Quality Difference Analysis Among Soy Whey Produced by Different Processing Methods

We obtained volatile aroma compounds from the juices extracted from three different Red Delicious apple (Malus domestica) varieties, which included esters, alcohols, and aldehydes. Among these compounds, ethyl 2-methylbutanoate, methyl 2-methylbutanoate, ethyl butanoate, ethyl hexanoate, hexanal, and butyl 2-methylbutanoate showed high odour active values in the juices. Four compounds (ethyl 2-methylbutanoate, ethyl octanoate, ethyl butanoate, and ethyl hexanoate) were selected to investigate possible interactions occurring in the apple juices. The results demonstrated that the additions of these four aroma volatile compounds could decrease the threshold and intensity of the sensory notes of the solutions compared to those without the addition of these compounds. Lastly, ethyl 2-methylbutanoate was added to the solutions to investigate interactions with σ–τ function. Here, σ represents the ratio of the aroma intensity of the mixed solution to the sum of aroma intensities of all compounds in the solution before blending. The τ represents the aroma of the mixture ratio between the mixture and the sum of aroma compounds before mixing. The results clearly indicated that additive or synergistic effects occurred among these volatiles at sub-threshold concentrations.

Raw milk cheeses harbor complex microbial communities. Some of these microorganisms are technologically essential, but undesirable microorganisms can also be present. While most of the microbial dynamics and cross-talking studies involving interaction between food-derived bacteria have been carried out on agar plates in laboratory-controlled conditions, the present study evaluated the modulation of the resident microbiota and the changes of metabolite production directly in ripening raw milk cheese inoculated with Listeria innocua strains. Using a proxy of the pathogenic Listeria monocytogenes, we aimed to establish the key microbiota players and chemical signals that characterize Latteria raw milk cheese over 60 days of ripening time. The microbiota of both the control and Listeria-inoculated cheeses was analyzed using 16S rRNA targeted amplicon sequencing, while direct analysis in real time mass spectrometry (DART-HRMS) was applied to investigate the differences in the metabolic profiles of the cheeses. The diversity analysis showed the same microbial diversity trend in both the control cheese and the inoculated cheese, while the taxonomic analysis highlighted the most representative genera of bacteria in both the control and inoculated cheese: Lactobacillus and Streptococcus. On the other hand, the metabolic fingerprints revealed that the complex interactions between resident microbiota and L. innocua were governed by continuously changing chemical signals. Changes in the amounts of small organic acids, hydroxyl fatty acids, and antimicrobial compounds, including pyroglutamic acid, hydroxy-isocaproic acid, malic acid, phenyllactic acid, and lactic acid, were observed over time in the L. innocua-inoculated cheese. In cheese that was inoculated with L. innocua, Streptococcus was significantly correlated with the volatile compounds carboxylbenzaldheyde and cyclohexanecarboxylic acid, while Lactobacillus was positively correlated with some volatile and flavor compounds (cyclohexanecarboxylic acid, pyroxidal acid, aminobenzoic acid, and vanillic acid). Therefore, we determined the metabolic markers that characterize a raw milk cheese inoculated with L. innocua, the changes in these markers with the ripening time, and the positive correlation of flavor and volatile compounds with the resident microbiota. This multi-omics approach could suggest innovative food safety strategies based on the enhanced management of undesirable microorganisms by means of strain selection in raw matrices and the addition of specific antimicrobial metabolites to prevent the growth of undesirable microorganisms.

The volatilomic fingerprint of nine different whiskeys was established using a rapid and sensitive analytical approach based on dispersive liquid–liquid microextraction (DLLμE) followed by gas chromatography mass spectrometry detection (GC-MS) and gas chromatography with flame ionization detection (GC-FID). The influence of the extractor solvent on the extraction efficiency of volatile compounds (VOCs) was evaluated by DLLμE/GC-MS. The highest amounts of VOCs were obtained using 5 mL of sample, dichloromethane as the extractor solvent, and acetone as the disperser solvent. The proposed method showed no matrix effect, good linearity (R2 ≥ 0.993) in the assessed concentration range, recovery (ranging from 70 to 99%, precision (RSD ≤ 15%) and sensitivity (low limits of detection and quantification). A total of 37 VOCs belonging to different biosynthetic pathways including alcohols, esters, acids, carbonyl compounds, furanic compounds and volatile phenols were identified and quantified using DLLμE/GC-MS and DLLμE/GC-FID, respectively. Alcohols (3-methylbutan-1-ol, propan-1-ol), esters (ethyl decanoate, ethyl octanoate, ethyl hexanoate), and acids (decanoic acid, octanoic acid, hexanoic acid) were the most abundant chemical families. The multivariate statistical analysis allowed for the discrimination of whiskeys based on their volatilomic fingerprint, namely octanoic acid, 2-furfural, ethyl octanoate, ethyl hexanoate, acetic acid, ethyl dodecanoate, butan-1-ol, and ethyl decanoate.

To identify core bacterial communities and volatile compounds and to investigate their relationships in Doubanjiang, a Chinese traditional red pepper paste. Two main culture-independent methods, polymerase chain reaction-denaturing gradient gel electrophoresis (PCR-DGGE) and MiSeq sequencing technique, were used to investigate bacterial composition. Headspace solid-phase microextraction combined with gas chromatography-mass spectrometry (HS-SPME-GC-MS) was used to isolate and identify volatile organic compounds. Partial least squares (PLS) regression and correlation coefficients analyses were used for elucidating the relationship between core bacterial community and volatile compounds. Lactic acid bacteria (LAB) and Enterobacteriaceae family were identified primarily by the PCR-DGGE fingerprinting. Furthermore, the core microbiome (>1% average relative abundance) were indentified by Miseq sequencing technique, which mainly assigned to Proteobacteria, Cyanobacteria and Firmicutes phyla. For volatile profile, a total of 29 volatile compounds were identified by HP-SPME-GC-MS, mainly alcohols, esters, aldehydes, ketones and phenols. PLS regression and Pearson's correlation coefficients analyses revealed highly covariable relationships between volatile compounds and bacterial taxa. Notably, Pseudomonas most highly significantly associated with 3-methyl butanal, 2-methyl butanal, benzeneacetaldehyde and 2-acetylpyrrole (P<0·001), and significantly correlated with 5-methylfurfural and 5-methyl-2-phenyl-2-hexenal (P<0·01). Core bacterial communities were identified and the relationship between bacterial taxa and flavour compounds was revealed, these results could be beneficial for improving the quality of Doubanjiang.

The objective of this study was performed to develop low-fat sausages(LFSs) with similar flavor profiles to those of regular-fat counterpart(RFC) using the addition of various kinds and levels of sugars in combined with 0.1 M lysine. Approximately 42 flavor compounds were identified and observed in most phenols, aldehydes, hetero compounds, ketones and alkans. Among them, phenols and aldehydes were the predominant flavor compounds and 28 flavor compounds were observed as affected by various kinds and levels of sugars. Although the volatile compounds such as 5-methyl furfural, 2-methoxy phenol, 2-methoxy-4-methyl phenol and 17-octadecenal were not different between the RFC and low-fat control(LFC), the addition of fructose and sucrose in combination with 0.1 M lysine affected the composition of volatile compounds in LFSs. Approximately 14 volatile compounds including 2-chloro-2-methyl butane, cyclopentanol, octane and furfural showed differences between RFC and LFC, but these differences were also reduced with the addition of sugars in combination with 0.1 M lysine. The volatile compounds such as nonanal, α-terpinene, myristicine, 2-pentadecanone, pentadecanal and octadecanal were not affected by the addition of sugars and lysine. However, the volatile compounds such as 2-methyl-2-butanol, 5-methyl furfural, 2-methoxy phenol, 2-methoxy-4-methyl phenol and 17-octadecenal were reduced with increased level of sugar.

SummaryThe HS‐SPME‐GC‐MS analysis of Fiano di Avellino (white wine, Southern Italy) and Aglianico del Vulture (red wine, Southern Italy) showed the presence of ethyl acetate, 2‐methyl‐1‐propanol, 2‐methyl‐1‐butanol (MB), 2‐methylbutyl acetate (MBA), ethyl hexanoate (EH), diethyl butanedioate (DB), ethyl octanoate (EO) and ethyl decanoate (ED). UV irradiation of both the wines in a Pyrex vial with a 15‐W low pressure mercury arc showed an extensive degradation of all the compounds. After 24 h irradiation in the red wine, ethyl acetate decreased from 208 mg L−1 to 58 mg L−1, DB from 16.7 to 4 mg L−1, MBA from 19 to 3 mg L−1, 2‐methyl‐1‐propanol disappeared and MB decreased from 796 to 92.5 mg L−1. Only in the case of DB, MBA, EH, EO and ED in the red wine the degradation occurred after an initial increase of the concentrations of the esters. The irradiation of the esters in the presence of riboflavin showed a clear degradation of the esters (9%–17%). The irradiation of both the wines in the original bottles for 7 days showed an extensive degradation of all the volatile compounds observed in the wines. 2‐Methyl‐1‐propanol disappeared while 90% of MB disappeared. The amount of the esters decreases in the range 65%–91%.

Influence of flavor compound chemical structure, including functional group and stereochemistry, and environmental relative humidity (RH) on the binding of volatile flavor compounds to dehydrated soy protein isolates (SPIs) was evaluated by inverse gas chromatography. Binding of selected volatile flavor compounds differed slightly between SPIs of different origins. Results showed that the flavor compound chemical structure greatly determined its binding potential to SPIs. Binding of nonpolar flavor compounds (hydrocarbon) to soy proteins was attributed mainly to nonspecific van der Waals dispersion forces and was not affected by adsorbed water. The more polar flavor compounds (ester, ketone, aldehyde, and alcohol) exhibited both specific (hydrogen bonding, dipole forces) and nonspecific interactions, and their binding with soy proteins was greatly impaired by adsorbed water in the extremely low humidity region (approaching 0% RH). Further water uptake in the 30 to 50% RH region did not significantly affect the binding of polar compounds, although sorption of alcohol compounds (when present at high levels) further increased.

ABSTRACT: The main sensory contribution of each post‐fermentation production stage of muscat wine distillates can be tracked by following the concentration of just 1 corresponding chemical marker. Matching sample clusters of sensory and chemical data by using principal components analysis (PCA) revealed potential chemical markers. The data used in this study correspond to 12 sensory attributes that showed significant differences among products ( P &lt; 0.05) and concentrations of 23 volatile compounds of 14 distillate fractions and 15 finished Piscos. Artificial fruit attribute, characteristic of the head fraction (FR1) can be tracked with esters. Linalool, main odor attribute of the 1st part of the heart (FR2) can be tracked with linalool molecule. The 2nd part of the heart (FR3) can be tracked with octanoic acid, decanoic acid, furfural and ethyl lactate, accounting for tails attribute. In blended and aged finished products, chemical markers accounting for the effects of distillate fractions were similar but not identical to the markers from samples obtained from the purely distilled samples. Chemical markers for FR1 are ethyl hexanoate, ethyl octanoate, ethyl decanoate. Differentiation between FR1 and FR2 is less evident than in the purely distilled samples due to the linalool and artificial fruit attribute correlation. Chemical markers for FR2, therefore, include linalool and esters ethyl hexanoate, ethyl octanoate, and ethyl decanoate. The blending of the 2nd part of the heart (FR3) can be tracked with 2‐phenylethanol, ethyl lactate, and decanoic acid. Oak aging was tracked with eugenol and whisky lactones, while 5‐hydroxy‐methyl‐2‐furfural accounted for added caramel.

The application of headspace solid phase microextraction (SPME) for flavor analysis has been studied. Headspace SPME sampling was tested for nine common wine flavor compounds in 10% (v/v) aqueous ethanol: linalool, nerol, geraniol, 3-methyl-1-butanol, hexanol, 2-phenylethanol, ethyl hexanoate, ethyl octanoate, and ethyl decanoate. The chemical groups (monoterpenoids, aliphatic and aromatic alcohols, and esters) showed specific behavior in SPME analysis. SPME sampling parameters were optimized for these components. Relative response factors (RRFs), which establish the relationship between the concentration of the compound in the matrix liquid solution and the GC peak area, were estimated for all compounds. Log(10)(RRF) varied from 0 (3-methyl-1-butanol) to 3 (ethyl decanoate), according to their molecular weight. Quantification by SPME was shown to be highly dependent on the matrix composition; the compounds with higher RRF were the less affected. As a consequence, the data obtained with this methodology should be used taking into consideration these limitations, as shown in the analysis of four monovarietal Bairrada white wines (Arinto, Bical, Cerceal, and Maria Gomes).

Wuyi Rock tea (WRT), originating from the northern region of Fujian province, has a good reputation for its distinctive Yan flavor and floral–fruity aroma. The aroma quality, an essential element of the Yan flavor, undergoes various changes during the manufacturing process of WRT. To enhance the understanding of the formation patterns of WRT aroma and its influence on the flavor quality of WRT, we utilized both manufactured WRT (Rougui tea) and primary tea as materials. Utilizing a sensory evaluation, detection of volatile compounds, and multivariate statistical analysis, we identified and characterized the distinctive volatile components present in WRT. The sensory evaluation and radar chart analysis revealed that the primary tea exhibited a strong and lasting aroma, along with a mellow taste and a prominent Yan flavor. Through gas chromatography time-of-flight mass spectrometry (GC-TOF MS), a total of 251 volatile compounds were identified. The odor activity value (OAV) was calculated to identify key aroma-active compounds in the primary tea. The results indicated that a total of 14 compounds had an OAV greater than 1.0, including (2-nitroethyl) benzene, indole, and geranylacetone. These compounds exhibited floral and fruity aroma attributes. They primarily formed and accumulated during the latter stages of WRT. Using a partial least squares discrimination analysis (PLS-DA) combined with a variable importance in projection (VIP) score greater than 1.0 as a criterion, a total of 89 compounds were identified. Furthermore, out of the selected compounds, 15 types, including geraniol, 1-nonanol, and 1-butyl-2-ethyl-cyclopropene, were found to exclusively exist during the enzymatic manufacturing stages, particularly during the intermediate and later phases of the turn-over process (the last-three-times turn-over treatments), exhibiting predominantly floral and sweet fragrances. In contrast, during the non-enzymatic stages, only four compounds, such as pentanoic acid and phenylmethyl ester, were detected, exhibiting a fruity aroma profile. These volatile compounds significantly influenced the quality attributes of the final tea product, resulting in strong and lasting characteristics, particularly marked by a pronounced floral and fruity aroma. This study revealed how the aroma quality in WRT is developed and pinpointed possible volatile compounds that react to post-harvest treatments, thereby offering valuable insights relating to the intelligent production strategies of WRT.

Changes on physiochemical properties and volatile compounds of Chinese kombucha during fermentation

Effects of microbial community succession on flavor compounds and physicochemical properties during CS sufu fermentation

Lemon juice vesicles have abundant flavor components that can undergo complex changes during drying. Three drying methods, including integrated freeze-drying (IFD), conventional freeze-drying (CFD), and hot-air drying (AD), were studied to determine their effects on the dynamic changes in the flavor compounds in lemon juice vesicles. Compared with the fresh samples, the final dried samples that underwent IFD, CFD, and AD lost seven, seven, and six volatile flavor compounds and three, four, and five amino acids, respectively; the order of the loss ratios with respect to the volatile compound content was: 82.73% in CFD > 71.22% in IFD > 28.78% in AD. AD resulted in the highest total amino acid content (10.83 ± 0.20 mg/g), which was 1.39 and 5.54 mg/g higher than that of IFD and CFD, respectively; CFD resulted in the highest total organic acid content (45.94 ± 0.34 mg/g), which was 8.01 and 7.87 mg/g higher than that of IFD and AD, respectively; and AD contributed to the highest total soluble sugars (17.12 ± 0.20 mg/g), which was 1.24 and 1.49 mg/g higher than that of IFD and CFD, respectively. A correlation analysis demonstrated that most of the amino acids and the soluble sugars were closely related to the profiles of the volatile compounds in the lemon juice vesicles during drying.

To accelerate cheese ripening, enhance its flavor types and intensity and make cheese flavoring agent in shorter time, surface ripening bacterium (<em>Brevibacterium linens</em> and <em>Debaryomyces hansenii</em>) and/or enzymes (<em>Flavorzyme</em> 500 MG and <em>Palatase</em> 20000 L) were used in cheese curd. In this study, aroma compounds generated by using ripening cultures and/or enzymes were analyzed. The control l was made by inoculating ripening cultures, while the control 2 was made through enzymes-modified only. Results showed that cheese flavoring agent made by using ripening strains in combination with enzymes had more volatile flavor compounds (at least 44) than that used just ripening bacterium (26) or just two enzymes (27). Then, through Solid-phase microextraction and Gas Chromatography-Mass Spectrometry analysis, we knew that sample 1, which was made through proteolysis first, next sprayed ripening cultures and last lipolysis, generated 54 flavor compounds. Sample 2, which enzymed cheese curd first, then incubated ripening cultures, had 44 aroma compounds. However, the controls 1, incubated ripening strains only, had 26 volatile compounds, while the control 2, enzymed only, had 27 volatile compounds. This study reveals that ripening bacterium could contribute more to the generation of acids, sulphur compounds, miscellaneous compounds and alcohols, it has a good potential to be used in cheese flavoring agents making. Besides, the combination of surface strains and enzymes, especially using Flavorzyme 500 MG first, then sprayed ripening cultures and at last Palatase 20000 L, could get more volatile compounds.

ABSTRACTThis study investigated the changes in volatile flavor compounds of Boletus edulis under different cooking methods (fresh, steaming, frying, roasting and boiling) using gas chromatography‐ion mobility spectrometry (GC‐IMS) and electronic nose technology. Characteristic fingerprints of flavor compounds were established, and principal component analysis (PCA) was applied for quantitative analysis of flavor substance changes, combined with a sensory evaluation system to comprehensively assess the impact of cooking processes on the volatile flavor of B. edulis. A total of 49 volatile compounds were detected in the samples of B. edulis subjected to five different processing methods. These include 27 thioethers, 16 aldehydes, 12 alcohols, 10 ketones, 1 ester, 4 pyrazines, 2 furans, 2 acids, and 2 heterocyclic compounds. Flavor fingerprint analysis revealed significant compositional differences among groups: Fresh B. edulis (NG0) had higher signal intensities of 2‐octenal, 1‐octen‐3‐one, and 3‐octanone; steamed samples (NG1) showed weakened signals of these three compounds but enhanced 1‐octen‐3‐ol and heptanal; fried samples (NG2) exhibited stronger signals of 2‐furaldehyde, 1‐octen‐3‐ol and other compounds; roasted samples (NG3) had prominent signals of 1‐octen‐3‐one, 2‐methyl‐2‐hepten‐6‐one, etc.; boiled samples (NG4) were characterized by high signals of 2‐propanone, 1‐octen‐3‐ol, etc. Fresh, steamed, and boiled B. edulis mainly contained E‐2‐octenal, 1‐octen‐3‐one, and other compounds, while high‐temperature cooking (frying, roasting) led to flavor compounds dominated by aldehydes and pyrazines. The electronic nose detection effectively discriminated among B. edulis samples prepared with different cooking methods. From the perspective of the comprehensive sensory evaluation scores, fried and roasted B. edulis obtained higher scores and demonstrated a more well‐balanced flavor profile, suggesting that frying and roasting might be the optimal cooking methods for B. edulis. These results provide a theoretical basis for flavor regulation during B. edulis cooking, data support for the improvement and innovation of B. edulis dishes, and technical guidance for the development of B. edulis processed products.