Untargeted fatty acid profiles based on the selected ion monitoring mode

A new isopropyl esterification method for quantitative profiling of short-chain fatty acids in human and cow milk by gas chromatograph-mass spectrometer

Short-chain fatty acids (SCFA) content in milk may have been underestimated due to the neglect of the esterified SCFA content and the lack of an accurate detection method, especially for C1:0, C2:0, and C3:0 SCFA. In this study, an accurate GC-MS profiling method was established for 10 SCFA. A 2-step esterification, including alkaline saponification (60°C for 30 min) and acid-catalyzed esterification (80°C for 150 min) in water/isopropyl/hexane (1:2:1, volume ratio), was found to be the most suitable for the quantification of esterified and nonesterified SCFA analysis. The validation results demonstrate satisfactory linearity, sensitivity, matrix effects, precision, and accuracy. The recoveries of nonesterified and esterified SCFA ranged from 82.78% to 112.49%, respectively. Human milk is distinguished from cow milk by its higher C1:0 and C2:0 content and lower C4:0 and C6:0 content. This method successfully accomplished qualitative and quantitative estimation of all 10 SCFA in milk, including both nonesterified and esterified SCFA. Furthermore, whether our method is applicable for the determination of SCFA in serum, rumen fluid, and feces remains to be explored.

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.

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.

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.

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..

Simultaneous Determination of C18 Fatty Acids in Milk by GC-MS

The determination of C18 fatty acids (FAs) is a key and difficult aspect in FA profiling, and a qualified method with good chromatographic separation and high sensitivity, as well as easy methylation, is required. A GC-MS method was established to simultaneously determine C18 FAs in milk. To simplify the methylation protocol for milk samples, besides a base-catalyzation methylation (50 °C for 20 min), the necessity of an additional acid-catalyzation was also studied using different temperatures (60 °C, 70 °C, 80 °C, and 90 °C) and durations (90 min and 150 min). The results showed that the chromatographic resolution was improved, although three co-eluted peaks existed. The base-catalyzation was sufficient, and an additional acid-catalyzation was not necessary. The proposed method was validated with good sensitivity, linearity, accuracy, and precision, and then applied in determining C18 FAs in 20 raw milk and 30 commercial milk samples. UHT milk presented a different profile of C18 FAs from raw milk and PAS milk samples, which indicated that excessive heating could change the profile. Overall, the proposed method is a high-throughput and competent approach for the determination of C18 FAs in milk, and which presents an improvement in chromatographic resolution and sensitivity, as well as a simplification of methylation.

Quantification of fatty acids in the muscle of Antarctic fish Trematomus bernacchii by gas chromatography-mass spectrometry: Optimization of the analytical methodology

This work presents data on the quantification of fatty acids (FAs, in terms of mass unit per tissue weight) in the muscle of Trematomus bernacchii, a key species in Antarctica, often used as bioindicator for contamination studies. Modifications in fatty acids content should be considered a useful biomarker to study how contaminants affect Antarctic biota. Until now, very few studies quantified fatty acids of muscle of T. bernacchii, and only as percentage of a single fatty acid on total lipids. To perform the quantification of fatty acids, we used an analytical method based on a fast microwave-assisted extraction of lipids from a lyophilized sample, a base-catalyzed trans-esterification of lipid extract to obtain Fatty Acids Methyl Esters (FAMEs), and a separation and identification of FAMEs by gas chromatography-mass spectrometry. With the optimized and validated method, a fast and accurate separation of Fatty Acids Methyl Esters was performed in 43 min. The linearity was checked up to about 320 μg mL^-1; limit of detection and limit of quantification are in the range 4-22 μg mL^-1 and 13-66 μg mL^-1, respectively. The optimized method showed a good accuracy and precision. Major fatty acids were 14:0, 16:0, 16:1n7, 18:1n9, 18:1n7, 20:1n9, 20:5n3 and 22:6n3. Quantified FAs compute for about 47 mg g^-1 tissue dry weight (dw), with 9.1 ± 0.1 mg g^-1 dw of saturated FAs, 25.5 ± 0.1 mg g^-1 dw of mono-unsaturated FAs, and 12.2 ± 0.1 mg g^-1 dw of poly-unsaturated FAs.

Simultaneous determination of capsaicin and dihydrocapsaicin for vegetable oil adulteration by immunoaffinity chromatography cleanup coupled with LC-MS/MS

Capsaicin and dihydrocapsaicin were selected as adulteration markers to authenticate vegetable oils. In this study, a method of immunoaffinity chromatography (IAC) combined with liquid chromatography-tandem mass spectrometry was established for the determination of capsaicin and dihydrocapsaicin in vegetable oils. In this method, immunosorbents were obtained by covalently coupling highly specific capsaicinoid polyclonal antibodieswith CNBr-activated Sepharose 4B, and then packed into a polyethylene column. In this paper, the major parameters affecting IAC extraction efficiency, including loading, washing and eluting conditions, were also investigated. The IAC column displayed high selectivity for capsaicin and dihydrocapsaicin with the maximum capacity of 240ng. The limit of detection (LOD) and limit of quantification (LOQ) for capsaicin were calculated as 0.02 and 0.08μgkg(-1), and for dihydrocapsaicin were 0.03 and 0.10μgkg(-1). The recoveries of capsaicin and dihydrocapsaicin in oil samples were in the range of 87.3-95.2% with the relative standard deviation (RSD) of less than 6.1%. The results indicated that capsaicinoid compounds could not be found in edible vegetable oils. Therefore, the proposed method is simple, reliable and adequate for routine monitoring of capsaicinoid compounds in vegetable oils and has an excellent potential for detection of adulteration with inedible waste oil.

One-class classification based authentication of peanut oils by fatty acid profiles

In this study, the authenticity identification model was built by the one-class partial least squares (OCPLS) classifier for peanut oils, which could effectively detect adulterated oils at the adulteration level of more than 4%.

Classification and adulteration detection of vegetable oils based on fatty acid profiles

The detection of adulteration of high priced oils is a particular concern in food quality and safety. Therefore, it is necessary to develop authenticity detection method for protecting the health of customers. In this study, fatty acid profiles of five edible oils were established by gas chromatography coupled with mass spectrometry (GC/MS) in selected ion monitoring mode. Using mass spectral characteristics of selected ions and equivalent chain length (ECL), 28 fatty acids were identified and employed to classify five kinds of edible oils by using unsupervised (principal component analysis and hierarchical clustering analysis), supervised (random forests) multivariate statistical methods. The results indicated that fatty acid profiles of these edible oils could classify five kinds of edible vegetable oils into five groups and are therefore employed to authenticity assessment. Moreover, adulterated oils were simulated by Monte Carlo method to establish simultaneous adulteration detection model for five kinds of edible oils by random forests. As a result, this model could identify five kinds of edible oils and sensitively detect adulteration of edible oil with other vegetable oils about the level of 10%.