Quantification of Triacylglycerols in Olive Oils Using HPLC-CAD

Exploration of total synchronous fluorescence spectroscopy combined with pre-trained convolutional neural network in the identification and quantification of vegetable oil

In order to distinguish different vegetable oils, adulterated vegetable oils, and to identify and quantify counterfeit vegetable oils, a method based on a small sample size of total synchronous fluorescence (TSyF) spectra combined with convolutional neural network (CNN) was proposed. Four typical vegetable oils were classified by three ways of fine-tuning the pre-trained CNN, the pre-trained CNN as a feature extractor, and traditional chemometrics. The pre-trained CNN was combined with support vector machines to distinguish adulterated sesame oil and counterfeit sesame oil separately with 100% correct classification rates. The pre-trained CNN combined with partial least square regression was used to predict the level of counterfeit sesame oil. The coefficient of determination for calibration (R_c²) values were all greater than 0.99, and the root mean square errors of validation were 0.81% and 1.72%, respectively. These results show that it is feasible to combine TSyF spectra with CNN for vegetable oil identification.

Authentication of the Geographical Origin of Margarines and Fat-Spread Products from Liquid Chromatographic UV-Absorption Fingerprints and Chemometrics

Fat-spread products are a stabilized emulsion of water and vegetable oils. The whole fat content can vary from 10 to 90% (w/w). There are different kinds, which are differently named, and their composition depends on the country in which they are produced or marketed. Thus, having analytical solutions to determine geographical origin is required. In this study, some multivariate classification methods are developed and optimised to differentiate fat-spread-related products from different geographical origins (Spain and Morocco), using as an analytical informative signal the instrumental fingerprints, acquired by liquid chromatography coupled with a diode array detector (HPLC-DAD) in both normal and reverse phase modes. No sample treatment was applied, and, prior to chromatographic analysis, only the samples were dissolved in n‑hexane. Soft independent modelling of class analogy (SIMCA) and partial least squares-discriminant analysis (PLS-DA) were used as classification methods. In addition, several classification strategies were applied, and performance of the classifications was evaluated applying proper classification metrics. Finally, 100% of samples were correctly classified applying PLS-DA with data collected in reverse phase.

Differentiation of avocados according to their botanical variety using liquid chromatographic fingerprinting and multivariate classification tree

BACKGROUND

The oil content, composition and marketing threshold value of an avocado depends on the cultivar hence, identifying the cultivar of the avocado fruit is desirable. However, analytical methods have not been reported with this aim.

RESULTS

A multivariate classification tree method was proposed to discriminate three commercial botanical varieties of avocado: Hass, Fuerte and Bacon, using high-performance liquid chromatography coupled to a charged aerosol detector (HPLC-CAD). Prior to the chromatographic analysis the avocados were lyophilized and then the oil fraction was extracted using a pressurized liquid extraction system. Normal and reverse phase liquid chromatography were applied in order to obtain the chromatographic fingerprint for each sample. Soft independent modelling of class analogies (SIMCA) and partial least-squares discriminant analysis (PLS-DA) were applied. Classification quality metrics were determined to evaluate the performance of the classification. Several strategies to develop the classification models were employed. Finally, the useful application of 'classification trees' methodology, which has been scarcely applied in the field of analytical food control, was evaluated to perform a multiclass classification.

CONCLUSION

Discrimination of the three botanical varieties was achieved. The best classification was obtained when the PLS-DA is applied on the normal-phase chromatographic fingerprints. Classification trees are showed to be useful tools that provide complementary information to single concatenated models showing different results from the same prediction sample set. © 2019 Society of Chemical Industry.

Precolumn Derivatization with Bromine to Improve Separation and Detection Sensitivity of Triacylglycerols in Edible Oil by Reversed-Phase High Performance Liquid Chromatography

The complexity of triacylglycerols (TAGs) in edible oils is largely due to the many similar unsaturated TAG compounds, which makes profiling TAGs difficult. In this study, precolumn derivatization with bromine (Br₂) was used to improve the separation and detection sensitivity of TAGs in edible oils by RP-HPLC. Oil samples dissolved in n-hexane and TAGs were derived by reaction with a Br2-CCl₄ (1:1, v/v) solution for 3 h at room temperature. The derivate product solution was stable and was best separated and detected by RP-HPLC using a C18 column, with a mobile phase of methanol-n-hexane (91.5:8.5, v/v) at 25°C. A detection wavelength of 230 nm was used. The results showed that the approach enabled the separation and detection of more similar TAGs by RP-HPLC. The method was applied to profile 20 types of edible oil, and the results presented the differences in the TAG profiles of various edible oils, which may be useful in the identification of edible oils.

A new application of charged aerosol detection in liquid chromatography for the simultaneous determination of polar and less polar ginsenosides in ginseng products

INTRODUCTION

Conventional liquid chromatographic methods coupled with ultraviolet or evaporative light scattering detection are not sensitive enough to determine both polar and less polar ginsenosides at low concentrations.

OBJECTIVE

To establish a liquid chromatography-charged aerosol detection method for the simultaneous determination of polar and less polar ginsenosides in a variety of ginseng products

METHODS

Fourteen polar and less polar ginsenosides were extracted and concentrated by solid phase extraction. These were subsequently baseline-separated on a conventional reversed-phase C18 -column (250 mm × 4.6 mm, 5 µm) with a simple mobile phase consisting of water and acetonitrile. Components were then detected by means of charged aerosol detection.

RESULTS

The method developed allowed the simultaneous determination of six polar ginsenosides (Rg1 , Re, Rb1 , Rc, Rb, Rd) and eight less polar ginsenosides (Rg6 , F4 , Rk3 , Rh4 , Rg3 (S), Rg3 (R), Rk1 , Rg5 ) in a single chromatographic run. Further, the method was linear (R(2)  > 0.99), accurate (relative recoveries, 90-112%), and precise (intraday RSD < 5.7% and interday RSD < 10.6%) within the concentration range tested. The method sensitivity was measured in terms of the limit of detection, which ranged from 0.5 to 4.0 µg/mL.

CONCLUSION

Concentrations of 14 ginsenosides were determined simultaneously in one homemade red ginseng and 13 commercial ginseng products of different types (liquid and solid samples), and results showed that ginsenoside content varied significantly among the samples tested. The method developed could serve as a useful analytical tool for the quality control of ginseng products.