Background: Qu was the core starter of traditional Chinese fermentation and had long relied on artisan experience, which led to limited batch stability and standardization. This review organized the preparation processes, microbial diversity, and application patterns of qu in foods from experience to science perspective. Methods: This work summarized typical process parameters for daqu, xiaoqu, hongqu, wheat bran or jiangqu, douchi qu, and qu for mold curd blocks used for furu. Parameters covered raw material moisture, bed thickness, aeration or turning, drying, final moisture, and classification by peak temperature. Multi-omics evidence was used to analyze the coupling of temperature regime, community assembly, and functional differentiation. Indicators for pigment or enzyme production efficiency and safety control such as citrinin in hongqu were included. Results: Daqu showed low, medium, and high temperature regimes. Thermal history governed differences in communities and enzyme profiles and determined downstream fermentation fitness. Xiaoqu rapidly established a three-stage symbiotic network of Rhizopus, Saccharomyces, and lactic acid bacteria, which supported integrated saccharification and alcohol fermentation. Hongqu centered on Monascus and achieved coordinated pigment and aroma formation with toxin risk control through programmed control of temperature, humidity, and final moisture. Wheat bran or jiangqu served as an enzyme production engine for salt-tolerant fermentation, and the combined effects of heat and humidity during the qu period, aeration, and bed loading determined hydrolysis efficiency in salt. Douchi and furu mold curd blocks used thin-layer cultivation and near-saturated humidity to achieve stable mold growth and reproducible interfacial moisture. Conclusions: Parameterizing and online monitoring of key variables in qu making built a process fingerprint with peak temperature, heating rate, and moisture rebound curve at its core. Standardization and functional customization guided by temperature regime, community, and function were the key path for the transition of qu from workshop practice to industry and from experience to science. This approach provided replicable solutions for flavor consistency and safety in alcoholic beverages, sauces, vinegars, and soybean products.
<i>Neo-allo</i>-ocimene is a monoterpene which could be applied in pesticides, fragrances, and sustainable polymers. In this study, we mined a terpene synthase, AgTPS40, from the transcriptome of celery leaf tissues. Through sequence and phylogenetic analysis, AgTPS40 was characterized as a monoterpene synthase. The <i>AgTPS40</i> gene was introduced into a heterologous mevalonate pathway hosted in <i>Escherichia coli</i> to enable terpene production. Gas chromatography–mass spectrometry analysis confirmed that AgTPS40 catalyzes the formation of <i>neo-allo</i>-ocimene, marking the first reported identification of a <i>neo-allo</i>-ocimene synthase. Subsequently, we optimized the fermentation conditions and achieved a yield of 933.35 mg/L in a 1 L shake flask, which represents the highest reported titer of <i>neo-allo</i>-ocimene to date. These results reveal the molecular basis of <i>neo-allo</i>-ocimene synthesis in celery and provide a sustainable way to obtain this compound.
Raúl J. Delgado-Macuil, Beatriz Perez-Armendariz, Gabriel Abraham Cardoso-Ugarte
et al.
This paper comprehensively reviews whey, a by-product of cheese production, as a raw material for various biotechnological applications. It addresses its unique composition, the environmental impact of its inadequate disposal, and the opportunities it offers to develop high-value products in line with circular economy and sustainability principles. Using the PRISMA methodology, a systematic search was conducted in various databases (Science Direct, Scopus, and Google Scholar) with specific inclusion and exclusion criteria. Studies from the last five years were considered, focusing on food applications, the production of bioproducts (such as lactic acid, biopolymers, bioethanol, biomass, and enzymes), and the use of whey as a culture medium for the expression of recombinant proteins. It is concluded that the use of whey in biotechnological applications mitigates the environmental impact associated with its disposal and represents an economic and sustainable alternative for the industrial production of bioproducts. The integration of pretreatment technologies, experimental designs, and improvements in producing strains brings these processes closer to competitive conditions in the industry, opening new perspectives for innovation in the fermentation sector.
Victoria Kleinjan, Melisa González Flores, M. E. Rodríguez
et al.
Honey possesses unique properties, characterized by its high sugar concentration and the synergistic interaction among nectar, pollen, bees, and yeasts. These features render it an exceptional substrate for exploring microbial diversity for bioprospecting purposes. In this study, we characterized fermentative yeast populations from 19 honey samples collected in Northern Patagonia, Argentina. A total of 380 yeast isolates were obtained, identifying eight yeast species. Starmerella magnoliae emerged as the dominant species, found in 76% of samples and representing 63% of total isolates. Intraspecific diversity analysis, using mtDNA-RFLP and sequencing of nuclear genes (FSY1 and FFZ1), revealed the presence of two distinct phylogeographic populations. Phenotypic assays indicated that most S. magnoliae strains tolerate high sulfite and ethanol concentrations, alongside exhibiting broad temperature tolerance, with some strains thriving even at 37 °C. Despite the fact that none of the strains completed the fermentation, microfermentation trials confirmed the fructophilic nature of this species and highlighted intraspecific variability in glycerol and acetic acid production. These findings underscore S. magnoliae as a promising non-Saccharomyces yeast for the fermented beverage industry.
Accurate industry classification is critical for many areas of portfolio management, yet the traditional single-industry framework of the Global Industry Classification Standard (GICS) struggles to comprehensively represent risk for highly diversified multi-sector conglomerates like Amazon. Previously, we introduced the Multi-Industry Simplex (MIS), a probabilistic extension of GICS that utilizes topic modeling, a natural language processing approach. Although our initial version, MIS-1, was able to improve upon GICS by providing multi-industry representations, it relied on an overly simple architecture that required prior knowledge about the number of industries and relied on the unrealistic assumption that industries are uncorrelated and independent over time. We improve upon this model with MIS-2, which addresses three key limitations of MIS-1 : we utilize Bayesian Non-Parametrics to automatically infer the number of industries from data, we employ Markov Updating to account for industries that change over time, and we adjust for correlated and hierarchical industries allowing for both broad and niche industries (similar to GICS). Further, we provide an out-of-sample test directly comparing MIS-2 and GICS on the basis of future correlation prediction, where we find evidence that MIS-2 provides a measurable improvement over GICS. MIS-2 provides portfolio managers with a more robust tool for industry classification, empowering them to more effectively identify and manage risk, particularly around multi-sector conglomerates in a rapidly evolving market in which new industries periodically emerge.
William Bekerman, Marina Bogomolov, Ruth Heller
et al.
The harmful effects of growing up with a parent with an alcohol use disorder have been closely examined in children and adolescents, and are reported to include mental and physical health problems, interpersonal difficulties, and a worsened risk of future substance use disorders. However, few studies have investigated how these impacts evolve into later life adulthood, leaving the ensuing long-term effects of interest. In this article, we provide the protocol for our observational study of the long-term consequences of growing up with a father who had an alcohol use disorder. We will use data from the Wisconsin Longitudinal Study to examine impacts on long-term economic success, interpersonal relationships, physical, and mental health. To reinforce our findings, we will conduct this investigation on two discrete subpopulations of individuals in our study, allowing us to analyze the replicability of our conclusions. We introduce a novel statistical design, called data turnover, to carry out this analysis. Data turnover allows a single group of statisticians and domain experts to work together to assess the strength of evidence gathered across multiple data splits, while incorporating both qualitative and quantitative findings from data exploration. We delineate our analysis plan using this new method and conclude with a brief discussion of some additional considerations for our study.
An interaction site-based model of two-dimensional alcohols is proposed as a follow up of the recent SSMB site-site model for 2D water [J. Mol. Liq. 386 (2023 122475]. Computer simulation studies indicate that the model exhibits hbond-type clustering based on the same charge order feature observed in real alcohols. Hence, the equivalent of 2D mono-ols ranging from methanol to octanol were studied for their clustering properties, focusing on how the micro-structure affects the shape of the site-site pair correlation functions and structure factors, as well as the combination of the latter into the radiation scattering intensities. The major finding is the apparent contradiction between the existence of large pre-peaks in the structure factors, usually associated to the existence of clusters, and the exponential decay of the cluster distribution indicating the absence of specific clusters, contrary to the 3D case. This is resolved by realizing that the pair correlation function is an observable of the local density fluctuations, hence the pre-peak witnesses fluctuations around clustering tendencies, which are the result of charge ordering of the polar groups, and visible in the snapshots. The scattering pre-peak witnesses only fluctuations due to charge ordering, and not the clusters themselves, underlining the fact that these are labile entities. The study highlights how charge order through atomic sites is a universal feature behind the micro-structure of organized liquids, and, in the particular case of 2D liquids, a more realistic alternative to orientation based models such as the Mercedes-Benz model, for instance.
Ishmael Apachigawo, Dhruvil Solanki, Santanu Maity
et al.
Photonics/light localization techniques are important in understanding the structural changes in biological tissues at the nano- to sub-micron scale. It is now known that structural alteration starts at the nanoscale at the beginning of cancer progression. This study examines the molecular-specific nano-structural alterations of chronic alcoholism and probiotic effects on colon cancer using a mouse model of colon cancer. Confocal microscopy and mesoscopic light-scattering analysis are applied to quantify structural changes in DNA (chromatin), cytoskeleton, and ki-67 protein cells with appropriate staining dyes. We assessed alcohol-treated and azoxymethane (AOM) with dextran sulfate sodium (DSS)-induced colitis models, including ethanol (EtOH) and probiotic (L.Casei) treatments separately and together. The inverse participation ratio (IPR) technique was employed to quantify the degree of light localization to access the molecular-specific spatial structural disorder as a biomarker for cancer progression detection. Significant enhancement of cancer progression was observed in the alcohol-treated group, and probiotics treatment with alcohol showed partial reversal of these changes in colon cancer. The results underscore the potential of the IPR technique in detecting early structural changes in colon cancer, offering insights into the mitigating effects of probiotics on alcohol-induced enhancement of colon cancer.
Developing a green and cost-effective catalytic system for the selective oxidation of biomass-derived alcohols is vital for the sustainable synthesis of fine chemicals. Herein, highly dispersed subnanometric amorphous CoOx clusters in anatase TiO2 nanosheets (Co-TiO2) fabricated by green solvent CO2 assisted approach could directly activate peroxymonosulfate (PMS) for the highly selective oxidation of various biomass-derived alcohols. Advanced characterizations (e.g., EXAFS, EPR, AC HAADF-STEM) reveal that a strong interaction of CoOx clusters and the anatase TiO2 support exist in Co-TiO2 and Co atom in Co-TiO2 is mainly consisted of Co2+ and Co3+. The Co-TiO2 catalyst offers superior catalytic performance in the conversion of six types of alcohols (e.g., benzyl alcohol (BAL), 5-hydroxymethylfurfural (HMF)) with high selectivity to produce corresponding aldehydes. Highly dispersed CoOx clusters and the interaction between CoOx clusters and TiO2 support contribute to the superior performance. Mechanism studies show that SO4 radicals play the dominant role in the selective oxidation of model reactant BAL and 1O2 participates in the non-radical pathway. DFT calculations are well matched with experiment and decipher that the strong interaction between CoOx clusters and TiO2 support promotes the formation of SO4 and SO5.
This review critically examines the multifaceted role of acetic acid bacteria (AAB) in the intricate production process of port wine vinegar, particularly in its transformative process from port wine. With the emergence of port wine vinegar as a distinctive agricultural product in 2018, producers have been faced with a diverse array of challenges, ranging from reducing the high alcohol content to preserving the inherent sweetness. Through an exhaustive exploration of acetic fermentation processes and the indispensable role of AAB, this review meticulously elucidates the complex biochemistry underlying vinegar formation, delving into the nuanced interactions between microbial activity and chemical composition. Furthermore, this review underscores the importance of sensory characteristics and consumer perception derived from vinegar production, providing invaluable insights into these fermented products’ sensory profiles and marketability. In summary, this study offers valuable insights into the evolution of port wine into vinegar, highlighting its significance in agricultural and culinary contexts.
<i>Vibrio cholerae</i> and <i>Vibrio parahaemolyticus</i> are common pathogens linked to human gastroenteritis, particularly in seafood like shrimp. This study investigated the impact of lactic acid bacteria on <i>V. cholerae</i> and <i>V. parahaemolyticus</i> regarding the production of cadaverine, a concerning compound. <i>V. cholerae</i> NCCP 13589 and <i>V. parahaemolyticus</i> ATCC 27969 were significant producers of amines in experiments conducted using white-leg shrimp (<i>Litopenaeus vannamei</i>) and lysine decarboxylase broth. Notably, the <i>Lactiplantibacillus plantarum</i> NCIMB 6105 and <i>Leuconostoc mesenteroides</i> ATCC 10830 lactic acid bacteria strains demonstrated a pronounced antagonistic effect on the production of biogenic amines by these food-borne pathogenic bacteria. The presence of lactic acid bacteria led to a substantial reduction in cadaverine production in the lysine decarboxylase broth and shrimp extract. The co-culture of two lactobacilli species reduced the cadaverine production in <i>V. cholerae</i> and <i>V. parahaemolyticus</i> by approximately 77 and 80%, respectively. Consequently, the favorable influence of lactic acid bacteria in curbing cadaverine production by food-borne pathogens presents clear advantages for the food industry. Thus, effectively managing these pathogens could prove pivotal in controlling the biogenic amine levels in shrimp.
Dhanush Kenchanna, Tina Marie Waliczek, Merritt L. Drewery
Black Soldier Fly (<i>Hermetia illucens</i>) is well-known for having a high protein and lipid content during its larval stage and is cultivated for animal feed. Rearing Black Soldier Fly larvae (BSFL) produces byproducts known as frass and larval sheddings in large volumes with limited applications. Therefore, there is a need to identify viable sustainable management strategies to prevent potential environmental issues associated with their accumulation. Accordingly, the purpose of this study was to evaluate BSFL frass and larval sheddings as viable ingredients in composts that utilize additional nitrogen feedstocks. Four experimental compost piles (22.7 m<sup>3</sup>) with different ratios of BSFL frass and sheddings were developed based on previous research; two piles included 25% frass, whereas the other two included 30% frass. Across these piles, the inclusion of wood chips, food waste, and livestock manure varied to determine the best proportions for compost. The compost piles were maintained for five months, including a curing phase. After curing, samples from each pile were collected to analyze their pH, macro- and micro-nutrients, particle size, stability, and maturity. The findings indicated that the pH levels (7.1–8.1) and carbon-to-nitrogen ratios (10.40–13.20) were within the optimal ranges for all piles. The phosphorus levels (0.75–1.30%) of each pile exceeded typical ranges, likely due to the high phosphorus content of the frass itself. The moisture content varied widely (24.5–51.7%), with some piles falling below optimal levels. Stability and maturity tests yielded mixed results, with some piles demonstrating continued decomposition activity. Overall, the findings indicated that inclusion rates of 25–30% of BSFL frass and sheddings produced compost with generally favorable characteristics when high nitrogen feedstocks were also incorporated into the compost piles. These findings align with those from previous research and highlight both the potential and challenges of incorporating BSFL frass into compost production.
In this research, five commercial lactic acid bacteria (LAB) strains were selected for the fermentation of blended edible rose and shiitake beverage for their frequent application and strong adaptability in plant-based beverages. The viable counts of all strains reached above 10.0 log CFU/mL in the blended beverage after fermentation (48 h). Meanwhile, higher contents of total phenols, total flavonoids, free amino acids, and flavor nucleotide as well as stronger antioxidant capacity were observed in the fermented samples than the control. The results of electronic tongue (E-tongue) analysis showed that LAB fermentation significantly (p＜0.05) lowered the signals of bitterness, astringency, aftertaste-A, and aftertaste-B, which ultimately improved the taste profiles of the fermented samples. Additionally, a total of 76 volatiles compounds were detected, among which alcohols were the dominant compounds. LAB fermentation also enriched the aroma complex of the fresh beverage, which resulted in new compounds, including 13 alcohols, 9 acids, 6 ketones, 4 esters, and 5 hydrocarbons in the fermented samples.
Gluconic acid (GA) and its derivatives, as multifunctional biological chassis compounds, have been widely used in the food, medicine, textile, beverage and construction industries. For the past few decades, the favored production means of GA and its derivatives are microbial fermentation using various carbon sources containing glucose hydrolysates due to high-yield GA production and mature fermentation processes. Advancements in improving fermentation process are thriving which enable more efficient and economical industrial fermentation to produce GA and its derivatives, such as the replacement of carbon sources with agro-industrial byproducts and integrated routes involving genetically modified strains, cascade hydrolysis or micro- and nanofiltration in a membrane unit. These efforts pave the way for cheaper industrial fermentation process of GA and its derivatives, which would expand the application and widen the market of them. This review summarizes the recent advances, points out the existing challenges and provides an outlook on future development regarding the production of GA and its derivatives by microbial fermentation, aiming to promote the combination of innovative production of GA and its derivatives with industrial fermentation in practice.
Saccharomyces cerevisiae is commonly used as a starter culture for alcoholic beverages but is less applied in meat products. In this study, the effects of S. cerevisiae LXPSC1 on sour meat during fermentation were investigated. It was found that samples inoculated with S. cerevisiae LXPSC1 (Sc group) had better sensory characteristics and higher levels of pH, ethanol, free amino acids (FAAs), volatile organic compounds (VOCs). The bacterial communities of both groups were dominated by Lactobacillus sakei, Weissella hellenica, and Lactobacillus plantarum, which might play a role in reducing pH and aw and increasing the content of lactic acid, FAAs, and esters. However, Candida zeylanoides and S. cerevisiae were the dominant fungi in the control group and Sc group, respectively. Moreover, S. cerevisiae was positively related to esters, alcohols, ethanol and total VOCs. Overall, S. cerevisiae LXPSC1 might be regarded as a desirable starter culture for improving product quality.
Brewing industry is one of the most progressive and dynamically developing areas of the food and beverage industry in the world. In Kazakhstan brewing is currently the most developed segment of the beverage market. In recent years, production capacities have been increasing, the range of products has been expanding, and craft brewing has been developing. Non-alcoholic beer is becoming more and more popular. The production technology is carried out in two ways - it is the dealcoholization of the finished drink, or a change in the technological processes of production. In the presented article, the possibility of preparing a low-gravity wort and fermenting it with various strains of yeast for the preparation of non-alcoholic beer is investigated. The technological characteristics of three types of yeast used for the production of low-alcohol drinks, fermentation activity and absorption of solids during fermentation were studied. It has been established that the yeast strain Saf Brew TM LA-01 has the lowest degree of fermentation and is most suitable for the fermentation of low-gravity wort in the production of non-alcoholic beer. The mode of fermentation and post-fermentation of beer has been selected, as a result of which the content of ethyl alcohol does not exceed 0.5 vol.% and contains fermentation by-products in quantities corresponding to established standards.
Agricultural production heavily exploits the soil, resulting in high erosion in cultivated land, which poses a threat to food security and environmental sustainability. To address this issue, we stabilize the soil using polyvinyl alcohol (PVA). PVA strongly adheres to the soil after mixing and annealing, enhancing the cohesive strength of the soil. The PVA-soil withstands the impact of water at 7 m/s, protecting it from rainfall-induced erosion. Furthermore, the water-retaining capability and drainage of PVA-soil can be adjusted based on its sizes. This customized PVA-soil provides optimal growing conditions for various plants in different climates. Our method contributes to improved soil management and conversion.
We consider a Prohorov metric-based nonparametric approach to estimating the probability distribution of a random parameter vector in discrete-time abstract parabolic systems. We establish the existence and consistency of a least squares estimator. We develop a finite-dimensional approximation and convergence theory, and obtain numerical results by applying the nonparametric estimation approach and the finite-dimensional approximation framework to a problem involving an alcohol biosensor, wherein we estimate the probability distribution of random parameters in a parabolic PDE. To show the convergence of the estimated distribution to the "true" distribution, we simulate data from the "true" distribution, apply our algorithm, and obtain the estimated cumulative distribution function. We then use the Markov Chain Monte Carlo Metropolis Algorithm to generate random samples from the estimated distribution, and perform a generalized (2-dimensional) two-sample Kolmogorov-Smirnov test with null hypothesis that our generated random samples from the estimated distribution and generated random samples from the "true" distribution are drawn from the same distribution. We then apply our algorithm to actual human subject data from the alcohol biosensor and observe the behavior of the normalized root-mean-square error (NRMSE) using leave-one-out cross-validation (LOOCV) under different model complexities.