Progress in Pretreatment and Analysis of Fatty Acids in Foods: An Update since 2012

Effect of derivatization method (KOH and BF3) on fatty acid profile data of boiled Tetracarpidium conophorum, and egusi pudding oils

Fatty acids are present in many foods, either free or esterified. Their presence helps to characterize and classify the food. The nature of these fatty acids is also associated with the treatments applied. To assess the fatty acid profile of these matrices, extractions are carried out using different solvents that influence the nature and lipid profile. The subsequent derivatization of fatty acids to more volatile fatty acyl methyl esters (FAMEs) prior to determination of the fatty acid profile takes into account the nature of the extraction solvent. Thus, the present work proposes to determine the fatty acid profile by Gas Chromatography Flame Ionisation Detector (GC-FID) of two lipid extracts derivatized by the MeOH/KOH and Hexane/MeOH/MeOH-BF3 procedures. Freshly harvested Tetracarpidium conophorum nuts from fields in the Fombap locality were brought to the laboratory where they were boiled (95 °C; 30 min), shelled, cut into small cubes and dried for 48 h at 45 °C. The dried seeds were ground and the resulting paste macerated in hexane for 48 h. The liquid fraction obtained was concentrated using a rotavapor, and the lipid extracts were stored at -15 °C. The egusi pudding was obtained by mixing 100 g of egusi seed paste with 0.50 g of white Piper nigrum powders, then packed in bulrush leaves and steamed for 120 min. After cooking, the product was stored for 4 days at room temperature and reheated twice a day. At the end of the last day, the lipid fraction oil was extracted following the methodology of Bligh and Dyer [1], then concentrated and preserved as before. The lipid extracts were then methylated using MeOH/KOH and Hexane/MeOH/MeOH-BF3 methods before injection into a GC-FID equipped with a Stabil Wax®-DA column. Supelco's standard mix of 37 FAMEs was used to identify and quantify the fatty acids present in the various samples. The results obtained enable us to identify the different fatty acids according to the retention time of their corresponding FAMEs and to quantify them. The fatty acids obtained were classified as saturated and unsaturated (mono and polyunsaturated). These analyses showed that the rapid derivatization method (MeOH/KOH) identified the same number of fatty acids as the Hexane/MeOH/MeOH-BF3 method in the lipid extract from the egusi pudding, whereas the Hexane/MeOH/MeOH-BF3 method identified four more fatty acids in the lipid extract coming from Tetracarpidium conophorum. Although the number of fatty acids was similar, the derivatization method influenced the nature of the fatty acids in the egusi pudding lipid extract. Overall, polyunsaturated fatty acids were the most abundant in the different oils. Omega-3 were the majority subclass in Tetracarpidium conophorum nuts, while omega-6 were in egusi pudding. The derivatization method did not influence the majority fatty acid (alpha linolenic) in Tetracarpidium conophorum nuts, whereas derivatization with BF3 gave trans linoleic and KOH cis linoleic in egusi pudding. These results show that the choice of derivatization method for fatty acid profiling and quantification is very important and depends on the technique and extraction solvents used.

Predictions of Milk Fatty Acid Contents by Mid-Infrared Spectroscopy in Chinese Holstein Cows

Genetic improvement of milk fatty acid content traits in dairy cattle is of great significance. However, chromatography-based methods to measure milk fatty acid content have several disadvantages. Thus, quick and accurate predictions of various milk fatty acid contents based on the mid-infrared spectrum (MIRS) from dairy herd improvement (DHI) data are essential and meaningful to expand the amount of phenotypic data available. In this study, 24 kinds of milk fatty acid concentrations were measured from the milk samples of 336 Holstein cows in Shandong Province, China, using the gas chromatography (GC) technique, which simultaneously produced MIRS values for the prediction of fatty acids. After quantification by the GC technique, milk fatty acid contents expressed as g/100 g of milk (milk-basis) and g/100 g of fat (fat-basis) were processed by five spectral pre-processing algorithms: first-order derivative (DER1), second-order derivative (DER2), multiple scattering correction (MSC), standard normal transform (SNV), and Savitzky-Golsy convolution smoothing (SG), and four regression models: random forest regression (RFR), partial least square regression (PLSR), least absolute shrinkage and selection operator regression (LassoR), and ridge regression (RidgeR). Two ranges of wavebands (4000~400 cm^-1 and 3017~2823 cm^-1/1805~1734 cm^-1) were also used in the above analysis. The prediction accuracy was evaluated using a 10-fold cross validation procedure, with the ratio of the training set and the test set as 3:1, where the determination coefficient (R²) and residual predictive deviation (RPD) were used for evaluations. The results showed that 17 out of 31 milk fatty acids were accurately predicted using MIRS, with RPD values higher than 2 and R² values higher than 0.75. In addition, 16 out of 31 fatty acids were accurately predicted by RFR, indicating that the ensemble learning model potentially resulted in a higher prediction accuracy. Meanwhile, DER1, DER2 and SG pre-processing algorithms led to high prediction accuracy for most fatty acids. In summary, these results imply that the application of MIRS to predict the fatty acid contents of milk is feasible.

Fatty acid profiles of milk from Holstein cows, Jersey cows, buffalos, yaks, humans, goats, camels, and donkeys based on gas chromatography-mass spectrometry

Due to the diversity and limitation of determination methods, published data on the fatty acid (FA) compositions of different milk samples have contributed to inaccurate comparisons. In this study, we developed a high-throughput gas chromatography-mass spectrometry method to determinate milk FA, and the proposed method had satisfactory linearity, sensitivity, accuracy, and precision. We also analyzed the FA compositions of 237 milk samples from Holstein cows, Jersey cows, buffalos, yaks, humans, goats, donkeys, and camels. Holstein, Jersey, goat, and buffalo milks contained high content of even-chain saturated FA, whereas goat milk had higher content of medium- and short-chain FA (MSCFA). Yak and camel milk are potential functional foods due to their high levels of odd- and branched-chain FA and low ratios of n-6 to n-3 polyunsaturated FA (PUFA). Human milk contained lower levels of saturated FA, MSCFA, and conjugated linoleic acid, and higher levels of monounsaturated FA and PUFA. As a special nonruminant milk, donkey milk contained low levels of monounsaturated FA and high levels of PUFA and MSCFA. Based on the FA profiles of 8 types of milk, nonruminant milk was distinct from ruminant milk, whereas camel and yak milk were different from other ruminant milks and considered as potential functional foods for balanced human diet.

Technical Overview of Orbitrap High Resolution Mass Spectrometry and Its Application to the Detection of Small Molecules in Food (Update Since 2012)

Food safety and quality issues are becoming increasingly important and attract much attention, requiring the development of better analytical platforms. For example, high-resolution (especially Orbitrap) mass spectrometry simultaneously offers versatile functions such as targeted/non-targeted screening while providing qualitative and quantitative information on an almost unlimited number of analytes to facilitate routine analysis and even allows for official surveillance in the food field. This review covers the current state of Orbitrap mass spectrometry (OMS) usage in food analysis based on research reported in 2012-2019, particularly highlighting the technical aspects of OMS application and the achievement of OMS-based screening and quantitative analysis in the food field. The gained insights enhance our understanding of state-of-the-art high-resolution mass spectrometry and highlight the challenges and directions of future research.