Determination Geographical Origin and Flavonoids Content of Goji Berry Using Near-Infrared Spectroscopy and Chemometrics

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• 作者：Shen Tingting ; Zou Xiaobo ; Shi Jiyong ; Li Zhihua ; Huang Xiaowei…
• 关键词：Near ; infrared (NIR) spectroscopy ; Least ; squares support vector machine ; Goji berry ; Geographic origin ; Total flavonoid content ; Synergy interval partial least squares
• 刊名：Food Analytical Methods
• 出版年：2016
• 出版时间：January 2016
• 年：2016
• 卷：9
• 期：1
• 页码：68-79
• 全文大小：1,443 KB
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• 作者单位：Shen Tingting (1)
  Zou Xiaobo (1) (2)
  Shi Jiyong (1)
  Li Zhihua (1)
  Huang Xiaowei (1)
  Xu Yiwei (1)
  Chen Wu (1)
  
  1. School of Food and Biological Engineering, Jiangsu University, 301 Xuefu Rd., 212013, Zhenjiang, Jiangsu, China
  2. Key Laboratory of Modern Agricultural Equipment and Technology, 301 Xuefu Rd., 212013, Zhenjiang, Jiangsu, 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

The feasibility of near-infrared (NIR) spectroscopy and chemometrics as tools to analyze Chinese Goji berry samples from four different topographical regions was investigated. Firstly, a consumer panel was asked to rate sensory attributes of the samples on a nine-point hedonic scale. Secondly, NIR original spectra of Goji berries in the wavelength range of 10,000–4000/cm were acquired. Least-squares support vector machine (LS-SVM) was firstly performed to calibrate the discrimination model to identify the geographical origins of the Goji berries, and the accuracy of correct identification was more than 96.67 %. Compared with artificial neural network (ANN) and K-nearest neighbors (KNN) approach, LS-SVM algorithm showed excellent generalization for identification results. Thirdly, as total flavonoid content (TFC) is highly related with the quality of the Goji berry, synergy interval partial least squares (Si-PLS) was applied to build the TFC prediction model. The determination coefficient for prediction (R _p ) of the Si-PLS model was 0.9075, and root mean square error for prediction (RMSEP) was 0.376 mg/g. The three regions (4580–4860, 5720–6010, and 6290–6580/cm) selected by Si-PLS corresponded to the absorptions of two aromatic rings in the basic flavonoid structure. This work indicates that NIR spectroscopy combined with LS-SVM and Si-PLS offers significant potential and could be used as a rapid and efficient technique for evaluating the quality of retail Goji berries. Keywords Near-infrared (NIR) spectroscopy Least-squares support vector machine Goji berry Geographic origin Total flavonoid content Synergy interval partial least squares