2014 · 10 citations · 7 references
AgricultureChemistryFood ScienceFood AnalysisSpectroscopic AnalysisSpectroscopyAdulteration DetectionInfrared SpectroscopyLipid AnalysisSpectroscopic AuthenticationSpectroscopic Food AnalysisFeasibility Study DesignOil Composition AnalysisPattern Recognition Models
Detection of adulteration in food is one of the most important issues in food industry today. In this study, the feasibility of classifying canola oil samples from the one adulterated with palm oil using NIR spectroscopy in combination with multivariate analysis is investigated. An experiment to obtain the NIR spectra was conducted and analyzed using multivariate analysis. The result using open source R software has shown that adulterated oil samples could be detected with an overall correct classification rate of 100 % with minimum detection level of 3.23 %.
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Abdullatif Tay, Rakesh K. Singh, S. Krishnan et al. · LWT · 2002 · 180 citations
Agriculture, Chemistry, Food Science +12
Lu Wang, F LEE, Xiaoxing Wang et al. · Food Chemistry · 2005 · 136 citations
Engineering, Agricultural Engineering, Biomedical Optics +11