The objective of this work was to develop a methodology based on multiparametric methods (FTIR and a voltammetric e-tongue based on SPE) to evaluate simultaneously fourteen parameters related to the phenolic content of red wines. Eight types of Spanish red wines, elaborated with different grape varieties from different regions and with different aging, were analyzed with both systems. Input variables used for multivariate analysis were extracted from FTIR spectra and voltammograms using the kernel method. PCA analysis could discriminate wines according to their phenolic content with PC1, PC2 and PC3 explaining the 99.8% of the total variance between the samples for FTIR analysis and 85.8% for the e-tongue analysis. PLS calculations were used to establish regression models with phenolic content parameters measured by UV-Vis spectroscopy (TPI, Folin-Ciocalteu, CIELab and Glories) with high correlation coefficients (R 2 > 0.85), and low RMSEs (< 3.0) and number of factors (< 4). Both, PCA and PLS, were carried out using the full cross validation method. As time is a critical factor in the food industry, the main advantage of these multivariate techniques is their capability to evaluate many parameters in a single experiment and in shorter time than using independent classical techniques.

Phenolic compounds such as catechol are present in a wide variety of foods and beverages; they are of great importance due to their antioxidant properties. This research presents the development of a sensitive and biocompatible molecular imprinted sensor for the electrochemical detection of catechol, based on natural biopolymer-electroactive nanocomposites. Gold nanoparticle (AuNP)-decorated multiwalled carbon nanotubes (MWCNT) have been encapsulated in a polymeric chitosan (CS) matrix. This chitosan nanocomposite has been used to develop a molecular imprinted polymers (MIP) in the presence of catechol on a boron-doped diamond (BDD) electrode. The structure of the decorated MWCNT has been studied by TEM, whereas the characterization of the sensor surface has been imaged by AFM, demonstrating the satisfactory adsorption of the film and the adequate coverage of the decorated carbon nanotubes on the electrode surface. The electrochemical response of the sensor has been analyzed by cyclic voltammetry (CV) where excellent reproducibility and repeatability to catechol detection in the range of 0 to 1 mM has been found, with a detection limit of 3.7 × 10−5 M. Finally, the developed sensor was used to detect catechol in a real wine sample.

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The integration of nanomaterials as electron mediators in electrochemical biosensors is taking on an essential role. Due to their high surface-to-volume ratio and high conductivity, metallic nanowires are an interesting option. In this paper, silver nanowires (AgNWs) were exploited to design a novel catechol electrochemical biosensor, and the benefits of increasing the aspect ratio of the electron mediator (nanowires vs. nanoparticles) were analyzed. Atomic force microscopy (AFM) studies have shown a homogeneous distribution of the enzyme along the silver nanowires, maximizing the contact surface. The large contact area promotes electron transfer between the enzyme and the electrode surface, resulting in a Limit of Detection (LOD) of 2.7 × 10−6 M for tyrosinase immobilized onto AgNWs (AgNWs-Tyr), which is one order of magnitude lower than the LOD of 3.2 × 10−5 M) obtained using tyrosinase immobilized onto silver nanoparticles (AgNPs-Tyr). The calculated KM constant was 122 mM. The simultaneous use of electrochemistry and AFM has demonstrated a limited electrochemical fouling that facilitates stable and reproducible detection. Finally, the biosensor showed excellent anti-interference characteristics toward the main phenols present in wines including vanillin, pyrogallol, quercetin and catechin. The biosensor was able to successfully detect the presence of catechol in real wine samples. These results make AgNWs promising elements in nanowired biosensors for the sensitive, stable and rapid voltammetric detection of phenols in real applications.

A nanostructured electrochemical bi-sensor system for the analysis of milks has been developed using the layer-by-layer technique. The non-enzymatic sensor [CHI+IL/CuPcS]2, is a layered material containing a negative film of the anionic sulfonated copper phthalocyanine (CuPcS) acting as electrocatalytic material, and a cationic layer containing a mixture of an ionic liquid (IL) (1-butyl-3-methylimidazolium tetrafluoroborate) that enhances the conductivity, and chitosan (CHI), that facilitates the enzyme immobilization. The biosensor ([CHI+IL/CuPcS]2-GAO) results from the immobilization of galactose oxidase on the top of the LbL layers. FTIR, UV–vis, and AFM have confirmed the proposed structure and cyclic voltammetry has demonstrated the amplification caused by the combination of materials in the film. Sensors have been combined to form an electronic tongue for milk analysis. Principal component analysis has revealed the ability of the sensor system to discriminate between milk samples with different lactose content. Using a PLS-1 calibration models, correlations have been found between the voltammetric signals and chemical parameters measured by classical methods. PLS-1 models provide excellent correlations with lactose content. Additional information about other components, such as fats, proteins, and acidity, can also be obtained. The method developed is simple, and the short response time permits its use in assaying milk samples online.

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A bio-electronic tongue has been developed to evaluate the phenolic content of grape residues (seeds and skins) in a fast and easy way with industrial use in mind. A voltammetric electronic tongue has been designed based on carbon resin electrodes modified with tyrosinase combined with electron mediators. The presence of the phenoloxydase promotes the selectivity and specificity towards phenols. The results of multivariate analysis allowed discriminating seeds and skins according to their polyphenolic content. Partial least squares (PLS) has been used to establish regression models with parameters related to phenolic content measured by spectroscopic methods i.e., total poliphenol content (TPC) and Folin–Ciocalteu (FC) indexes. It has been shown that electronic tongue can be successfully used to predict parameters of interest with high correlation coefficients (higher than 0.99 in both calibration and prediction) and low residual errors. These values can even be improved using genetic algorithms for multivalent analysis. In this way, a fast and simple tool is available for the evaluation of these values. This advantage may be due to the fact that the electrochemical signals are directly related to the phenolic content.

Biosensor platforms consisting of layer by layer films combining materials with different functionalities have been developed and used to obtain improved catechol biosensors. Tyrosinase (Tyr) or laccase (Lac) were deposited onto LbL films formed by layers of a cationic linker (chitosan, CHI) alternating with layers of anionic electrocatalytic materials (sulfonated copper phthalocyanine, CuPcS or gold nanoparticles, AuNP). Films with different layer structures were successfully formed. Characterization of surface roughness and porosity was carried out using AFM. Electrochemical responses towards catechol showed that the LbL composites efficiently improved the electron transfer path between Tyr or Lac and the electrode surface, producing an increase in the intensity over the response in the absence of the LbL platform. LbL structures with higher roughness and pore size facilitated the diffusion of catechol, resulting in lower LODs. The [(CHI)-(AuNP)-(CHI)-(CuPcS)]2-Tyr showed an LOD of 8.55∙10−4 μM, which was one order of magnitude lower than the 9.55·10−3 µM obtained with [(CHI)-(CuPcS)-(CHI)-(AuNP)]2-Tyr, and two orders of magnitude lower than the obtained with other nanostructured platforms. It can be concluded that the combination of adequate materials with complementary activity and the control of the structure of the platform is an excellent strategy to obtain biosensors with improved performances.