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Fermentation strategies in mead production: A multitechnique volatilomic approach to aroma characterization
Thermal processing-induced changes in volatilome and metabolome of Brussels sprouts: focus on glucosinolate metabolism
AbstractThis study aimed to investigate the influence of different thermal treatment methods (boiling, steaming) on the metabolome and volatilome of Brussels sprouts. Targeted, quantitative analysis of primary metabolites (amino acids and sugars), glucosinolates as well as untargeted analysis of volatile organic compounds (VOCs) were performed. The composition of primary metabolites was affected only by boiling, where the loss of nutrients was observed. Glucosinolate content increased after cooking, which can be explained by the loosening of the plant tissues and its better extractability. Most marked changes were noticed in the volatilome. Among the degradation products of glucosinolates, isothiocyanates were the main chemical group in the raw and boiled vegetable. In contrast, steaming favored the formation of nitriles. Another dominant group of VOCs were aldehydes, which were the most abundant in raw Brussels sprouts and their level significantly decreased after thermal treatment. It is well known that isothiocyanates are substances with widely proven bioactive properties. Therefore, their formation in the glucosinolate degradation process is favorable. Based on the obtained results, it was concluded that boiling seems to be the most beneficial form of Brussels sprouts’ processing.
The Combined Effect of Lactic Acid Bacteria and Galactomyces geotrichum Fermentation on the Aroma Composition of Sour Whey
The increase in demand for food flavorings due to the shortening and simplification of food production technology also entails an increase in the demand for new technologies for their production. The biotechnological production of aromas is a solution characterized by a high efficiency, an independence from environmental factors and a relatively low cost. In this study, the influence of the implementation of lactic acid bacteria pre-fermentation into the production of aroma compounds by Galactomyces geotrichum on a sour whey medium on the intensity of the obtained aroma composition was analyzed. The monitoring of the culture in terms of biomass buildup, the concentration of selected compounds, and the pH resulted in the confirmation of interactions between the analyzed microorganisms. The post-fermentation product underwent a comprehensive sensomic analysis for the identification and quantification of the aroma-active compounds. The use of gas chromatography−olfactometry (GC−O) analysis and the calculation of odor activity values (OAVs) allowed 12 key odorants to be identified in the post-fermentation product. The highest OAV was found for phenylacetaldehyde with a honey odor (1815). The following compounds with the highest OAVs were 2,3-butanedione with a buttery aroma (233), phenylacetic acid with a honey aroma (197), 2,3-butanediol with a buttery aroma (103), 2-phenylethanol with a rosy aroma (39), ethyl octanoate with a fruity aroma (15), and ethyl hexanoate with a fruity aroma (14).
Effect of Cricket Powder Incorporation on the Profile of Volatile Organic Compounds, Free Amino Acids and Sensory Properties of Gluten-Free Bread
Combining Targeted Metabolomics with Untargeted Volatilomics for Unraveling the Impact of Sprouting on the Volatiles and Aroma of False Flax (Camelina sativa) Cold-Pressed Oil
Machine Learning in Sensory Analysis of Mead—A Case Study: Ensembles of Classifiers
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.
Application of Sorbent-Based Extraction Techniques in Food Analysis
This review presents an outline of the application of the most popular sorbent-based methods in food analysis. Solid-phase extraction (SPE) is discussed based on the analyses of lipids, mycotoxins, pesticide residues, processing contaminants and flavor compounds, whereas solid-phase microextraction (SPME) is discussed having volatile and flavor compounds but also processing contaminants in mind. Apart from these two most popular methods, other techniques, such as stir bar sorptive extraction (SBSE), molecularly imprinted polymers (MIPs), high-capacity sorbent extraction (HCSE), and needle-trap devices (NTD), are outlined. Additionally, novel forms of sorbent-based extraction methods such as thin-film solid-phase microextraction (TF-SPME) are presented. The utility and challenges related to these techniques are discussed in this review. Finally, the directions and need for future studies are addressed.
Comprehensive two-dimensional gas chromatography-time of flight mass spectrometry as a tool for tracking roasting-induced changes in the volatilome of cold-pressed rapeseed oil
AbstractThe aim of this study was to track changes in the volatilome of cold-pressed oil and press cakes obtained from roasted seeds and to combine it with the profile of non-volatile metabolites in a single study, in order to understand pathways of volatile organic compound (VOC) formation caused by thermal processing. Comprehensive two-dimensional gas chromatography-time of flight mass spectrometry was used for the analysis of VOCs in cold-pressed oils and corresponding press cakes obtained after roasting of seeds at 140 and 180 °C prior to pressing. Contents of primary metabolites (amino acids, saccharides, fatty acids) as well as selected secondary metabolites (glucosinolates, polyphenols) were determined, as many of them serve as precursors to volatile compounds formed especially in thermal reactions. After roasting, the formation of Maillard reaction products increased, which corresponded to the reduction of free amino acids and monosaccharides. Moreover, levels of the products of thermal oxidation of fatty acids, such as aldehydes and ketones, increased with the increasing temperature of roasting, although no significant changes were noted for fatty acids. Among sulphur-containing compounds, contents of the products and intermediates of methionine Strecker degradation increased significantly with the increasing temperature of roasting. Degradation of glucosinolates to nitriles occurred after thermal treatment. The results of this study confirmed that seed roasting before cold pressing has a significant effect on the volatiles, but also indicated roasting-induced changes in non-volatile metabolites of oil and press cake. Such an approach helps to understand metabolic changes occurring during rapeseed processing in cold-pressed oil production. Graphical Abstract
Betaine supplementation modulates betaine concentration by methylenetetrahydrofolate reductase genotype, but has no effect on amino acid profile in healthy active males: A randomized placebo-controlled cross-over study
Metabolic Changes during Sprouting of Rapeseed and Their Consequences for the Volatilome of Cold‐Pressed Oil
AbstractAll the procedures before pressing seeds have a great influence on the flavor of cold‐pressed rapeseed oil. However, the studies on the modification of aroma caused by inappropriate storage leading to sprouting are scarce. Therefore, this study aims to determine the effects of sprouting on the metabolome and volatilome of rapeseed cold‐pressed oil and press cakes. The presence of 56 and 21 nonvolatile metabolites is detected in seeds/press cakes and oil, respectively. Sprouting significantly affects the total contents of all groups of compounds, except sugars. At the same time, 375 volatile organic compounds (VOCs) are detected. The abundance of VOCs in sprouted oil is almost threefold higher compared to control oil, with the biggest contribution of sulfur‐containing compounds (dimethyl sulfide), glucosinolate derivatives (4‐isothiocyanato‐1‐butene), and aldehydes (3‐methylbutanal). A similar tendency is observed in press cake. Moreover, sprouting results in the biggest number of VOCs detected only in this oil (61). The abundance of aroma‐active compounds is much higher in sprouted products compared to corresponding controls, which has a confirmation in sensory analysis. This study shows that simultaneous volatilomics and metabolomics can be used to track the changes in the oil quality caused by the inappropriate storage of seeds. Sprouting leads to metabolic changes in seeds, which intensify the formation of new VOCs and consequently aroma of oils.Practical applications: The results of this study will help to understand the formation of volatile organic compounds (VOCs) during the processing and production of cold‐pressed rapeseed oil. The combination of VOCs with nonvolatile precursors can help to understand the pathways involved in VOCs formation. Moreover, the oil obtained from sprouted seeds is characterized by many VOCs not present in control oil, which can potentially be used to develop tools for quick evaluation if the seeds used for pressing initiated sprouting, which can lead to changes in its sensory quality.
Unravelling the importance of seed roasting for oil quality by the non-targeted volatilomics and targeted metabolomics of cold-pressed false flax (Camelina sativa L.) oil and press cakes
Influence of Honey Varieties, Fermentation Techniques, and Production Process on Sensory Properties and Odor-Active Compounds in Meads
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.