文章基本信息

标题：Rapid Detection of Fatty Acids in Edible Oils Using Vis-NIR Reflectance Spectroscopy with Multivariate Methods
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作者：Ning Su ; Fangfang Pan ; Liusan Wang 等
期刊名称：Biosensors
电子版ISSN：2079-6374
出版年度：2021
卷号：11
期号：8
DOI：10.3390/bios11080261
语种：English
出版社：MDPI Publishing
摘要：The composition and content of fatty acids are critical indicators to identify the quality of edible oils. This study was undertaken to establish a rapid determination method for quality detection of edible oils based on quantitative analysis of palmitic acid, stearic acid, arachidic acid, and behenic acid. Seven kinds of oils were measured to obtain Vis-NIR spectra. Multivariate methods combined with pretreatment methods were adopted to establish quantitative analysis models for the four fatty acids. The model of support vector machine (SVM) with standard normal variate (SNV) pretreatment showed the best predictive performance for the four fatty acids. For the palmitic acid, the determination coefficient of prediction ( R P 2 ) was 0.9504 and the root mean square error of prediction ( R M S E P ) was 0.8181. For the stearic acid, R P 2 and R M S E P were 0.9636 and 0.2965. In the prediction of arachidic acid, R P 2 and R M S E P were 0.9576 and 0.0577. In the prediction of behenic acid, the R P 2 and R M S E P were 0.9521 and 0.1486. Furthermore, the effective wavelengths selected by successive projections algorithm (SPA) were useful for establishing simplified prediction models. The results demonstrate that Vis-NIR spectroscopy combined with multivariate methods can provide a rapid and accurate approach for fatty acids detection of edible oils.
关键词：enVis-NIR reflectance spectroscopy;multivariate analysis;fatty acid;edible oil;quality detection