Xuelian Yang

Fermented meat flavouring, characterized by its natural, layered, and rich sensory profile, addresses the growing demand for premium and differentiated food products, and has become a prominent research area in the flavour industry. This study elucidated the precursor‐flavour relationships in dual‐strain fermentation using O2PLS modelling, enabling targeted process optimization and substantial quality improvement. Meat flavouring was first prepared through multi‐strain fermentation of soybean protein, followed by the Maillard reaction. HPLC was subsequently employed to quantitatively track the dynamic changes of free amino acids, while key volatile flavour compounds were identified through HS‐SPME‐GC‐O‐MS combined with AEDA. The O2PLS model was then applied to elucidate the correlation between free amino acids and volatile flavour compounds, revealing alanine, arginine, histidine, and the < 1000 Da peptide content as critical precursors for target optimization. Under optimal conditions (40 h fermentation, 10% inoculum, 1:1 inoculation ratio, the total amino acid content of the resulting sample was 142.2 ± 2.69 mg/100 mL, and the peptide components with molecular weights < 1000 Da was 84.9% ± 1.11%, p < 0.05), sensory evaluation confirmed significantly enhanced intensity of meaty (3.2 ± 0.2, p < 0.05), roasted (1.62 ± 0.01, p < 0.05), and caramel (1.6 ± 0.47, p < 0.05) notes with reduced sulfur (1.0 ± 0.22, p < 0.05) off‐odour. This study provides theoretical insights and technical guidance for flavour quality modulation of fermented meat flavourings, contributing to the advancement of flavour‐oriented regulation strategies in fermented seasoning systems.

The fermentation cycle critically influences flavor formation in Laobaigan Baijiu, but its effect on the bacterial community–flavor compound correlation remains unclear. This study investigated the co-variation between bacterial community turnover and flavor changes across distinct fermentation rounds of Hengshui Laobaigan Baijiu. Bacterial community structure was characterized via high-throughput sequencing (HTS), while volatile flavor compounds were profiled using headspace solid-phase microextraction combined with gas chromatography–mass spectrometry (HS-SPME–GC–MS). Partial least squares regression (PLSR) revealed their correlation. The analysis revealed 45 volatile compounds in total, with the D-2–D-3 stages serving as the peak production period and stages E-5–E-6 as the key formation period for esters. Lactobacillus dominated the early Dacha (first batch) fermentation, whereas Pseudomonas, Chryseobacterium, and Delftia became dominant after Jiuqu addition in Ercha (second batch). Sphingomonas and Pseudomonas were the major flavor contributors, showing very strong correlations with 9 and 6 compounds, respectively. Sphingomonas was positively correlated with nine compounds (e.g., isoamyl acetate, ethyl pentanoate, acids, benzaldehyde), while Pseudomonas was positively correlated with six esters (e.g., ethyl acetate, ethyl butyrate). Delftia, Pantoea, and Lactobacillus also played important roles in volatile formation. This study establishes a correlation network between bacterial communities and flavor compounds in a multi-round solid-state fermentation system, offering a methodological reference for flavor regulation not only in Laobaigan Baijiu but potentially in other traditional fermented foods with similar batch fermentation processes. This study provides theoretical support for the optimization of Laobaigan Baijiu fermentation and the enhancement of final Baijiu quality.

To investigate the core fungal community succession and its effects of volatile compound production during different stages (D-1, D-2, D-3, E-4, E-5, and E-6) of Hengshui Laobaigan Baijiu, high-throughput sequencing (HTS) was carried out, accompanied by the identification and quantification of the volatile flavor compounds using headspace solid-phase coupled with gas chromatography–mass spectrometry (HS-SPME-GC-MS). HTS results demonstrated that the fungal community of stage D-1 was similar to that of E-4 after adding Daqu, while the richness and diversity of the fungal community were most prominent at stage E-6. Moreover, the addition of Daqu at the beginning of Ercha fermentation resulted in a significant increase in the relative abundances of the fungal community at the genus level, setting the stage for the production of volatile compounds. GC–MS analysis revealed the presence of a total of 45 volatile compounds. Combining the GC-MS result with the heat map and principal component analysis (PCA), the concentrations of volatile compounds were highest in stage E-5. Meanwhile, concentrations of esters, especially ethyl acetate, ethyl lactate, isoamyl acetate and ethyl hexanoate, were high in both stages E-5 and E-6. This indicated that stage E-5 was crucial to the fermentation process of Laobaigan Baijiu. Three fungal genera (Saccharomyces, Candida, and Pichia) were indicated as the core microbiota for the production of the main volatile flavor compounds of Laobaigan Baijiu through partial least square (PLS) analysis. The information provided in this study offered valuable insights into the fermentation mechanism of Laobaigan Baijiu, thereby serving as a theoretical framework for enhancing the quality of Baijiu and realizing cost-effective production.

To comprehensively understand the volatile flavor composition of dry-rendered beef fat, solvent-assisted flavor evaporation (SAFE) with four extraction solvents (dichloromethane, pentane, ethyl ether, and methanol) combined with gas chromatography–mass spectrometry (GC–MS) and gas chromatography–olfactormetry (GC–O) were performed. GC–MS analysis found 96 different volatile compounds in total using the four extraction solvents. According to the GC–MS results and the heat map and principal component analysis (PCA), most of the volatile compounds resulted from dichloromethane and pentane extraction, followed by ethyl ether. Methanol extraction found a few volatile compounds of higher polarity, which was supplementary to the analysis results. Moreover, GC–O analysis found 73 odor-active compounds in total using the four extraction solvents. The GC–O results found that pentane and dichloromethane extraction had a significantly larger number of odor-active compounds than ethyl ether and methanol extraction. This indicated that pentane and dichloromethane were more effective solvents for the extraction of odor-active compounds than the other two solvents. Finally, a total of 15 compounds of odor-active values (OAVs) ≥ 1 were determined to be the key aroma compounds in the dry-rendered beef fat, including 2–methyl–3–furanthiol, 3–methylthiopropanal, (E,E)–2,4–nonadienal, 12–methyltridecanal, and 1–octen–3–one.

BACKGROUND: Monacolin K, an important secondary metabolite of Monascus, possesses a cholesterol‐lowering effect and is widely used in the manufacture of antihypertensive drugs. In the present study, we constructed an extractive fermentation system by adding non‐ionic surfactant and acquired a high monacolin K yield. The mechanism was determined by examining both cell morphology and the transcription levels of the related mokA‐I genes in the monacolin K biosynthetic gene cluster.RESULTS: The monacolin K yield was effectively increased to 539.59 mg L⁻¹ during extraction, which was an increase of 386.16% compared to that in the control group fermentation. The non‐ionic surfactant showed good biocompatibility with Monascus. Electron scanning microscopy revealed alterations in the morphology of Monascus. The loosened mycelial structure and increased number of cell surface wrinkles were found to be related to the increased cell‐membrane permeability and extracellular accumulation of monacolin K. Gene expression levels were measured via a quantitative reverse transciptase‐polymerase chain reaction. By contrast, in the control group, mokA, mokB, mokC, mokD and mokF showed higher‐level and longer‐term expression in the extractive fermentation group, whereas mokE and mokG did not present a similar trend. The expression levels of mokH and mokI, encoding a transcription factor and efflux pump, respectively, were also higher than the control levels.CONCLUSION: The addition of a non‐ionic surfactant to Monascus fermentation effectively increases the yield of monacolin K by transforming the fungus morphology and promoting the expression of monacolin K biosynthesis genes. © 2021 Society of Chemical Industry.

BACKGROUND: Nonionic surfactant Brij 35 in submerged fermentation of Monascus can significantly increase Monascus pigment yield. Here, the effects of nonionic surfactant Brij 35 on Monascus pigment secretion in extractive fermentation are discussed in terms of cell morphology, cloud point change, and pigment stability.RESULTS: At Brij 35 concentrations up to 32 g L⁻¹, the higher concentrations led to the loosening of the network structure on the surface of the fungal wall, enhanced cell wall permeability, and increased abundance of lipid droplets. Alternatively, when the concentration of Brij 35 exceeded 32 g L⁻¹, a large amount of substances accumulated on the surface of the fungal wall, permeability reduced, and the degree of oil droplet dispersion in cells decreased. Further, during extractive fermentation, Brij 35 induced formation of a grid structure on the fungal wall surface beginning on day 2, increased the number of intracellular lipid droplets, and promoted intracellular pigment secretion into the extracellular environment. When the cloud point temperature in the fermentation system approached that of fermentation, the nonionic surfactant exhibited stronger Monascus pigment extraction capacity, thereby enhancing pigment yield. Hence, Brij 35 can improve pigment stability and effectively reduce damage caused by natural factors, such as light and temperature.CONCLUSION: Brij 35 promotes the secretion of pigment by changing the fungal wall structure and cloud point, as well as by improving pigment stability. © 2020 Society of Chemical Industry

BACKGROUND: Different nonionic surfactants in submerged fermentation of Monascus sp. demonstrate significant differences regarding increasing pigment yield. In this study, 15 surfactants from five series were analyzed to investigate the influence of nonionic surfactants on Monascus pigments, with the aim of simultaneously obtaining a novel nonionic surfactant.RESULTS: Addition of the novel surfactant Brij 35 greatly enhanced pigment excretion and demonstrated good biocompatibility. Extracellular red, orange and yellow pigments increased by 1.47‐, 1.71‐ and 2.07‐fold respectively. Production of extracellular pigments was not only related to the hydrophile–lipophile balance value (HLB) but also affected by the cloud point temperature (CP) of the fermentation medium. It was found that nonionic surfactants can improve cell membrane permeability and cell storage capacity by modifying the cell walls of Monascus mycelium and by increasing lipid droplet levels, enhancing pigment excretion. Different nonionic surfactants modify Monascus mycelium to different degrees.CONCLUSION: The novel surfactant Brij 35, which has good capacity for pigment extraction and biocompatibility, was identified in the analysis. The effects of nonionic surfactants on the secretion of pigments are related to not only the modification of the cell wall and internal structure but also the CP and HLB. © 2018 Society of Chemical Industry