Application of triacylglycerol and fatty acid analyses to discriminate blended sesame oil with soybean oil

Improved physicochemical properties of bigels produced with ethyl cellulose-based oleogel and moderately deacetylated konjac glucomannan hydrogel

The ideal physicochemical properties of bigels are important for food applications. Therefore, a new bigel was prepared based on mixed beef tallow and soybean oil oleogel and deacetylated konjac glucomannan (KGM) hydrogel. The effect of the deacetylation degree of KGM on the physicochemical properties and microstructure of bigels was studied. The bigel containing moderate deacetylation degree of KGM had better rheological properties and hardness (319.84 g) than that with low and high deacetylation degrees of KGM. The interactions among the bigel components were analyzed by Fourier transform infrared spectroscopy and molecular dynamics simulation, indicating that the formation of the bigels was dominated by electrostatic interactions. Overall, the bigels containing moderate deacetylation degree of KGM had better physical properties, which may provide a theoretical foundation to develop bigels with low cholesterol, trans and saturated fats levels to replace traditional solid fats in food industry.

Quantitative Analysis of Blended Oils Based on Intensity Ratios of Marker Ions in MALDI-MS Spectra

Determination of quantitative compositions of blended oils is an essential but challenging step for the quality control and safety assurance of blended oils. We herein report a method for the quantitative analysis of blended oils based on the intensity ratio of triacylglycerol marker ions, which could be obtained from the highly reproducible spectra acquired by using matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) to directly analyze blended oils in their oily states. We demonstrated that this method could provide good quantitative results to binary, ternary, and quaternary blended oils, with simultaneous quantitation of multiple compositions, and was applicable for quantitative analysis of commercial blended oil products. Moreover, the intensity ratio-based method could be used to rapidly measure the proportions of oil compositions in blended oils, only based on the spectra of the blended oils and related pure oils, making the method as a high-throughput approach to meet the sharply growing analytical demands of blended oils.

Development of methods for determining free fatty acid contents in red colored oils

Buah merah oil and red palm oil are red colored and unrefined edible oils. Because of this color characteristic, measuring acid value by titration method can be uncertain and subjective, so more accurate and objective methods are needed. Gas chromatography-flame ionization detector (GC-FID) and high-performance liquid chromatography-evaporative light scattering detector (HPLC-ELSD) methods were developed to determine acid value in 3 buah merah oils and 1 red palm oil by measuring free fatty acid contents. The acid value was high in the order of titration > GC-FID > HPLC-ELSD in all samples. GC-FID method showed accurate and reliable results, whereas HPLC-ELSD showed rough data partly due to the non-linear standard curve and high limit of detection. Difference in acid value between titration method and GC-FID might be due to unrefined components that reacted with KOH titration solution. GC-FID can be used measuring free fatty acid contents in red colored oils.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10068-021-00964-2.

Detection and quantification of palmolein and palm kernel oil added as adulterant in coconut oil based on triacylglycerol profile

Economically motivated adulteration of expensive coconut oil with low cost oil, like palm kernel oil and palmolein is difficult to detect and quantify by available methods primarily due to their overlapping physicochemical properties with coconut oil. In the present work, a HPLC method has been developed to detect and quantify the degree of adulteration of coconut oil with palmolein and palm kernel oil based on triglyceride structure. The normalized area percentage of trilaurin (C36) among the three major TAG molecular species dilaurin-monocaprin/myristin-caprylin-laurin (C34), trilaurin (C36) and dilaurin-monomyristin (C38) of coconut oil was chosen as detection index for quantifying degree of adulteration of coconut oil with palm kernel oil, while the area ratio of dipalmitoyl-monoolein: trilaurin was chosen as detection index for quantifying adulteration of coconut oil with palmolein. The RP-HPLC based method developed in the present work is effective with a 2-4% minimum detection limit of adulterant oils and 78-98% detection accuracy depending on the degree of adulteration and types of oil.

Characterization of Sweet Almond Oil Content of Four European Cultivars (Ferragnes, Ferraduel, Fournat, and Marcona) Recently Introduced in Morocco

This study concerns the characterization of oil content and quality indices for almond cultivars (Marcona (Mr), Fournat (Fn), Ferragnes (Fg), and Ferraduel (Fd)) recently introduced into marginal agricultural areas in eastern Morocco. These verities are known for their rusticity and late flowering stage. The analyzed almond oils showed low acidity and peroxide values ranging, respectively, from 0.32 to 0.36% and 1.88 to 3.18 meq O₂/kg. Fatty acid (FA) profile revealed a predominance of the unsaturated FA represented essentially by the oleic (56.64-64.03%) and linoleic FA (24.57-29.80%). Triacylglycerol (TAG) analysis allowed the determination of eleven species with a remarkable dominance of trioleylglycerol (OOO: 30%) and dioleyllinoleoylglcerol (OOL: 27.25%). Regarding the minor compounds, the results showed that the total phenol content ranges between 85.33 and 141.66 mg/kg. Concerning the tocopherol content, the studied oils showed richness in these secondary metabolites (408.99-491.77 mg/kg) with a dominance of α-tocopherol. In comparison to their homologues in the Mediterranean area, the evaluated almond oils demonstrated a slight superiority in terms of quality, in particular, to those produced in Spain.

Mycobiome analysis for distinguishing the geographical origins of sesame seeds

Sesame (Sesamum indicum) is one of the most widely cultivated crops in Asia and Africa. The identification of the geographical origins of sesame seeds is important for the detection of fraudulent samples. This study was conducted to build a prediction model and suggest potential biomarkers for distinguishing the geographical origins of sesame seeds using mycobiome (fungal microbiome) analysis coupled with multivariate statistical analysis. Sesame seeds were collected from 25 cities in Korea, six cities in China, and five sites in other countries (Ethiopia, India, Nigeria, and Pakistan). According to the expression of fungal internal transcribed spacer (ITS) sequences in sesame seeds, 21 fungal genera were identified in sesame seeds from various countries. The optimal partial least squares-discriminant analysis model was established by applying two components with unit variance scaling. Based on seven-fold cross validation, the predictive model had 94.4% (Korea vs. China/other countries), 91.7% (China vs. Korea/other countries), and 88.9% (other countries vs. Korea/China) accuracy in determining the geographical origins of sesame seeds. Alternaria, Aspergillus, and Macrophomina were suggested as the potential fungal genera to differentiate the geographical origins of sesame seeds. This study demonstrated that mycobiome analysis could be used as a complementary method for distinguishing the geographical origins of raw sesame seeds.

Quantitative analysis of blended oils by matrix-assisted laser desorption/ionization mass spectrometry and partial least squares regression

Quantitative labeling of oil compositions has become a trend to ensure the quality and safety of blended oils in the market. However, methods for rapid and reliable quantitation of blended oils are still not available. In this study, matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) was used to profile triacylglycerols in blended oils, and partial least squares regression (PLS-R) was applied to establish quantitative models based on the acquired MALDI-MS spectra. We demonstrated that this new method allowed simultaneous quantitation of multiple compositions, and provided good quantitative results of binary, ternary and quaternary blended oils, enabling good limits of detection (e.g., detectability of 1.5% olive oil in sunflower seed oil). Compared with the conventional GC-FID method, this new method could allow direct analysis of blended oils, analysis of one blended oil sample within minutes, and accurate quantitation of low-abundance oil compositions and blended oils with similar fatty acid contents.

Sustainable Palm Oil-The Role of Screening and Advanced Analytical Techniques for Geographical Traceability and Authenticity Verification

Palm oil production from oil palm (Elaeis guineensis Jacq.) is vital for the economy of Malaysia. As of late, sustainable production of palm oil has been a key focus due to demand by consumer groups, and important progress has been made in establishing standards that promote good agricultural practices that minimize impact on the environment. In line with the industrial goal to build a traceable supply chain, several measures have been implemented to ensure that traceability can be monitored. Although the palm oil supply chain can be highly complex, and achieving full traceability is not an easy task, the industry has to be proactive in developing improved systems that support the existing methods, which rely on recorded information in the supply chain. The Malaysian Palm Oil Board (MPOB) as the custodian of the palm oil industry in Malaysia has taken the initiative to assess and develop technologies that can ensure authenticity and traceability of palm oil in the major supply chains from the point of harvesting all the way to key downstream applications. This review describes the underlying framework related to palm oil geographical traceability using various state-of-the-art analytical techniques, which are also being explored to address adulteration in the global palm oil supply chain.

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.

Multispecies Adulteration Detection of Camellia Oil by Chemical Markers

Adulteration of edible oils has attracted attention from more researchers and consumers in recent years. Complex multispecies adulteration is a commonly used strategy to mask the traditional adulteration detection methods. Most of the researchers were only concerned about single targeted adulterants, however, it was difficult to identify complex multispecies adulteration or untargeted adulterants. To detect adulteration of edible oil, identification of characteristic markers of adulterants was proposed to be an effective method, which could provide a solution for multispecies adulteration detection. In this study, a simple method of multispecies adulteration detection for camellia oil (adulterated with soybean oil, peanut oil, rapeseed oil) was developed by quantifying chemical markers including four isoflavones, trans-resveratrol and sinapic acid, which used liquid chromatography tandem mass spectrometry (LC-MS/MS) combined with solid phase extraction (SPE). In commercial camellia oil, only two of them were detected of daidzin with the average content of 0.06 ng/g while other markers were absent. The developed method was highly sensitive as the limits of detection (LODs) ranged from 0.02 ng/mL to 0.16 ng/mL and the mean recoveries ranged from 79.7% to 113.5%, indicating that this method was reliable to detect potential characteristic markers in edible oils. Six target compounds for pure camellia oils, soybean oils, peanut oils and rapeseed oils had been analyzed to get the results. The validation results indicated that this simple and rapid method was successfully employed to determine multispecies adulteration of camellia oil adulterated with soybean, peanut and rapeseed oils.

Determination of 2-Propenal Using Headspace Solid-Phase Microextraction Coupled to Gas Chromatography–Time-of-Flight Mass Spectrometry as a Marker for Authentication of Unrefined Sesame Oil

Ascertaining the authenticity of the unrefined sesame oil presents an ongoing challenge. Here, the determination of 2-propenal was performed by headspace solid-phase microextraction (HS-SPME) under mild temperature coupled to gas chromatography with time-of-flight mass spectrometry, enabling the detection of adulteration of unrefined sesame oil with refined corn or soybean oil. Employing this coupled technique, 2-propenal was detected in all tested refined corn and soybean oils but not in any of the tested unrefined sesame oil samples. Using response surface methodology, the optimum extraction temperature, equilibrium time, and extraction time for the HS-SPME analysis of 2-propenal using carboxen/polydimethylsiloxane fiber were determined to be 55°C, 15 min, and 15 min, respectively, for refined corn oil and 55°C, 25 min, and 15 min, respectively, for refined soybean oil. Under these optimized conditions, the adulteration of unrefined sesame oil with refined corn or soybean oils (1–5%) was successfully detected. The detection and quantification limits of 2-propenal were found to be in the range of 0.008–0.010 and 0.023–0.031 µg mL−1, respectively. The overall results demonstrate the potential of this novel method for the authentication of unrefined sesame oil.

Comparison of different classification methods for analyzing electronic nose data to characterize sesame oils and blends

An electronic nose (e-nose) was used to characterize sesame oils processed by three different methods (hot-pressed, cold-pressed, and refined), as well as blends of the sesame oils and soybean oil. Seven classification and prediction methods, namely PCA, LDA, PLS, KNN, SVM, LASSO and RF, were used to analyze the e-nose data. The classification accuracy and MAUC were employed to evaluate the performance of these methods. The results indicated that sesame oils processed with different methods resulted in different sensor responses, with cold-pressed sesame oil producing the strongest sensor signals, followed by the hot-pressed sesame oil. The blends of pressed sesame oils with refined sesame oil were more difficult to be distinguished than the blends of pressed sesame oils and refined soybean oil. LDA, KNN, and SVM outperformed the other classification methods in distinguishing sesame oil blends. KNN, LASSO, PLS, and SVM (with linear kernel), and RF models could adequately predict the adulteration level (% of added soybean oil) in the sesame oil blends. Among the prediction models, KNN with k = 1 and 2 yielded the best prediction results.