Machine learning based age-authentication assisted by chemo-kinetics: Case study of strong-flavor Chinese Baijiu

Decoding the Qu-aroma of medium-temperature Daqu starter by volatilomics, aroma recombination, omission studies and sensory analysis

Qu-aroma is of great significance for evaluation the quality of Daqu starter. This study aimed to decode the Qu-aroma of medium-temperature Daqu (MT-Daqu) via "top-down" and "bottom-up" approaches. Firstly, 52 aroma descriptors were defined to describe the MT-Daqu aroma by quantitative descriptive analysis. Secondly, 193 volatile organic compounds (VOCs) were identified from 42 MT-Daqu samples by HS-SPME-GC-MS, and 43 dominant VOCs were screened out by frequence of occurrence or abundance. By Thin Film (TF)-SPME-GC-O-MS, 27 odors and 90 VOCs were detected in MT-Daqu mixture, and 14 odor-active VOCs were screened out by odor intensity. Thirdly, a five-level MT-Daqu aroma wheel was constructed by matching 52 aroma descriptors and 37 aroma-active VOCs. Finally, Qu-aroma of MT-Daqu was reconstructed with 37 aroma-active VOCs and evaluated by omission experiments. Hereinto, 26 key aroma-active VOCs were determined by OAV value ≥1, including isovaleric acid, 1-hexanol, isovaleraldehyde, 2-octanone, trimethylpyrazine, γ-nonalactone, 4-vinylguaiacol, etc.

Unveiling the synthesis of aromatic compounds in sauce-flavor Daqu from the functional microorganisms to enzymes

Aromatic compounds serve as the primary source of floral and fruity aromas in sauce-flavor (Maotai flavor) baijiu, constituting the skeleton components of its flavor profile. Nevertheless, the formation mechanism of these compounds and key aroma-producing enzymes in sauce-flavor Daqu (fermentation agent, SFD) remain elusive. Here, we combined metagenomics, metaproteomics, metabolomics, and key enzyme activity to verify the biosynthesis pathway of aromatic compounds and to identify key enzymes, genes, and characteristic microorganisms in SFD. The results showed that the later period of fermentation was critical for the generation of aromatic compounds in SFD. In-situ verification was conducted on the potential key enzymes and profiles in various metabolites, providing comprehensive evidence for the main synthetic pathways of aromatic compounds in SFD. Notably, our results showed that primary amine oxidase (PrAO) and aldehyde dehydrogenase (ALDH) emerged as two key enzymes promoting aromatic compound synthesis. Additionally, two potential key functional genes regulating aromatics generation were identified during SFD fermentation through correlation analysis between proteins and relevant metabolites, coupled with in vitro amplification test. Furthermore, original functional strains (Aspergillus flavus-C10 and Aspergillus niger-IN2) exhibiting high PrAO and ALDH production were successfully isolated from SFD, thus validating the results of metagenomics and metaproteomics analyses. This study comprehensively elucidates the pathway of aromatic compound formation in SFD at the genetic, proteomic, enzymatic, and metabolomic levels, providing new ideas for the investigation of key flavor substances in baijiu. Additionally, these findings offer valuable insights into the regulatory mechanisms of aromatic compounds generation.

Organic-Acid-Sensitive Visual Sensor Array Based on Fenton Reagent-Phenol/Aniline for the Rapid Species and Adulteration Assessment of Baijiu

Baijiu is an ancient, distilled spirit with a complicated brewing process, unique taste, and rich trace components. These trace components play a decisive role in the aroma, taste, and especially the quality of baijiu. In this paper, the redox reaction between the Fenton reagent and four reducing agents, including o-phenylenediamine (OPD), p-phenylenediamine (PPD), 4-aminophenol (PAP), and 2-aminophenol (OAP), was adopted to construct a four-channel visual sensor array for the rapid detection of nine kinds of common organic acids in baijiu and the identification of baijiu and its adulteration. By exploiting the color-changing fingerprint response brought by organic acids, each organic acid could be analyzed accurately when combined with an optimized variable-weighted least-squares support vector machine based on a particle swarm optimization (PSO-VWLS-SVM) model. What is more, this novel sensor also could achieve accurate semi-quantitative analysis of the mixed organic acid samples via partial least squares discriminant analysis (PLSDA). Most importantly, the sensor array could be further used for the identification of baijiu with different species through the PLSDA model and the adulteration assessment with the one-class partial least squares (OCPLS) model simultaneously.

Insight investigation into the response pattern of microbial assembly succession and volatile profiles during the brewing of sauce-flavor baijiu based on bioaugmentation

To improve the flavor profile and sensory quality of baijiu, the utilization of bioaugmented fermentation inoculated with functional microbiota normally serves as an effective method for directional regulation during the baijiu fermentation process. In this study, a systematic analysis of the succession patterns and volatile flavor compound profiles of microbial communities was carried out by high-throughput sequencing and solid-phase microextraction gas chromatography-mass spectrometry, respectively. The results demonstrated that the Saccharomyces cerevisiae YS222-related bioaugmentation clearly altered the microbial composition, particularly the assembly of bacteria, and promoted the quantity of the most volatile flavoring compounds, including alcohols, esters, and pyrazines. In addition, the correlation analysis showed that Saccharomyces and Lactobacillus in the augmented group were the main biomarkers associated with the dynamics of microbial community and greatly contributed to the brewing of sauce-flavor baijiu, which congruent with the outcomes of the enrichment analysis of integrated metabolic pathway. Thus, this work is beneficial for promoting the quality of baijiu and will serve as a useful reference for clarifying the possible mechanism of augmented fermentation on flavor development.

Exploring the Role of Active Functional Microbiota in Flavor Generation by Integrated Metatranscriptomics and Metabolomics during Niulanshan Baijiu Fermentation

Active functional microbiota for producing volatile flavors is critical to Chinese baijiu fermentation. Microbial communities correlated with the volatile metabolites are generally explored using DNA-based sequencing and metabolic analysis. However, the active functional microbiota related to the volatile flavor compounds is poorly understood. In this study, an integrated metatranscriptomic and metabolomics analysis was employed to unravel the metabolite profiles comprehensively and the contributing active functional microbiota for flavor generation during Niulanshan baijiu fermentation. A total of 395, 83, and 181 compounds were annotated using untargeted metabolomics, including LC-MS, GC-MS, and HS-SPME-GC-MS, respectively. Significant variances were displayed in the composition of compounds among different time-point samples according to the heatmaps and orthogonal partial least-square discriminant analysis. The correlation between the active microbiota and the volatile flavors was analyzed based on the bidirectional orthogonal partial least squares discriminant analysis (O2PLS-DA) model. Six bacterial genera, including Streptococcus, Lactobacillus, Pediococcus, Campylobacter, Yersinia, and Weissella, and five fungal genera of Talaromyces, Aspergillus, Mixia, Rhizophagus, and Gloeophyllum were identified as the active functional microbiota for producing the volatile flavors. In summary, this study revealed the active functional microbial basis of unique flavor formation and provided novel insights into the optimization of Niulanshan baijiu fermentation.

Application of GC-IMS coupled with chemometric analysis for the classification and authentication of geographical indication agricultural products and food

Geographical indications (GI) are used to protect the brand value of agricultural products, foodstuffs, and wine and promote the sustainable development of the agricultural and food industries. Despite the necessity for the traceability and recognition of GI product characteristics, no rapid, non-destructive approaches currently exist to identify, classify, and predict these properties. The application of gas chromatography-ion mobility spectrometry (GC-IMS) has increased exponentially due to instrument robustness and simplicity. This paper provided a detailed overview of recent GC-IMS applications in China for the quality evaluation of GI products and food, including agricultural products, as well as traditional Chinese food and liquor. The general workflow of GC-IMS coupled with chemometric analysis is presented, including sample collection, model construction and interpretation, and data acquisition, processing, and fusion. Several conclusions are drawn to increase partial least squares-discriminant analysis (PLS-DA) model precision, a chemometric technique frequently combined with GC-IMS.

Integration of Chemometrics and Sensory Metabolomics to Validate Quality Factors of Aged Baijiu (Nianfen Baijiu) with Emphasis on Long-Chain Fatty Acid Ethyl Esters

The storage process of Baijiu is an integral part of its production (the quality undergoes substantial changes during the aging process of Baijiu). As the storage time extends, the flavor compounds in Baijiu tend to undergo coordinated transformation, thereby enhancing the quality of Baijiu. Among them, long-chain fatty acid ethyl esters (LCFAEEs) were widely distributed in Baijiu and have been shown to have potential contributions to the quality of Baijiu. However, the current research on LCFAEEs in Baijiu predominantly focuses on the olfactory sensation aspect, while there is a lack of systematic investigation into their influence on taste and evaluation after drinking Baijiu during the aging process. In light of this, the present study investigates the distribution of LCFAEEs in Baijiu over different years. We have combined modern flavor sensory analysis with multivariate chemometrics to comprehensively and objectively explore the influence of LCFAEEs on Baijiu quality. The results demonstrate a significant positive correlation between the concentration of LCFAEEs and the fruity aroma (p < 0.05, r = 0.755) as well as the aged aroma (p < 0.05, r = 0.833) of Baijiu within a specific range; they can effectively reduce the off-flavors and spicy sensation of Baijiu. Furthermore, additional experiments utilizing a single variable suggest that LCFAEEs were crucial factors influencing the flavor of Baijiu, with Ethyl Palmitate (EP) being the most notable LCFAEE that merits further systematic investigation.