Rapid Detection of Fatty Acids in Edible Oils Using Vis-NIR Reflectance Spectroscopy with Multivariate Methods.

Ning Su,Shizhuang Weng,Fangfang Pan,Liusan Wang

doi:10.3390/bios11080261

Abstract

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 () was 0.9504 and the root mean square error of prediction () was 0.8181. For the stearic acid, and were 0.9636 and 0.2965. In the prediction of arachidic acid, and were 0.9576 and 0.0577. In the prediction of behenic acid, the and 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.

Highlights

The consumption of various edible oils has been increasing due to the growth of population
The gas chromatography-mass spectrometry (GC-MS) was used to determine the content of palmitic acid, stearic acid, arachidic acid and behenic acid in 93 brands of edible oils as the reference values
The prediction results showed that the support vector machine (SVM) regression model with standard normal variate (SNV) pretreatment on full wavelengths had the best predictive effect on the four fatty acids

Summary

Introduction

The consumption of various edible oils has been increasing due to the growth of population. Edible oil is good of taste and health properties which provides many health beneficial substances including fatty acids, energy, and other essential trace elements [1]. The quality of edible oil is closely related to public health and food safety and the choice of edible oils affects the nutritional balance of the human body [2]. The quality of edible oils is frequently subjected to adulteration, contamination, deterioration, and re-use problems in production process [3,4], which greatly affects their edibility. Every kind of pure edible oil has a relatively stable composition ratio of fatty acids, and all the above quality problems cause the significant change of the content of fatty acids in terms of the internal composition of edible oils. The quantitative analysis of fatty acids would be an effective method to assess the quality of edible oils

Methods

Results

Conclusion