4.7 Article

Untargeted detection and quantitative analysis of poplar balata (PB) in Chinese propolis by FT-NIR spectroscopy and chemometrics

期刊

FOOD CHEMISTRY
卷 141, 期 4, 页码 4132-4137

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.foodchem.2013.07.013

关键词

Chinese propolis; Adulteration; FT-NIR; Poplar balata; One-class partial least squares (OCPLS); Partial least squares regression (PLSR)

资金

  1. National Public Welfare Industry Projects of China [201210010, 201210092, 2012104019]
  2. National Natural Science Foundation of China [31000357]
  3. Hangzhou Programs for Agricultural Science and Technology Development [20101032B28]
  4. Key Scientific and Technological Innovation Team Program of Zhejiang Province [2010R50028]

向作者/读者索取更多资源

This paper investigates the feasibility of using FT-NIR spectroscopy and chemometrics for rapid analysis of poplar balata (PB) in Chinese propolis. Because practical adulterations usually involve addition of certain known active components, together with commercial PB, the commonly targeted analysis methods are insufficient to identify PB-adulterated propolis. Untargeted analysis of PB was performed by developing class models of pure propolis using one-class partial least squares (OCPLS). Quantitative analysis of PB was performed using partial least squares regression (PLSR). For untargeted analysis, the most accurate OCPLS model was obtained with SNV spectra with sensitivity 0.960 and specificity 0.941. OCPLS could detect adulterations with 2% (w/w) or more PB. For quantitative analysis, the root mean squared error of prediction (RMSEP) value of PB was 0.902 (w/w, %) with SNV-PLS. FT-NIR spectrometry and chemometrics demonstrate potential for rapid analysis of PB adulterations in Chinese propolis. (C) 2013 Elsevier Ltd. All rights reserved.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据