Front-face fluorescence spectroscopy: A new tool for control in the wine industry

Comprehensive analysis of colloid formation, distribution, and properties of monovarietal red wines using asymmetrical flow field-flow fractionation with online multidetection

Red wine colloids, crucial in determining wine quality and stability, are understudied due to inadequate techniques for studying them effectively in the natural wine environment. Recently, Asymmetrical Flow Field-flow Fractionation (AF4) with online multidetection has emerged as a novel analytical tool for quantifying, fractionating, and characterizing red wine colloids in their native state. This study aimed to characterize the colloidal composition of 24 monovarietal Italian wines produced without filtration, oak contact, fining treatments, malolactic fermentation, macerating enzymes or ageing on yeast lees. AF4 analysis allowed quantification and characterization of wine colloids based on light scattering signal (MALS; gyration radius - Rg), size (hydrodynamic radius - Rh) and absorbance (A280 & A520 nm). The results showed that each wine contained up to five distinct colloids' populations, varying in size and gyration radii. Despite possessing very similar Rh, most colloids exhibited great differences in compactness, as indicated by their varying Rg values. Comparing the A280 signal of whole wines to those of wines containing only species larger than 5 kDa (considered colloids) allowed to calculate the percentage of molecules involved in colloidal particles assembly, ranging from 1 to 44 % of the total A280 absorbing compounds, reflecting the diversity among wines. The A520 signal indicated the presence of polymeric pigments in the colloidal fraction. Notably, colored colloids all had Rg > 20 nm, indicating their association with other colloidal-forming compounds. This observation led to the conclusion that, apart from free anthocyanins and polymeric pigments, the color of red wines is also due to colloidal particles formed by the latter bound to proteins, with their quantity being highly variable across wines of different origin. These findings, which highlight the fundamental role of proteins in shaping the colloidal status of red wines, were utilized to propose an updated hypothetical model for colloidal aggregation in red wine.

A simple light path modifying device to reduce scattering in front-face fluorescence spectra

This technical note presents a device to diminish scattering signal in front-face fluorescence spectra while obtaining fluorescence signal. The beam path in a commercial fluorescence spectrometer was modified by two deflecting mirrors, leading reflections away from the sensor. This light path modifying (LPM) device was tested with two fluid and three solid substances, where the scattering-to-fluorescence ratio improved by a factor of 1.7 to 7.6. The spectra obtained with the LPM were much clearer, and distortion of the fluorescence peaks was avoided. Scans of quinine sulphate complied well with reference spectra.

Machine Learning Model Stability for Sub-Regional Classification of Barossa Valley Shiraz Wine Using A-TEEM Spectroscopy

With a view to maintaining the reputation of wine-producing regions among consumers, minimising economic losses caused by wine fraud, and achieving the purpose of data-driven terroir classification, the use of an absorbance-transmission and fluorescence excitation-emission matrix (A-TEEM) technique has shown great potential based on the molecular fingerprinting of a sample. The effects of changes in wine composition due to ageing and the stability of A-TEEM models over time had not been addressed, however, and the classification of wine blends required investigation. Thus, A-TEEM data were combined with an extreme gradient boosting discriminant analysis (XGBDA) algorithm to build classification models based on a range of Shiraz research wines (n = 217) from five Barossa Valley sub-regions over four vintages that had aged in bottle for several years. This spectral fingerprinting and machine learning approach revealed a 100% class prediction accuracy based on cross-validation (CV) model results for vintage year and 98.8% for unknown sample prediction accuracy when splitting the wine samples into training and test sets to obtain the classification models. The modelling and prediction of sub-regional production area showed a class CV prediction accuracy of 99.5% and an unknown sample prediction accuracy of 93.8% when modelling with the split dataset. Inputting a sub-set of the current A-TEEM data into the models generated previously for these Barossa sub-region wines yielded a 100% accurate prediction of vintage year for 2018-2020 wines, 92% accuracy for sub-region for 2018 wines, and 91% accuracy for sub-region using 2021 wine spectral data that were not included in the original modelling. Satisfactory results were also obtained from the modelling and prediction of blended samples for the vintages and sub-regions, which is of significance when considering the practice of wine blending.

Structure, stability and antioxidant activity of dialdehyde starch grafted with epicatechin, epicatechin gallate, epigallocatechin and epigallocatechin gallate

BACKGROUND

Catechins, a member of the flavonoids, exist widely in teas, and have health benefits. However, catechins have poor stability, which greatly limits their application. In order to improve the stability of catechins, different catechins including (-)-epicatechin (EC), (-)-epicatechin gallate (ECG), (-)-epigallocatechin (EGC) and (-)-epigallocatechin gallate (EGCG) were conjugated onto dialdehyde starch by acid-mediated coupling method. The structure, stability and antioxidant activity of dialdehyde starch-catechin conjugates were determined.

RESULTS

Thin-layer chromatography and ultraviolet-visible spectroscopy, fluorescence, nuclear magnetic resonance and infrared spectra revealed that catechins were successfully conjugated onto dialdehyde starch, coupling between 6-H/8-H of catechins' A ring and dialdehyde starch's aldehyde groups. The conjugates presented an amorphous structure and sheet-like and/or blocky morphologies. As compared to dialdehyde starch, the conjugates showed enhanced thermal stability. Furthermore, the stability of catechins in pH 7.4 phosphate-buffered saline was improved after conjugating onto dialdehyde starch. The conjugates exhibited significantly higher antioxidant activities than dialdehyde starch, decreasing in the following order: dialdehyde starch-ECG, dialdehyde starch-EGCG, dialdehyde starch-EC, dialdehyde starch-EGC and dialdehyde starch.

CONCLUSION

Dialdehyde starch-catechin conjugates have great potential as stable antioxidant agents. © 2022 Society of Chemical Industry.

Functionalization with Polyphenols of a Nano-Textured Ti Surface through a High-Amino Acid Medium: A Chemical-Physical and Biological Characterization

The study aimed to identify an effective mechanism of adsorption of polyphenols on a nano-textured Ti surface and to evaluate the osteogenic differentiation on it. The source of polyphenols was a natural extract from red grape pomace. A chemical etching was used to form an oxide layer with a nanoscale texture on Ti; this layer is hydrophilic, but without hydroxyl groups with high acidic-basic chemical reactivity. The samples were characterized by electron and fluorescence microscopies, UV-Vis spectroscopy, contact angle measurements, zeta potential titration curves, and Folin-Ciocâlteu test. The presence of an adsorbed layer of polyphenols on the functionalized surface, maintaining redox ability, was confirmed by several tests. Consistent with the surface features, the adsorption was maximized by dissolving the extract in a high-amino acid medium, with respect to an inorganic solution, exploiting the high affinity of amino acids for polyphenols and for porous titanium surfaces. The osteogenic differentiation was assessed on an osteoblastic cell line by immunofluorescence, cell viability, expression of key osteoblast markers, and extracellular matrix mineralization. The surfaces functionalized with the extract diluted in the range 1 × 10^-5-1 mg/mL resulted in having a greater osteogenic activity for the highest concentration, with lower values of cell viability; higher expression of alkaline phosphatase, bone sialoprotein, and collagen; and lower levels of osteopontin. In conclusion, the functionalization of a nano-textured Ti surface with polyphenols can potentially favor the osteogenic activity of osseointegrated implants.

Determination of Cabernet Sauvignon wine quality parameters in Chile by Absorbance-Transmission and fluorescence Excitation Emission Matrix (A-TEEM) spectroscopy

A-TEEM spectroscopy is presented as a novel rapid quantitative analysis method for 44 individual phenolic and basic wine chemistry compounds. To date no practical and combined analysis method for these recognized quality parameters important to the wine industry exists. The method was implemented in a Lambert-Beer linear concentration range to facilitate traceable absorbance and fluorescence spectral signatures. Both components were comparatively analyzed as single- and combined multi-block variable sets, and regressed against HPLC-DAD, UV-vis spectroscopy and other analytical reference data, using the Extreme Gradient Boost Regression (XGBR) and Partial Least Squares Regression (PLSR) algorithms. The approach was applied on 126 wines, and subsequently validated by a random split of 13% of the set and an additional independent set of 16 wines. XGBR with multi-block data organization systematically yielded the highest prediction accuracy and precision with respective overall valid fits indicated by mean R² and relative bias of 0.94 ± 0.04 and 4.1 ± 1.8%.

Multispectral fluorescence sensitivity to acidic and polyphenolic changes in Chardonnay wines - The case study of malolactic fermentation

In this study, stationary and time-resolvedfluorescence signatures, were statistically and chemometrically analyzed among three typologies of Chardonnay wines (A, B and C) with the objectives to evaluate their sensitivity to acidic and polyphenolic changes. For that purpose, a dataset was built using Excitation Emission Matrices of fluorescence (N = 103) decomposed by a Parallel Factor Analysis (PARAFAC), andfluorescence decays (N = 22), mathematically fitted, using the conventional exponential modeling and the phasor plot representation. Wine PARAFAC component C4 coupledwith its phasor plot g and s values enable the description of malolactic fermentation (MLF) occurrence in Chardonnay wines. Such proxies reflect wine concentration modifications in total acidity, malic/lactic and phenol acids.Lower g values among fresh MLF + wines compared to MLF- wines are explained by a quenching effect on wine fluorophores by both organic and phenolic acids.The combination of multispectral fluorescence parametersopens a novel routinely implementable methodology to diagnose fermentative processes.

Direct quantification of red wine phenolics using fluorescence spectroscopy with chemometrics

Phenolic compounds are secondary metabolites known to play crucial roles in important chemical reactions impacting the mouthfeel, colour and ageing potential of red wine. Their complexity has resulted in a number of advanced analytical methods, which often prevent routine phenolic analysis in winemaking. Fluorescence spectroscopy could be an alternative to current spectrophotometric techniques and its combination with chemometrics was investigated for its suitability in directly quantifying phenolic content of unaltered red wine and fermenting samples. Front-face fluorescence was optimised and used to build predictive models for total phenols, total condensed tannins, total anthocyanins, colour density and polymeric pigments. Machine learning algorithms were used for model development. The most successful models were built for total phenols, total condensed tannins and total anthocyanins with coefficient of determination (R²cal) and RMSECV of 0.81, 0.89, 0.80 and 5.71, 104.03 mg/L, 60.67 mg/L, respectively. The validation results showed R²val values of 0.77, 0.8 and 0.77, and RMSEP values of 7.6, 172.37 mg/L and 76.57 mg/L, respectively. A novel approach for the classification of South African red wine cultivars based on unique fluorescent fingerprints was also successful with an overall cross validation score of 0.8. The best classification ability (validation score = 0.93) was shown for the data set containing only fermenting wines for the most widely represented cultivars (>20 samples). This approach may provide a useful tool for authentication and quality control by regulatory bodies.

The application of right-angle fluorescence spectroscopy as a tool to distinguish five autochthonous commercial Greek white wines

White wine is among the most widely consumed alcoholic beverages. Varietal discrimination of wines has received increasing attention. Today's consumers require a sense of authenticity and are deterred by falsehood or misrepresentation in product marketing. However, wine can involve various types of frauds, which directly affects the distribution of wine in national and international markets. Right-angle fluorescence spectroscopy is a simple and rapid analytical technique that in combination with chemometric algorithms, constitutes a novel method for wine authentication. In this study, the stepwise-Linear Discriminant Analysis algorithm was applied in three representative spectral regions related to phenolic compounds for the purpose of distinguishing white wines according to the grape variety. The wavelength at 310 nm attributed to the hydroxycinnamic acids and stilbene provided a higher classification rate (95.5%) than the λex 280 and 295 nm regions (79.8%), suggesting that these compounds are highly related to the botanical origin of samples. The chemometric models were validated utilizing cross-validation and an external validation set to enhance the robustness of the proposed methodology. The above-mentioned methodology constitutes a powerful tool for the varietal discrimination of white wines and can be used in industrial setting. The ultimate goal of this study is to contribute to the efforts towards the authentication of Greek white wine which will eventually support producers and suppliers to remain competitive and simultaneously protect the consumers from fraudulent practices.

A Review of Wine Authentication Using Spectroscopic Approaches in Combination with Chemometrics

In a global context where trading of wines involves considerable economic value, the requirement to guarantee wine authenticity can never be underestimated. With the ever-increasing advancements in analytical platforms, research into spectroscopic methods is thriving as they offer a powerful tool for rapid wine authentication. In particular, spectroscopic techniques have been identified as a user-friendly and economical alternative to traditional analyses involving more complex instrumentation that may not readily be deployable in an industry setting. Chemometrics plays an indispensable role in the interpretation and modelling of spectral data and is frequently used in conjunction with spectroscopy for sample classification. Considering the variety of available techniques under the banner of spectroscopy, this review aims to provide an update on the most popular spectroscopic approaches and chemometric data analysis procedures that are applicable to wine authentication.

Spectrofluorometric analysis combined with machine learning for geographical and varietal authentication, and prediction of phenolic compound concentrations in red wine

Fluorescence spectroscopy is rapid, straightforward, selective, and sensitive, and can provide the molecular fingerprint of a sample based on the presence of various fluorophores. In conjunction with chemometrics, fluorescence techniques have been applied to the analysis and classification of an array of products of agricultural origin. Recognising that fluorescence spectroscopy offered a promising method for wine authentication, this study investigated the unique use of an absorbance-transmission and fluorescence excitation emission matrix (A-TEEM) technique for classification of red wines with respect to variety and geographical origin. Multi-block data analysis of A-TEEM data with extreme gradient boosting discriminant analysis yielded an unrivalled 100% and 99.7% correct class assignment for variety and region of origin, respectively. Prediction of phenolic compound concentrations with A-TEEM based on multivariate calibration models using HPLC reference data was also highly effective, and overall, the A-TEEM technique was shown to be a powerful tool for wine classification and analysis.

Geographical origin authentication of southern Brazilian red wines by means of EEM-pH four-way data modelling coupled with one class classification approach

EEM data recorded at different pH values was exploited by MCR-ALS in order to determine qualitative information about Brazilian red wines. In addition, the geographical traceability of wines produced in the Serra Gaúcha (Rio Grande do Sul) was carried out by DD-SIMCA considering 53 samples from the target class and 20 from other producing regions. The fluorescence signal corresponds to 9 EEMs recorded at different pH (3-11), generating four-way data. By MCR-ALS decomposition, eight factors were retrieved and related to typical chemical compounds found in red wine. In addition, the EEM pH data was used to build a one-class classification model, considering that MCR scores and all samples of the target class were properly recognised as belonging to the target class, with maximal sensitivity equal to 1. Samples of the non-target class were also adequately rejected by the model, and the specificity was found to be 0.97.

Application of Ultraviolet-Visible Absorption Spectroscopy with Machine Learning Techniques for the Classification of Cretan Wines

The present study was aimed at the identification, differentiation and characterization of red and white Cretan wines, which are described with Protected Geographical Indication (PGI), using ultraviolet–visible absorption spectroscopy. Specifically, the grape variety, the wine aging process and the role of barrel/container type were investigated. The combination of spectroscopic results with machine learning-based modelling demonstrated the use of absorption spectroscopy as a facile and low-cost technique in wine analysis. In this study, a clear discrimination among grape varieties was revealed. Moreover, a grouping of samples according to aging period and container type of maturation was accomplished, for the first time.

Front-face fluorescence excitation-emission matrix (FF-EEM) for direct analysis of flocculated suspension without sample preparation in coagulation-ultrafiltration for wastewater reclamation

Fluorescence spectroscopy has been suggested as a promising online monitoring technique in water and wastewater treatment processes due to its high sensitivity and selectivity. However, a pre-filtration is still indispensable in fluorescence measurement for removing ubiquitous particles and flocs in real samples to eliminate the strong light scattering that could attenuate fluorescence detection significantly. This study proposed a front-face fluorescence spectroscopy, which could characterize the liquid sample with suspended solids directly without pre-filtration. Front-face excitation-emission matrix (FF-EEM) coupled with parallel factor (PARAFAC) analysis was used for analyzing fluorescence components and to probe coagulation of secondary effluent and fouling in the subsequent ultrafiltration (UF), and conventional right-angle fluorescence EEM (RA-EEM) was also compared. The results showed that FF-EEM was less susceptible to turbidity (induced by standard particles) in the secondary effluent compared to RA-EEM. FF-EEM could successfully measure dissolved fluorophores in coagulated suspension without pre-filtration, while conventional RA-EEM was undermined significantly due to the existing flocs. FF-EEM coupled with PARAFAC could accurately probe dissolved organic matter and fouling in coagulation- UF wastewater reclamation processes. Therefore, it was demonstrated that this front-face fluorescence without any sample preparation step might be highly promising in real-time online fluorescence monitoring in multi water and wastewater treatment processes.

Monitoring winemaking process using tyrosine influence in the excitation-emission matrices of wine

Wine samples collected during the winemaking process have been analyzed employing a previously optimized UHPLC-FD method, determining their biogenic amines and amino acids profile. The results obtained have been submitted to a statistical analysis from which it was extracted that the most influential analyte was tyrosine. Thanks to its fluorescence, a method for its determination by excitation-emission matrices has been proposed. The accuracy of the method has been checked by means of Elliptical Joint Confidence Region test. The winemaking process has been monitored with this method, obtaining a faster and cheaper way to follow the process.

Authentication of the geographical origin of Australian Cabernet Sauvignon wines using spectrofluorometric and multi-element analyses with multivariate statistical modelling

With the increased risk of wine fraud, a rapid and simple method for wine authentication has become a necessity for the global wine industry. The use of fluorescence data from an absorbance and transmission excitation-emission matrix (A-TEEM) technique for discrimination of wines according to geographical origin was investigated in comparison to inductively coupled plasma-mass spectrometry (ICP-MS). The two approaches were applied to commercial Cabernet Sauvignon wines from vintage 2015 originating from three wine regions of Australia, along with Bordeaux, France. Extreme gradient boosting discriminant analysis (XGBDA) was examined among other multivariate algorithms for classification of wines. Models were cross-validated and performance was described in terms of sensitivity, specificity, and accuracy. XGBDA classification afforded 100% correct class assignment for all tested regions using the EEM of each sample, and overall 97.7% for ICP-MS. The novel combination of A-TEEM and XGBDA was found to have great potential for accurate authentication of wines.

Sensory and spectroscopic characterization of Argentinean wine and balsamic vinegars: A comparative study with European vinegars

In Argentina, vinegars are cheap agro-food products without exhaustive regulation and the production of high-quality vinegars has not been exploited yet. In fact, Argentinean vinegars have not been studied. In this context, a first study of Argentinean balsamic and wine vinegars was carried out by a sensory and spectroscopic characterization and by a comparison with well-recognized European vinegars. For that, ultraviolet-visible and fluorescence spectroscopies were applied together with principal component analysis (PCA) and parallel factor analysis (PARAFAC) performed on each data set, respectively. Results showed differences between acetification processes, origin countries and a wide variability within Argentinean production. The sensory characterization on Argentinean wine vinegars was performed by triangular and ordering preference tests showing statistically significant preferences toward the traditional and the rapid vinegars. This work highlights the effect of production on quality in order to provide added value to the Argentinean vinegars.

Application of fluorescence spectroscopy using classical right angle technique in white wines classification

The potential of excitation - emission matrices (EEM) measurements using classical right angle technique, in conjunction with chemometrics, was prospected for white wine classification with respect to their cultivar and geographical origin. For this purpose, wines belonging to four cultivars (Chardonnay, Pinot Gris, Riesling and Sauvignon) from two different countries (Romania and France) were investigated. The excitation - emission matrices were statistically processed using parallel factor analysis (PARAFAC). According to Soft Independent Modeling Classification Analogy (SIMCA) model, for cultivar differentiation, only 3 out of 107 wine samples (1 Pinot Gris (Romania); 1 Riesling (Romania) and 1 Sauvignon (France)) were misclassified while for geographical origin assessment, only 2 wines (1 Romania and 1 France) were misclassified. This study  demonstrates the potential of excitation - emission fluorescence matrices spectroscopy using the classical right angle technique in wine authentication, without sample dilution.

Multivariate spectroscopy for targeting phenolic choreography in wine with A-TEEMTM and NMR crosscheck non-targeted metabolomics

Present work comprises the use of different multivariate spectroscopic methods for tracking novel metabolomics signatures related to red wine chemistry. It is presented for the first time the proton nuclear magnetic resonance metabolomics fingerprint of a monovarietal Mexican Merlot, obtained with acquisition improvements recently proposed to the OIV Methods of Analysis sub-commission. Effective multi-presaturation solvent schemes have revealed a rich (poly)-phenolics aromatic region, so far not exploited for wine-fingerprinting or – targeted profiling routines. It is presented as well for the first time the use of simultaneous absorbance-transmission and fluorescence excitation-emission matrix “push-one-bottom” method (A-TEEMTM) at specific chemical conditions for a rapid, effective and high-sensitivity characterization of phenolic choreography in wines, as novel observables to quantify oenological practices and aging.

Phytotoxic metabolites produced by Verticillium dahliae Kleb. in olive wilting: a chemical and spectroscopic approach for their molecular characterisation

Most of the symptoms associated with Verticillium wilt disease in olive cultivation are due to complexes excreted by Verticillium dahliae. In this study chemical and physico-chemical techniques were combined to investigate how the molecular structure of phytotoxins isolated from two pathotypes of Verticillium dahliae, defoliating, D, and non-defoliating, ND, grown on two different media, Verticillium-dahliae-Medium (VdM) and Simulated Xylem-fluid-Medium (SXM), can affect their aggressiveness. Data obtained highlight important structural differences, both in term of elemental composition and in functional groups distribution. Such peculiarities strongly affect their solubility, resulted higher for the phytotoxins from D pathotype. This property likely induces serious modifications of the conformational state of the proteinaceous component, making tyrosine residues accessible to the phosphate ion. A phosphorylation mechanism would thus be promoted, that is going to interfere with the function of the involved proteins in intracellular signalling networks, likely by altering its role in modulating the plant's response.

Phenolic distribution in apple epidermal and outer cortex tissue by multispectral deep-UV autofluorescence cryo-imaging

Phenolic compounds in fruit are involved in responses to biotic and abiotic stresses and are responsible for organoleptic properties. To establish the distribution of these secondary metabolites at the tissue and sub-cellular scales, mapping of fluorescence in apple epidermis and outer cortex tissue in cryogenic condition was performed after deep-UV excitation at 275 nm. Douce Moën and Guillevic cider apple varieties were sampled and frozen after harvest, after 30 days at 4 °C and after 20 days at room temperature. Image analysis of fluorescence emission images acquired between 300 and 650 nm allowed the assignment of fluorescence signals to phenolic compound families based on reference molecules. Emission attributed to monomeric and/or condensed flavanol was localized in whole tissue with major fluorescence in the cuticle region. Hydroxycinnamic acids were found predominantly in the outer cortex and appeared in the cell wall. Fluorescent pigments were mostly found in the epidermis. The distribution of flavanols in the sub-cuticle and phenolic acids in the outer cortex distinguished apple varieties. Storage conditions had no impact on phenolic distribution. The proposed fluorescent imaging and analysis approach enables studies on phenolic distribution in relation to fruit development, biotic/abiotic stress resistance and quality.

Exploiting combined absorption and front face fluorescence spectroscopy to chase classification: A proof of concept in the case of Sardinian red wines

We present the analysis of optical spectroscopy fingerprints of three different varieties of Sardinian red wine, Carignano, Cannonau and Monica, belonging to Italian DOC (Controlled Origin Designation) red wines family. We selected 15 commercial wines (five for each variety), produced in the middle and south regions of Sardinia form monovarietal grapes. Despite different grapes, farming and tasting, all the samples share common absorption and fluorescence features. A two steps analysis is applied to achieve good classification of the wines. We recorded typical absorbance spectra with a large absorption below 300 nm and a visible absorption band at about 520 nm. Colour attributes according to chromaticity coordinates were evaluated by means of transmittance data and coupled to wine aging data to achieve classification. Despite similar values of lightness (L*), chroma (C*_ab), and hue angle (h°_ab) for the three varieties, good clustering was gathered for Carignano and Cannonau wines, whilst Monica variety has wide spread chromatic coordinates. UV excited fluorescence spectra display large and composite emission bands from the near UV down to the whole visible range. We performed multivariate analysis in the framework of the principal component analysis of fluorescence spectra coupled with absorption ones being able to achieve good clustering between the three varieties. One anomaly among Cannonau wines is discussed.

Data fusion approaches in spectroscopic characterization and classification of PDO wine vinegars

Spain is one of the major producers of high-quality wine vinegars having three protected designations of origin (a.k.a. PDOs): "Vinagre de Jerez", "Vinagre de Condado de Huelva" and "Vinagre de Montilla-Moriles". Their high prices due to their high quality and their high production costs explain the need for developing an adequate quality control technique and the interest in extensive characterization in order to capture the identity of each denomination. In this framework, methodologies based on non-targeted techniques, such as spectroscopies, are becoming popular in food authentication. Thus, for improving vinegar quality assessment, fusion of data blocks obtained from the same samples but different analytical techniques could be a good strategy, since the quantity and quality of sample knowledge could be enhanced providing new insights into the differentiation of vinegars. Therefore, the aim of this manuscript is the development of a multi-platform methodology and a model able to classify the Spanish wine vinegar PDOs. Sixty-five PDO wine vinegars were analyzed by four spectroscopic techniques: Fourier-transform mid-infrared spectroscopy (MIR), near infrared spectroscopy (NIR), multidimensional fluorescence spectroscopy (EEM) and proton nuclear magnetic resonance (¹H-NMR). Two different data fusion strategies were evaluated: Mid-level data fusion with different preprocessing, and Common Component and Specific Weights analysis multiblock method. Exploratory and classification analysis on the data from individual techniques were also performed and compared with data fusion models. The data fusion models improved the classification, providing a more efficient differentiation, than the models based on single methods, and supporting the approach to combine these methods to achieve synergies for an optimized PDO differentiation.

Characterization of fluorescence foulants on ultrafiltration membrane using front-face excitation-emission matrix (FF-EEM) spectroscopy: Fouling evolution and mechanism analysis

The understanding of fouling behavior and mechanism is critical for fouling control in membrane processes. This study adopted a novel fluorescence front-face excitation-emission matrix (FF-EEM) approach to characterize the fluorescence foulants deposited on membrane surface. Methods for quantifying protein and humic substances deposited on ultrafiltration (UF) membrane were established. Foulants deposited on the membrane surface during the UF of model foulants (bovine serum albumin (BSA) and humic acids (HA)) and wastewater effluent organic matter (EfOM) were quantified using the FF-EEM and liquid EEM coupled with mass balance calculation. The foulants mass data obtained by FF-EEM were further used to analyze fouling mechanism involved in UF. The FF-EEM based method was more accurate than the liquid EEM based method, as the problems associated with liquid EEM based method (such as the error propagation in the mass balance calculation and the ineffectiveness of inner filter correction) were avoided in FF-EEM based method. The fouling resistance did not correlate well with the amount of foulants, as the major fouling mechanism instead of the mass of foulants mainly determined the extent of fouling. This work demonstrated FF-EEM could be a powerful tool for investigating fouling evolution and fouling mechanism in UF process.

Effects of low sulfur dioxide concentrations on bioactive compounds and antioxidant properties of Aglianico red wine

This study analyzed the effect of low sulfur dioxide concentrations on the chromatic properties, phytochemical composition and antioxidant activity of Aglianico red wines with respect to wines produced from conventional winemaking. We determined the phytochemical composition by spectrophotometric methods and HPLC-DAD analysis and the in vitro antioxidant activity of different wine samples by the ORAC assay. The main important classes of fluorophore molecules in red wine were identified by Front-Face fluorescence spectroscopy, and the emission intensity trend was investigated at various sulfur dioxide concentrations. Lastly, we tested the effects of both conventional and low sulfite wines on ex vivo human erythrocytes under oxidative stimulus by the cellular antioxidant activity (CAA) assay and the hemolysis test. The addition of sulfur dioxide, which has well-known side effects, increased the content of certain bioactive components but did not raise the erythrocyte antioxidant capacity.