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Article

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

by 1,2, 3, 1,2,* and 3,*
1
Institute of Intelligent Machines, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China
2
Intelligent Agriculture Engineering Laboratory of Anhui Province, Hefei 230031, China
3
National Engineering Research Center for Agro-Ecological Big Data Analysis and Application, Anhui University, Hefei 230601, China
*
Authors to whom correspondence should be addressed.
Biosensors 2021, 11(8), 261; https://doi.org/10.3390/bios11080261
Received: 30 June 2021 / Revised: 27 July 2021 / Accepted: 28 July 2021 / Published: 3 August 2021
(This article belongs to the Special Issue Sensors for Food Safety)
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 (RP2) was 0.9504 and the root mean square error of prediction (RMSEP) was 0.8181. For the stearic acid, RP2 and RMSEP were 0.9636 and 0.2965. In the prediction of arachidic acid, RP2 and RMSEP were 0.9576 and 0.0577. In the prediction of behenic acid, the RP2 and RMSEP 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. View Full-Text
Keywords: Vis-NIR reflectance spectroscopy; multivariate analysis; fatty acid; edible oil; quality detection Vis-NIR reflectance spectroscopy; multivariate analysis; fatty acid; edible oil; quality detection
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MDPI and ACS Style

Su, N.; Pan, F.; Wang, L.; Weng, S. Rapid Detection of Fatty Acids in Edible Oils Using Vis-NIR Reflectance Spectroscopy with Multivariate Methods. Biosensors 2021, 11, 261. https://doi.org/10.3390/bios11080261

AMA Style

Su N, Pan F, Wang L, Weng S. Rapid Detection of Fatty Acids in Edible Oils Using Vis-NIR Reflectance Spectroscopy with Multivariate Methods. Biosensors. 2021; 11(8):261. https://doi.org/10.3390/bios11080261

Chicago/Turabian Style

Su, Ning, Fangfang Pan, Liusan Wang, and Shizhuang Weng. 2021. "Rapid Detection of Fatty Acids in Edible Oils Using Vis-NIR Reflectance Spectroscopy with Multivariate Methods" Biosensors 11, no. 8: 261. https://doi.org/10.3390/bios11080261

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