A simplified FTIR chemometric method for simultaneous determination of four oxidation parameters of frying canola oil

Fast visual detection of sunflower oil thermal oxidation using Polyacrylonitrile/Congo red nanofiber mats

Lipid oxidation monitoring is essential for food safety and quality, but traditional techniques are expensive and complicated for daily use. This study developed novel nanofiber mats using solution-blowing spinning technology to visually detect the oxidation of sunflower oil that was heated for six hours at 200 °C. These mats (Mat_1-9) are made from polyacrylonitrile (compatible with the used technique) containing various concentrations of Congo red as pH-sensitive dye (0.0025, 0.005, and 0.01 %) and hydroxylamine hydrochloride (0.125, 0.250, and 0.50 %) that react with volatile oxidation compounds to produce a striking color change. Results indicated an increase in peroxide and acid values after six hours. Mat_9 outperformed Mat_1 with a high color change (27.74 ± 0.2) and a response time of only 5 s, whereas Mat_1 took 65 s and had a far lesser response. These mats enable non-experts and food auditors to quickly assess oil quality while efficiently promoting food safety and consumer health.

Recent advances in spectroscopic approaches for assessing the stability of bioactive compounds and quality indices of olive oil during deep-frying: Current knowledge, challenges, and implications

Foods fried in olive oil received great attention due to its bioactive profile, antioxidants, high stability, and health benefits. However, several chemical alterations contribute to olive oil degradation during deep-frying (DF), and negatively modify its safety and quality. Therefore, measuring the quality indices of olive oil is a vital topic. The classical chemical approaches are destructive and use toxic chemicals, thus, a harmless and real-time analytical technique has become increasingly critical. This review highlights the recent advances of spectroscopic technologies (STs) stand-alone or integrated with chemometrics to provide reliable, rapid, low-cost, sustainable, multi-parametric, and eco-friendly method for monitoring the quality and safety of olive oil during thermal processing, moreover, the limitations of STs are included. The present review offers fundamental insights regarding the degradation of deep-fried olive oil and provides recent evidence in spectroscopy that can be used as consistent method, providing more benefits for the consumers and food industry.

Machine Learning-based Predictive Analysis of Total Polar Compounds (TPC) content in Frying Oils: A Comprehensive Electrochemical Study of 6 Types of Frying Oils with Various Frying Timepoints

Standard approaches to determining the total polar compounds (TPC) content in frying oils such as the chromatographic techniques are slow, bulky, and expensive. This paper presents the electrochemical analysis of 6 types of frying oils inclusive of 52 frying timepoints, without sample preparation. This is achieved via impedance spectroscopy to capture sample-specific electrical polarization states. To the best of our knowledge, this is a first-of-its-kind comprehensive study of various types of frying oils, with progressively increasing frying timepoints for each type. The principal component analysis distinguishes the frying timepoints well for all oil types. TPC prediction follows, involving supervised machine learning with sample-wise leave-one-out implementation. The R² values and mean absolute errors across the test samples measure 0.93-0.97 and 0.43-1.19 respectively. This work serves as a reference for electrochemical analysis of frying oils, with the potential for portable TPC predictors for rapid accurate screening of frying oils.

Effects of Ligustrum robustum (Rxob.) Blume extract on the quality of peanut and palm oils during storage and frying process

The potential uses of Ligustrum robustum (Rxob.) Blume extract as a natural antioxidant to protect the quality of different oils during storage and frying process were studied. The results showed that L. robustum extract has been shown to retard the decline in the quality of both oils based on the tests of acid value, peroxide value, p-anisidine value, color, volatile flavor, and fatty acid compositions, and the protective effect of L. robustum extract on the quality of peanut oil was better than that of palm oil. By the component analysis, L. robustum extract was found to have a total phenols content of 140.75 ± 1.52 mg/g, and ligurobustoside C was identified as the main phenolic compound. The thermogravimetric and differential scanning calorimetry results showed that L. robustum extract enhanced the oxidative stability of peanut and palm oils. In addition, Fourier transform infrared results indicated that L. robustum extract had protective effects on the C=C bond and ester bond of oil molecule. Moreover, by using electron spin resonance technique, L. robustum extract showed the ability to inhibit and scavenge alkyl-free radicals in both oils. The present results suggested that L. robustum extract may protect the quality of oils during the storage and frying process by inhibiting the oxidation of unsaturated fatty acids and might be a potential natural antioxidant in the food industry. PRACTICAL APPLICATIONS: The excellent antioxidant ability of Ligustrum robustum (Rxob.) Blume extract on the oxidation of different oils and its low price indicated that it could be used as a new low-cost natural antioxidant in oil processing.

Rapid Assessment of Quality Changes in French Fries during Deep-frying Based on FTIR Spectroscopy Combined with Artificial Neural Network

Fourier transform infrared (FTIR) spectroscopy combined with backpropagation artificial neural network (BP-ANN) were utilized for rapid and simultaneous assessment of the lipid oxidation indices in French fries. The conventional indexes (i.e. total polar compounds, oxidized triacylglycerol polymerized products, oxidized triacylglycerol monomers, triacylglycerol hydrolysis products, and acid value), and FTIR absorbance intensity in French fries were determined during the deep-frying process, and the results showed the French fries had better quality in palm oil, followed by sunflower oil, rapeseed oil and soybean oil. The FTIR spectra of oil extracted from French fries were correlated to the reference oxidation indexes determined by AOCS standard methods. The results of BP-ANN prediction showed that the model based on FTIR fitted well (R² > 0.926, RMSEC < 0.481) compared with partial least-squares model (R² > 0.876). This facile strategy with excellent performance has great potential for rapid characterization quality of French fries during frying.

Application of vibrational spectroscopic techniques for determination of thermal degradation of frying oils and fats: a review

Deep fried foods are popular among consumers due to their unique taste and texture. During the process of deep-frying, oil is subjected to a high temperature that results into the generation of harmful compounds. The repeated usage of frying oil is a common exercise and associated with various health hazards. Thus, determination of frying oil quality is a critical practice to follow. The chemical methods employed to determine the quality of frying oil are destructive and require large amount of harmful chemical, thus researchers are exploring the application of various vibrational spectroscopic techniques for this purpose. The first part of this review provides a detailed insight into fundamental theoretical aspects of two main vibrational spectroscopic techniques (infrared and Raman spectroscopy) and chemical alteration in frying oils under thermal stress. While in the following parts, the application of near-infrared (NIR) and Fourier transform infrared (FTIR) and Raman spectroscopy for evaluating the quality of various frying oils and fats under thermal stress has been discussed. It is anticipated that this review paper can serve as a reference source for impending research in this field.

Genetic algorithm based support vector machine regression for prediction of SARA analysis in crude oil samples using ATR-FTIR spectroscopy

In the current research, an analytical method was proposed for rapid quantitative determination of saturates, aromatics, resins and asphaltenes (SARA) fractions of crude oil samples. Rapid assessments of SARA analysis of crude oil samples are of substantial value in the oil industry. The conventional SARA analysis procedures were determined with the standards established by the American Society for Testing and Materials (ASTM). However, the standard test methods are time consuming, environmental nonfriendly, expensive, and require large amounts of the crude oil samples to be analyzed. Thus, it be would useful to approve some supportive approaches for rapid evaluation of the crude oils. The attenuated total reflection Fourier-transform infrared spectroscopy ATR-FTIR coupled with chemometric methods could be used as analytical method for crude oil analysis. A hybrid of genetic algorithm (GA) and support vector machine regression (SVM-R) model was applied to predict SARA analysis of crude oil samples from different Iranian oil field using ATR-FTIR spectroscopy. The result of GA-SVM-R model were compared with genetic algorithm-partial least square regression (GA-PLS-R) model. Correlation coefficient (R²) and root mean square error (RMSE) for calibration and prediction of samples were also calculated, in order to evaluate the calibration models for each component of SARA analysis in crude oil samples. The performance of GA-SVM-R is found to be reliably superior, so that it can be successfully applied as an alternative approach for the quantitative determination of the SARA analysis of crude oil samples.

Effects and mechanism of tea polyphenols on the quality of oil during frying process

The effects and action mechanism of tea polyphenols (TP) on the quality of rapeseed oil during frying process were investigated. Results showed that compared with control, TP (0.04%, w/w) exhibited the remarkable ability to inhibit the deterioration of acid value, peroxide value, anisidine value, viscosity, and color of frying oil. By using gas chromatography-mass spectrometry, frying oil with TP showed the higher content of unsaturated fatty acids (72.79%) and lower content of trans fatty acids (3.36%) than those of control. Meanwhile, frying oil with TP had a higher total phenolic content than control at the same frying time. In addition, the thermo gravimetric-differential scanning calorimetry results showed that TP could increase the oxidation stability of rapeseed oil. Furthermore, according to the Fourier transform infrared and molecular dynamic simulation results, TP could reduce the breaking degree of = C-H bond, C-O-C bond, and C = C bond in oil molecules, and inhibit the oxidation of oil components by inhibiting the generation of free radicals and eliminating free radicals. All present results suggested that TP showed the potential value to be used for protecting the quality of oil during the frying process in food and chemical industries. PRACTICAL APPLICATIONS: The inhibitory effect of tea polyphenols on the deterioration of quality of rapeseed oil during frying was found and the mechanism had also preliminarily interpretation. This work provided a method for monitoring the quality of fry oil and provided the theoretical basis for the use of tea polyphenols in frying.

Multivariate analysis for FTIR in understanding treatment of used cooking oil using activated carbon prepared from olive stone

In this study, activated carbons prepared from the green and black olive stone (green OSAC and black OSAC) were used as adsorbents to investigate their removal efficiencies for oxidation products and polar compounds from used sunflower and corn cooking oils. The degree of oxidation level and polar compounds were evaluated using Fourier transform infrared (FTIR) with the principal component analysis and ultra-performance liquid chromatography. Two FTIR absorption peaks were used for the oil evaluation, namely 3007-3009 cm-1, which is related to C-H symmetric stretching vibration of the cis double bonds, and ~1743 cm-1, which is related to = CH and ester carbonyl stretching vibration of the functional groups of the triglycerides, C = O. The principal component analysis results showed significant variations in the oxidation level of the sunflower and the corn oils occurred after consecutive heating and French fries frying for 10 days. The oxidation products that are adsorbed on the surface of the OSAC forms π-complexes with the C = C parts of the OSAC system. It can be concluded that the prepared adsorbents can be promising, efficient, economically effective, and environmentally friendly alternative adsorbents for oil treatment applications.

Rapid determination and classification of crude oils by ATR-FTIR spectroscopy and chemometric methods

Classification based on °API gravity is very important to estimate the parameters related to the extraction, purification, toxicity, and pricing of crude oils. Spectroscopy methods show some advantages over ASTM and API methods for crude oil analysis. The attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy coupled with chemometric methods has been applied as a quick and non-destructive method for crude oil analysis. In this work, a new analytical method using ATR-FTIR spectroscopy associated with chemometric methods were proposed for adressing regression and classification tasks for crude oils analysis based on °API gravity values. The designed methods are rapid, economic, and nondestructive ways in production process of oil industry. The spectral data were used for estimation of °API gravity using two approaches according to PLS-R and SVM-R algorithm, separately. The ATR-FTIR spectral data were also analyzed by classification method using the partial least squares-discriminant analysis (PLS-DA) for crude oil classification. The samples were classified into three classes based on their °API gravity values. The SVM-R model showed better results than PLS-R for °API gravity values using the F-test at 95% of confidence. The result of classification, showed about 100% accuracy and a zero classification error for calibration and prediction samples in PLS-DA algorithm.

A novel method for qualitative analysis of edible oil oxidation using an electronic nose

An electronic nose (E-nose) was used for rapid assessment of the degree of oxidation in edible oils. Peroxide and acid values of edible oil samples were analyzed using data obtained by the American Oil Chemists' Society (AOCS) Official Method for reference. Qualitative discrimination between non-oxidized and oxidized oils was conducted using the E-nose technique developed in combination with cluster analysis (CA), principal component analysis (PCA), and linear discriminant analysis (LDA). The results from CA, PCA and LDA indicated that the E-nose technique could be used for differentiation of non-oxidized and oxidized oils. LDA produced slightly better results than CA and PCA. The proposed approach can be used as an alternative to AOCS Official Method as an innovative tool for rapid detection of edible oil oxidation.