Application of visible and near infrared spectroscopy for rapid and non-invasive quantification of common adulterants in Spirulina powder

Di Wu, Pengcheng Nie, Joel L Cuello, Yong He, Zhiping Wang, Hongxi Wu

Research output: Contribution to journalArticle

52 Scopus citations


The authentication of food products is critically important in a global economy in public-health and economic terms. The specific aims of this study were to evaluate the application of full-spectrum and NIR spectroscopy and to evaluate the adoption of PLS and LS-SVM models to accomplish a rapid and non-invasive quantification of the two common adulterants, flour and mungbean powder, in Spirulina powder. The results showed that, using all treatment sets, only the LS-SVM models were adequate in predicting either adulterant under both full spectra and NIR spectra. The use of NIR spectra would allow detection of adulterants even when masked by food dyes. Design value analysis indicated that the benefits per unit cost of applying the NIR spectra to quantify adulterants in Spirulina powder significantly exceeded that of using full spectra, and that the value of employing the LS-SVM models under NIR spectra exceeded that of using the PLS models.

Original languageEnglish (US)
Pages (from-to)278-286
Number of pages9
JournalJournal of Food Engineering
Issue number3
Publication statusPublished - Feb 2011



  • Adulterants
  • Least-square support vector machine (LS-SVM)
  • Partial least square (PLS)
  • Spirulina powder
  • Visible-near infrared (Vis-NIR) spectroscopy

ASJC Scopus subject areas

  • Food Science

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