Detection of honey adulteration by high fructose corn syrup and maltose syrup using Raman spectroscopy
文献类型： 外文期刊
作者： Li, Shuifang 1 ; Shan, Yang 2 ; Zhu, Xiangrong 2 ; Zhang, Xin 3 ; Ling, Guowei 1 ;
作者机构： 1.Cent S Univ Forestry & Technol, Coll Sci, Changsha 410004, Hunan, Peoples R China
2.Hunan Acad Agr Sci, Hunan Agr Prod Proc Inst, Changsha 410125, Hunan, Peoples R China
3.Cent S Univ, Grad Sch, Longping Branch, Changsha 410025, Hunan, Peoples R China
关键词： Food composition;Food analysis;Honey;Adulteration;Raman spectroscopy;Adaptive iteratively reweighted penalized least squares (airPLS);Spectral background signal removing;Partial least squares-linear discriminant analysis (PLS-LDA)
期刊名称：JOURNAL OF FOOD COMPOSITION AND ANALYSIS （ 影响因子：4.556； 五年影响因子：4.89 ）
ISSN： 0889-1575
年卷期： 2012 年 28 卷 1 期
页码：
收录情况： SCI
摘要： Raman spectroscopy was used to detect adulterants such as high fructose corn syrup (HFCS) and maltose syrup (MS) in honey. HFCS and MS were each mixed with authentic honey samples in the following ratios: 1:10 (10%), 1:5 (20%) and 1:2.5 (40%, w/w). Adaptive iteratively reweighted penalized least squares (airPLS) was chosen to remove background of spectral data. Partial least squares-linear discriminant analysis (PLS-LDA) was used to develop a binary classification model. Classification of honey authenticity using PLS-LDA showed a total accuracy of 91.1% (authentic honey vs. adulterated honey with HFCS), 97.8% (authentic honey vs. adulterated honey with MS) and 75.6% (authentic honey vs. adulterated honey with HFCS and MS), respectively. Classification of honey adulterants (e.g. HFCS or MS) using PLS-LDA gave a total accuracy of 84.4%. The results showed that Raman spectroscopy combined with PLS-LDA was a potential technique for detecting adulterants in honey. (C) 2012 Elsevier Inc. All rights reserved.
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