Extra virgin Argan oils’ shelf-life monitoring and prediction based on chemical properties or FTIR fingerprints and chemometrics

A novel method for determination of peroxide value and acid value of extra-virgin olive oil based on fluorescence internal filtering effect correction

Peroxide value (PV) and acid value (AV) are widely used indicators for evaluating oxidation degree of olive oils. Fluorescence spectroscopy has been extensively studied on the detection of oil oxidation, however, the detection accuracy is limited due to internal filtering effect (IFE). Due to the primary and secondary IFE, at least two wavelengths of absorption information are required. Least squares support vector regression (LSSVR) models for PV and AV were established based on two absorption coefficients (μa) at 375 nm and emission wavelength and one fluorescence intensity at corresponding wavelength. The regression results proved that the model based on 375 and 475 nm could reach the best performance, with the highest correlation coefficient for prediction (rp) of 0.889 and 0.960 for PV and AV respectively. Finally, the explicit formulations for PV and AV were determined by nonlinear least squares fitting, and the rp could reach above 0.94 for two indicators.

Assessment of Quality and Efficiency of Cold-Pressed Oil from Selected Oilseeds

In this present study, an oil press was used to process 200 g each of sesame, pumpkin, flax, milk thistle, hemp and cumin oilseeds in order to evaluate the amount of oil yield, seedcake, sediments and material losses (oil and sediments). Sesame produced the highest oil yield at 30.60 ± 1.69%, followed by flax (27.73 ± 0.52%), hemp (20.31 ± 0.11%), milk thistle (14.46 ± 0.51%) and pumpkin (13.37 ± 0.35%). Cumin seeds produced the lowest oil yield at 3.46 ± 0.15%. The percentage of sediments in the oil, seedcake and material losses for sesame were 5.15 ± 0.09%, 60.99 ± 0.04% and 3.27 ± 1.56%. Sediments in the oil decreased over longer storage periods, thereby increasing the percentage oil yield. Pumpkin oil had the highest peroxide value at 18.45 ± 0.53 meq O2/kg oil, an acid value of 11.21 ± 0.24 mg KOH/g oil, free fatty acid content of 5.60 ± 0.12 mg KOH/g oil and iodine value of 14.49 ± 0.16 g l/100 g. The univariate ANOVA of the quality parameters against the oilseed type was statistically significant (p-value < 0.05), except for the iodine value, which was not statistically significant (p-value > 0.05). Future studies should analyze the temperature generation, oil recovery efficiency, percentage of residual oil in the seedcake and specific energy consumption of different oilseeds processed using small-large scale presses.

Quality Control and Authentication of Argan Oils: Application of Advanced Analytical Techniques

In addition to the nutritional and therapeutic benefits, Argan oil is praised for its unique bio-ecological and botanic interest. It has been used for centuries to treat cardiovascular issues, diabetes, and skin infections, as well as for its anti-inflammatory and antiproliferative properties. Argan oil is widely commercialized as a result of these characteristics. However, falsifiers deliberately blend Argan oil with cheaper vegetable oils to make economic profits. This reduces the quality and might result in health issues for consumers. Analytical techniques that are rapid, precise, and accurate are employed to monitor its quality, safety, and authenticity. This review provides a comprehensive overview of studies on the quality assessment of Moroccan Argan oil using both untargeted and targeted approaches. To extract relevant information on quality and adulteration, the analytical data are coupled with chemometric techniques.

Argan Oil: Chemical Composition, Extraction Process, and Quality Control

Argan oil is considered a relatively international product exported from Morocco, although different companies in Europe and North America distribute argan oil around the globe. Argan oil is non-refined vegetable oil, of the more well-known “virgin oil” type, is produced from the argan tree [Argania spinosa (L.) Skeels]. The argan tree is deemed to be an important forest species from both social and economic standpoints. Argan oil has rapidly emerged as an important product able to bring more income to the local population. In addition, it also has important environmental implications, owing to its ability to stand against desert progression. Currently, argan oil is mainly produced by women's cooperatives in Morocco using a semi-industrial mechanical extraction process. This allows the production of high-quality argan oil. Depending on the method used to prepare argan kernels, two types of argan oil can be obtained: food or cosmetic grade. Cosmetic argan oil is prepared from unroasted kernels, whereas food argan oil is achieved by cold pressing kernels roasted for a few minutes. Previously, the same food argan oil was prepared exclusively by women according to a laborious ancestral process. Extraction technology has been evolved to obtain high-quality argan oil at a large scale. The extraction process and several accompanying parameters can influence the quality, stability, and purity of argan oil. In view of this, the present review discusses different aspects related to argan oil chemical composition along with its nutritional and cosmetic values. Similarly, it details different processes used to prepare argan oil, as well as its quality control, oxidative stability, and authenticity assessment.

Comparison of green bio-based cerium/alginate vs. copper/alginate beads: a study of vibrational and thermal properties using experimental and theoretical methods

Herein, bio-based alginates (Alg) containing metallic beads (Ce and Cu) were synthesized via an alginate cross-linking method, and their properties were studied using experimental techniques combined with theoretical simulations. Materials were characterized through Fourier transform infrared spectroscopy (FTIR), thermogravimetric analysis (TGA), and scanning electron microscope (SEM) images, to determine the cross-linking structural features, thermal stability, and surface morphology of alginates. Besides, density functional theory (DFT) methods were employed to calculate global reactivity parameters such as HOMO-LUMO gap energies (ΔE_H-L), electronegativity (χ), hardness (η), and electrophilic and nucleophilic indicators, using both gas and aqueous media for the study of the complexation process. Among other features, characterization of the thermal properties showed that Alg@Ce and Alg@Cu alginate beads behave differently as a function of the temperature. This behavior was also predicted by the conformation energy differences between Alg@Ce and Alg@Cu, which were found out theoretically and explained with the combined study of the vibrational modes between the carboxylate group with either Ce or Cu. Overall, the reactivity of the Alg@Ce alginate bead was higher than that of the Alg@Cu counterpart, results could be used as a cornerstone to employed the materials here studied in a wide range of applications.

Comparative study of three fingerprint analytical approaches based on spectroscopic sensors and chemometrics for the detection and quantification of argan oil adulteration

BACKGROUND

Argan oil is one of the purest and rarest oils in the world, so that the addition of any further product is strictly prohibited by international regulations. Consequently, it is necessary to establish reliable analytical methods to ensure its authenticity. In this study, three multivariate approaches have been developed and validated using fluorescence, UV-visible, and attenuated total reflectance Fourier transform mid-infrared (FT-MIR) spectroscopies.

RESULTS

The application of a partial least squares discriminant analysis model showed an accuracy of 100%. The quantification of adulteration have been evaluated using partial least squares (PLS) regression. The PLS model developed from fluorescence spectroscopy provided the best results for the calibration and cross-validation sets, as it showed the highest R² (0.99) and the lowest root mean square error of calibration and cross-validation (0.55, 0.79). The external validation of the three multivariate approaches by the accuracy profile shows that these approaches guarantee reliable and valid results of 0.5-32%, 7-32%, and 10-32% using fluorescence, FT-MIR and UV-visible spectroscopies respectively.

CONCLUSION

This study confirmed the feasibility of using spectroscopic sensors (routine technique) for rapid determination of argan oil falsification. © 2021 Society of Chemical Industry.

Diving Deep into the Data: A Review of Deep Learning Approaches and Potential Applications in Foodomics

Deep learning is a trending field in bioinformatics; so far, mostly known for image processing and speech recognition, but it also shows promising possibilities for data processing in food analysis, especially, foodomics. Thus, more and more deep learning approaches are used. This review presents an introduction into deep learning in the context of metabolomics and proteomics, focusing on the prediction of shelf-life, food authenticity, and food quality. Apart from the direct food-related applications, this review summarizes deep learning for peptide sequencing and its context to food analysis. The review’s focus further lays on MS (mass spectrometry)-based approaches. As a result of the constant development and improvement of analytical devices, as well as more complex holistic research questions, especially with the diverse and complex matrix food, there is a need for more effective methods for data processing. Deep learning might offer meeting this need and gives prospect to deal with the vast amount and complexity of data.