Application of untargeted volatile profiling and data driven approaches in wine flavoromics research

Drying methods affected the fatty acids oxidation and bacterial community of traditional dry-cured ducks during processing and its relation with the aroma formation

The formation of volatile compounds in dry-cured ducks produced by hot and cold air circular drying (HCAD), hot air drying (HAD), and traditional sun drying (TSD) were analyzed by E-nose and GC-MS. The HCAD exhibited higher alcohols, aldehydes, esters, and furans than that of the other two. Six, five, and three key compounds were identified by OAV in HCAD, HAD, and TSD, respectively. Nonanal was the highest relative content of aldehydes in all groups. (E)-2-octenal was detected only in HCAD. HAD accelerated the oxidation of fatty acids. The POV and AV of HAD were 0.24 g/100 g and 2.02 mg/g when stored for 15 days, which were higher than that of HCAD and TSD. Proteobacteria, Actinobacteriota and Firmicutes were the most abundant phylum, Psychrobacter, Kocuria, and Macrococcus were the primary dominant genus. The hightest abundance of Firmicutes and Macrococcus in the HCAD-15d might contribute to the aroma formation. HCAD showed a better quality and flavor than TSD and HAD, indicating it is an innovative method for producing dry-cured duck.

A comparative study to determine the key aroma components of yogurt aroma types based on Sensomics and Flavoromics

This study used Sensomics to examine four previously obtained yogurt aroma type profiles. 14 key aroma-active compounds were identified as significant contributors (p ≤ 0.05) in the four aroma types using gas chromatography-mass spectrometry-olfactometry (GC-MS/O), aroma extract dilution analysis (AEDA), odor activity values (OAV), and aroma recombination and omission experiments. The Sensomics and previous Flavoromics results were compared, showing that Flavoromics identified 10 indicator compounds for distinguishing aroma types. Eight were the same as the key aroma-active compounds identified via Sensomics, namely acetic acid, pentanoic acid, decanoic acid, 3-hydroxy-2-butanone, 2,3-pentanedione, acetaldehyde, δ-decalactone, and dimethyl sulfone. Sensomics revealed a prominent similarity between the categories of key aroma-active compounds of the four aroma types, with a higher sensory contribution. Flavoromics showed less overlapping between the indicator compounds, mainly related to the distinction between the four aroma types. Sensomics and Flavoromics serve distinct research objectives and should be selected according to the study subject.

From Traditional to Intelligent, A Review of Application and Progress of Sensory Analysis in Alcoholic Beverage Industry

Sensory analysis is an interdisciplinary field that combines multiple disciplines to analyze food qualitatively and quantitatively. At present, this analysis method has been widely used in product development, quality control, marketing, flavor analysis, safety supervision and inspection of alcoholic beverages. Due to the changing needs of analysis, new and more optimized methods are still emerging. Thereinto, intelligent and biometric technologies with growing attention have also been applied to sensory analysis. This work summarized the sensory analysis methods from three aspects, including traditional artificial sensory analysis, intelligent sensory technology, and innovative technologies. Meanwhile, the application sensory analysis in alcoholic beverages and its industrial production was scientifically emphasized. Moreover, the future tendency of sensory analysis in the alcoholic beverage industry is also highlights.

Flavoromics Analysis of Passion Fruit-Roasted Chicken

Currently, research on the flavor components and their dynamic changes in roasted chicken with a special flavor is rare. In this study, a passion fruit-roasted chicken was prepared, its characteristic flavor components were profiled by flavoromics, and their evolution patterns and precursors were determined. The results showed that the characteristic flavor component with the highest contribution rate was ethyl butyrate (50.44%). In particular, some unique flavor compounds were identified compared with other roasted chicken products available. The main volatile flavor components in all stages of processing were alcohols, esters, and hydrocarbons, 15 to 30 min of roasting is an important stage for establishing the aroma system, and at the end, hydrocarbons were the main volatile compounds. During the 30-day storage period, the characteristic flavor components included ethyl butyrate, ethyl maltol, β-caryophyllene, and guaiacene. In conclusion, passion fruit-roasted chicken contained many characteristic flavor components, which were mainly formed within 15 to 30 min of roasting and were basically stable during the 30-day storage period. In a word, this work prepared a novel roasted chicken and revealed its mechanism of flavor formation at different baking stages and storage periods, which provided references for industrial production.

Benchtop volatilomics supercharged: How machine learning based design of experiment helps optimizing untargeted GC-IMS gas phase metabolomics

Gas chromatography-ion mobility spectrometry (GC-IMS) plays a significant role in both targeted and non-targeted analyses. However, the non-linear behavior of IMS and its complex ion chemistry pose challenges for finding optimal experimental conditions using existing methodologies. To address these issues, integrating machine learning (ML) strategies offers a promising approach. In this study, we propose a hybrid strategy, combining design of experiment (DOE) and machine learning (ML) for optimizing GC-IMS conditions in non-targeted volatilomic/flavoromic analysis, with saffron volatiles as a case study. To begin, a rotatable circumscribed central composite design (CCD) is used to define five influential GC-IMS factors of sample amount, headspace temperature, incubation time, injection volume, and split ratio. Subsequently, two ML models are utilized: multiple linear regression (MLR) as a linear model and Bayesian regularized-artificial neural network (BR-ANN) as a nonlinear model. These models are employed to predict the response variables of total peak areas (PAs) and the number of detected peaks (PNs) in GC-IMS. The findings show that there is a direct correlation between the factors in GC-IMS and the PNs, suggesting that MLR is a suitable approach for building a model in this scenario. However, the PAs exhibit nonlinear behavior, suggesting that BR-ANN is better suitable to capture this complexity. Notably, Derringer's desirability function is utilized to integrate the PAs and PNs, and in this scenario, MLR demonstrates satisfactory performance in modeling the GC-IMS factors.

Superior high-efficiency and high-throughput volatile flavor extraction of Japanese fermented seasonings by solvent-assisted stir bar solid extraction with reverse extraction

Fermented seasonings have pleasant flavors that stimulate our appetite. Their flavoring properties change depending on factors such as their materials and fermented conditions. Therefore, a comparative analysis of their flavor is important when evaluating their quality. However, seasonings contain high levels of various matrices such as sugars, proteins, lipids, and ethanol, making it difficult to extract aroma compounds efficiently from them. In this study, we verified a high-efficient and high-throughput volatile flavor analysis of fermented seasonings by solvent-assisted stir bar solid extraction (SA-SBSE) with reverse extraction. We applied SA-SBSE to Japanese fermented seasonings, soy sauce, miso (fermented beans), and mirin (sweet rice wine) and compared their profiles with those from other common extraction methods, headspace gas-solid-phase microextraction (HS-SPME), liquid extraction with solvent-assisted flavor evaporation (LE-SAFE), and conventional SBSE (C-SBSE). The aroma properties and profiles of extracts from SA-SBSE were close to those of the original sample, being similar to that of LE-SAFE. In addition, potent aroma compounds in each sample were extracted by SA-SBSE and LE-SAFE, which were far superior to those by C-SBSE. For quantification, SA-SBSE extracts showed a good standard curve by the standard addition method. We could quantify maltol, one of the most common potent aroma compounds in all samples, for various commercial samples by such high-throughput analysis.

Drivers of the In-Mouth Interaction between Lupin Protein Isolate and Selected Aroma Compounds: A Proton Transfer Reaction-Mass Spectrometry and Dynamic Time Intensity Analysis

Plant proteins often carry off-notes, necessitating customized aroma addition. In vitro studies revealed protein-aroma binding, limiting release during consumption. This study employs in vivo nose space proton transfer reaction-time-of-flight-mass spectrometry and dynamic sensory evaluation (time intensity) to explore in-mouth interactions. In a lupin protein-based aqueous system, a sensory evaluation of a trained "green" attribute was conducted simultaneously with aroma release of hexanal, nonanal, and 2-nonanone during consumption. Results demonstrated that enlarging aldehyde chains and relocating the keto group reduced maximum perceived intensity (Imax_R) by 71.92 and 72.25%. Protein addition decreased Imax_R by 30.91, 36.84, and 72.41%, indicating protein-aroma interactions. Sensory findings revealed a perceived intensity that was lower upon protein addition. Aroma lingering correlated with aroma compounds' volatility and hydrophobicity, with nonanal exhibiting the longest persistence. In vitro mucin addition increased aroma binding four to 12-fold. Combining PTR-ToF-MS and time intensity elucidated crucial food behavior, i.e., protein-aroma interactions, that are pivotal for food design.

UHPLC-QTOF-MS-based untargeted metabolomic authentication of Chinese red wines according to their grape varieties

Wine is a very popular alcoholic drink owing to its health benefits of antioxidant effects. However, profits-driven frauds of wine especially false declarations of variety frequently occurred in markets. In this work, an UHPLC-QTOF-MS-based untargeted metabolomics method was developed for metabolite profiling of 119 bottles of Chinese red wines from four varieties (Cabernet Sauvignon, Merlot, Cabernet Gernischt, and Pinot Noir). The metabolites of red wines from different varieties were assessed using orthogonal partial least-squares discriminant analysis (OPLS-DA) and analyzed using KEGG metabolic pathway analysis. Results showed that the differential compounds among different varieties of red wines are mainly flavonoids, phenols, indoles and amino acids. The KEGG metabolic pathway analysis showed that indoles metabolism and flavonoids metabolism are closely related to wine varieties. Based on the differential compounds, OPLS-DA models could identify external validation wine samples with a total correct rate of 90.9 % in positive ionization mode and 100 % in negative ionization mode. This study indicated that the developed untargeted metabolomics method based on UHPLC-QTOF-MS is a potential tool to identify the varieties of Chinese red wines.

Unraveling the relationship between key aroma components and sensory properties of fragrant peanut oils based on flavoromics and machine learning

Key aroma components of 33 fragrant peanut oils with different aroma types were screened by combined using flavoromics and machine learning. A total of 108 volatile compounds were identified and 100 kinds of them were accurately quantified, and 38 compounds out of them were with odorant activity value ≥1. The 33 peanut oils presented varied intensity of 'fresh peanuts', 'roasted nut', 'burnt', 'over-burnt', 'sweet', 'peanut butter-like', 'puffed food' and 'exotic flavor', and could be classified into four aroma types, namely raw, light, thick and salty. Partial least squares regression analysis, random forest and classification regression tree revealed that 2-acetyl pyrazine had a negative effect on 'fresh peanuts' and could distinguish raw flavor samples well; 2-methylbutanal and 4-vinylguaiacol were key compounds of 'roasted nut' and had significant differences (P < 0.0001) in thick and raw flavor samples; furfural contributed to the 'puffed food' as well as key compound of salty flavor.

Stressing the importance of plant specialized metabolites: omics-based approaches for discovering specialized metabolism in plant stress responses

Plants produce a diverse range of specialized metabolites that play pivotal roles in mediating environmental interactions and stress adaptation. These unique chemical compounds also hold significant agricultural, medicinal, and industrial values. Despite the expanding knowledge of their functions in plant stress interactions, understanding the intricate biosynthetic pathways of these natural products remains challenging due to gene and pathway redundancy, multifunctionality of proteins, and the activity of enzymes with broad substrate specificity. In the past decade, substantial progress in genomics, transcriptomics, metabolomics, and proteomics has made the exploration of plant specialized metabolism more feasible than ever before. Notably, recent advances in integrative multi-omics and computational approaches, along with other technologies, are accelerating the discovery of plant specialized metabolism. In this review, we present a summary of the recent progress in the discovery of plant stress-related specialized metabolites. Emphasis is placed on the application of advanced omics-based approaches and other techniques in studying plant stress-related specialized metabolism. Additionally, we discuss the high-throughput methods for gene functional characterization. These advances hold great promise for harnessing the potential of specialized metabolites to enhance plant stress resilience in the future.

Analysis for different flavor compounds in mature milk from human and livestock animals by GC × GC-TOFMS

Breast milk plays a crucial role in the taste development of infants, which cannot be replicated by other mammalian milk or formulas. This study aimed to identify and characterize the flavor substances in 15 different types of milk and analyze the differences among them. The results showed that human milk contained high levels of esters, particularly fatty acid ethyl esters, which contribute to its unique flavor. The four substances that had the highest flavor contribution in all species were identified as 2,3-butanedione, trimethylamine, isophorone, and acetaldehyde. Furthermore, the analysis of differences revealed that thermal-oxidation of lipids could explain the variation between human milk and other species in terms of flavor compounds. The key differential flavor compounds identified in milk from all species were trimethylamine, propanal, 1-pentanol, pyridine 2-methyl, and 2-butanone. These findings can potentially aid in developing formulas that better meet the taste needs of infants.

Flavor profile and role of macromolecules in the flavor generation of shrimp meat and valorization of shrimp by-products as a source of flavor compounds: a review

Shrimps are a widely cultivated species among crustaceans worldwide due to their nutritional profile and delicacy. Because of their unique flavor, shrimp-based food products are gaining consumer demand, so there is a need to understand the flavor chemistry of shrimp meat. Further, the processing and macromolecules of shrimp meat play a significant role in flavor generation and suggest a focus on their research. However, shrimp processing generates a large amount of solid and liquid waste, creating disposal problems and environmental hazards. To overcome this, utilizing these waste products, a rich source of valuable flavor compounds is necessary. This review comprehensively discusses the nutritional aspects, flavor profile, and role of macromolecules in the flavor generation of shrimp meat. Besides, recent trends in analyzing the aroma profile of shrimp and the benefits of shrimp by-products as a source of flavor compounds have been addressed. The delicious flavor of shrimp meat is due to its volatile and nonvolatile flavor compounds. Proteins play a major role in the textural and flavor adsorption properties of shrimp meat-based products. Green extraction technologies, especially ultrasonication, are recommended for valorizing shrimp by-products as a source of flavor compounds, which have enormous applications in the food and flavor industries.

Integration of Volatilomics and Metabolomics Unveils Key Flavor-Related Biological Pathways in Different Carambola Cultivars

Carambola is a tropical fruit that is highly sought after by consumers due to its unique flavor, star shape, and nutritional value. Enhancing the flavor quality of this fruit can increase the consumer acceptance and market demand. However, flavor is an intrinsic characteristic of fruits. Its decoding requires in-depth knowledge based on recognizing key biological pathways relevant to flavor formation and development. In this study, the volatile and non-volatile metabolites contributing to the flavor variation of five carambola cultivars were investigated by a novel strategy combining GC-MS/O-based volatilomics with LC-MS-based metabolomics. Several significant flavor-related pathways, involving biosynthesis or metabolism of amino acids, terpenoids, fatty acids, sugar and organic acid, and flavonoids were identified based on the enrichment analysis of important volatile and non-volatile metabolites. The results indicated that there were metabolites in the flavor-related pathways being up- or downregulated, leading to the differences in flavor traits of different carambola cultivars. This study could provide a valuable reference for breeders and researchers of interest in the mechanisms underlying the regulation of flavor, which would ultimately lead to the creation of carambola cultivars with more attractive flavor profiles and pleasurable consuming experiences.

Isolation, Characterization, and Compositional Analysis of Polysaccharides from Pinot Noir Wines: An Exploratory Study

It has been reported that polysaccharides in wine can interact with tannins and other wine components and modify the sensory properties of the wine. Unfortunately, the contribution of polysaccharides to wine quality is poorly understood, mainly due to their complicated structure and varied composition. In addition, the composition and molecular structure of polysaccharides in different wines can vary greatly. In this study, the polysaccharides were isolated from pinot noir wine, then separated into high-molecular-weight (PNWP-H) and low-molecular-weight (PNWP-L) fractions using membrane-based ultrafiltration. Each polysaccharide fraction was further studied using size exclusion chromatography, UV-Vis, FT-IR, matrix-assisted laser desorption/ionization-high-resolution mass spectrometry, and gas chromatography-mass spectrometry (GC-MS). The results showed that PNWP-L and PNWP-H had different chemical properties and compositions. The FT-IR analysis showed that PNWPs were acidic polysaccharides with α- and β-type glycosidic linkages. PNWP-L and PNWP-H had different α- and β-type glycosidic linkage structures. FT-IR showed stronger antisymmetric and symmetric stretching vibrations of carboxylate anions of uronic acids in PNWP-L, suggesting more uronic acid in PNWP-L. The size exclusion chromatography results showed that over 72% of the PNWP-H fraction had molecular sizes from 25 kDa to 670 kDa. Only a small percentage of smaller molecular polysaccharides was found in the PNWP-H fraction. In comparison, all of the polysaccharides in the PNWP-L fraction were below 25 KDa, with a majority distributed approximately 6 kDa (95.1%). GC-MS sugar composition analysis showed that PNWP-L was mainly composed of galacturonic acid, rhamnose, galactose, and arabinose, while PNWP-H was mainly composed of mannose, arabinose, and galactose. The molecular size distribution and sugar composition analysis suggested that the PNWP-L primarily consisted of rhamnogalacturonans and polysaccharides rich in arabinose and galactose (PRAG). In comparison, PNWP-H were mostly mannoproteins and polysaccharides rich in arabinose and galactose (PRAG). Further research is needed to understand the impacts of these fractions on wine organoleptic properties.

Uncovering aroma boundary compositions of barley malts by untargeted and targeted flavoromics with HS-SPME-GC-MS/olfactometry

In this study, HS-SPME/GC-MS based untargeted and targeted flavoromics combing with olfactometry were employed to uncover aroma boundary compositions of five types of commercial barley malts with a wide range of Lovibond (L), including kilned base malts (1.8 L and 3.5 L) and roasted caramel malts (10 L, 60 L, and 120 L). Thirty-two compounds were identified as aroma-active with modified detection frequency (MF) > 50%. 3-Methylbutanal (malty), (2E)-nonenal (fatty, cardboard-like), and 2-furfural (burnt, bready) were recognized as the most influential odorants with MF > 70% in all the malts. After untargeted flavoromics, twenty-eight aromas were retained and quantitated. Furthermore, aroma boundary compositions inside/among malt groups were explored with PLS-DA. Eight aroma markers, 3-methylbutanal, 2-isopropyl-5-methyl-2-hexenal, (2E,4E)-Decadienal, 2-furfual, maltol, 2-acetylpyrrole, phenylacetaldehyde, and ethyl hexadecanoate were shortlisted for aroma boundary compositions regarding to the Lovibond of malts.

Metabolic Footprint Analysis of Volatile Organic Compounds by Gas Chromatography-Ion Mobility Spectrometry to Discriminate Mandarin Fish (Siniperca chuatsi) at Different Fermentation Stages

Chinese fermented mandarin fish (Siniperca chuatsi) have unique aroma characteristics that are appreciated by local consumers. In this study, electronic nose (E-nose) and gas chromatography–ion mobility spectrometry analyses were combined to establish a volatile fingerprint of fermented mandarin fish during fermentation. Clear separation of the data allowed mandarin fish samples at different fermentation stages to be distinguishing using E-nose analysis. Forty-three volatile organic compounds were identified during fermentation. Additionally, partial least squares discrimination analysis was performed to screen for different VOC metabolites in the fermented mandarin fish; the levels of six VOCs changed significantly during fermentation (variable importance in projection >1; p < 0.05). Three VOCs, i.e., hexanal-D, nonanal, and limonene were identified as potential biomarkers for fermentation. This study provided a theoretical basis for flavor real-time monitoring and quality control of traditional mandarin fish fermentation.