Rapid geographical origin analysis of pure West Lake lotus root powder (WL-LRP) by near-infrared spectroscopy combined with multivariate class modeling techniques

被引:11
作者
Xu, Lu [1 ]
Shi, Peng-Tao [1 ]
Ye, Zi-Hong [1 ]
Yan, Si-Min [1 ]
Cai, Chen-Bo [2 ]
Zhong, Wei [2 ]
Yu, Xiao-Ping [1 ]
机构
[1] China Jiliang Univ, Coll Life Sci, Zhejiang Prov Key Lab Biometrol & Inspect & Quara, Hangzhou 310018, Peoples R China
[2] Chuxiong Normal Univ, Dept Chem & Life Sci, Chuxiong 675000, Peoples R China
关键词
Lotus root powder; Near-infrared spectroscopy; Multivariate quality control; Partial least squares class model; Support vector data description; NELUMBO-NUCIFERA; PHYSICOCHEMICAL PROPERTIES; CHEMOMETRICS; VALIDATION; STARCHES; SEEDS;
D O I
10.1016/j.foodres.2012.08.016
中图分类号
TS2 [食品工业];
学科分类号
0832 ;
摘要
A rapid analysis method was proposed for the identification of a popular traditional Chinese food with Protected Geographical Indication (PGI), West Lake lotus root powder (WL-LRP), by near-infrared spectroscopy and chemometric methods. A set of 105 pure and real WL-IRP samples were collected from 9 main producers to obtain a representative training set of the authentic objects. 95 non-WL-LRP samples from 8 different main lotus producing areas of China were analyzed for validation of model specificity. Linear partial least squares class model (PLSCM) and nonlinear support vector data description (SVDD) were used to develop quality control models of authentic and pure WL-LRP objects. Spectral data were preprocessed by taking derivatives and standard normal variate (SNV) transformation. The analysis results indicate performing SNV transformation can obtain more stable and accurate models compared with taking derivatives. The best models were obtained with SNV spectra, the sensitivity and specificity was 0.87 and 0.90 for PLSCM, 0.93 and 0.92 for SVDD, respectively. (C) 2012 Elsevier Ltd. All rights reserved.
引用
收藏
页码:771 / 777
页数:7
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