Real-time assessing the lipid oxidation of prawn (Litopenaeus vannamei) during air-frying by iKnife coupling rapid evaporative ionization mass spectrometry

Exploring the influence and mechanism of different frying methods on the flavor quality of low-salt sour meat

To obtain nutritious, healthy, and flavor-enriched sour meat products, the effects of different frying methods (microwave, air-frying, and traditional frying) on the flavor quality of low-salt sour meat were evaluated using metabolomics and other flavor analysis techniques. The pH value of the sour meat rose dramatically, while the TBARS value dropped significantly after frying. E-nose and E-tongue results showed that air-frying could reduce acidity and improve umami. The comprehensive analysis of all samples revealed the identification of 107 volatile flavor compounds, including 10 unique aroma compounds that were specifically detected in the AF group. Additionally, the air frying process notably increased the free amino acid and nucleotide concentrations in sour meat by 53.58% and 159.29%, respectively, while causing a significant reduction in both fatty acid and lactic acid content by 22.84% and 49.29%, respectively. All three frying methods altered the flavor of the samples, but air frying performed better in terms of flavor and texture.

Exploring molecular mechanisms underlying changes in lipid fingerprinting of salmon (Salmo salar) during air frying integrating machine learning-guided REIMS and lipidomics analysis

Lipid oxidation in air-fried seafood poses a risk to human health. However, the effect of a prooxidant environment on lipid oxidation in seafood at different air frying (AF) temperatures remains unknown. An integrated machine learning (ML) - guided REIMS and lipidomics method was applied to explore lipid profiles, lipid oxidation, and lipid metabolic pathways of salmons under different AF temperatures (140, 160, 180, and 200 °C). A significant difference in the lipidomic fingerprinting of air-dried salmon at different temperatures was shown by the main ML methods (neural networks, support vector machines, ensemble learning, and naïve bayes). In total, 773 differential expression metabolites (DEMs) were identified, including glycerophospholipids (GPs), glycerides (GLs), and sphingolipids. A total of 34 DEMs with p values <0.05 and variable importance of projection values >1.0 were analyzed, belonging to linoleic acid metabolism, GL metabolism, and GP metabolism pathways. Correlation network analysis revealed that some characteristic DEMs (phosphatidylcholine, lyso-phosphatidylcholine, triglycerides, fatty acids, and phosphatidylethanolamine) were highly correlated with lipid oxidation. In addition, variations of volatile compounds, color values, texture characteristics, and thiobarbituric acid-reactive substance values were analyzed to corroborate the oxidation characteristics.

Rapid evaporative ionization mass spectrometry: A survey through 15 years of applications

Rapid evaporative ionization mass spectrometry (REIMS) is a relatively recent MS technique explored in many application fields, demonstrating high versatility in the detection of a wide range of chemicals, from small molecules (phenols, amino acids, di- and tripeptides, organic acids, and sugars) to larger biomolecules, that is, phospholipids and triacylglycerols. Different sampling devices were used depending on the analyzed matrix (liquid or solid), resulting in distinct performances in terms of automation, reproducibility, and sensitivity. The absence of laborious and time-consuming sample preparation procedures and chromatographic separations was highlighted as a major advantage compared to chromatographic methods. REIMS was successfully used to achieve a comprehensive sample profiling according to a metabolomics untargeted analysis. Moreover, when a multitude of samples were available, the combination with chemometrics allowed rapid sample differentiation and the identification of discriminant features. The present review aims to provide a survey of literature reports based on the use of such analytical technology, highlighting its mode of operation in different application areas, ranging from clinical research, mostly focused on cancer diagnosis for the accurate identification of tumor margins, to the agri-food sector aiming at the safeguard of food quality and security.

Evaluation of Lipid Oxidation Characteristics in Salmon after Simulation of Cold Chain Interruption Using Rapid Evaporation Ionization Mass Spectrometry

Temperature fluctuations occurring during the cold chain logistics of salmon contribute to lipid oxidation. This study aimed to simulate cold chain interruption through freeze-thaw operations and evaluate the lipidomics data from salmon samples subjected to different numbers of freeze-thaw cycles by using rapid evaporative ionization mass spectrometry (REIMS) combined with an intelligent surgical knife (iKnife). The results indicated significant differences in the relative abundance of characteristic ions among the samples (p < 0.05). A total of 34 ions with variable importance for the projection values ≥1 were identified as potential biomarkers, including m/z 719.4233 ([PCC36:5-NH(CH3)3]-), m/z 337.3134 ([FAC22:1]-), m/z 720.4666 ([PEC35:6-H]-), m/z 309.2780 ([FAC20:1]-), m/z 777.4985 ([PCC40:4-NH(CH3)3]-), m/z 745.4421 ([PCC38:6-NH(CH3)3]-/[PEC38:6-NH3]-), m/z 747.4665 ([PCC38:5-NH(CH3)3]-/[PEC38:5-NH3]-), etc. The degree of lipid oxidation was found to be associated with the number of freeze-thaw cycles, exhibiting the most significant alterations in the relative abundance of lipid ions in the 8T samples. Additionally, sensory evaluation by the CIE-L*a*b* method and volatile analysis by headspace solid-phase microextraction gas chromatography-mass spectrometry demonstrated significant differences (p < 0.05) in color and odor among the salmon samples, with a correlation to the number of freeze-thaw cycles. The primary compounds responsible for alterations in salmon odor were aldehydes with lower odor thresholds. In summary, the iKnife-REIMS method accurately differentiated salmon muscle tissues based on varying levels of lipid oxidation, thus expanding the application of REIMS.

Integrative deep learning framework predicts lipidomics-based investigation of preservatives on meat nutritional biomarkers and metabolic pathways

Preservatives are added as antimicrobial agents to extend the shelf life of meat. Adding preservatives to meat products can affect their flavor and nutrition. This review clarifies the effects of preservatives on metabolic pathways and network molecular transformations in meat products based on lipidomics, metabolomics and proteomics analyses. Preservatives change the nutrient content of meat products via altering ionic strength and pH to influence enzyme activity. Ionic strength in salt triggers muscle triglyceride hydrolysis by causing phosphorylation and lipid droplet splitting in adipose tissue hormone-sensitive lipase and triglyceride lipase. DisoLipPred exploiting deep recurrent networks and transfer learning can predict the lipid binding trend of each amino acid in the disordered region of input protein sequences, which could provide omics analyses of biomarkers metabolic pathways in meat products. While conventional meat quality assessment tools are unable to elucidate the intrinsic mechanisms and pathways of variables in the influences of preservatives on the quality of meat products, the promising application of omics techniques in food analysis and discovery through multimodal learning prediction algorithms of neural networks (e.g., deep neural network, convolutional neural network, artificial neural network) will drive the meat industry to develop new strategies for food spoilage prevention and control.

An overview of food lipids toward food lipidomics

Increasing evidence regarding lipids' beneficial effects on human health has changed the common perception of consumers and dietary officials about the role(s) of food lipids in a healthy diet. However, lipids are a wide group of molecules with specific nutritional and bioactive properties. To understand their true nutritional and functional value, robust methods are needed for accurate identification and quantification. Specific analytical strategies are crucial to target specific classes, especially the ones present in trace amounts. Finding a unique and comprehensive methodology to cover the full lipidome of each foodstuff is still a challenge. This review presents an overview of the lipids nutritionally relevant in foods and new trends in food lipid analysis for each type/class of lipids. Food lipid classes are described following the LipidMaps classification, fatty acids, endocannabinoids, waxes, C8 compounds, glycerophospholipids, glycerolipids (i.e., glycolipids, betaine lipids, and triglycerides), sphingolipids, sterols, sercosterols (vitamin D), isoprenoids (i.e., carotenoids and retinoids (vitamin A)), quinones (i.e., coenzyme Q, vitamin K, and vitamin E), terpenes, oxidized lipids, and oxylipin are highlighted. The uniqueness of each food group: oil-, protein-, and starch-rich, as well as marine foods, fruits, and vegetables (water-rich) regarding its lipid composition, is included. The effect of cooking, food processing, and storage, in addition to the importance of lipidomics in food quality and authenticity, are also discussed. A critical review of challenges and future trends of the analytical approaches and computational methods in global food lipidomics as the basis to increase consumer awareness of the significant role of lipids in food quality and food security worldwide is presented.

Nutritional lipidomics for the characterization of lipids in food

Lipids represent one out of three major macronutrient classes in the human diet. It is estimated to account for about 15-20% of the total dietary intake. Triacylglycerides comprise the majority of them, estimated 90-95%. Other lipid classes include free fatty acids, phospholipids, cholesterol, and plant sterols as minor components. Various methods are used for the characterization of nutritional lipids, however, lipidomics approaches become increasingly attractive for this purpose due to their wide coverage, comprehensiveness and holistic view on composition. In this chapter, analytical methodologies and workflows utilized for lipidomics profiling of food samples are outlined with focus on mass spectrometry-based assays. The chapter describes common lipid extraction protocols, the distinct instrumental mass-spectrometry based analytical platforms for data acquisition, chromatographic and ion-mobility spectrometry methods for lipid separation, briefly mentions alternative methods such as gas chromatography for fatty acid profiling and mass spectrometry imaging. Critical issues of important steps of lipidomics workflows such as structural annotation and identification, quantification and quality assurance are discussed as well. Applications reported over the period of the last 5years are summarized covering the discovery of new lipids in foodstuff, differential profiling approaches for comparing samples from different origin, species, varieties, cultivars and breeds, and for food processing quality control. Lipidomics as a powerful tool for personalized nutrition and nutritional intervention studies is briefly discussed as well. It is expected that this field is significantly growing in the near future and this chapter gives a short insight into the power of nutritional lipidomics approaches.

Study on the physicochemical and flavor characteristics of air frying and deep frying shrimp (crayfish) meat

This study aimed to compare the changes in the quality characteristics of air-fried (AF) shrimp meat and deep-fried (DF) shrimp meat at different frying temperatures (160, 170, 180, 190°C). Results showed that compared with DF, the moisture and fat content of air-fried shrimp meat (AFSM) was lower, while the protein content was higher. At the same frying temperature, the fat content of the AFSM was 4.26-6.58 g/100 g lower than that of the deep-fried shrimp meat (DFSM). The smell of the AFSM and DFSM was significantly different from that of the control group. The results of the electronic tongue showed that each of the two frying methods had its flavor profile. Gas chromatography-ion mobility spectrometry (GC-IMS) identified 48 compounds, and the content of volatile compounds detected in AFSM was lower than that in DFSM. Among them, the highest level of volatile compound content was found in the DF-190. E-2-pentenal, 2-heptenal (E), and methyl 2-methyl butanoate were identified only in DFSM. In addition, a total of 16 free amino acids (FAAs) were detected in shrimp meat. As judged by sensory evaluation, the AFSM at 170°C was the most popular among consumers.

Effect of air fryer frying temperature on the quality attributes of sturgeon steak and comparison of its performance with traditional deep fat frying

In this study, the influence of air-frying temperature on the physical properties of sturgeon steaks was explored. Meanwhile, the comparison of traditional deep fat frying (TF) and air fryer frying (AFF) methods on the quality, flavor, and digestibility of sturgeon steaks were investigated. The results indicated that along with the increase of temperature (130, 160, and 190℃) for 15 min, the moisture content of AFF sturgeon steak surface decreased dramatically while that of interior was well preserved. The applied texture property analysis exhibited that AFF sturgeon steak showed the enhanced elasticity, low hardness, and soft texture. The results indicated that AFF sturgeon steak contained higher essential amino acid content than TF sturgeon steak. More flavor compounds (aldehydes, alcohols, and esters) were produced after AFF than TF. Although the digestibility of fried sturgeon steaks decreased after frying, AFF sturgeon steaks were digested rapidly in the stomach and intestine. Conclusively, AFF sturgeon steaks exhibited a crispy texture, appealing flavor, and low oil content. This work provides a certain reference for the suitable frying methods in the processing industry of sturgeon products.

Investigation of the changes in lipid profiles induced by hydroxyl radicals in whiteleg shrimp (Litopenaeus vannamei) muscle using LC/MS-based lipidomics analysis

The oxidative effects of hydroxyl radical on the alterations of lipid profiles were investigated in shrimp muscle. Chemical results indicate peroxide value (PV) and thiobarbituric acid index (TBA-i) value in oxidation-treated shrimp significantly increased with oxidation time, and hydroxyl radical concentration increased, compared with those of in fresh samples. It was assumed that radical attack might induce lipid decomposition, backbone cleavage, and/or side-chain modifications. LC/MS-based lipidomics analysis revealed 835 lipids in shrimp assigned to 27 lipid classes, including 219 PCs and 98 CLs. In total, 86 and 34 differentially abundant lipids (DALs) accumulated at lower and higher levels, respectively, were identified in OS, compared with that in FS. This indicates hydroxyl radical attack altered the lipidomics profiles of shrimp muscle to a large extent. Furthermore, DALs, including CL 62:2, PC 38:3, and PE 34:9, could be considered as promising biomarkers to distinguish fresh and oxidation-treated shrimp products.

In Situ Quality Assessment of Dried Sea Cucumber (Stichopus japonicus) Oxidation Characteristics during Storage by iKnife Rapid Evaporative Ionization Mass Spectrometry

Sea cucumber (Stichopus japonicus) is one of the most luxurious and nutritious seafoods in Asia. It is always processed into dried products to prevent autolysis, but its quality is easily destructed during storage. Herein, an extremely simplified workflow was established for real-time and in situ quality assessment of dried sea cucumbers (DSCs) during storage based on the lipid oxidation characteristics using an intelligent surgical knife (iKnife) coupled with rapid evaporative ionization mass spectrometry (REIMS). The lipidomic phenotypes of DSCs at different storage times were acquired successfully, which were then processed by multivariate statistical analysis. The results showed that the discrepancy in the characteristic ions in different DSCs was significant (p < 0.05) with high R²(Y) and Q² values (0.975 and 0.986, respectively). The receiver operating characteristic curve revealed that the ions of m/z 739.5, m/z 831.5, m/z 847.6, and m/z 859.6 were the most specific and characteristic candidate biomarkers for quality assessment of DSCs during accelerated storage. Finally, this method was validated to be qualified in precision (RSD_intraday ≤ 9.65% and RSD_interday ≤ 9.36%). In conclusion, the results showed that the well-established iKnife-REIMS method was high-throughput, rapid, and reliable in the real-time quality assessment of DSCs.

Real-Time In Situ Screening of Omega-7 Phospholipids in Marine Biological Resources Using an iKnife-Rapid-Evaporative-Ionization-Mass-Spectrometry-Based Lipidomics Phenotype

Omega-7 (n-7) phospholipids were bioactive substances in marine animals. In this study, a fast lipidomics phenotyping approach for real-time in situ screening of n-7 phospholipids in five kinds of economic seafood, salmon, prawn, bluefin tuna, hairtail, and butterfish, was established using iKnife rapid evaporative ionization mass spectrometry (REIMS). The n-7 phospholipids were structurally characterized and quantitatively analyzed, and the profiles were statistically analyzed by multivariate recognition analysis. It indicated that the difference of n-7 phospholipids in seafood samples was significant (p < 0.05), with R²(cum) and Q²(cum) values of >0.9. The proportion of n-7 phospholipids in salmon was the highest (20.43%), followed by bluefin tuna, prawn, hairtail, and butterfish. The ions of m/z 742.54 (PC 16:1-18:1), 768.55 (PC 16:1-20:2), 697.48 (PE 16:1-18:1), and 699.48 (PE 16:1-18:0) were the main n-7 phospholipids. The effectiveness of iKnife REIMS was further verified by hydrophilic interaction chromatography mass spectrometry and gas chromatography. The results demonstrated that proposed iKnife REIMS was an excellent technique for front-line screening of n-7 phospholipids in a large variety of marine biological resources.

Ultrasound, infrared and its assisted technology, a promising tool in physical food processing: A review of recent developments

Traditional food processing techniques can no longer meet the ever increasing demand for high quality food across the globe due to its low process efficiency, high energy consumption and low product yield. This review article is focused on the mechanism and application of Infrared (IR) and ultrasound (US) technologies in physical processing of food. We herein present the individual use of IR and US (both mono-frequency and multi-frequency levels) as well as IR and US supported with other thermal and non-thermal technologies to improve their food processing performance. IR and US are recent thermal and non-thermal technologies which have now been successfully used in food industries to solve the demerits of conventional processing technologies. These environmentally-friendly technologies are characterized by low energy consumption, reduced processing time, high mass-transfer rates, better nutrient retention, better product quality, less mechanical damage and improved shelf life. This work could be, with no doubt, useful to the scientific world and food industries by providing insights on recent advances in the use of US and IR technology, which can be applied to improve food processing technologies for better quality and safer products.

Impact of air-frying on the plasmalogens deterioration and oxidation in oyster revealed by mild acid hydrolysis and HILIC-MS-based lipidomics analysis

Oyster is rich in plasmalogens that are ether phospholipids with biological functions to human body. Air-frying is a popular technique for preparing delicious oyster but makes the plasmalogens vulnerable to oxidation. In this study, the effect of air-frying processing on plasmalogens oxidation was studied by lipidomic approach. Plasmalogens were always mixed with normal phospholipids, thus the lipid extract was treated with mild acid hydrolysis to rapidly degrade plasmalogens owing to the acid lability of vinyl ether linkage at sn-1 position. After hydrophilic interaction chromatography MS/MS analysis, there were three plasmalogen classes, plasmanylcholine, plasmanylethanolamine, and plasmanylinositol, completely separated, and each plasmalogen molecular species was identified and quantified. It indicated that the content of plasmalogens underwent an obvious decrease during the air-frying process. To weaken such effect, the influence of air-frying temperature was further inspected by multivariate statistical analyses. The main variables, including the ions of m/z 756.4927, 784.5486, 828.5812, etc., were revealed by unsupervised principle component analysis, supervised orthogonal partial least-square analysis, and variable importance in projection plot. As a conclusion, air-frying has health benefits in reducing fat content but destructive to plasmalogens, thus interventions are recommended to prevent the degradation of plasmalogens.

Differentiation between Fresh and Frozen-Thawed Meat using Rapid Evaporative Ionization Mass Spectrometry: The Case of Beef Muscle

An intelligent surgical knife (iKnife) coupled with rapid evaporative ionization mass spectrometry (REIMS) was employed for the lipidomic profiling of fresh and frozen-thawed beef muscle. The data were obtained by REIMS and then processed using multivariate statistical analysis methods including principal component analysis-linear discriminant analysis (PCA-LDA) and orthogonal partial least-squares discriminant analysis (OPLS-DA). The discrimination of fresh and frozen-thawed meat has been achieved, and the real-time identification accuracy was 92-100%. Changes in the composition and content of fatty acids and phospholipids were statistically analyzed by OPLS-DA, and the ions of m/z 279.2317, m/z 681.4830, and m/z 697.4882 were selected as differential compounds/metabolites. The developed method was also successfully applied in the discrimination of fresh and frozen-thawed meat samples. These results showed that REIMS as a high-throughput, rapid, and real-time mass spectrometry detection technology can be used for the identification of fresh and frozen-thawed meat samples.

In situ and real-time authentication of Thunnus species by iKnife rapid evaporative ionization mass spectrometry based lipidomics without sample pretreatment

Tuna adulteration and mislabeling are serious problem worldwide and have caused economic loss and consumer rights violation. In this study, an electrometric knife (iKnife) coupling rapid evaporative ionization mass spectrometry (REIMS) and a multivariate recognition model were developed and employed for in situ and real-time authentication of four tuna species without sample preparation. The results showed that the lipidomic profiles were successfully acquired and the differences in fatty acids and phospholipids were statistically analyzed to be significant (p < 0.05). The model displayed the superb classification accuracy (>93%) and validation (R²(Y) = 0.992, Q² = 0.986), and the main contributors of m/z 817.64, m/z 809.68, etc. were screened out to be used as potential biomarkers. Based on this technique, the identity of blind tuna samples could be unambiguously authenticated with the results displayed on a monitor screen directly. This study provided a front-line rapid detection method to prove the authenticity of tuna species.

Electric Soldering Iron Ionization Mass Spectrometry Based Lipidomics for in Situ Monitoring Fish Oil Oxidation Characteristics during Storage

An electric soldering iron ion source (ESII) coupling with rapid evaporative ionization mass spectrometry (REIMS) was developed and used for in situ monitoring the dynamic variation trend in oxidation characteristics of fish oil during storage. The lipidomics profiles of fish oil stored at various days were acquired by ESII-REIMS. The fatty acid and triacylglycerol species were structurally identified, and their abundances were analyzed according to multivariate statistical models mainly including principle component analysis as well as orthogonal partial least-squares analysis. On the shared and unique structure plot, the ions of m/z 255.23, 281.24, 877.72, and 901.72 displayed the most significant variation among the oxidized fish oil samples. Based on receiver operating characteristic curve analysis with an optimal Youden index of 0.91, these markers were further verified. The variation of viscosity and volatiles were also evaluated to further verify the oxidation characteristics of fish oil. The study demonstrated that ESII-REIMS technology used as an advanced detection method could ensure fish oil quality during storage.

Real-Time Monitoring of the Oxidation Characteristics of Antarctic Krill Oil (Euphausia superba) during Storage by Electric Soldering Iron Ionization Mass Spectrometry-Based Lipidomics

Antarctic krill oil (AKO) is susceptible to oxidation due to the high unsaturation degree of bioactive substances. Herein, a lipidomics method for in situ monitoring of the dynamic oxidation characteristics in AKO was explored based on electric soldering iron ion source (ESII) coupling with rapid evaporative ionization mass spectrometry (REIMS). The lipidomics profiles of AKO at different storage periods were successfully acquired. On the basis of principal component analysis and orthogonal partial least-squares analysis, the obtained REIMS data were employed to build a multivariate recognition model. The ions of m/z 707.50, 721.50, 833.49, and 837.54 contributed the most significant effect on the multivariate data model for the authentication of different AKO samples. Besides, the variation of viscosity, astaxanthin, and volatile compounds were also evaluated to corroborate the oxidation characteristics. The results indicated that the ESII-REIMS technology could be applied as an advanced rapid detection method to secure oil and fat quality during storage.