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Monitoring of frying process in canola oil blend using fourier transform infrared and chemometrics techniques
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Monitoring of frying process in canola oil blend using fourier transform infrared and chemometrics techniques
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Journal Article
Monitoring of frying process in canola oil blend using fourier transform infrared and chemometrics techniques
2021
Overview
The production of trans‐fats and chemical changes during the process of frying are serious public health concerns and must be monitored efficiently. For this purpose, the canola oil was formulated with different ratio of extra virgin olive oil and palm olein using D‐optimal mixture design, and the best formulation (67:22:11) based on free fatty acid (FFA) content, peroxide value (PV), and iodine value (IV) as responses was selected for multiple frying process. The data on FFA, PV, and IV along with Fourier transform‐infrared (FT‐IR) spectra were taken after each frying up to ten frying. The spectral data were preprocessed with standard normal variate followed by principal component analysis which is clearly showing the differentiation for various frying. Similarly, partial least square regression was applied to predict the FFA (0.37%–1.63%), PV (4.47–13.85 meqO2/kg), and IV (111.51–51.39 I2/100 g) which demonstrated high coefficient of determination (R2) 0.84, 0.83, and 0.81, respectively. It can be summarized that FT‐IR can be used as a novel tool for fast and noninvasive quality determination of frying oils.
The current study was designed to make canola oil blends with different concentrations of olive oil and palm olein. These blends were optimized by D‐optimal Design using the oil stability parameters such as free fatty acid (FFA), peroxide (PV), and iodine values (IV). The optimized canola oil blend was further used for multiple frying, and FT‐IR spectral fingerprints were taken which is considered to be a rapid, non‐destructive, and environment‐friendly analytical tool for characterization of the chemical changes taken place due to the processing.
