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

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          Abstract

          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.

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          Author and article information

          Journal
          Food Chem
          Food chemistry
          Elsevier BV
          0308-8146
          0308-8146
          Dec 15 2013
          : 141
          : 4
          Affiliations
          [1 ] Zhejiang Provincial Key Laboratory of Biometrology and Inspection & Quarantine, College of Life Sciences, China Jiliang University, Xueyuan Street, Xiasha Higher Education District, Hangzhou 310018, China. lxchemo@163.com
          Article
          S0308-8146(13)00934-5
          10.1016/j.foodchem.2013.07.013
          23993596
          35bea91e-8cbe-4597-9043-5f0f32bfbced
          History

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

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