled Plasma Mass Spectrometry. Yin, M. and Li, B., Interpret, Atomic Energy Press, Beijing.


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