Multi-block analysis coupled with GC-FID and ATR-MIR for the evaluation of thermal degradation in vegetable oils

Data fusion of middle-resolution NMR spectroscopy and low-field relaxometry using the Common Dimensions Analysis (ComDim) to monitor diesel fuel adulteration

Medium-resolution (MR-NMR) and time-domain NMR relaxometry (TD-NMR) using benchtop and low-field NMR instruments are powerful tools to tackle fuel adulteration issues. In this work, for the first time, we investigate the possibility of enhancing the low-field NMR capability on fuel analysis using data fusion of MR and TD-NMR. We used the ComDim (Common Dimensions Analysis) multi-block analysis to join the data, which allowed exploration, classification, and quantification of common adulterations of diesel fuel by vegetable oils, biodiesel, and diesel of different sources as well as the sulfur content. After data exploration using ComDim, classification (applying linear discriminant analysis, LDA), and regression (applying multiple linear regression, MLR), models were built using ComDim scores as input variables on the LDA and MLR analyses. This approach enabled 100% of accuracy in classifying diesel fuel source (refinery), sulfur content (S10 or S500), vegetable oil, and biodiesel source. Moreover, in the quantification step, all MLR models showed a root mean square error of prediction (RMSEP) and the residual prediction deviation (RPD) values comparable to the literature for determining diesel, vegetable oil, and biodiesel contents.

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.

Photo and thermal stress of linseed oil and stabilization strategies

The thermal and light stability of linseed oil has been studied by monitoring the concentrations of fatty acids and lignans, as main nutraceutical components. Linseed oil was subjected to stressing light and temperature conditions, in accordance with the ICH international rules, and monitored by UV-vis spectroscopy and HPLC-DAD. The change of UV spectra along the photodegradation tests, setting the irradiation power at 350 W/m2, confirmed a significant overall sensitivity of linseed oil to light. At the same time, the HPLC determination of the major fatty acids showed a marked variation in their concentration up to a residual concentration of 62.3 and 67.2% for α-linolenic and linoleic acid, respectively, after 18 h. In contrast, thermal tests at 60 °C showed some stability, with a concentration of residual fatty acids in the range 82-95% after 48 h. The examined lignans showed significant stability when exposed to both light and heat. Several photoprotection approaches have been also studied to increase the photostability of linseed oil. A significant increase in the stability of fatty acids has been observed using amber glass containers or ascorbic acid or by combining the two protection factors.

Multi-block analysis for the correlation of physico-chemical and rheological data of 42 fruit pulps

The common dimension (ComDim) chemometric method for multi-block analysis and hierarchical cluster analysis (HCA) were used to evaluate the data obtained from the physico-chemical and rheological characterization of 42 commercial fruit pulps. The physico-chemical characteristics and the rheological behavior of the pulps were found to be considerably different. The Herschel-Bulkley equation was fit to the steady-state flow curves of the fruit pulps, and it was found to appropriately describe the materials, which showed a wide range of yield stresses. The soluble solids content and the yield stress were the main factors responsible for the sample discrimination in the multivariate statistical analysis. The ComDim model indicates that these parameters may have a direct correlation. Namely, the soluble solids amount can influence the viscosity, as demonstrated by the similar scores of the samples in both common components, and this corroborated with the HCA analysis. PRACTICAL APPLICATIONS: Fruit pulps can be used as raw materials in the food industry to obtain several products, such as nectars, jellies, ice creams, and juices, which can also be sold directly to consumers. To evaluate the technical and economic feasibility of those industrial processes, it is important to know the physico-chemical properties of the products. Therefore, in this study we attempt to correlate the physical-chemical and rheological data using a new statistical approach.