New Method for the Discrimination of Adulterated Flaxseed Oil Using Dielectric Spectroscopy

Fluorescence Spectroscopy Based Characterization of Flaxseed Oil

Fluorescence spectroscopy has been employed for the compositional analysis of flaxseed oil, detection of its adulteration and investigation of the thermal effects on its molecular composition. Excitation wavelengths from 320 to 420 nm have been used to explore the valued ingredients in flaxseed oil. The emission bands of flaxseed oil centred at 390, 414, 441, 475, 515 and 673/720 nm represent vitamin K, isomers of vitamin E, carotenoids and chlorophylls, which can be used as a marker for quality analysis. Due to its high quality, it is highly prone to adulteration and in this study, detection of its adulteration with canola oil is demonstrated by applying principal component analysis. Moreover, the effects of temperature on the molecular composition of cold pressed flaxseed oil has been explored by heating them at cooking temperatures of 100, 110, 120, 130, 140, 150, 160, 170 and 180 °C, each for 30 min. On heating, the deterioration of vitamin E, carotenoids and chlorophylls occurred with an increase in the oxidation products. However, it was found that up to 140 °C, flaxseed oil retains much of its natural composition whereas up to 180 oC, it loses much of its valuable ingredients along with increase of oxidized products.

Comparing Different Chemometric Approaches to Detect Adulteration of Cold-Pressed Flaxseed Oil with Refined Rapeseed Oil Using Differential Scanning Calorimetry

Flaxseed oil is one of the best sources of n-3 fatty acids, thus its adulteration with refined oils can lead to a reduction in its nutritional value and overall quality. The purpose of this study was to compare different chemometric models to detect adulteration of flaxseed oil with refined rapeseed oil (RP) using differential scanning calorimetry (DSC). Based on the melting phase transition curve, parameters such as peak temperature (T), peak height (h), and percentage of area (P) were determined for pure and adulterated flaxseed oils with an RP concentration of 5, 10, 20, 30, and 50% (w/w). Significant linear correlations (p ≤ 0.05) between the RP concentration and all DSC parameters were observed, except for parameter h1 for the first peak. In order to assess the usefulness of the DSC technique for detecting adulterations, three chemometric approaches were compared: (1) classification models (linear discriminant analysis-LDA, adaptive regression splines-MARS, support vector machine-SVM, and artificial neural networks-ANNs); (2) regression models (multiple linear regression-MLR, MARS, SVM, ANNs, and PLS); and (3) a combined model of orthogonal partial least squares discriminant analysis (OPLS-DA). With the LDA model, the highest accuracy of 99.5% in classifying the samples, followed by ANN > SVM > MARS, was achieved. Among the regression models, the ANN model showed the highest correlation between observed and predicted values (R = 0.996), while other models showed goodness of fit as following MARS > SVM > MLR. Comparing OPLS-DA and PLS methods, higher values of R2X(cum) = 0.986 and Q2 = 0.973 were observed with the PLS model than OPLS-DA. This study demonstrates the usefulness of the DSC technique and importance of an appropriate chemometric model for predicting the adulteration of cold-pressed flaxseed oil with refined rapeseed oil.

Qualitative identification of mature milk adulteration in bovine colostrum using noise-reduced dielectric spectra and linear model

BACKGROUND

The rapid and accurate identification of colostrum, a strong non-homogeneous food, remains a challenge. In the present study, the dielectric spectra including the dielectric constant (ε') and loss factor (ε″) of 154 colostrum samples adulterated with 0-50% mature milk were measured from 20 to 4500 MHz.

RESULTS

The results showed that the noise-reducing spectral preprocessing, including Savitzky-Golay (S-G), second derivative (SD), and S-G + SD, was significantly better than scattering-eliminating, including standard normal variate (SNV), multiplicative scatter correction (MSC), and SNV + MSC. The combination of S-G and SD was the best. Principal component analysis results demonstrated that dielectric spectroscopy is less susceptible to the inhomogeneity of colostrum and can be used to identify doped colostrum. The identification performance of linear models was better than that of non-linear models. The established linear discriminant analysis model based on full spectra had the best accuracy rates of 99.14% and 97.37% in the calibration and validation sets, respectively. Confirmatory tests on samples from different sources confirmed the satisfactory robustness of the proposed model.

CONCLUSION

We found that the main unfavorable effect on the identification based on dielectric spectroscopy was noise interference, rather than scattering effect caused by inhomogeneity of colostrum. The satisfactory results undoubtedly cast light on rapid detection of strongly non-homogeneous foods based on dielectric spectroscopy. © 2022 Society of Chemical Industry.

Rapid identification of flaxseed oil based on portable fiber optic Raman spectroscopy combined with an oil microscopy method

To explore a fast, simple, and accurate method to identify adulteration in flaxseed oil, the Raman spectral data of 130 samples containing flaxseed, canola, cottonseed, and adulterated oils were obtained using a portable fiber optic Raman spectrometer. The Raman spectral results showed that the Raman spectra of the flaxseed and canola oils had noticeable peak shifts, whereas the peak positions of the flaxseed and cottonseed oils were relatively similar. Clear peak intensity differences were observed in the flaxseed, cottonseed, and canola oils, mainly at 868 cm^-1 , 1022 cm^-1 , 1265 cm^-1 , and 1655 cm^-1 , with Raman shift intensities in the following order: I_{flaxseed oil}  > I_{cottonseed oil}  > I_{canola oil} . Similarly, the peak intensity of the flaxseed and adulterated oils also exhibited certain differences (at 868 cm^-1 , 1022 cm^-1 , 1265 cm^-1 , and 1655 cm^-1 ), and the Raman shift intensity tended to decrease gradually with the increasing content of canola and cottonseed oils in the flaxseed oil. Additionally, the results of Raman spectroscopy combined with the "oil microscopy" method exhibited large variations in the radar patterns of the flaxseed, canola, and cottonseed oils, whereas the radar patterns of the flaxseed and adulterated oils closely resembled each other. The results indicated that Raman spectroscopy in combination with oil microscopy more effectively revealed the subtle differences in the Raman shift intensity, serving as a more visual and comprehensive approach for differentiating the quality variations between pure flaxseed oil and other oil species and adulterated oil. PRACTICAL APPLICATION: This study analyzed the Raman spectra of flaxseed, canola, cottonseed, and adulterated oils using fiber optic Raman spectroscopy. Combined with the oil microscopy method for comprehensive evaluation and analysis, it is feasible to effectively identify the quality differences among flaxseed, canola, cottonseed, and adulterated oils.

Highly efficient authentication of edible oils by FTIR spectroscopy coupled with chemometrics

A novel improved method for the authentication of edible oil samples based on Fourier-transform infrared (FTIR) spectroscopy coupled with chemometrics has been developed. A discrimination analysis model has been developed. On this basis, 100% correct classification of 135 samples from eleven species has been achieved. Recognition rates with respect to external validation for 91 pure oil samples and 231 blend samples were 100% and 92.6%, respectively. A general quantitative model for detecting edible oil adulteration (taking Camellia oil as an example) has also been built. An optimal backward interval partial least-squares model, based on the spectral regions ν = 3100-2900, 1800-1700, 1500-1400, and 1200-1100 cm^-1, has been determined, giving good performances. A specific sub-model using a single adulterant oil has also been constructed, which showed higher prediction accuracy. Based on the developed qualitative and quantitative FTIR methods, adulterant oils in Camellia blends could be rapidly detected, effectively differentiated, and accurately quantified.

Microwave Spoof Surface Plasmon Polariton-Based Sensor for Ultrasensitive Detection of Liquid Analyte Dielectric Constant

In this paper, a microwave microfluidic sensor based on spoof surface plasmon polaritons (SSPPs) was proposed for ultrasensitive detection of dielectric constant. A novel unit cell for the SSPP structure is proposed and its behaviour and sensing potential analysed in detail. Based on the proposed cell, the SSPP microwave structure with a microfluidic reservoir is designed as a multilayer configuration to serve as a sensing platform for liquid analytes. The sensor is realized using a combination of rapid, cost-effective technologies of xurography, laser micromachining, and cold lamination bonding, and its potential is validated in the experiments with edible oil samples. The results demonstrate high sensitivity (850 MHz/epsilon unit) and excellent linearity (R² = 0.9802) of the sensor, which, together with its low-cost and simple fabrication, make the proposed sensor an excellent candidate for the detection of small changes in the dielectric constant of edible oils and other liquid analytes.

Advanced techniques in edible oil authentication: A systematic review and critical analysis

Adulteration of edible substances is a potent contemporary food safety issue. Perhaps the overt concern derives from the fact that adulterants pose serious ill effects on human health. Edible oils are one of the most adulterated food products. Perpetrators are adopting ways and means that effectively masks the presence of the adulterants from human organoleptic limits and traditional oil adulteration detection techniques. This review embodies a detailed account of chemical, biosensors, chromatography, spectroscopy, differential scanning calorimetry, non-thermal plasma, dielectric spectroscopy research carried out in the area of falsification assessment of edible oils for the past three decades and a collection of patented oil adulteration detection techniques. The detection techniques reviewed have some advantages and certain limitations, chemical tests are simple; biosensors and nuclear magnetic resonance are rapid but have a low sensitivity; chromatography and spectroscopy are highly accurate with a deterring price tag; dielectric spectroscopy is rapid can be portable and has on-line compatibility; however, the results are susceptible to variation of electric current frequency and intrinsic factors (moisture, temperature, structural composition). This review paper can be useful for scientists or for knowledge seekers eager to be abreast with edible oil adulteration detection techniques.