Recent progress in food flavor analysis using gas chromatography–ion mobility spectrometry (GC–IMS)

Influence of Frying Methods on Quality Characteristics and Volatile Flavor Compounds of Giant Salamander (Andrias davidianus) Meatballs

Effects of deep fat frying and hot air frying on texture, color difference, sensory score, yield, fat content, and volatile flavor compounds of giant salamander meatballs before and after frying were investigated. The results showed that, compared with the deep fat frying group, hot air-fried giant salamander meatballs had higher hardness, elasticity, and L ${}^{\ast }$ ( $p<0.05$ ), but lower a ${}^{\ast }$ , b ${}^{\ast }$ value, fat content, and yield ( $p<0.05$ ). There was little distinction in sensory score, cohesiveness, and chewiness between the two frying methods ( $p>0.05$ ). Gas chromatography ion migration chromatography (GC-IMS) was used for flavor compound analysis, and 50 flavor compounds were analyzed, containing 22 aldehydes, 11 ketones, 6 olefins, 4 acids, 3 esters, 3 alcohols, and 1 phenol. Compared with the samples before frying, the relative contents of aldehydes and ketones of fried giant salamander meatballs increased significantly, while the relative contents of esters and alkenes decreased significantly. Principal component analysis showed that the GC-IMS spectra of volatile flavor compounds before and after deep fat frying and hot air frying varied greatly, and the cumulative contribution rate of the two principal components reached 86.1%, indicating that the GC-IMS technology might be used to distinguish giant salamander meatballs before and after frying, or with different frying methods. These results may offer a note for development and quality control of the precooked giant salamander meatballs in the future.

Volatile Profile and Biosynthesis of Post-harvest Apples are Affected by the Mechanical Damage

Mechanical damage to fruit causes flavor changes during post-harvest supply chains. It is important to identify the main volatiles and explore their biosynthesis mechanism. In this study, the volatile changes in apples caused by mechanical damage were analyzed by gas chromatography-ion mobility spectrometry. Hexanal and ethyl acetate were accumulated and identified as potential volatile biomarkers to detect damaged apples. The study on the lipoxygenase (LOX) pathway and transcription factors (TFs) shows that mechanical damage up-regulated the expression of MdLOX-like, MdLOX3b, MdLOX7b, MdLOX7c, MdLOX2a, and MdAAT in the LOX pathway and that of one MYB TF (MdMYB-like), five ERF TFs (MdERF073, MdERF003, MdERF114, MdERF15, and MdERF2), and five WRKY TFs (MdWRKY23, MdWRKY17, MdWRKY46, MdWRKY48, and MdWRKY71). Notably, MdAAT was significantly correlated to MdMYB-like, MdWRKY23, MdWRKY71, MdERF15, and MdERF2. Thus, TFs may attribute to the accumulation of hexanal and ethyl acetate by regulating the expression of LOX pathway-related genes.

Monoterpenes: current knowledge on food source, metabolism, and health effects

Monoterpenes, volatile metabolites produced by plants, are involved in the taste and aroma perception of fruits and vegetables and have been used for centuries in gastronomy, as food preservatives and for therapeutic purposes. Biological activities such as antimicrobial, analgesic and anti-inflammatory are well-established for some of these molecules. More recently, the ability of monoterpenes to regulate energy metabolism, and exert antidiabetic, anti-obesity and gut microbiota modulation activities have been described. Despite their promising health effects, the lack of reliable quantification of monoterpenes in food, hindered the investigation of their role as dietary bioactive compounds in epidemiological studies. Moreover, only few studies have documented the biotransformation of these compounds and identified the monoterpene metabolites with biological activity. This review presents up-to-date knowledge about the occurrence of monoterpenes in food, their bioavailability and potential role in the modulation of intermediate metabolism and inflammation, focusing on novel findings of molecular mechanisms, underlining research gaps and new avenues to be explored.

Evaluation of volatile metabolites as potential markers to predict naturally-aged seed vigour by coupling rapid analytical profiling techniques with chemometrics

Rapid volatile detection methods for seed vigour rely heavily on artificial ageing (AA), however the comparability of volatile organic compounds (VOCs) to natural ageing (NA) and practicability of the detection models were not well known. In this study, VOCs between AA and NA sweet corn seeds were compared and Partial Least Squares Regression (PLS-R) modelswere constructed based on AA to predict the seed vigour of NA. A total of 33 VOCs were identified, among which aldehydes showed the highest consistency between NA and AA. Furthermore, a AS-PLS-R model with variable importance in projection (VIP > 1) and Pearson Correlation Coefficient (r > 0.9) algorithms, which was built on 3 volatile markers: benzaldehyde monomer, n-nonanal, 1-butanol monomer, achieved the best performance (R²p of 0.901 and RMSEP of 0.050). Therefore, coupling Gas Chromatography- Ion Mobility Spectrometry (GC-IMS) with chemometrics can be an effective way to monitor and predict stored seeds vigour.

Behavioral responses of Platycladus orientalis plant volatiles to Phloeosinus aubei by GC-MS and HS-GC-IMS for discrimination of different invasive severity

In recent years, the invasive cypress bark beetle (Phloeosinus aubei) has caused extensive damage to Platycladus orientalis plants in China, but its infestation is hard to monitor in the early stages. In this study, gas chromatography-mass spectrometry (GC-MS) was initially employed to investigate the volatile organic compound (VOC) emissions of P. aubei-infested P. orientalis saplings. The emissions of total sesquiterpenes were dominating (84-86% of total VOCs) and increased by 3.09-fold in P. aubei-damaged P. orientalis samples compared to undamaged samples, and the monoterpenes, aromatic compounds, and ketone emissions also had varying degrees of increase between 1.39-fold and 5.65-fold. Based on this variation, gas chromatography-ion mobility spectrometry (GC-IMS) was applied, as an untargeted analytical approach, to discriminate P. orientalis samples with different invasive severity. Two different features derived from GC-IMS data were adopted as the input information for classification and prediction models. Results showed that grid search support vector machine (GS-SVM) combined with multilinear principal component analysis (MPCA) based on spectral fingerprint achieved the best classification performances (> 88.98%), and partial least squares discriminant analysis (PLSR) method can accurately predict the pest numbers (R² > 0.9423 and RMSE < 0.9827). In a word, the VOC profiling-based approach had the potential for evaluating P. aubei invasive severity and pest management.

Effects of different cooking methods on volatile flavor compounds of chicken breast

Chicken is one of the highest selling meats worldwide. Different cooking methods produce various flavor compounds in cooked chicken, which affect consumers' food choices. In this study, the volatile flavor components of Gushi chicken breast after stewing and air frying were detected using gas chromatography-ion mobility chromatography (GC-IMS) and principal component analysis (PCA), and the relative odor activity value (ROAV) was determined using PCA. A total of 43 volatile substances were identified. 3-(methylthio)propionaldehyde-M and benzene acetaldehyde can be used as characteristic flavor markers in the air-fried chicken breast.ethyl acetate, (E)-2-octenal-D, and 2-ethyl-1-hexanol-D can be used as characteristic flavor markers in the stewed chicken breast. Because these five substances have the most obvious contrast in the fingerprint. The following part describes the specific substances that have mainly contributed to the flavor system in the volatile system obtained by different cooking methods. Finally, the main flavor compounds of the stewed chicken breast were 3-methylbutanal-D, octanal-D, (E)-2-nonenal, and other 11 types of compounds (ROAV ≥1). Nine types of compounds (ROAV ≥1), including 3-methylbutanal-D, (E)-2-nonenal-M octanal-M, and hexanal-M, were the main compounds to characterize the air-fried chicken breast. PRACTICAL APPLICATIONS: GC-IMS technology combined with the principal component analysis of ROAV can be used to rapidly identify the main flavor substances and the flavor substances having an important role in modifying the overall taste of the sample. It plays a considerably important role in the aroma recombination of substances and can play a role in food processing.

Volatile organic compounds sensing based on Bennet doubler-inspired triboelectric nanogenerator and machine learning-assisted ion mobility analysis

Ion mobility analysis is a well-known analytical technique for identifying gas-phase compounds in fast-response gas-monitoring systems. However, the conventional plasma discharge system is bulky, operates at a high temperature, and inappropriate for volatile organic compounds (VOCs) concentration detection. Therefore, we report a machine learning (ML)-enhanced ion mobility analyzer with a triboelectric-based ionizer, which offers good ion mobility selectivity and VOC recognition ability with a small-sized device and non-strict operating environment. Based on the charge accumulation mechanism, a multi-switched manipulation triboelectric nanogenerator (SM-TENG) can provide a direct current (DC) bias at the order of a few hundred, which can be further leveraged as the power source to obtain a unique and repeatable discharge characteristic of different VOCs, and their mixtures, with a special tip-plate electrode configuration. Aiming to tackle the grand challenge in the detection of multiple VOCs, the ML-enhanced ion mobility analysis method was successfully demonstrated by extracting specific features automatically from ion mobility spectrometry data with ML algorithms, which significantly enhance the detection ability of the SM-TENG based VOC analyzer, showing a portable real-time VOC monitoring solution with rapid response and low power consumption for future internet of things based environmental monitoring applications.

Microwave pretreatment of camellia (Camellia oleifera Abel.) seeds: Effect on oil flavor

Microwave is a new pretreatment technology, and microwave processing time of camellia seeds is a factor affecting the flavor of camellia seed oil (CSO). Therefore, this study on the characteristic volatile compounds of CSO from microwaved seeds with different processing time was carried out by electronic nose (E-nose), headspace-solid phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS) and headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS). The results of E-nose show that W1W, W2W and W5S were the main sensors to distinguish the flavor profile of CSOs. Through HS-SPME-GC-MS and odor activity value analysis, 80 volatile compounds were detected and 22 key aroma compounds were screened in CSOs. Compared with HS-SPME-GC-MS, 44 volatile compounds were detected by HS-GC-IMS, including 9 identical compounds and 35 different compounds. In general, the volatile compounds of 0, 2 and 3 min CSOs were mainly alcohols and esters, while the 4, 5 and 6 min CSOs were mainly heterocycles and aldehydes.

Aroma characteristics of traditional Huangjiu produced around Winter Solstice revealed by sensory evaluation, gas chromatography-mass spectrometry and gas chromatography-ion mobility spectrometry

Traditional Huangjiu (a kind of traditional Chinese rice wine) produced around Winter Solstice has higher quality and a more harmonious aroma than those produced during other periods. To determine the specific differences in aroma characteristics, sensory evaluation, gas chromatography-mass spectrometry (GC-MS) and gas chromatography-ion mobility spectrometry (GC-IMS) were used to analyze the volatile profiles of the traditional Huangjiu samples produced under different ambient temperature conditions. The sensory evaluation results showed that the aroma attributes of wheat, sweet, ester, alcoholic and sauce were stronger for the samples fermented near Winter Solstice than those for the other samples. GC-MS combined with heatmap analysis showed that with the decrease in average ambient temperature, the contents of esters such as diethyl succinate and ethyl butanoate gradually increased, and the contents of alcohols such as phenylethyl alcohol, 2-methylpropanol and 3-methylbutanol gradually decreased. Some key aroma compounds, such as ethyl butyrate (OAV: 97-151), nonanal (OAV: 189-200), ethyl octanoate (OAV: 859-1134) and ethyl phenylacetate (OAV: 307-353), were more abundant in the samples fermented near Winter Solstice than the other samples. The visualization of GC-IMS suggested that isoamyl acetate, 2-methylpropyl acetate, ethyl 3-methylbutyrate, and ethyl 2-methylbutanoate were enriched near Winter Solstice. Together, the results suggested that the traditional Huangjiu produced around Winter Solstice contained more flavor volatiles and had better aroma quality than those produced during other periods.

Metabolic footprint analysis of volatile metabolites by gas chromatography-ion mobility spectrometry to discriminate between different fermentation temperatures during Streptococcus thermophilus milk fermentation

Streptococcus thermophilus is widely used in the dairy industry to produce fermented milk. Gas chromatography-ion mobility spectrometry-based metabolomics was used to discriminate different fermentation temperatures (37°C and 42°C) at 3 time points (F0: pH = 6.50 ± 0.02; F1: pH = 5.20 ± 0.02; F2: pH = 4.60 ± 0.02) during S. thermophilus milk fermentation, and differences of fermentation physical properties and growth curves were also evaluated. Fermentation was completed (pH 4.60) after 6 h at 42°C and after 8 h at 37°C; there were no significant differences in viable cell counts and titratable acidity; water-holding capacity and viscosity were higher at 37°C than at 42°C. Different fermentation temperatures affected volatile metabolic profiles. After the fermentation was completed, the volatile metabolites that could be used to distinguish the fermentation temperature were hexanal, butyraldehyde, ethyl acetate, ethanol, 3-methylbutanal, 3-methylbutanoic acid, and 2-methylpropionic acid. Specifically, at 37°C of milk fermentation, branched-chain AA had higher levels, and leucine, isoleucine, and valine were involved in growth and metabolism, which promoted accumulation of some short-chain fatty acids such as 3-methylbutanoic acid and 2-methylpanprooic acid. At 42°C, at 3 different time points during fermentation, ethanol from glycolysis all presented higher levels, including acetone and 3-methylbutanal, producing a more pleasant flavor in the fermented milk. This work provides detailed insight into S. thermophilus fermented milk metabolites that differed between incubation temperatures; these data can be used for understanding and eventually predicting metabolic changes during milk fermentation.

Geographical origin identification of two salmonid species via flavor compound analysis using headspace-gas chromatography-ion mobility spectrometry combined with electronic nose and tongue

The flavor of salmonids is affected by species and origin. Sources of salmonid fish fillets are complex and difficult to identify and label fraud occasionally occurs in the market. In this study, headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS), electronic nose, electronic tongue and amino acid detection technologies were used to analyze flavor compounds in two salmonid species from different geographical origins. Fingerprints of volatile compounds of salmonid were constructed using HS-GC-IMS technology. Free amino acid (FAA) content differed in salmonids from different geographical origins. Regarding salmonid odor, HS-GC-IMS analysis results were basically consistent with those of the electronic nose. Regarding taste, the conclusions drawn from the electronic tongue were consistent with the amino acid test results. Therefore, our results demonstrate that flavor compounds can be used to distinguish salmonids from different geographical origins, providing a new dimension to food safety and authenticity. Furthermore, HS-GC-IMS, electronic nose and tongue can be used as tools in the market to identify food fraud.

Nitrogen monoxide as dopant for enhanced selectivity of isomeric monoterpenes in drift tube ion mobility spectrometry with 3H ionization

The ion mobility spectra of the isomeric monoterpenes α-pinene, β-pinene, myrcene, and limonene in drift tube ion mobility spectrometry (IMS) with ³H radioactive ionization are highly similar and difficult to distinguish. The aim of this work was to enhance the selectivity of IMS by the addition of nitrogen monoxide (NO) as dopant and to investigate the underlying changes in ion formation responsible for the modified ion signals observed in the ion mobility spectra. Even though ³H-based-IMS systems have been used in hyphenation with gas chromatography (GC) for profiling of volatile organic compounds (VOCs), the investigation of ion formation still remains challenging and was exemplified by the investigated monoterpenes. Nonetheless, the formation of monomeric, dimeric, and trimeric ion clusters could be tentatively confirmed by a mass-to-mobility correlation and the highly similar pattern of ion signals in the monomer region was attributed to isomerization mechanisms potentially occurring after proton transfer reactions. The addition of NO as dopant could finally lead to the formation of additional product ions and increased the selectivity of IMS for the investigated monoterpenes as confirmed by principal component analysis (PCA). The discrimination of monoterpenes in the volatile profile is highly relevant in the quality control of hops and was given as the example for application. The results indicate that additional product ions were obtained by the formation of NO⁺ adduct ions, next to hydride abstraction, charge transfer, or fragmentation reactions. This approach can potentially leverage selectivity issues in VOC profiling of complex matrices, such as food matrices or raw materials in combination with chemometric pattern recognition techniques.

Recent trends in the chromatographic analysis of volatile flavor and fragrance compounds: Annual review 2020

The chromatographic analysis of volatile flavor and fragrance compounds is performed routinely in several industries and in many fields of scientific research. Typical applications include food-, environmental-, essential oil- and cosmetics analysis. Even though the analysis of flavors and fragrances have become increasingly standardized during the past decade, there are still a large variety of techniques that can be used for their extraction, chemical analysis, and sensory analysis. Moreover, there are certain less commonly used techniques that are now being used with increased frequency and that are showing the potential of being used as alternatives to the existing standard techniques. In this annual review, the techniques that were most commonly used in 2020 for the investigation of these volatile compounds are discussed. In addition, a number of emerging trends are discussed, notably the use of solvent assisted flavor evaporation (SAFE) for extraction, GC ion mobility spectrometry (IMS) for volatile compound analysis and electronic senses, that is, E-noses and E-tongues, for sensory analysis. Miscellaneous hyphenated techniques, advances in stationary phase chemistry and a number of interesting applications are also highlighted.

Volatile-Based Prediction of Sauvignon Blanc Quality Gradings with Static Headspace-Gas Chromatography-Ion Mobility Spectrometry (SHS-GC-IMS) and Interpretable Machine Learning Techniques

The analytical scope of static headspace-gas chromatography-ion mobility spectrometry (SHS-GC-IMS) was applied to wine aroma analysis for the first time. The method parameters were first fine-tuned to achieve optimal analytical results, before the method stability was demonstrated, in terms of repeatability and reproducibility. Succinct qualitative identification of compounds was also realized, with the identification of several volatiles that have seldom been described previously in Sauvignon Blanc wine, such as methyl acetate, ethyl formate, and amyl acetate. Using the SHS-GC-IMS data in an untargeted approach, computer modeling of large datasets was applied to link aroma chemistry via prediction models to wine sensory quality gradings. Six machine learning models were compared, and artificial neural network (ANN) returned the most promising performance with a prediction accuracy of 95.4%. Despite its inherent complexity, the ANN model offered intriguing insights on the influential volatiles that correlated well with higher and lower sensory gradings. These findings could, in the future, guide winemakers in establishing wine quality, particularly during blending operations prior to bottling.

Effect of dielectric barrier discharge cold plasma treatments on flavor fingerprints of brown rice

A non-thermal processing method was developed to promote preservation of brown rice using dielectric barrier discharge cold plasma (DBD-CP). Physicochemical properties including free fatty acid (FFA) content, surface color change, volatile organic components (VOCs) and flavor fingerprints were evaluated in brown rice submitted to DBD-CP. FFA levels were 25.2% lower in treated samples compared to the control, and a more stable surface color was obtained at the end of the storage period. A total of 35 major VOCs could be detected in treated samples, and reduced levels of hexanal can be used as an indicator of DBD-CP treatment in brown rice during storage. Moreover, the flavor fingerprints in DBD-CP treated groups can be successfully distinguished through headspace gas chromatography ion mobility spectrometry. Collectively, application of DBD-CP treatment could be utilized as a feasible approach to promote stabilization of brown rice and preserve flavor during storage.

Food safety and quality assessment: comprehensive review and recent trends in the applications of ion mobility spectrometry (IMS)

Ion mobility spectrometry (IMS) is an analytical separation and diagnostic technique that is simple and sensitive and a rapid response and low-priced technique for detecting trace levels of chemical compounds in different matrices. Chemical agents and environmental contaminants are successfully detected by IMS and have been recently considered to employ in food safety. In addition, IMS uses stand-alone or coupled analytical diagnostic tools with chromatographic and spectroscopic methods. Scientific publications show that IMS has been applied 21% in the pharmaceutical industry, 9% in environmental studies and 13% in quality control and food safety. Nevertheless, applications of IMS in food safety and quality analysis have not been adequately explored. This review presents the IMS-related analysis and focuses on the application of IMS in food safety and quality. This review presents the important topics including detection of traces of chemicals, rate of food spoilage and freshness, food adulteration and authenticity as well as natural toxins, pesticides, herbicides, fungicides, veterinary, and growth promoter drug residues. Further, persistent organic pollutants (POPs), acrylamide, polycyclic aromatic hydrocarbon (PAH), biogenic amines, nitrosamine, furfural, phenolic compounds, heavy metals, food packaging materials, melamine, and food additives were also examined for the first time. Therefore, it is logical to predict that the application of the IMS technique in food safety, food quality, and contaminant analysis will be impressively increased in the future. HighlightsCurrent status of IMS for residues and contaminant detection in food safety.To assess all the detected contaminants in food safety, for the first time.Identified IMS-related parameters and chemical compounds in food safety control.

Evaluating the Authenticity of the Raw-Milk Cheese Fontina (PDO) with Respect to Similar Cheeses

The implementation of quality assurance schemes for the assessment of PDO food authenticity is an issue involving manufacturers, traders, retailers and consumers. In this respect, reliable analytical methods are needed to integrate paper-trailing information. The feasibility of distinguishing the Italian Fontina PDO cheese from the generic Fontal cheese was preliminarily evaluated on a set of commercial samples by measuring selected parameters (pH, alkaline phosphatase activity, content of copper, volatiles, extent of proteolysis) related to the different manufacturing processes. The relative profile of free amino acids proved to be a promising tool. A new set of 41 samples of Fontina PDO cheese was collected at representative dairies within the recognized production area and analyzed for free amino acids. A chemometric model of Fontina PDO cheese was built based on the mean content and standard deviation of 15 free amino acids. On this basis, all of the PDO samples were correctly identified, whereas all of the Fontal cheeses were recognized as different cheeses.

Characterization of volatile compounds in differently coloured Chenopodium quinoa seeds before and after cooking by headspace-gas chromatography-ion mobility spectrometry

Aroma is an important feature of quinoa that influences consumer preferences. Differently coloured quinoa seeds exhibit diverse nutritional characteristics; however, their aromatic profile differences are poorly investigated. The volatile components of 11 quinoa samples were characterized by headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS). A total of 120 peaks were detected, with 61 compounds identified. White quinoa liberated a high concentration of volatiles with grass (n-hexanol) and green ((E)-2-octenal, (E)-2-heptenal, etc.) aromas before and after cooking, respectively. Raw flaxen samples uniquely released a caramel compound (cyclotene) and exhibited several sweet and caramel volatiles (decanal, 5-methyl-furfural, and 2-furfural) after cooking. Additionally, cooked black quinoa exerted more fruity substances (methyl hexanoate and phenylacetaldehyde). Orthogonal partial least square discriminant analysis clearly distinguished the samples before and after cooking and differentiated the seeds into different colours. The results confirm the potential of HS-GC-IMS to evaluate volatiles in quinoa and are meaningful for quinoa consumption.

A Comparison of Various Algorithms for Classification of Food Scents Measured with an Ion Mobility Spectrometry

The present aim was to compare the accuracy of several algorithms in classifying data collected from food scent samples. Measurements using an electronic nose (eNose) can be used for classification of different scents. An eNose was used to measure scent samples from seven food scent sources, both from an open plate and a sealed jar. The k-Nearest Neighbour (k-NN) classifier provides reasonable accuracy under certain conditions and uses traditionally the Euclidean distance for measuring the similarity of samples. Therefore, it was used as a baseline distance metric for the k-NN in this paper. Its classification accuracy was compared with the accuracies of the k-NN with 66 alternative distance metrics. In addition, 18 other classifiers were tested with raw eNose data. For each classifier various parameter settings were tried and compared. Overall, 304 different classifier variations were tested, which differed from each other in at least one parameter value. The results showed that Quadratic Discriminant Analysis, MLPClassifier, C-Support Vector Classification (SVC), and several different single hidden layer Neural Networks yielded lower misclassification rates applied to the raw data than k-NN with Euclidean distance. Both MLP Classifiers and SVC yielded misclassification rates of less than 3% when applied to raw data. Furthermore, when applied both to the raw data and the data preprocessed by principal component analysis that explained at least 95% or 99% of the total variance in the raw data, Quadratic Discriminant Analysis outperformed the other classifiers. The findings of this study can be used for further algorithm development. They can also be used, for example, to improve the estimation of storage times of fruit.

Aroma release during wine consumption: Factors and analytical approaches

During wine consumption, aroma compounds are released from the wine matrix and are transported to the olfactory receptor in vivo, leading to retronasal perception which can affect consumer acceptance. During this process, in addition to the influence of the wine matrix compositions, some physiological factors can significantly influence aroma release leading to altered concentrations of the aroma compounds that reach the receptors. Therefore, this review is focused on the impact of multiple factors, including the physiology and wine matrix, on the aroma released during wine tasting. Moreover, to reflect the pattern of volatiles that reach the olfactory receptors during wine consumption, some analytical approaches have been described for in vitro and in vivo conditions.

Role of lactic acid bacteria in flavor development in traditional Chinese fermented foods: A review

Traditional Chinese fermented foods are favored by consumers due to their unique flavor, texture and nutritional values. A large number of microorganisms participate in the process of fermentation, especially lactic acid bacteria (LAB), which are present in almost all fermented foods and contribute to flavor development. The formation process of flavor is complex and involves the biochemical conversion of various food components. It is very important to fully understand the conversion process to direct the flavor formation in foods. A comprehensive link between the LAB community and the flavor formation in traditional Chinese fermented foods is reviewed. The main mechanisms involved in the flavor formation dominated by LAB are carbohydrate metabolism, proteolysis and amino acid catabolism, and lipolysis and fatty acid metabolism. This review highlights some useful novel approaches for flavor enhancement, including the application of functional starter cultures and metabolic engineering, which may provide significant advances toward improving the flavor of fermented foods for a promising market.

Analytical Tools for Disease Diagnosis in Animals via Fecal Volatilome

Volatilome analysis is growing in attention for the diagnosis of diseases in animals and humans. In particular, volatilome analysis in fecal samples is starting to be proposed as a fast, easy and noninvasive method for disease diagnosis. Volatilome comprises volatile organic compounds (VOCs), which are produced during both physiological and patho-physiological processes. Thus, VOCs from a pathological condition often differ from those of a healthy state and therefore the VOCs profile can be used in the detection of some diseases. Due to their strengths and advantages, feces are currently being used to obtain information related to health status in animals. However, they are complex samples, that can present problems for some analytical techniques and require special consideration in their use and preparation before analysis. This situation demands an effort to clarify which analytic options are currently being used in the research context to analyze the possibilities these offer, with the final objectives of contributing to develop a standardized methodology and to exploit feces potential as a diagnostic matrix. The current work reviews the studies focused on the diagnosis of animal diseases through fecal volatilome in order to evaluate the analytical methods used and their advantages and limitations. The alternatives found in the literature for sampling, storage, sample pretreatment, measurement and data treatment have been summarized, considering all the steps involved in the analytical process.

Targeted versus Nontargeted Green Strategies Based on Headspace-Gas Chromatography-Ion Mobility Spectrometry Combined with Chemometrics for Rapid Detection of Fungal Contamination on Wheat Kernels

Conventional methods for detecting fungal contamination are generally time-consuming and sample-destructive, making them impossible for large-scale nondestructive detection and real-time analysis. Therefore, the potential of headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) was examined for the rapid determination of fungal infection on wheat samples in a rapid and nondestructive manner. In addition, the validation experiment of detecting the percent A. flavus infection presented in simulated field samples was carried out. Because the dual separation of HS-GC-IMS could generate massive amounts of three-dimensional data, proper chemometric processing was required. In this study, two chemometric strategies including: (i) nontargeted spectral fingerprinting and (ii) targeted specific markers were introduced to evaluate the performances of classification and prediction models. Results showed that satisfying results for the differentiation of fungal species were obtained based on both strategies (>80%) by the genetic algorithm optimized support vector machine (GA-SVM), and better values were obtained based on the first strategy (100%). Likewise, the GA-SVM model based on the first strategy achieved the best prediction performances (R² = 0.979-0.998) of colony counts in fungal infected samples. The results of validation experiment showed that GA-SVM models based on the first strategy could still provide satisfactory classification (86.67%) and prediction (R² = 0.889) performances for percent A. flavus infection presented in simulated field samples at day 4. This study indicated the feasibility of HS-GC-IMS-based approaches for the early detection of fungal contamination in wheat kernels.

Gas chromatographic-ion mobility spectrometry combined with a multivariate analysis model exploring the characteristic changes of odor components during the processing of black sesame

Black sesame (Sesamum indicum L.) is a Chinese dietary herb that has been widely used in the medical and healthcare fields in China. According to the theory of Traditional Chinese medicine processing, reasonable processing (steaming and drying many times) can increase the tonic effect and reduce the adverse factors generated during long-term use. At present, the processing degree of black sesame is mainly judged based on subjective experience. However, due to the lack of objective and quantitative control indicators, quality fluctuations easily occur. Therefore, for better application, its processing technology needs scientific monitoring methods. Herein a gas chromatography-ion mobility spectrometry (GC-IMS) technique was applied as a monitoring method to differentiate the processed products of black sesame in different processing stages. The response data of volatile components obtained from the samples were processed by the built-in data processing software in the instrument to identify the different components for further principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA). From fingerprint comparison, 70 differential signal peaks were screened, 32 of which were qualitatively identified, mainly monomers and dimers of 20 compounds. On this basis, the PCA model shows that there was a significant difference between the raw product (S1) and the processed products (H1-9); moreover, there was a certain correlation between the differential changes of samples in different processing stages (H1-9) and the processing times. The OPLS-DA model specifically shows the differential components in the processing with potential characteristics peaks of 41, 105, n-nonanal, 2 and ethanol can discriminate whether the BS has undergone the first processed. And the dynamic changes of the three characteristic peaks of 1-hexanol, acetic acid and 107 can determine the specific degree of processing of BS. The research proves that GC-IMS combined with a multivariate analysis model can provide scientific data for identifying the characteristic odor components of black sesame.

Evolution of VOC and Sensory Characteristics of Stracciatella Cheese as Affected by Different Preservatives

Undesired volatile organic compounds (VOCs) can negatively affect the flavor of fresh food products; especially those characterized by a mild and delicate aroma. Finding connections between chemical and sensory analyses is a useful way to better understand the arising of off-flavors. A study was conducted on stracciatella; a traditional Italian cream cheese that is emerging on international markets. Samples were prepared by adding two different preservatives (alone or combined): sorbic acid and an olive leaf extract. Their influence on flavor preservation during refrigerated storage was investigated by chemical, microbiological and sensory analyses. A strong change of the VOC profile was ascertained after 8 days in the control cheese and in the sample added with leaf extract alone. The samples containing sorbic acid, alone or in combination with leaf extract, gave the best chemical and sensory results, demonstrating a significant shelf-life extension. In particular, these samples had lower concentrations of undesired metabolites, such as organic acids and volatiles responsible for off-flavor, and received better scores for odor and taste. Ex and Ex-So samples had significantly higher antioxidant activity than Ctr and So throughout the entire storage period, and the color parameter shows no differences among samples taken on the same day. The use of the olive leaf extract, at the concentration tested, seemed to be interesting only in the presence of sorbic acid due to possible synergic effect that mainly acted against Enterobacteriaceae.

The Role of the Bacterial Community in Producing a Peculiar Smell in Chinese Fermented Sour Soup

In this paper, the volatile flavour constituents and the bacterial diversity in characteristic Chinese fermented sour soup were analysed, and the dynamics of bacteria associated with the odour were characterized. The bacterial diversity of sour soup was studied by high-throughput sequencing. A total of 10 phyla and 89 genera were detected. Firmicutes was the dominant phylum of sour soup, accounting for 87.14-98.57%. The genus structure of normal sour soup was relatively simple, and Lactobacillus (78.05-90.26%) was the dominant genus. In addition to Lactobacillus, the foul-smelling sour soup contained more Pediococcus spp., Caproiciproducens spp., and Clostridium-sensu-stricto12 spp. (relative abundance >1%) than the normal sour soup. A total of 51 aroma compounds were detected by gas chromatography-mass spectrometry(GC-IMS), including 25 esters, 8 terpenes, 8 alcohols, 3 sulfur compounds, 2 acids, 2 ketones, 1 pyrazine, 1 monoterpene and 1 aldehyde. According to the relative odour active value (ROAV) calculation, 51 important flavour-contributing substances and 7 flavour-coordinating substances were determined. The esters with the highest relative percentages and ROAV values provided the pleasant flavour of the sour soup. In the foul-smelling sour soup, the ROAV values of 1,8-cineole, isobutyl acetate, ethyl butanoate, ethyl octanoate-M, and ethyl hexanoate-M decreased, while those of diallyl disulfide-M and diallyl disulfide-D, which were probably responsible for the foul flavour, increased. Through Pearson correlation analysis, the odour production of the foul-smelling soup was determined to be related to Pediococcus spp., Caproiciproducens spp., Clostridiumsensu_stricto_12 spp., Oscillibacter spp., Bacteroides spp., Fibaculaceae_unclassified spp., Acinetobacter spp. and Halomonas spp.