近红外光谱及多变量分析检测菜籽油掺假棕榈油的可行性研究

Mutia Nurulhusna Hussain, M. F. Abdul Khir, M. H. Hisham, Zalhan Md Yusof
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引用次数: 9

摘要

食品掺假检测是当今食品工业中最重要的问题之一。本研究探讨了近红外光谱结合多变量分析对菜籽油样品与掺假棕榈油样品进行分类的可行性。进行了近红外光谱实验,并采用多变量分析方法进行了分析。利用开源R软件的结果表明,掺假油样的总体正确分类率为100%,最低检测水平为3.23%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Feasibility study of detecting canola oil adulteration with palm oil using NIR spectroscopy and multivariate analysis
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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