Fatty acid profiles based adulteration detection for flaxseed oil by gas chromatography mass spectrometry

Novel PCR-Based Technology for the Detection of Sunflower in Edible and Used Cooking Oils

Reliable detection of sunflower (Helianthus annuus) in edible and used cooking oil (UCO) is crucial for the sustainable production of food and biodiesel. In this study, a variety of sunflower oils (crude, cold pressed, extra virgin, refined, and UCO) were examined using different methods of DNA extraction and PCR amplification to develop an efficient technology for the identification of sunflower in oils. DNA extraction kits such as NucleoSpin Food, DNeasy mericon Food, and Olive Oil DNA Isolation as well as modified CTAB method were found to be able to isolate amplifiable genomic DNA from highly processed oils. Novel uniplex, double, and nested PCR systems targeting the sunflower-specific helianthinin gene were developed for efficient identification of sunflower. New sunflower DNA markers were revealed by uniplex PCRs. The combination of modified CTAB and nested PCR was demonstrated as a reliable, rapid, and cost-effective technology for detecting traces of sunflower in 700 μL of highly processed oil, including refined and used cooking oil. The study will contribute to both the food industry and the energy sector as developed methods can be used for oil authenticity testing in food and biodiesel production.

A review of the emerging technologies and systems to mitigate food fraud in supply chains

Food fraud has serious consequences including reputational damage to businesses, health and safety risks and lack of consumer confidence. New technologies targeted at ensuring food authenticity has emerged and however, the penetration and diffusion of sophisticated analytical technologies are faced with challenges in the industry. This review is focused on investigating the emerging technologies and strategies for mitigating food fraud and exploring the key barriers to their application. The review discusses three key areas of focus for food fraud mitigation that include systematic approaches, analytical techniques and package-level anti-counterfeiting technologies. A notable gap exists in converting laboratory based sophisticated technologies and tools in high-paced, live industrial applications. New frontiers such as handheld laser-induced breakdown spectroscopy (LIBS) and smart-phone spectroscopy have emerged for rapid food authentication. Multifunctional devices with hyphenating sensing mechanisms together with deep learning strategies to compare food fingerprints can be a great leap forward in the industry. Combination of different technologies such as spectroscopy and separation techniques will also be superior where quantification of adulterants are preferred. With the advancement of automation these technologies will be able to be deployed as in-line scanning devices in industrial settings to detect food fraud across multiple points in food supply chains.

Food authentication, current issues, analytical techniques, and future challenges: A comprehensive review

Food authentication and contamination are significant concerns, especially for consumers with unique nutritional, cultural, lifestyle, and religious needs. Food authenticity involves identifying food contamination for many purposes, such as adherence to religious beliefs, safeguarding health, and consuming sanitary and organic food products. This review article examines the issues related to food authentication and food fraud in recent periods. Furthermore, the development and innovations in analytical techniques employed to authenticate various food products are comprehensively focused. Food products derived from animals are susceptible to deceptive practices, which can undermine customer confidence and pose potential health hazards due to the transmission of diseases from animals to humans. Therefore, it is necessary to employ suitable and robust analytical techniques for complex and high-risk animal-derived goods, in which molecular biomarker-based (genomics, proteomics, and metabolomics) techniques are covered. Various analytical methods have been employed to ascertain the geographical provenance of food items that exhibit rapid response times, low cost, nondestructiveness, and condensability.

Discrimination between the Triglyceride Form and the Ethyl Ester Form of Fish Oil Using Chromatography-Mass Spectrometry

Although the triglyceride form is the natural form of fish oil found in fish, the ethyl ester form of fish oil, which is used during processing to save costs, is also present on the market. In this study, fatty acids and lipids were determined using gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-linear ion trap mass spectrometry (LC-LIT/MS), respectively, according to developed methods. The identification of fatty acids was based on the mass spectral characteristics and equivalent chain lengths. However, the fatty acid contents of both forms of fish oils are quite similar. The application of the LC-LIT/MS method for the structural characterization of triacylglycerols (TAGs) and the mechanism of LIT/MS fragmentation are also discussed. Neutral losses of CH2=CH2 (m/z 28) and CH3CH2OH (m/z 46), which are LIT/MS characteristics of ethyl ester from fish oil, were found for the first time. The triglyceride form of fish oils was easily and accurately identified using fingerprint chromatography. In conclusion, lipid analysis combined with LC-LIT/MS showed an improved capability to distinguish between types of fish oil.

Identification of Adulteration of Flaxseed Oil From QINGHAI Area Using GC-MS Profiling of Phytosterol Composition and Chemometrics

Flaxseed oil is an important source of vegetable oil with a polyunsaturated fatty acid. It is significant to establish a method to quickly identify adulterated flaxseed oil. In the present study, the qualitative and quantitative analysis of phytosterol of flaxseed oil from different varieties and different production areas in the Qinghai area was first performed by gas chromatography-mass spectrometry (GC-MS) and the phytosterol standard profile of flaxseed oil was established. Then, a combination of similarity evaluation and cluster analysis was used to distinguish pure flaxseed oil from flaxseed oil adulterated with concentrations of 10-50% rapeseed oil, peanut oil, sunflower oil, and sesame oil, and discriminant analysis was used to identify the types of adulterated flaxseed oil. The results showed that similarity evaluation combined with cluster analysis can distinguish pure and adulterated flaxseed oil when the concentration of the adulterant was greater than 10%. Discriminant analysis models accurately identified the types of adulterating oil in flaxseed oil when the concentration of rapeseed, peanut, or sunflower oil was greater than 20%, and that of sesame oil was greater than 30%. This study shows that the determination of the phytosterol composition and chemometrics is a valuable tool to evaluate the purity of flaxseed oil.

Geographical origin identification of camellia oil based on fatty acid profiles combined with one-class classification

Geographical Indication (GI) agricultural products possess specific geographical origins and high qualities, which require an effective geographical origin traceability method for the important protective trademarks. In this study, authentication models for Changshan camellia oil were developed by fatty acid profiles and one-class classification methods including data-driven soft independent modeling of class analogy (DD-SIMCA) and one-class partial least squares (OCPLS), and compared with traditional two-class classification models. The results indicated that the prediction errors of three two-class classification models were 63.8%, 12.1%, and 65.2% for the samples out of targeted geographical origins, respectively. By contrast, the one-class classification models could completely differentiate Changshan from non-Changshan camellia oils, even from the adjacent counties. Moreover, compared with traditional indicators of mineral elements, the model built by fatty acid profiles possessed higher sensitivity and specificity. It also offered a reference strategy for the geographical origin identification of other high-value oils or foods.

Trends and advances in pre- and post-harvest processing of linseed oil for quality food and health products

Linseed is an ancient crop used for diverse purposes since the beginning of civilization. In recent times, linseed has emerged as a superfood due to its high content of health-promoting omega-3 fatty acids and other bioactive compounds. Among primary health effects, it has potential to manage hypertension, diabetes, osteoporosis, atherosclerosis, cancer, arthritis, neurological, cardiovascular diseases including blood cholesterol levels, constipation, diarrhea, and autoimmune disorders etc. due to the presence of omega-3 fatty acid, lignans, high dietary fibers, and proteins, whereas, secondary health effects comprise of relieving from various skin disorders. Due to these health-beneficial properties, interest in linseed oil necessitates the intensification of research efforts on various aspects. These include cultivation technology, varietal and genetic improvement, post-harvest processing, profiling of nutrients and bioactive compounds, pre-clinical and clinical studies, etc. The present review discussed the advances in linseed research including pre- and post-harvest processing. However, focus on the bioactive compounds present in linseed oil and their health effects are also presented. Linseed cultivation, pre- and post-harvest processing aspects are covered including climatic, edaphic, agronomic factors, type of cultivar and storage conditions etc, which impact the overall oil yield and its nutritional quality. Various emerging applications of linseed oil in functional food, nutraceutical, pharmaceutical, and cosmeceutical preparations were also presented in detail. Further, recommendations were made on linseed oil research in the field of genetics, breeding germplasm resources and genome editing for exploring its full applications as a nutrition and health product.

A dedicated electronic nose combined with chemometric methods for detection of adulteration in sesame oil

Sesame oil (SO), one of the most popular and expensive edible oils, is prone to adulteration. In this study, the fatty acid profiles of pure sesame seed oil and samples adulterated with two less expensive edible oils (canola and sunflower) were analyzed using Gas Chromatography. A dedicated e-nose system was developed and tested on 15 mixtures of sesame-canola and sesame-sunflower samples. Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), and Multi-Layered Perceptron (MLP) methods were utilized to identify adulteration through the evaluation of Volatile Organic Compound. Result of chromatography showed that most samples of sesame oil containing impurities at levels less than 30% were recognized incorrectly in the standard range of SO fatty acids. This is while the developed e-nose system was able to detect adulteration at much lower levels. According to the results, PCA and LDA methods can describe the data set variance with precision of 95.6% and 97%, respectively. The MLP model had better results compared to PCA and LDA, with high determination coefficient (R2 = 0.981) and low RMSE (0.0178). Results indicate that the e-nose system provided an effective non-destructive method to detect SO adulteration at levels as low as 5%, which GC was unable to detect.

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.

Changes in the quality of flaxseed oil powder produced by incorporating with microcrystalline cellulose and thyme

Flaxseed oil is a high nutrition oil, rich in ω-3 fatty acid, tocopherols and phenolic compounds. However, it is prone to oxidation due to its high unsaturation which needs pretreatments to be easily introduce to the market. In this study, flaxseed oil was converted to powder form by mixing with microcrystalline cellulose (MC) and thyme powder to produce flaxseed oil powder. For this purpose, 3 different levels of thyme powder (5%, 10% and 15% of oil) were mixed with oil, followed by mixing with different proportions of MC (50:50, 50:75, 50:100 (oil:MC)) and stored for 90 days at 25 °C and 4 °C. Results indicated that the total phenolic compounds (23.2-91.2 mg GAE/100 g), chlorophyll (9-63.6 mg/kg), and carotenoid (4.4-9.9 mg/kg) contents increased with the incorporation of thyme powder into the flaxseed oil on the first day in 25 °C and 4 °C. Also during 90 days storage, phenolic compound (21.8%), chlorophyll (32.5%) and carotenoid (24%) decreased in both 25 °C and 4 °C temperatures. The results confirmed that adding thyme powder to samples decreased acidity and peroxide value in compare with control. Using thyme as a natural antioxidant and also transforming the oil to powder form by MC increased the oxidative stability in compare with control. The produced high stable flaxseed oil powder has the potential to be used directly on food products like salads or to be used in different food formulations to fortify them with natural antioxidants and ω-3 essential fatty acids.

Establishment and evaluation of multiple adulteration detection of camellia oil by mixture design

Multiple adulteration is a common trick to mask adulteration detection methods. In this study, the representative multiple adulterated camellia oils were prepared according to the mixture design. Then, these representative oils were employed to build two-class classification models and validate one-class classification model combined with fatty acid profiles. The cross-validation results indicated that the recursive SVM model possessed higher classification accuracy (97.9%) than PLS-DA. In OCPLS model, the optimal percentage of RO, SO, CO and SUO was 2.8%, 0%, 7.2%, 0% respectively in adulterated camellia oil, which is the most similar to the authentic camellia oils. Further validation showed that five adulterated oils with the optimal percentage could be correctly identified, indicating that the OCPLS model could identify multiple adulterated oils with these four cheaper oils. Moreover, this study serves as a reference for one class classification model evaluation and a solution for multiple adulteration detection of other foods.

Transcriptome Analysis and GC-MS Profiling of Key Fatty Acid Biosynthesis Genes in Akebia trifoliata (Thunb.) Koidz Seeds

Simple Summary

Plant oil is an important renewable energy substance, and A. trifoliata seeds are of value in this regard. A. trifoliata fruits have many seeds with high oil content, but research progress on A. trifoliata seed oil is slow. Fatty acid biosynthesis is the most important factor affecting plant oil content. Therefore, analysis of the key genes for fatty acid biosynthesis is beneficial for breeding A. trifoliata varieties with high oil content. Here, we report changes in seed oil and key oil biosynthesis genes in the growth period of A. trifoliata based on transcriptome analysis. We found that the development of A. trifoliata seeds and fruits was not synchronized, and when the fruit was ripe, the seed oil content was not the highest. With the development of A. trifoliata seeds, linoleic and oleic acid content was found to decrease and increase, respectively. Subsequently, several key genes for oil biosynthesis in A. trifoliata were identified. These results further our understanding of the mechanism underlying oil biosynthesis in A. trifoliata seeds.

Abstract

Akebia trifoliata (Thunb.) Koidz is an important Chinese medicinal and economic crop. Its seeds, which are rich in fatty acids, are usually discarded. As of now, A. trifoliata lipid biosynthesis pathways and genes have not been clearly described. In this work, we found that seed and fruit development of A. trifoliata were not synchronized, and that when the fruit was ripe, seed oil content was not at its highest. As seeds developed, linoleic and oleic acid content was found to decrease and increase, respectively. RNA sequencing yielded 108.45 GB of clean reads from 15 cDNA libraries, containing 8756 differentially expressed genes. We identified 65 unigenes associated with lipid biosynthesis, including fatty acid and triacylglycerol biosynthesis. The 65 unigenes were mapped to the A. trifoliata lipid synthesis pathway. There were 20 AtrFAD family members in A. trifoliata, which could be divided into four sub-groups with the highest number of AtrSADs. Our study revealed the dynamic changes in A. trifoliata seed oil content and composition during its growth period and provides large-scale and comprehensive transcriptome data of A. trifoliata seeds. These findings provide a basis for the improvement of A. trifoliata seed oil yield and quality.

Recent advances in the development of bitter gourd seed oil: from chemical composition to potential applications

Non-conventional seed oils are being considered novelty foods due to the unique properties of their chemical constituents. Numerous such seed oils serve as nutritional and functional supplements, making them a point of interest for scholars. Bitter gourd (Momordica charantia L.) seed oil (BGSO) has been widely used in folk medicine worldwide for the treatment of different pathologies, such as diabetes, cancer, and several inflammatory diseases. Therefore, its nutritional and medicinal value has been extensively studied. Considering the potential use of BGSO, it is imperative to have a comprehensive understanding of this product to develop and use its biologically active ingredients in innovative food and pharmaceutical products. An extensive understanding of BGSO would also help improve the economic feasibility of the bitter gourd seed processing industry and help prevent environmental pollution associated with the raw waste produced during the processing of bitter gourd seeds. This review addresses the potential uses of BGSO in terms of food and pharmaceuticals industry perspectives and comprehensively summarizes the oil extraction process, chemical composition, biological activity, and the application prospects of BGSO in clinical medicine.

Mass spectrometry in food authentication and origin traceability

Food authentication and origin traceability are popular research topics, especially as concerns about food quality continue to increase. Mass spectrometry (MS) plays an indispensable role in food authentication and origin traceability. In this review, the applications of MS in food authentication and origin traceability by analyzing the main components and chemical fingerprints or profiles are summarized. In addition, the characteristic markers for food authentication are also reviewed, and the advantages and disadvantages of MS-based techniques for food authentication, as well as the current trends and challenges, are discussed. The fingerprinting and profiling methods, in combination with multivariate statistical analysis, are more suitable for the authentication of high-value foods, while characteristic marker-based methods are more suitable for adulteration detection. Several new techniques have been introduced to the field, such as proton transfer reaction mass spectrometry, ambient ionization mass spectrometry (AIMS), and ion mobility mass spectrometry, for the determination of food adulteration due to their fast and convenient analysis. As an important trend, the miniaturization of MS offers advantages, such as small and portable instrumentation and fast and nondestructive analysis. Moreover, many applications in food authentication are using AIMS, which can help food authentication in food inspection/field analysis. This review provides a reference and guide for food authentication and traceability based on MS.

Evaluation of Portable Vibrational Spectroscopy Sensors as a Tool to Detect Black Cumin Oil Adulteration

Black cumin oil adulteration has become a concern because it has numerous health benefits and a high price. Therefore, a simple, non-destructive, and rapid method to identify adulterations in black seed oil is necessary to protect the quality of the oils. This study aimed to perform a non-invasive method to authenticate black cumin oil by portable FT-NIR, FT-MIR, and Raman spectrometers. Spectra were collected with portable devices and analyzed using Soft Independent Modelling of Class Analogy (SIMCA) to generate a classification model to identify pure black cumin oil and partial least squares regression (PLSR) to predict the adulterant levels. For confirmation, the fatty acid profile of the oils was determined by gas chromatography (GC). SIMCA and PLSR models provided a very high performance in detecting adulterated samples in all portable units. These portable units showed great potential for rapid and non-destructive monitoring to identify adulterated black cumin oils.

Physicochemical properties, content, composition and partial least squares models of A. trifoliata seeds oil

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Feasibility of using A. trifoliata seed oil (ASO) as an edible oil was studied.

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A partial least squares regression model for the ASO content was established.

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The PLS model was well suited for the determination of ASO and UFA content.

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Based on the study, High ASO content germplasm could be used in A. trifoliata breeding.

Physicochemical properties, oil content, and fatty acids (FAs) composition are key for determining the value of oil crops. The aim of this study was to illustrate the potential of exploiting A. trifoliata as an edible oil crop, and establish a rapid measurement model for the A. trifoliata seeds oil (ASO) content and composition. In 130 A. trifoliata germplasms, the highest content of ASO was 51.27%, and unsaturated fatty acids (UFAs) mainly accounted for 74–78% of ASO. The partial least squares (PLS) model based on GC–MS and near-infrared spectroscopy was well-suited for the determination of ASO and UFA content; however, the PLS model for oleic acid (OA) and linoleic acid (LA) was not effective. The acid values and peroxide values for ASO also conformed to the Chinese food safety standards. Our findings will provide new insights and guidance for the use of A. trifoliata as oil crops..

Fatty Acid Profile of Lipid Fractions of Mangalitza (Sus scrofa domesticus) from Northern Romania: A GC-MS-PCA Approach

Mangalitza pig (Sus scrofa domesticus) becomes more popular in European countries. The goal of this study was to evaluate the fatty acid profile of the raw and thermally processed Mangalitza hard fat from Northern Romania. For the first time, the gas chromatography-mass spectrometry-Principal component analysis technique (GC-MS-PCA)—was applied to evaluate the dissimilarity of Mangalitza lipid fractions. Three specific layers of the hard fat of Mangalitza from Northern Romania were subjected to thermal treatment at 130 °C for 30 min. Derivatized samples were analyzed by GC-MS. The highest relative content was obtained for oleic acid (methyl ester) in all hard fat layers (36.1–42.4%), while palmitic acid was found at a half (21.3–24.1%). Vaccenic or elaidic acids (trans) were found at important concentrations of 0.3–4.1% and confirmed by Fourier-transform infrared spectroscopy. These concentrations are consistently higher in thermally processed top and middle lipid layers, even at double values. The GC-MS-PCA coupled technique allows us to classify the unprocessed and processed Mangalitza hard fat specific layers, especially through the relative concentrations of vaccenic/elaidic, palmitic, and stearic acids. Further studies are needed in order to evaluate the level of degradation of various animal fats by the GC-MS-PCA technique.

Identification and Validation of Metabolic Markers for Adulteration Detection of Edible Oils Using Metabolic Networks

Food adulteration is a challenge faced by consumers and researchers. Due to DNA fragmentation during oil processing, it is necessary to discover metabolic markers alternative to DNA for adulteration detection of edible oils. However, the contents of metabolic markers vary in response to various factors, such as plant species, varieties, geographical origin, climate, and cultivation measures. Thus, it is difficult to identify a universal marker for all adulterants that may be present in some authentic samples. Currently, the specificity and selectivity of metabolic biomarkers are difficult to validate. Therefore, this study developed a screening strategy based on plant metabolic networks by developing a targeted analytical method for 56 metabolites in a metabolic network, using liquid/liquid extraction-liquid chromatography-tandem mass spectrometry (LC-MS/MS). We identified a chain of 11 metabolites that were related to isoflavonoid biosynthesis, which were detected in soybean oils but not rapeseed oils. Through multiple-marker mutual validation, these metabolites can be used as species-specific universal markers to differentiate soybean oil from rapeseed oil. Moreover, this method provides a model for screening characteristic markers of other edible vegetable oils and foods.

Chemical, Nutritional and Antioxidant Characteristics of Different Food Seeds

The objective of this study was to determine the chemical composition of five different food seeds (sunflower, poppy, hemp, flax and sesame) regarding fatty acid, mineral (Fe, Cu, Zn, Na, Mg, K, Ca, Al) and protein content. In addition, the total antioxidant capacity of the seeds was evaluated using the photochemiluminescent assay. The food seeds were subjected to lipid extraction and converted into fatty acid methyl esters before the gas chromatography analysis. In all food seeds, the saturated (SFAs), monounsaturated (MUFAs) and polyunsaturated fatty acids (PUFAs) were identified, respectively. PUFAs were the most abundant fatty acids (61.2% ± 0.07% and 84.8% ± 0.08% of total fatty acids), with the highest content in flax and hemp seed oil. Also, high amounts of omega-3 from PUFAs were determined in flax and hempseed oil. Based on the obtained results the sunflower, sesame and poppy seeds are good sources of omega-6, while flax and hemp seeds are good sources of omega-3. All samples are rich in minerals (Na, K, Ca, Mg) and have more than 20% protein content.

Effect of infrared-assisted spouted bed drying of flaxseed on the quality characteristics of its oil extracted by different methods

BACKGROUND

Infrared (IR)-assisted spouted bed drying (SBD) has emerged as a potential alternative to the traditional hot air drying for heat sensitive components. The aim of this study was to investigate effect of IR-assisted SBD and application of cold press (CP), solvent extraction (SE) and ultrasound assisted extraction (UAE) on the quality of flaxseed oil. SBD and IR-assisted SBD were performed at air temperatures of 40, 60, 80 °C and their effects on the drying rate, fatty acids composition and oil peroxide and acid values were evaluated. Quality of oil extracted from the dried flaxseeds by CP, SE and UAE methods was then evaluated.

RESULTS

Increasing air temperature in the presence of IR increased the drying rate. The peroxide values (PVs) of IR-SBD samples were higher than those of SBD at the same temperature. IR treatment did not notably change the composition of fatty acids in flaxseed oil, except in linoleic acid content. UAE gave higher extraction yield than CP and SE methods. UAE yielded an oil with higher percentage of saturated fatty acids, whereas the percentage of omega-3 and omega-6 fatty acids was higher in the CP method. The oil extracted by CP exhibited lower levels of PV (0.516 meq O₂ /kg oil) and acid value (1.36%), as compared to oils extracted by SE and UAE methods.

CONCLUSION

Both UAE and conventional methods did not significantly influence the composition of fatty acids in the extracted oils. Nonetheless, the CP method yielded an oil with a high percentage of omega-3 and omega-6 fatty acids. © 2019 Society of Chemical Industry.

Gas Chromatography-Ion Mobility Spectrometry Detection of Odor Fingerprint as Markers of Rapeseed Oil Refined Grade

In this work, gas chromatography-ion mobility spectrometry (GC-IMS) was used to analyze the volatile organic compound changes of rapeseed oil with different refined grades, the odor fingerprints of refined rapeseed oil were constructed, and a nonlinear model was built to realize rapid and accurate discrimination of rapeseed oil with different refined grades. 124 rapeseed oil samples with different refined grades were collected and analyzed by GC-IMS and chemometric tools, and 34 characteristic peaks were selected by the colorized difference method as variables to characterize the internal quality in rapeseed oil of different refined grades. The principal component analysis algorithm was used to further reduce dimensionality and extract the most relevant information. The k-nearest neighbor algorithm was applied to build a discriminant model. All the samples were recognized accurately without errors, and the results show the potential of this method to discriminate different refined grades of vegetable oil.

Detection of Adulteration in Canola Oil by Using GC-IMS and Chemometric Analysis

The aim of the present study was to detect adulteration of canola oil with other vegetable oils such as sunflower, soybean, and peanut oils and to build models for predicting the content of adulterant oil in canola oil. In this work, 147 adulterated samples were detected by gas chromatography-ion mobility spectrometry (GC-IMS) and chemometric analysis, and two methods of feature extraction, histogram of oriented gradient (HOG) and multiway principal component analysis (MPCA), were combined to pretreat the data set. The results evaluated by canonical discriminant analysis (CDA) algorithm indicated that the HOG-MPCA-CDA model was feasible to discriminate the canola oil adulterated with other oils and to precisely classify different levels of each adulterant oil. Partial least square analysis (PLS) was used to build prediction models for adulterant oil level in canola oil. The model built by PLS was proven to be effective and precise for predicting adulteration with good regression (R²>0.95) and low errors (RMSE ≤ 3.23).

Rapid detection of adulterated peony seed oil by electronic nose

Peony seed oil has recently been introduced as a high-quality food oil. Because the high price of peony seed oil may tempt unscrupulous merchants to dilute it with cheaper substitutes, a rapid detection method for likely adulterants is required. In this study, the fatty acid composition of peony seed oil and four less expensive edible oils (soybean oil, corn oil, sunflower oil, and rapeseed oil) were measured by gas chromatography mass spectrometry. Peony oil adulterated by other edible oils was assessed using iodine values to estimate the extent of adulteration. Adulteration was also measured using an electronic nose (E-nose) combined with principal component analysis (PCA) or linear discriminant analysis (LDA). Results indicated that peony seed oil was highly enriched in α-linolenic acid. Although the iodine value can be used to detect some adulterants by measuring unsaturation, it was not able to detect all four potential adulterants. In contrast, the E-nose can rapidly identify adulterated peony seed oil by sampling vapor. Data analyses using PCA and LDA show that LDA more effectively clusters the data, discriminates between pure and adulterated oil, and can detect adulteration at the 10% level. E-nose combined with LDA suitable for detection of peony seed oil adulteration.

Polycyclic aromatic hydrocarbons content and fatty acids profile in coconut, safflower, evening primrose and linseed oils

This study aimed at evaluating the polycyclic aromatic hydrocarbons (PAHs) contamination of commercial vegetable oils and examined the identity through the fatty acids profiles. Coconut, safflower, evening primrose, and linseed oils marketed in São Paulo (Brazil) were investigated totaling 69 samples. Four PAHs, benzo[a]anthracene (BaA), chrysene (Chr), benzo[b]fluoranthene (BbF), and benzo[a]pyrene (BaP), were detected in 96% of the samples at individual levels ranging from not detected to 14.99 μg kg^-1. Chrysene was the abundant hydrocarbon found among all types of oils, with the highest median values. The results of the fatty acid profiles revealed that 43% showed different profiles according to the ones on their labels, with a higher incidence of adulteration of evening primrose oils. The maximum tolerable limits by European Regulation No. 835/2011 were exceeded for BaP in 12%, and for total 4 PAHs in 28%, with a greater contribution of adulterated samples.

Nigella sativa oil with a calorie-restricted diet can improve biomarkers of systemic inflammation in obese women: A randomized double-blind, placebo-controlled clinical trial

BACKGROUND

Inflammation is one of the primary mechanisms in the development of metabolic complications. Although anti-inflammatory characteristics of Nigella sativa (NS) have been indicated in animal models, clinical trials related to the effects of NS on inflammatory parameters are relatively scarce.

OBJECTIVE

The aim of the present study was to determine the effects of NS oil combined with a calorie-restricted diet on systemic inflammatory biomarkers in obese women.

METHODS

In this double-blind placebo-controlled randomized clinical trial, 90 volunteer obese (body mass index = 30-34.9 kg/m(2)) women aged 25-50 years were recruited. Participants were randomly divided into two groups, an intervention group (n = 45) and a placebo group (n = 45). Each group received either: (1) a low-calorie diet with 3 g/day of NS oil or (2) a low-calorie diet with 3 g/day placebo for 8 weeks.

RESULTS

A total of 84 females (intervention group = 43; placebo group = 41) completed the trial. Subjects in the intervention group did not report any side effects with the NS oil supplementation. NS oil decreased serum levels of tumor necrosis factor-alpha (-40.8% vs -16.1%, P = .04) and high-sensitivity C-reactive protein (-54.5% vs -21.4%, P = .01) compared to the placebo group. However, there were no significant changes in interleukin-6 levels (-8.6 vs -2.4%, P = .6) in the NS group compared to the placebo group.

CONCLUSIONS

NS oil supplementation combined with a calorie-restricted diet may modulate systemic inflammatory biomarkers in obese women. However, more studies are needed to clarify the efficacy of NS oil as an adjunct therapy to improve inflammatory parameters in obese subjects.

TDDFT prediction of UV-vis absorption and emission spectra of tocopherols in different media

We use the TDDFT/PBE0/6-31+G* method to determine the electronic absorption and emission energies, in different media, of the four forms of tocopherol, which differ by the number and the position of methyl groups on the chromanol. Geometries of the ground state S0 and the first singlet excited state S1 were optimized in the gas phase, and various solvents. The solvent effect is evaluated using an implicit solvation model (IEF-PCM). Our results are compared to the experimental ones obtained for the vitamin E content in several vegetable oils. For all forms of tocopherols, the HOMO-LUMO first vertical excitation is a π-π* transition. Gas phase and non-polar solvents (benzene and toluene) give higher absorption wavelengths than polar solvents (acetone, ethanol, methanol, DMSO, and water); this can be interpreted by a coplanarity between the O-H group and the chroman, allowing a better electronic resonance of the oxygen lone pairs and the aromatic ring, and therefore giving an important absorption wavelength, whereas the polar solvents give high emission wavelengths comparatively to gas phase and non-polar solvents. Fluorescence spectra permit the determination, the separation, and the identification of the four forms of tocopherols by a large difference in emission wavelength values. Graphical Abstract Scheme from process methodological to obtain the absorption and emission spectra for tocopherols.