Comparison between ATR-IR, Raman, concatenated ATR-IR and Raman spectroscopy for the determination of total antioxidant capacity and total phenolic content of Chinese rice wine

Determination of antioxidant capacity and phenolic content of haskap berries (Lonicera caerulea L.) by attenuated total reflectance-Fourier transformed-infrared spectroscopy

The total phenolic content (TPC) and antioxidant capacity (TAC) of haskap berries cultivated in various locations across Alberta were analyzed using attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy. The Folin-Ciocalteu assay was used to determine TPC, while TAC was quantified by 2,2-diphenyl-1-picrylhydrazl radicals (DPPH) assay and oxygen radical absorbance capacity (ORAC) assay. Three tenfold cross-validated partial least-squares regression (PLSR) models and three fivefold cross-validated deep learning models were developed separately based on FT-IR spectra collected from 22 haskap berry samples and their corresponding reference values determined through Folin-Ciocalteu, DPPH, and ORAC assays. The deep learning models (R2 = 0.95, 0.93, and 0.90 for Folin-Ciocalteu, DPPH, and ORAC assays, respectively) demonstrated better prediction capability compared to the PLSR models (R2 = 0.74, 0.72, and 0.66 for Folin-Ciocalteu, DPPH, and ORAC assays, respectively). In addition, PLS loading plots indicated that phenolic contents and polysaccharides in haskap berries could contribute to their antioxidant capacity. Using ATR-FTIR to estimate the TPC and TAC of fruits offers a rapid alternative to the conventional chemical assays.

Characterization of differences in physicochemical properties, volatile organic compounds and non-volatile metabolites of prune wine by inoculation of different lactic acid bacteria during malolactic fermentation

To investigate the effects of inoculating with three strains of lactic acid bacteria on prune wine quality during malolactic fermentation, this study determined its antioxidant activity, phenolic compounds, organic acids, and volatile/non-volatile metabolites. The results showed that inoculation with Lactobacillus paracasei SMN-LBK improved the antioxidant activity and phenolic compounds of prune wine. 73 VOCs were detected in prune wine by HS-SPME-GC-MS, and VOC content increased by 4.3% and 9.1% in MLFS and MLFB, respectively. Lactobacillus delbrueckii subsp. Bulgaricus showed better potential for winemaking, and citral and 5-nonanol, were detected in the MLF samples. 39 shared differential metabolites were screened and their metabolic pathways were investigated based on nontargeted metabolomics. Differences in amino acid and flavonoid content between strains reflected their specificity in flavonoid biosynthesis and amino acid biosynthesis. These findings will provide useful information for the biochemical study and processing of prune wine.

Engineering an enzyme-like catalytic sensor for on-site dual-mode evaluation of total antioxidant capacity

A novel Fe-MoOx nanozyme, engineered with enhanced peroxidase (POD)-like activity through strategic doping and the creation of oxygen vacancies, is introduced to catalyze the oxidation of TMB with high efficiency. Furthermore, Fe-MoOx is responsive to single electron transfer (SET) and hydrogen atom transfer (HAT) mechanisms related to antioxidants and can serve as a desirable nanozyme for total antioxidant capacity (TAC) determination. The TAC colorimetric platform can reach a low LOD of 0.512 μM in solution and 24.316 μM in the smartphone-mediated RGB hydrogel (AA as the standard). As proof of concept, the practical application in real samples was explored. The work paves a promising avenue to design diverse nanozymes for visual on-site inspection of food quality.

Application of Strain Selection Technology in Alcoholic Beverages: A Review

The diversity of alcohol beverage microorganisms is of great significance for improving the brewing process and the quality of alcohol beverage products. During the process of making alcoholic beverages, a group of microorganisms, represented by yeast and lactic acid bacteria, conducts fermentation. These microorganisms have complex synergistic or competitive relationships, and the participation of different microorganisms has a major impact on the fermentation process and the flavor and aroma of the product. Strain selection is one of the key steps. Utilizing scientific breeding technology, the relationship between strains can be managed, the composition of the alcoholic beverage microbial community can be improved, and the quality and flavor of the alcoholic beverage products can be increased. Currently, research on the microbial diversity of alcohol beverages has received extensive attention. However, the selection technology for dominant bacteria in alcohol beverages has not yet been systematically summarized. To breed better-quality alcohol beverage strains and improve the quality and characteristics of wine, this paper introduces the microbial diversity characteristics of the world's three major brewing alcohols: beer, wine, and yellow wine, as well as the breeding technologies of related strains. The application of culture selection technology in the study of microbial diversity of brewed wine was reviewed and analyzed. The strain selection technology and alcohol beverage process should be combined to explore the potential application of a diverse array of alcohol beverage strains, thereby boosting the quality and flavor of the alcohol beverage and driving the sustainable development of the alcoholic beverage industry.

Sustainable Valorization of Coffee Silverskin: Extraction of Phenolic Compounds and Proteins for Enzymatic Production of Bioactive Peptides

Coffee silverskin (CS), a by-product of the coffee roasting process, has high protein content (16.2-19.0%, w/w), making it a potential source for plant protein and bioactive peptide production. This study aims to develop innovative extraction methods for phenolic compounds and proteins from CS. The conditions for hydrothermal (HT) extraction of phenolic compounds from CS were optimized by varying CS loading (2.5-10%, w/v), temperature (110-130 °C), and time (5-30 min) using a one-factor-at-a-time (OFAT) approach. The highest TPC of 55.59 ± 0.12 µmole GAE/g CS was achieved at 5.0% (w/v) CS loading and autoclaving at 125 °C for 25 min. Following hydrothermal extraction, CS protein was extracted from HT-extracted solid fraction by microwave-assisted alkaline extraction (MAE) using 0.2 M NaOH at 90 W for 2 min, resulting in a protein recovery of 12.19 ± 0.39 mg/g CS. The CS protein was then subjected to enzymatic hydrolysis using protease from Bacillus halodurans SE5 (protease_SE5). Protease_SE5-derived CS protein hydrolysate had a peptide concentration of 0.73 ± 0.09 mg/mL, with ABTS, DPPH, and FRAP values of 15.71 ± 0.10, 16.63 ± 0.061, and 6.48 ± 0.01 µmole TE/mL, respectively. Peptide identification by LC-MS/MS revealed several promising biological activities without toxicity or allergenicity concerns. This study's integrated approach offers a sustainable and efficient method for extracting valuable compounds from CS, with potential applications in the food and pharmaceutical industries.

Effects of Active Ingredients in Alcoholic Beverages and Their De-Alcoholized Counterparts on High-Fat Diet Bees: A Comparative Study

The mechanisms by which alcohol, alcoholic beverages, and their de-alcoholized derivatives affect animal physiology, metabolism, and gut microbiota have not yet been clarified. The polyphenol, monosaccharide, amino acid, and organic acid contents of four common alcoholic beverages (Chinese Baijiu, beer, Chinese Huangjiu, and wine) and their de-alcoholized counterparts were analyzed. The research further explored how these alcoholic beverages and their non-alcoholic versions affect obesity and gut microbiota, using a high-fat diet bee model created with 2% palm oil (PO). The results showed that wine, possessing the highest polyphenol content, and its de-alcoholized form, particularly when diluted five-fold (WDX5), markedly improved the health markers of PO-fed bees, including weight, triglycerides, and total cholesterol levels in blood lymphocytes. WDX5 treatment notably increased the presence of beneficial microbes such as Bartonella, Gilliamella, and Bifidobacterium, while decreasing Bombilactobacillus abundance. Moreover, WDX5 was found to closely resemble sucrose water (SUC) in terms of gut microbial function, significantly boosting short-chain fatty acids, lipopolysaccharide metabolism, and associated enzymatic pathways, thereby favorably affecting metabolic regulation and gut microbiota stability in bees.

Valorisation of sawdust-based spent mushroom substrate for sustainable xylooligosaccharides production using low-cost crude xylanases from Aspergillus flavus KUB2

Spent mushroom substrate (SMS), a lignocellulosic waste after mushroom production is generally discarded without proper management. There is increasing interest in the sustainable transformation of lignocellulosic waste into high-value products. Within this context, the present study investigated the potential of the SMS from the cultivation of Pleurotus pulmonarius and Auricularia auricula on rubber tree wood sawdust as substrates for xylooligosaccharides (XOS) production. SMS samples from these two edible mushrooms were extracted using alkaline xylan extraction, producing maximum true recovery amounts of xylan in the range 34.61%-37.49% using 18% NaOH at 70 °C for 3 h. Production of XOS from alkaline-extracted xylan from the SMS samples of both mushroom species using economically crude xylanases from Aspergillus flavus KUB2 resulted in XOS (X2-X5) production of 241.47-249.04 mg/g, with X3 as the predominant XOS product. The produced XOS had excellent prebiotic activity and 2,2'-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging activity and contained high total phenolic contents. The combined beneficial bioactivities in terms of prebiotic and antioxidant properties suggested that the XOS produced from sawdust-based SMS samples of P. pulmonarius and A. auricula could be promising ingredients for both food and pharmaceutical applications.

Quantitative analysis of moisture content and particle size in a fluidized bed granulation process using near infrared spectroscopy and acoustic emission combined with data fusion strategies

Monitoring granule property is essential for fluidization maintenance and product quality control in fluidized bed granulation (FBG). In this study, two non-invasive techniques, near-infrared (NIR) spectroscopy and acoustic emission (AE), were applied for quantitative analysis of moisture content (MC) and median particle size (D50) in a FBG process, combined with chemometrics and data fusion strategies. Partial least squares (PLS) and support vector machine (SVM) regression models were established based on NIR and AE spectral data. The optimal quantitative models were identified considering the effect of spectra preprocessing and variable selection. In the comparison study, the best separate models for MC and D50 quantification were based on NIR and AE, respectively. The NIR model exhibited the better prediction ability with the determination coefficient of validation set (R2v) of 0.9815, root mean square error of validation set (RMSEv) of 0.2226 %, and residual predictive deviation (RPD) of 7.4674 for MC. Meanwhile, the AE model presented the better prediction performance with R2v of 0.9710, RMSEv of 18.2643 μm, and RPD of 5.9740 for D50. Furthermore, among three data fusion strategies, the high-level fusion model achieved the best overall performance on D50 quantification with R2v of 0.9863, RMSEv of 12.5707 μm, and RPD of 8.6798. The results indicated that both NIR and AE are effective monitoring tools for MC and D50 analysis in fluidized bed granulation process. In addition, a more accurate and reliable analysis of particle size can be achieved by combining NIR and AE technology with high-level data fusion.

Non-destructive recognition of copy paper based on advanced spectral fusion and feature optimization

In order to provide more clues for ongoing investigations and case handling, as well as achieve fast, non-destructive, and accurate identification of copy paper found at crime scenes, this study aims to utilize advanced spectral fusion technology to characterize and identify the three-dimensional features of the "origin-manufacturer-brand" of copy paper. Confocal Raman Microscopic and Fourier transform infrared spectroscopy were employed to collect spectral data from 200 samples from four regions (Shandong, Henan, Shaanxi, Jiangsu). The effects of different preprocessing methods, such as Hilbert transformation and deconvolution, on the model's ability to distinguish were compared. Feature variables were extracted using principal component analysis, and Bayesian discriminant classification models were constructed based on single infrared spectroscopy, Raman spectroscopy, and three types of spectral fusion datasets. By comparing the classification accuracy of different models, the primary fusion based on the full spectrum dataset was selected as the optimal model for the three-dimensional feature classification of copy paper. The accuracy achieved for origin (96%), manufacturer (100%), and brand (100%) was satisfactory, and the classification results were highly accurate. This study provides valuable insights and serves as a reference for its application in forensic science research.

Assessing Fermentation Broth Quality of Pineapple Vinegar Production with a Near-Infrared Fiber-Optic Probe Coupled with Stability Competitive Adaptive Reweighted Sampling

In this study, the performance of a near-infrared (NIR) fiber-optic probe coupled with stability competitive adaptive reweighted sampling (SCARS) was investigated for the analysis of acetic acid, ethanol, total soluble solids, caffeic acid, gallic acid, and tannic acid in the broth of pineapple vinegar during fermentation. The NIR spectra of the broth samples in the region of 11,536-3956 cm-1 were collected during vinegar fermentation promoted by Acetobacter aceti. This continuous biological process led to changes in the concentrations of all analytes studied. SCARS provided optimized and stabilized NIR spectral variables for the construction of a partial least squares (PLS) model for each analyte using a small number of optimal variables (under 88 variables). The SCARS-PLS model outperformed the conventional PLS model, and achieved excellent accuracy in accordance with ISO 12099:2017 for the four prediction models of acetic acid, ethanol, caffeic acid, and gallic acid, with root-mean-square error of prediction values of 0.137%, 0.178%, 0.637 μg/mL and 0.640 μg/mL, respectively. In contrast, only an acetic acid content prediction model constructed via the conventional PLS method and using the whole spectral region (949 variables) could pass with acceptable accuracy. These results indicate that the NIR optical probe coupled with SCARS is an appropriate method for the continuous monitoring of multianalytes during vinegar fermentation, particularly acetic acid and ethanol contents, which are indicators of the finished fermentation of pineapple vinegar.

Adjustment of impact phenolic compounds, antioxidant activity and aroma profile in Cabernet Sauvignon wine by mixed fermentation of Pichia kudriavzevii and Saccharomyces cerevisiae

Mixed fermentation using saccharomyces cerevisiae and non-saccharomyces cerevisiae has become one of the main research strategies to improve wine aroma. Hence, this study applied the mixed fermentation technique using Pichia kudriavzevii and Saccharomyces cerevisiae to brew Cabernet Sauvignon wine and to investigate the effects of inoculation timing and inoculation ratio on the polyphenolics, antioxidant activity and aroma of the resulting wine. The results showed that mixed fermentation significantly improved the amounts of flavan-3-ols. In particular, S1:5 had the highest amounts of (-)-catechin and procyanidin B1 (73.23 mg/L and 46.59 mg/L), while S1:10 had the highest (-)-epicatechin content (57.95 mg/L). Meanwhile, S1:10 showed the strongest FRAP, CUPRAC and ABTS + activities (31.46 %, 25.38 % and 13.87 % higher than that of CK, respectively). In addition, mixed fermentation also increased the amounts of phenylethanol, isoamyl alcohol and ethyl esters, which enhanced the rose-like and fruity flavor of wine. This work used a friendly non-saccharomyces cerevisiae alongside appropriate inoculation strategies to provide an alternative approach for improved wine aroma and phenolic profile.

Flavor compounds with high odor activity values (OAV > 1) dominate the aroma of aged Chinese rice wine (Huangjiu) by molecular association

Aging is an essential operation to perfect the flavor quality of Hungjiu. In this study, formation mechanism of flavor compounds responsible for the characteristic flavor of aged Huangjiu was investigated. The contents of umami and bitter free amino acids (FAA) increased with the storage period prolonged, while that of sweet FAA showed downward trend. Gas chromatograph-mass spectrometry and principal component analysis indicated that the volatile flavor compounds with OAV exceed 1, especially middle-chain fatty-acid-ethyl-esters and aromatic compounds, dominated the characteristic flavor of aged Huangjiu. Low field-NMR was firstly applied to characterize the molecular association between water and dissolved flavor compounds in aged Huangjiu. The results showed that basic amino acids contributed greatly to the flavor formation of aged Huangjiu via molecular association. In addition, the molecular association significantly promoted the accumulation of flavor compounds with OAV > 1, especially ethyl esters.

Challenges and Opportunities of Implementing Data Fusion in Process Analytical Technology-A Review

The release of the FDA's guidance on Process Analytical Technology has motivated and supported the pharmaceutical industry to deliver consistent quality medicine by acquiring a deeper understanding of the product performance and process interplay. The technical opportunities to reach this high-level control have considerably evolved since 2004 due to the development of advanced analytical sensors and chemometric tools. However, their transfer to the highly regulated pharmaceutical sector has been limited. To this respect, data fusion strategies have been extensively applied in different sectors, such as food or chemical, to provide a more robust performance of the analytical platforms. This survey evaluates the challenges and opportunities of implementing data fusion within the PAT concept by identifying transfer opportunities from other sectors. Special attention is given to the data types available from pharmaceutical manufacturing and their compatibility with data fusion strategies. Furthermore, the integration into Pharma 4.0 is discussed.

Quality improvement of sweet rice wine fermented with Rhizopus delemar on key aroma compounds content, phenolic composition, and antioxidant capacity compared to Rhizopus oryzae

The pure culture fermentation has led to less flavorful rice wine and relatively lower bioactive substance level compared to traditional mixed culture fermentation; however, a pure strain is easily controlled by industrialized producers. The purpose of the present research was to screen a species of Rhizopus for improving the flavor deficiency and antioxidant function of sweet rice wine. Seven rice wine samples fermented with isolated strains were analyzed for their total phenolics, total flavonoids, peptide and antioxidant activity using spectrophotometry, as well as ethanol, ethyl acetate, β-phenethyl alcohol, and volatile alcohol contents measured by headspace gas chromatography (HS-GC), the further principal component analysis determined Rhizopus delemar rice wine better on aroma and antioxidant capacity. A comparison of phenolics profile between R. delemar and R. oryzae rice wines was made based on the measurement data of ultrahigh-performance liquid chromatography coupled with Q-exactive orbitrap mass spectrometry (UHPLC-QE-MS) data. Thirty-two phenolics were identified in sweet rice wine. Overall, the results presented in this study showed that a strain of R. delemar is available for the improvement of flavor and antioxidant activity in sweet rice wine, which has the great potential to be applied to industrialized products.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13197-021-05250-x.

Comparison of Phenolic Content and Antioxidant Activity for Fermented and Unfermented Rooibos Samples Extracted with Water and Methanol

Rooibos is brewed from the medicinal plant Aspalathus linearis. It has a well-established wide spectrum of bio-activity properties, which in part may be attributed to the phenolic antioxidant power. The antioxidant capacity (AOC) of rooibos is related to its total phenolic content (TPC). The relation between TPC and AOC of randomly selected 51 fermented (FR) and 47 unfermented (UFR) rooibos samples was studied after extraction using water and methanol separately. The resulted extracts were assessed using two antioxidant assays, trolox equivalent antioxidant capacity (TEAC) and ferric reducing antioxidant power (FRAP). The results were analyzed using both simple statistical methods and machine learning. The analysis showed different trends of TPC and AOC correlations of FR and UFR samples, depending on the solvent used for extraction. The results of the water extracts showed similar TPC and higher AOC of FR than UFR samples, while the methanolic extracted samples showed higher TPC and AOC of UFR than FR. As a result, the methanolic extracts showed better agreement between TPC and AOC than water extracts. Possible explanations are given for these observed results. Although, the current literature demonstrates direct correlations of the TPC and AOC of rooibos water extracts. This study showed deviation and highlighted the importance of solvent selection and analysis methodology as an important factor in determining the TPC/AOC correlation and subsequently the expectation of the actual health benefits of rooibos herbal tea. In particular, unfermented and fermented samples can be accurately identified on the basis of a combination of assays (any two of TPC, FRAP and TEAC), especially if methanol is the solvent used. Machine learning analysis of assay data provides nearly identical results with classical statistical analytical methods. This is the first report on machine learning analysis and comparison of the TPC and AOC of rooibos herbal tea extracted with methanol and water, and highlights the importance of using methanol as a solvent to evaluate its AOC.

Alcoholic Fermentation Monitoring and pH Prediction in Red and White Wine by Combining Spontaneous Raman Spectroscopy and Machine Learning Algorithms

In the following study, total sugar concentrations before and during alcoholic fermentation, as well as ethanol concentrations and pH levels after fermentation, of red and white wine grapes were successfully predicted using Raman spectroscopy. Fluorescing compounds such as anthocyanins and pigmented phenolics found in red wine present one of the primary limitations of enological analysis using Raman spectroscopy. Unlike the spontaneous Raman effect, fluorescence is a highly efficient process and consequently emits a much stronger signal than spontaneous Raman scattering. For this reason, many enological applications of Raman spectroscopy are impractical as the more subtle Raman spectrum of any red wine sample is in large part masked by fluorescing compounds present in the wine. This work employs a simple extraction method to mitigate fluorescence in finished red wines. Ethanol and total sugars (fructose plus glucose) of wines made from red (Cabernet Sauvignon) and white (Chardonnay, Sauvignon Blanc, and Gruner Veltliner) varieties were modeled using support vector regression (SVR), partial least squares regression (PLSR) and Ridge regression (RR). The results, which compared the predicted to measured total sugar concentrations before and during fermentation, were excellent (R2SVR = 0.96, R2PLSR = 0.95, R2RR = 0.95, RMSESVR = 1.59, RMSEPLSR = 1.57, RMSERR = 1.57), as were the ethanol and pH predictions for finished wines after phenolic stripping with polyvinylpolypyrrolidone (R2SVR = 0.98, R2PLSR = 0.99, R2RR = 0.99, RMSESVR = 0.23, RMSEPLSR = 0.21, RMSERR = 0.23). The results suggest that Raman spectroscopy is a viable tool for rapid and trustworthy fermentation monitoring.

Lycium Barbarum Polysaccharide-Iron (III) Chelate as Peroxidase Mimics for Total Antioxidant Capacity Assay of Fruit and Vegetable Food

Quantitative evaluation of the antioxidant capacity of foods is of great significance for estimating food’s nutritional value and preventing oxidative changes in food. Herein, we demonstrated an easy and selective colorimetric method for the total antioxidant capacity (TAC) assay based on 3,3’,5,5’-tetramethyl-benzidine (TMB), hydrogen peroxide (H₂O₂) and synthetic Lycium barbarum polysaccharide-iron (III) chelate (LBPIC) with high peroxidase (POD)-like activity. The results of steady-state kinetics study showed that the K_m values of LBPIC toward H₂O₂ and TMB were 5.54 mM and 0.16 mM, respectively. The detection parameters were optimized, and the linear interval and limit of detection (LOD) were determined to be 2–100 μM and 1.51 μM, respectively. Additionally, a subsequent study of the determination of TAC in six commercial fruit and vegetable beverages using the established method was successfully carried out. The results implied an expanded application of polysaccharide-iron (III) chelates with enzymatic activity in food antioxidant analysis and other biosensing fields.

Application of benchtop NIR spectroscopy coupled with multivariate analysis for rapid prediction of antioxidant properties of walnut (Juglans regia)

Benchtop near-infrared (NIR) spectroscopy coupled with multivariate analysis was used for the classification and prediction of antioxidant properties of walnut. Total phenolic content (TPC), total flavonoid content (TFC), ABTS assay and FRAP assay were performed spectrophotometrically. The synergy interval partial least square coupled competitive adaptive reweighted sampling (Si-CARS-PLS) was used for the prediction. A decent discrimination using principal component analysis (PCA) was observed by mean of spectroscopic and antioxidant properties data with total cumulative variance of 99.26% (PC1 = 95.07%, PC2 = 2.98%, PC3 = 1.21%) and 96.60% (PC1 = 64.28%, PC2 = 32.32%) respectively. The Si-CARS-PLS yielded optimal performance, R_P = 0.9616, RPD = 3.807 for TPC, R_P = 0.9657, RPD = 3.367 for TFC, R_P = 0.9683, RPD = 2.728 for ABTS assay, and R_P = 0.914, RPD = 2.669 for FRAP assay. These findings revealed that NIR integrated with Si-CARS-PLS could be used for the prediction of antioxidant properties of walnut.

Quantification of schizophyllan directly from the fermented broth by ATR-FTIR and PLS regression

Non-destructive methods that allow the quantification of bioproducts in a simple and quick manner during fermentation are extremely desirable from a practical point of view. Therefore, a 9 day fermentation experiment with Schizophyllum commune was carried out to investigate the possibility of using ATR-FTIR to quantify the schizophyllan biopolymer (SPG) directly from the culture medium. On each day, aliquots of the fermentation were taken, and the cell-free supernatant was analyzed by ATR-FTIR. The main objective of this step was to evaluate whether FTIR would be able to detect the appearance of specific peaks related to the production of SPG. The results of the PCA analysis showed that there was a reasonable separation of the days through the FTIR spectra. Then PCA-LDA was applied to the same dataset, which confirmed the formation of groups for each day of fermentation, after which, a calibration and test set was developed. Through a matrix generated by an experimental design with 2 factors and 5 levels, 25 samples were created with variations in the concentration of the culture medium and SPG. The ATR-FTIR spectra of this data set were modeled using PLS regression with backward selection of predictors. The results revealed that the amount of SPG produced can be quantified directly in the culture medium with excellent precision with R²CV = 0.951, R²P = 0.970, RMECV = 0.205 g, RMSEP = 0.170 g, RPDcv = 4.53 and RPDp = 5.88. The traditional method to quantify SPG is time consuming, requires several steps and uses solvents. In contrast, the method proposed in this work is a viable, faster, and a simpler alternative, which does not use reagents and does not require extensive pre-treatment of the samples.

Sodium-Polyacrylate-Based Electrochemical Sensors for Highly Sensitive Detection of Gaseous Phenol at Room Temperature

The detection of volatile organic compounds with electrochemical gas sensors is still very challenging regarding their sensitivity, selectivity, and operation at room temperature. There is a need for robust, sensitive, inexpensive, and yet easy-to-operate sensors for phenol and other phenolic compounds that function reliably under ambient conditions. Herein, we present a phenol gas sensor based on a combination of a semisolid, alkaline sodium polyacrylate, and commercial screen-printed electrodes. Sodium polyacrylate was employed as a multifunctional sensing material serving as a (i) gel-like electrolyte, (ii) accumulation milieu, and (iii) derivatization medium. Under ambient conditions, the sensor showed excellent sensitivity in the low ppbv (μg m^–3) range, a good linear operation in the examined concentration range of 0.1–1.0 ppmv for up to 105 min accumulation, and low sensitivity toward examined interferences. The sensor also indicated a possibility to differentiate between several phenolic compounds based on their oxidation potential. Given its favorable electroanalytical performance, a strong application potential is envisioned in topical fields such as environmental monitoring, cultural heritage preservation, and occupational health and safety.

Comparison of Chemometric Problems in Food Analysis Using Non-Linear Methods

Food analysis is a challenging analytical problem, often addressed using sophisticated laboratory methods that produce large data sets. Linear and non-linear multivariate methods can be used to process these types of datasets and to answer questions such as whether product origin is accurately labeled or whether a product is safe to eat. In this review, we present the application of non-linear methods such as artificial neural networks, support vector machines, self-organizing maps, and multi-layer artificial neural networks in the field of chemometrics related to food analysis. We discuss criteria to determine when non-linear methods are better suited for use instead of traditional methods. The principles of algorithms are described, and examples are presented for solving the problems of exploratory analysis, classification, and prediction.

Isolation of biogenic amine-negative lactic acid bacteria for Chinese rice wine fermentation based on molecular marker reverse screening

BACKGROUND

Chinese rice wine (CRW; a traditional alcoholic beverage in China with unique flavor and high nutritional value) containing high level of biogenic amines (BAs) may be deleterious to human health. The processes of rice soaking, primary fermentation and secondary fermentation were found to be the major factors for accumulation of BAs during industrial CRW production.

RESULTS

To reduce the risk of the formation of BAs in CRW production, Enterococcus durans AR315, a BA-negative lactic acid bacterium, was isolated from CRW samples by PCR-based molecular marker reverse screening in this work. With addition of AR315 during steeping rice phase, the level of total BAs was significantly decreased by 45.1% in comparison with the control. Moreover, the final BA concentration with the addition of AR315 was 27.6% lower than that of the control during fermentation phase.

CONCLUSIONS

To our knowledge, this is the first report of decreased accumulation of BAs in CRW production using a BA-negative lactic acid bacterium. Hence, using a BA-negative lactic acid bacterium as a starter culture could be an efficient strategy for significantly reducing the formation of BAs, which has the potential for industrial application in CRW production. © 2020 Society of Chemical Industry.

Investigation of the sorption of 17α-ethynylestradiol (EE2) on soils formed under aerobic and anaerobic conditions

A study was conducted on the sorption of 17α-ethynylestradiol (EE2) on five soils formed under different redox conditions: an Arenosol (A_20) with fully aerobic conditions, two Gleysol samples (G_20 and G_40) with suboxic and anoxic conditions and two Histosols (H_20 and H_80) with mostly anoxic conditions. The soils were characterized on the basis of total organic carbon (TOC), specific surface area (SSA) and the Fourier transform infrared spectra of the humic acid and humin fractions (the soil remaining after alkali extraction) of the soil. The maximum adsorption capacity of the soils (Q_max) ranged from 10.7 to 83.6 mg/g in the order G_20 > H_20 > G_40 > A_20 > H_80, which reflected the organic matter content of the soils. The sorption isotherms were found to be nonlinear for all the soil samples, with Freundlich n values of 0.45-0.68. The strong nonlinearity found in the adsorption of the H_80 samples could be attributed to their high hard carbon content, which was confirmed by the high aromaticity of the humin fraction. The maximum sorption capacity (Q_max) of the soils did not increase indefinitely as the organic carbon content of the soils rose. There could be two reasons for this: (i) the large amount of organic matter may reduce the number of binding sites on the surface, and (ii) the decrease in SSA with increasing soil OC content may limit the ability to adsorb EE2 molecules. In anaerobic soil samples, where organic matter accumulation is pronounced, the amount of aromatic and phenolic compounds was higher than in better aerated soil profiles. Strong correlations were found between the amount of aromatic and phenolic compounds in the organic matter and the adsorption of EE2 molecules, indicating that π-π interaction and H-bonding are the dominant sorption mechanisms.

Using Raman Spectroscopy as a Fast Tool to Classify and Analyze Bulgarian Wines-A Feasibility Study

Raman spectroscopy, being able to provide rich information about the chemical composition of the sample, is gaining an increasing interest in the applications of food. Raman spectroscopy was used to analyze a set of wine samples (red and white) sourced from rarely studied traditional Bulgarian wines. One of the objectives of this study was to attempt the fast classification of Bulgarian wines according to variety and geographic origin. In addition, calibration models between phenolic compounds and Raman spectroscopy were developed using partial least squares (PLS) regression using cross-validation. Good calibration statistics were obtained for total phenolic compounds (by the Folin–Ciocalteu method) and total phenolic compounds and phenolic acids (spectrophotometrically at 280 nm) where the coefficient of determination (R²) and the standard error in the cross-validation (SECV) were 0.81 (474.2 mg/dm³ gallic acid), 0.87 (526.6 mg/dm³ catechin equivalents), and 0.81 (44.8 mg/dm³ caffeic equivalents), respectively. This study has demonstrated that Raman spectroscopy can be suitable for measuring phenolic compounds in both red and white wines.

Multistarter fermentation of glutinous rice with Fu brick tea: Effects on microbial, chemical, and volatile compositions

A higher fermentation efficiency was achieved, using multistarter fermentation of glutinous rice supplemented with Fu brick tea (FGR-FBT), than when using traditional fermentation. The effects of multistarter fermentation on the microbial, chemical, and volatile compositions were determined. When FBT was incorporated during glutinous rice fermentation, increased population of yeasts and fungi, as well as enhanced α-amylase, proteinase and β-glucosidase activities, were observed. Specific fungi were isolated and identified as Aspergillus spp., which are known to secrete extracellular enzymes that modify the chemical properties, including ethanol levels, pH, total acids, and total soluble solids. The aroma profile of fermented glutinous rice was studied in the absence and presence of FBT, using HS-SPME-GC-MS and the electronic-nose. This analysis indicated that 35 characteristic volatile compounds were only found in FGR-FBT. The results show that FBT can be added during the fermentation of food products to enhance microbial biotransformation and modify flavour metabolism.

Prediction of quality parameters in straw wine by means of FT-IR spectroscopy combined with multivariate data processing

This study represents the first attempt to combine mid infrared (MIR) spectroscopy and multivariate data processing for prediction of alcohol degree, sugars content and total acidity in straw wine. 302 Italian samples, representing different vintages, production regions and grape varieties, were analysed using FT-MIR spectroscopy and reference methods. New regression functions based on a combination of Orthogonal Signal Correction and Partial Least Squares regression are proposed for prediction of quality parameters: this approach allows overcoming the issue of matrix complexity, reducing spectral interferences and enhancing the information embodied in fingerprinting data. The models proposed are characterised by an excellent reliability, with low error in prediction (alcohol: 0.28%; sugars: 9.9 g/L; acidity: 0.29 g/L) comparable both to reference methods and table wine models. Results demonstrate that vibrational spectroscopy, combined with a proper multivariate data strategy, represents a suitable strategy for the quick and non-destructive assessment of quality parameters of straw wine.

Quantification and cytoprotection by vanillin, 4-methylguaiacol and 4-ethylguaiacol against AAPH-induced abnormal oxidative stress in HepG2 cells

Vanillin, 4-methylguaiacol, and 4-ethylguaiacol, three phenolic compounds in Gujinggong (GJG) Chinese baijiu (Chinese liquor), were quantified by liquid–liquid extraction (LLE) combined with gas chromatography-mass spectrometry (GC-MS) and evaluated for their possible cytoprotective effects by AAPH-induced HepG2 cell model. To confirm whether vanillin, 4-methylguaiacol, and 4-ethylguaiacol protected HepG2 cells against AAPH-induced abnormal oxidative stress via motivating the Keap1–Nrf2 pathway, the gene and protein expression of Nrf2, Keap1, SOD, CAT, and GPx from the Keap1–Nrf2 pathway were measured with real-time PCR and western blot. Three levels of treatment doses (1000, 500, and 100 mg L⁻¹) were applied. Results showed that vanillin, 4-methylguaiacol, and 4-ethylguaiacol exhibited potent cytoprotective effect in a dose-dependent manner, greatly alleviating or reversing the increased oxidative stress induced by AAPH through up-regulating the mRNA and protein expression levels of Nrf2, SOD, CAT, and GPx, and thereby, significantly improving the intracellular antioxidant defense system in HepG2 cells (p < 0.05). Based on these findings, it was confirmed that vanillin, 4-methylguaiacol, and 4-ethylguaiacol, natural components of Chinese baijiu, were able to modulate the expression of Nrf2 and its downstream antioxidative enzymes (i.e., SOD, CAT, and GPx) against AAPH-induced abnormal oxidative stress. Further, this study lays the foundation for better illustrating the health benefits of Chinese baijiu.

Vanillin, 4-methylguaiacol, and 4-ethylguaiacol widely exist in Gujinggong Chinese baijiu and could protect HepG2 cells against oxidative stress via activating the Nrf2 pathway.