Rapid Determination of Lycium Barbarum Polysaccharide with Effective Wavelength Selection Using Near-Infrared Diffuse Reflectance Spectroscopy

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• 作者：Yage Wang ; Yuan Gao ; Xiuzhu Yu ; Yuanyuan Wang ; Shan Deng…
• 关键词：Lycium Barbarum polysaccharide ; Near ; infrared diffuse reflectance spectroscopy ; Correlation coefficients ; X ; loading weights
• 刊名：Food Analytical Methods
• 出版年：2016
• 出版时间：January 2016
• 年：2016
• 卷：9
• 期：1
• 页码：131-138
• 全文大小：4,371 KB
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• 作者单位：Yage Wang (1)
  Yuan Gao (1)
  Xiuzhu Yu (1)
  Yuanyuan Wang (2)
  Shan Deng (2)
  Jin-ming Gao (2)
  
  1. College of Food Science and Engineering, Northwest A&F University, 28 Xinong Road, Yangling, 712100, Shaanxi, China
  2. College of Science, Northwest A&F University, 22 Xinong Road, Yangling, 712100, Shaanxi, China
  
• 刊物类别：Chemistry and Materials Science
• 刊物主题：Chemistry
  Food Science
  Chemistry
  Microbiology
  Analytical Chemistry
  
• 出版者：Springer New York
• ISSN：1936-976X

文摘

A rapid method to evaluate the amount of Lycium barbarum polysaccharides (LBPs) based on near-infrared diffuse reflectance spectroscopy (NIDRS) is proposed. A total of 114 dried L. barbarum samples from different regions of China were used for modeling by partial least squares (PLS) regression with the effective wavelengths (EWs) selected by correlation coefficients and X-loading weights. The PLS model worked best with EWs of 4003–5087, 5568–7002, and 7463–12,000 cm−1. These EWs were chosen by correlation coefficients after spectral pretreatment. Use of these EWs resulted in determination coefficients of calibration and validation of 0.982 and 0.938, respectively. The proposed model successfully predicted external samples, which further confirmed prediction ability of the model. Overall results indicated that both correlation coefficients and X-loading weights for EWs selection can improve model performance and that NIDRS can rapidly determine LBPs with intact particle samples. Keywords Lycium Barbarum polysaccharide Near-infrared diffuse reflectance spectroscopy Correlation coefficients X-loading weights