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Pasteurized yogurt is a healthy yogurt that can be stored in ambient temperature conditions. Dynamic headspace sampling (DHS) combined with gas chromatography-olfactory mass spectrometry (GC-O-MS), sensory evaluation, electronic nose (E-nose), and partial least squares discriminant analysis (PLS-DA) were used to analyze the flavor changes of pasteurized yogurt with different process combinations before and after aging. The results of odor profiles showed that the sensory descriptors of fermented, sweet, and sour were greatly affected by different process combinations. The results of odor-active compounds and relative odor activity value (r-OAV) showed that the combination of the production process affected the overall odor profile of pasteurized yogurt, which was consistent with the sensory evaluation results. A total of 15 odor-active compounds of 38 volatile compounds were detected in pasteurized yogurt samples. r-OAV results revealed that hexanal, (E)-2-octenal, 2-heptanone, and butanoic acid may be important odor-active compounds responsible for off-odor in aged, pasteurized yogurt samples. PLS-DA and variable importance of projection (VIP) results showed that butanoic acid, hexanal, acetoin, decanoic acid, 1-pentanol, 1-nonanal, and hexanoic acid were differential compounds that distinguish pasteurized yogurt before and after aging.

This study investigates the impact of key factors on the formation of odorants and sensory properties in mead. The effects of the honey type (acacia, buckwheat, linden), wort heating, and the fermentation method (commercial Saccharomyces cerevisiae yeasts, spontaneous fermentation, Galactomyces geotrichum molds) were examined. Twelve model mead batches were produced, matured for 12 months, and analyzed using gas chromatography–olfactometry (GC–O) and headspace SPME-GC/MS to identify odor-active compounds. Results confirmed that the honey type plays a significant role in sensory profiles, with distinct aroma clusters for buckwheat, acacia, and linden honey. Compounds like phenylacetic acid, 2- and 3-methylbutanal, and butanoic acid were identified as the most important odorants, correlating with sensory attributes such as honey-like, malty, and fermented aromas. Univariate and multivariate analyses, followed by correlation analysis, highlighted how production parameters affect mead aroma, providing insights to optimize sensory quality.

Background Rice plant growth is comprised of distinct phases, such as vegetative, reproductive, grain filling and maturity phases. In these phases synthesis and availability of primary and secondary metabolites including volatile organic compounds (VOC’s) is highly variable. In scented rice, aroma volatiles are synthesized in aerial plant parts and deposited in mature grains. There are more than 100 VOCs reported to be responsible for flavor in basmati rice. It will be interesting to keep track of aroma volatiles across the developmental stages in scented rice. Therefore, the aroma volatiles contributing in aroma with special reference to the major compound 2 acetyl-1-pyrroline (2AP) were screened at seven developmental stages in scented rice cultivars Basmati-370 and Ambemohar-157 along with non-scented rice cultivar IR-64 as a control following HS-SPME-GC-MS method. In addition, the expression levels of key genes and precursor levels involved in 2AP biosynthesis were studied. Results The study indicated that volatilome of scented rice cultivars is more complex than non-scented rice cultivar. N-heterocyclic class was the major distinguishing class between scented from non-scented rice. A total of 14 compounds including, 2AP were detected specifically in scented rice cultivars. Maximum number of compounds were synthesized at seedling stage and decreased gradually at reproductive and maturity. The seedling stage is an active phase of development where maximum number green leaf volatiles were synthesized which are known to act as defense molecules for protection of young plant parts. Among the 14 odor active compounds (OACs), 10 OACs were accumulated at higher concentrations significantly in scented rice cultivars and contribute in the aroma. 2AP content was highest in mature grains followed by at booting stage. Gene expression analysis revealed that reduced expression of betaine aldehyde dehydrogenase 2 ( badh 2) and glyceraldehyde-3-phosphate dehydrogenase ( GAPDH ) and elevated level of triose phosphate isomerase ( TPI ) and Δ 1-Pyrolline-5-carboxylic acid synthetase ( P5CS ) transcript enhances 2AP accumulation. Conclusions Most diverse compounds were synthesized at seedling stage and OACs were accumulated more at flowering followed by seedling stage. Distinct accumulation pattern exists for 2AP and other aroma volatiles at various developmental stages. The study revealed the mechanism of 2AP accumulation such that 2AP in mature grains might be transported from leaves and stem sheath and accumulation takes place in grains.

The aim was to explore using machine learning (including cluster mapping and k-means methods) to classify types of mead based on sensory analysis and aromatic compounds. Machine learning is a modern tool that helps with detailed analysis, especially because verifying aromatic compounds is challenging. In the first stage, a cluster map analysis was conducted, allowing for the exploratory identification of the most characteristic features of mead. Based on this, k-means clustering was performed to evaluate how well the identified sensory features align with logically consistent groups of observations. In the next stage, experiments were carried out to classify the type of mead using algorithms such as Random Forest (RF), adaptive boosting (AdaBoost), Bootstrap aggregation (Bagging), K-Nearest Neighbors (KNN), and Decision Tree (DT). The analysis revealed that the RF and KNN algorithms were the most effective in classifying mead based on sensory characteristics, achieving the highest accuracy. In contrast, the AdaBoost algorithm consistently produced the lowest accuracy results. However, the Decision Tree algorithm achieved the highest accuracy value (0.909), demonstrating its potential for precise classification based on aroma characteristics. The error matrix analysis also indicated that acacia mead was easier for the algorithms to identify than tilia or buckwheat mead. The results show the potential of combining an exploratory approach (cluster map with the k-means method) with machine learning. It is also important to focus on selecting and optimizing classification models used in practice because, as the results so far indicate, choosing the right algorithm greatly affects the success of mead identification.

Beer is a popular alcoholic beverage worldwide. However, limited research has been conducted on identifying key odor-active components in lager-type draft beers for the Chinese market. Therefore, this study aims to elucidate the odor characteristics of the four most popular draft beer brands through a sensory evaluation and an electronic nose. Subsequently, the four draft beers were analyzed through solid-phase microextraction and liquid–liquid extraction using a two-dimensional comprehensive gas chromatography–olfactometry–mass spectrometry analysis (GC×GC–O–MS). Fifty-five volatile odor compounds were detected through GC×GC–O–MS. Through an Aroma Extract Dilution Analysis, 22 key odor-active compounds with flavor dilution factors ≥ 16 were identified, with 11 compounds having odor activity values > one. An electronic nose analysis revealed significant disparities in the odor characteristics of the four samples, enabling their distinct identification. These findings help us to better understand the flavor characteristics of draft beer and the stylistic differences between different brands of products and provide a theoretical basis for objectively evaluating the quality differences between different brands of draft beer.

As the second most widely consumed eggs, duck eggs are made into preserved eggs, salted duck eggs, and roasted duck eggs to extend their shelf-life. To investigate the differences in potent odorants (POs) between salted duck egg yolk (SDEY) and roasted duck egg yolk (RDEY), the volatiles in SDEY and RDEY were extracted through solvent extraction coupled with solvent-assisted flavor evaporation and were assayed with gas chromatography-mass spectrometry-olfactometry. A total of 45 volatiles were identified in two samples, 24 odor-active compounds (OACs) were screened, and more OACs were in RDEY. The flavor-dilution (FD) factors of OACs were obtained by aroma extract dilution analysis and ranged from 3 to 6561. Twenty-two OACs with FD factors ≥ 9 were quantitated, and the results indicated the concentrations of OACs in yolk increased greatly after salted duck eggs were roasted. Based on the concentrations and thresholds, odor activity values (OAVs) were determined; 17 odorants with OAVs ≥ 1 were determined as POs. Acetoin was the most PO in SDEY; there were more POs in RDEY, including 2-ethyl-3,6-dimethylpyrazine, acetoin, 2-acetyl-3-methylthiophene, dihydro-4-hydroxy-2(3H)-furanone, etc. The outcomes obtained have reference values for making better use of duck eggs in the food industry.

In recent years, there has been a significant decline in interest in high-alcohol beers, while interest in low- and non-alcohol beers is growing. The aim of this study was to investigate the influence of the addition of coriander seeds at various stages of the production of low-alcohol wheat beer (mashing, boiling, and fermentation). The presented article uses biological methods to produce low-alcohol beer. For this purpose, first, the mashing process was modified (breaking 44 °C for 20 min, followed by 75 °C for 60 min). The chemical composition and aroma components of the obtained beers were determined using various chromatographic methods (HPLC, GC-MS, and GC-O). Differences were found between the aroma components depending on the stage of production at which the coriander seeds were added. Beers with the addition of coriander seeds at the fermentation stage had the highest terpene content (linalool, camphor, trans-linalool oxide, and γ-terpinene) and boiling (myrcene, limonene, citronellol, and geraniol). The least desirable process is the addition of coriander seeds at the mashing stage due to the lowest content of volatile compounds. Additionally, beers with the addition of coriander seeds for fermentation were characterized by a higher content of antioxidant compounds. This proves that the addition of coriander seeds during beer production could improve the fermentation process and modify the quality of the obtaining beer.

Branched aldehydes, such as 2-methyl propanal and 2- and 3-methyl butanal, are important flavour compounds in many food products, both fermented and non-fermented (heat-treated) products. The production and degradation of these aldehydes from amino acids is described and reviewed extensively in literature. This paper reviews aspects influencing the formation of these aldehydes at the level of metabolic conversions, microbial and food composition. Special emphasis was on 3-methyl butanal and its presence in various food products. Knowledge gained about the generation pathways of these flavour compounds is essential for being able to control the formation of desired levels of these aldehydes.

Charcoal-grilled marinated beef (CMB) is a popular Korean food that has garnered worldwide attention. In this study, volatile and odor-active compounds generated in CMB were analyzed using gas chromatography-mass spectrometry (GC-MS) and gas chromatography-olfactometry (GC-O). Solvent-assisted flavor extraction and solid-phase micro extraction were employed to extract the volatile compounds before GC-MS and GC-O analyses. In total, 196 compounds were identified in CMB. Certain heterocyclic compounds, such as pyrazines and thiazoles, could be produced by grilling at high temperatures. The formation of benzene derivatives and phenols could be attributed to charcoal grilling and marinade used. In the GC-O results, 3-methylsulfanylpropanal, 2-methoxyphenol, 1,3-benzothiazole, furaneol, 3-methylphenol, prop-2-ene-1-thiol, 2-ethyl-3,5-dimethylpyrazine, and 2,5-dimethylpyrazine exhibited relatively high flavor dilution factors. Based on these findings, sulfur-containing compounds, pyrazines, phenols, and aldehydes primarily influence the characteristic flavor of CMB.

Carvacrol-containing gelatin nanofibers were successfully produced, characterized, and applied on farmed trout fillets as coating material. Scanning electron microscopy (SEM) images revealed that the presence of carvacrol increased the average fiber diameter from 152.3 to 217 nm and less droplet formation was observed after carvacrol addition. Young’s modulus and stability of the nanofibers were found to increase with the increasing weight percentage of carvacrol. The applied nanocoating treatment positively slowed the growth of bacteria, yeast, and mold throughout 9 days of storage ( p  < 0.05). The decrease in hardness was slower in the gelatin nanofibers containing the 7.5% carvacrol (GLC7.5)-coated group compared to the uncoated group in the first 5 days ( p  > 0.05). A total of 14 volatile organic compounds (VOCs) were identified by gas chromatography-mass spectrometry (GC–MS) in the uncoated and GLC7.5-coated samples as volatile indicators of flavor deterioration. Volatile substances that cause an off-flavor in the fillets were found at a lower rate in the GLC7.5-coated group and showed higher sensory odor scores. The most important aroma compounds identified in the samples were dimethyl disulfide (DMDS) (garlic-like), dimethyl trisulfide (rotten egg), 3-methyl butanoic acid (cheesy), phenol (phenolic), and 1H-indole (fecal). Additionally, carvacrol (spicy) was found to be an important contributor of odor to meat with a GLC7.5 coating. The results showed that carvacrol-loaded nanocoatings have antimicrobial and antifungal properties that affect the formation of volatile compounds in fish meat. Therefore, the nanocoating technique could be useful in preventing spoilage and boosting the odor attributes of fresh fish products.