The cork from Quercus suber L. is the premium raw material used to produce wine- bottling stoppers. The cork plays an important role in determining wine quality due to its peculiar features: impermeability to air and liquids (preventing wine oxidation), ability to adhere to a glass surface, compressibility, resilience, and chemical inertness (Simpson et al. 1986). If the cork stoppers are in direct contact with the wine, volatile and
PC1 -0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8
Retention time (min)
Lo a d in gs a 10.1 44.9 41.1 62.9 12.0 27.5 38.2 39.3 PC2 -0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8
Retention time (min)
Lo a d in gs b 10.112.0 41.1 44.9 62.9 58.0 38.2 27.5 39.3 PC3 -0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8
Retention time (min)
Lo a d in gs c 10.1 27.5 62.9
Fig. 2.18. PCA loadings plot of the chromatographic SPME areas of coffee volatile compounds.
Methodologies for Improved Quality Control Assessment of Food Products 35
nonvolatile compounds soluble in ethanol/water can migrate, thus contributing to the wine’s sensorial properties. However, being a natural product, cork can be attacked and contaminated in ways that could promote differences in its properties.
Several studies on the off-flavors associated with cork stoppers have been carried out (Simpson et al. 1986; Rocha et al. 1996; Pollnitz et al. 1996), with the 2,4,6-trichloro- anisole reported as the main agent responsible for cork-related off-flavors (Capone et al. 2002). New and rapid methodological approaches have been developed in order to study the volatile fraction associated with the wine cork taint (Boudaoud and Eveleigh 2003; Juanola et al. 2004; Zalacain et al. 2004). Conversely, few studies have been carried out concerning the soluble cork fraction that can migrate to wine (Varea et al. 2001), which can have sensorial effects in wines and may form complexes with wine anthocyanins, thus influencing the astringency (Singleton and Trousdale 1992).
The material unbonded or loosely bonded to the cork cell wall (i.e., the low-molecular- weight material) may be extracted with ethanol/water. This fraction is composed, mainly, of phenolic compounds and exhibits only about 2 percent carbohydrates (Rocha 1997; Rocha et al. 2004b). The major sugar component is xylose (53 mol%), glucose accounts for 17 percent, and uronic acids and arabinose represent 13 and 10 percent, respectively. Only trace amounts of deoxyhexoses can be detected (Rocha et al. 2004b). Low-molecu- lar-weight polyphenols, such as ellagic acid, gallic acid, protocatechuic acid, cafeic acid, vanillic acid and vanillin, and ellagitannins, have been reported as the cork phenols sus- ceptible to migrating into wine (Varea et al. 2001).
A specific cork contamination is the defect known in the industry as mancha amarela, or yellow spot (MA). This cork contamination is represented by modifications in the cork’s mechanical, structural, and optical properties and is potentially able to cause off-flavors in wine. Studies by scanning electron microscopy carried out on healthy cork (S) and MA cork (fig. 2.19) showed that the cellular structures of the infected and healthy tissues are different and that the attacked tissues were composed of deformed and wrinkly cells with cell wall separation at the middle lamella level (Rocha et al. 2000). These changes were related to the degradation of lignin and of pectic polysaccharides, as could be inferred by the deposition of calcium in the intercellular space of the attacked cells (Rocha et al. 2000).
In order to evaluate if the cork stoppers were able to contaminate a wine, it would be useful to use a screening technique for monitoring cork prior to being in contact with wine. As an initial approach, the resulting solutions of the matrix ethanol/water (10 percent v/v) set in contact both with a standard cork (S) and with a contaminated cork (MA) were studied by voltammetric techniques (Rocha et al. 2005). The need for a fast and reliable methodology for monitoring modifications in a wine model solution promoted by contact with contaminated cork prompted the application of voltammetric techniques, such as cyclic voltammetry (CV) and/or square wave voltammetry (SWV).
Voltammetric methods are relatively simple, rapid, sensitive, and low cost, requir- ing minimal preparation of samples and, thus, can be appropriated as screening tech- niques. Furthermore, voltammetry is suitable for the determination of several redox active organic compounds, namely phenolics, including methoxyphenols, flavonoids, and other antioxidant molecules of interest in diverse areas (Wheeler et al. 1990; Evtuguin et al. 2000; Filipiak 2001; Papanikos et al. 2002). All these compounds can be detected by electrooxidation at glassy carbon electrodes. Cyclic voltammetry has also been used to identify phenolic compounds in beer (Filipiak 2001), tea and coffee (Kilmartin and Hsu
2003; Roginsky et al. 2003), and wines (Zou et al. 2002; Kilmartin et al. 2002). On the other hand, sugars cannot be detected by voltammetry at conventional carbon electrodes due to low-redox-reaction kinetics, more positive potential of oxidation (more positive than the limit of the working potential window), or self-poisoning of the electrode surface (Wittstock et al. 1998). A new methodological approach will be described for the rapid screening of cork-wine model interactions in order to determine if the cork stoppers were able to contaminate a wine (Rocha et al. 2005).
Evaluation of the Voltammetric Analysis in What Concerns the Cyclic and Square Wave Techniques
Figure 2.20 displays the voltammetric signature of cyclic voltammograms (fig. 2.20a) and square wave voltammograms (fig. 2.20b, c) of the S and MA cork extracts with 15 days of contact with the wine model matrix, diluted with the NaCl electrolyte (no pH adjustment).
The voltammograms of both samples showed the presence of oxidizable compounds within the potential window +200 to +800 mV; the overall responses are the sum of the various species present. For the S cork extracts the cyclic voltammograms exhibited a major oxidation peak at about +400 mV, whereas for the MA cork samples a second, more
b
d
a
c
Fig. 2.19. SEM photographs of tangential section of reproduction cork showing “honeycomb”- type arrangement of cells of standard cork (a) and of cork with mancha amarela showing cellular separation (b). Cell wall of standard cork (c) and of cork with mancha amarela, showing cellular separation (*) and thinning of the middle lamella (**) (d) (Rocha et al. 2000).
0 200 400 600 800 potential (mV) 2μA 2μA 2μA S MA 0 200 400 600 800 potential (mV) S MA 0 200 400 600 800 potential (mV) IF IF IR IR
a
b
c
Fig. 2.20. Cyclic voltammogram (a) and square wave voltammograms (b and c) of cork extracts with 15 days of extraction time, diluted in NaCl without pH adjustment, for corks S and MA (pH extracts S = 4.4, and pH extracts MA = 5.1). Dotted curves are the background voltammograms. Voltammograms in c represent the forward (F) and reverse (R) current components of voltam- mograms in b. Cyclic voltammetry with scan rate of 100 mV/s and square wave voltammetry with frequency 15 Hz (Rocha et al. 2005).
intense, oxidation peak at about +580 mV was also detected. The square wave voltammo- grams (fig. 2.20b, c) confirm the presence of two oxidizable populations at about +400 mV and 560 mV. This small deviation of peak potentials is due to the differential nature of the square wave signal. The first oxidizable population appears in both cork extracts, S and MA, but the population at more positive potential seems to be mostly related to the cork MA. The cyclic voltammograms of both sample extracts showed lack of reversibility because the cathodic counterparts were absent in the reverse scans. However, the analy- sis of the individual current components of the square wave voltammograms (fig. 2.20c) allowed the detection of small reverse (reduction) peaks for both oxidation processes.
The first anodic peak observed at 400–410 mV for both the S and MA samples (pHextracts S= 4.4, and pHextracts MA= 5.1) may be related to the presence of a population of
phenolics containing ortho-diphenol groups or triphenol (galloyl) groups (Zou et al. 2002) and eventually some flavonol glycosides (Kilmartin et al. 2002). However, the oxidation of ortho-diphenols is generally a fully reversible process at glassy carbon electrodes (Zou et al. 2002; Kilmartin et al. 2002). Consequently, if present in the cork extracts, this class of compounds is a smaller fraction. The major difference between samples S and MA is the occurrence of an important peak at about 580 mV in the MA cyclic voltammograms. This peak at more positive potential may be due to the presence of other phenolics with a lower antioxidant strength, such as vanillic (Kilmartin et al. 2002) and coumaric acids (Jorgensen and Skibsted 1998; Kilmartin et al. 2002), cafeic acid, protocatechuic acid (Filipiak 2001), vanillyl alcohol (Evtuguin et al. 2000) (all isolated phenols), or meta- diphenols on the A-ring of flavonoids (Kilmartin et al. 2002). Considering that some of these compounds are lignin-related compounds (Rocha et al. 1996), this peak can be pro- posed as a possible marker to follow lignin degradation. The fact that this peak at about 580 mV is characteristic of the MA also confirms, as expected, that lignin degradation may occur in MA cork.
Principal component analysis (PCA) was applied to the voltammetric data, in order to assess the differences in the analytical signals and to recover the main signal features that characterized the S and MA corks. The scores scatter plot of PC1 × PC2 of the cyclic voltammetry data (fig. 2.21a), containing 94 percent of the total variability, shows a clear separation between both types of samples along PC1 (which account for 77 percent of the total variability). The signal bands (fig. 2.21b) related to this separation are located at 391 mV (PC1 negative), which characterizes the S samples. At the PC1 positive side, the band located at 584 mV is related to MA samples. These results show a very different signal region contribution for the separation of samples.
The scores scatter plot of PC1 × PC2 of square wave data (fig. 2.21c), which represents 96 percent of the total variability, shows that the separation is, once more, possible along PC1 axis (contains 74 percent of the total variability). The S samples are mainly located at the PC1 negative side, except for one misplaced sample, while MA samples are found at the PC1 positive side. The PC1 loadings profile (fig. 2.21d) shows two intense bands: the one located at 336 mV seems to be characteristic of the S samples, whereas the MA samples are related to the variations linked to the 560 mV band. The slightly different location of the bands is certainly related to the use of different voltammetric techniques, namely due to the current acquisition regime of the square wave technique, which pro- vides a differential current. Cyclic voltammetry was elected as the analytical technique because it provided slightly better distinction of the characteristic bands by PCA (Rocha et al. 2005).
Methodologies for Improved Quality Control Assessment of Food Products 39
Cyclic Voltammetric Analysis for Cork Classifi cation
The extraction time of 15 days is time-consuming, and not adequate for prediction pur- poses. Experiments with just 1 day of extraction were devised.
Figure 2.22 displays the voltammetric signature of the 1-day extracts of S and MA cork. Two main conclusions can be drawn from these results. First, the overall current is lower than the observed for the data with 15 days of extraction (cf. fig. 2.20a).
Taking the peak at the more negative potential as a reference (at about +380 mV), the amount of extractable phenolics of high antioxidant strength (e.g., galloyl phenolics or flavonol glycosides) for the 1-day extracts may be estimated as approximately one-third of the value for the 15 days of extraction for the cork S, and two-thirds of that value for the cork MA. Therefore, this class of compounds is more rapidly extracted from the cork MA, which may be related to the high degradation of the cell tissues in this cork. Second, the voltammetric signature of the cork samples changed, especially for the MA cork (cf. fig. 2.20a), indicating qualitative changes in the population of extractables. It must be noted that there was a small shift of the peak potentials toward less positive potentials, compared to the data with 15 days of extraction, which is only a consequence of the higher pH values (increase of 0.5 pH units) of the extracts with 1 day of extraction time. The major qualitative differences were seen for the MA cork, namely in the potential region of 560–580 mV, where the characteristic peak that was detected in the 15 days extraction samples is apparently absent. Thus, it appears that the extraction kinetics of that population at more positive potential, which characterizes MA cork, is low.
PC1 (77%) P C 2 ( 1 7%) a A M S PC1 (74%) PC 2 ( 2 2 % ) c S MA -0.10 -0.08 -0.06 -0.04 -0.02 0.00 0.02 0.04 0.06 0 100 200 300 400 500 600 700 800 Potential (mV) P C 1 L o adi ngs 391 584 b MA S -0.15 -0.10 -0.05 0.00 0.05 0.10 0.15 0 100 200 300 400 500 600 700 800 Potential (mV) P C 1 Loa di n g s d 336 560 MA S
Fig. 2.21. Voltammetric PCA for cork extracts without pH adjustment, 15 days of extraction time. (a) Scores scatter plot from the cyclic voltammetric data (PC1 × PC2); (b) the corresponding loadings profiles (PC1 and PC2); (c) scores scatter plot from the square wave voltammetric data (PC1× PC2); (d) the corresponding loadings profiles (PC1 and PC2).
The application of a cluster analysis procedure (PLS_Cluster) to voltammetric data allows building of a discrimination model that was used to classify new samples. PLS_Cluster (Barros and Rutledge 2004) is a data-clustering method based on the PLS algorithm (Wold et al. 1982; Geladi and Kowalski 1986). This procedure provides a way to group samples based on the inner variability and/or relationships among samples and/or variables (features) and at the same time give information on the reasons for the groupings. The method is based on a self-organizing mechanism that uses the PLS1 procedure to achieve a hierarchical segregation of the samples based on the variability (or relationships) present in the X matrix to progressively build up a feature vector (y) that characterizes the relationships between the objects of the X matrix. PLS properties/ entities such as the regression vectors, loadings X (p), W (w), and B coefficients (b) can be used to characterize the segregation (e.g., the chemical relevance). This method can be used in two different approaches: (1) dichotomic PLS_Cluster (DiPLS_Cluster) and (2) generalized PLS_Cluster (GenPLS_Cluster). The present work uses the DiPLS_Cluster approach for a binary segmentation of the samples.
The application of the DiPLS_Cluster method gives the segregation of the samples shown as a dendrogram in figure 2.23. One can see from this dendrogram that node 1, apart from one MA and two misplaced S samples, clearly discriminates between the MA and S known groups. The S group is mostly characterized by the variation located around 201 mV, whereas the MA group is mainly related to variations located around 377 and 530 mV. The discrimination promoted by the band at 530 mV, which was unclear in the original voltammograms, is especially important as it indicates that the population at more positive potential, clearly seen in the former voltammograms for the 15 days contact samples, is present in the 1-day contact. Again that population is characteristic of the MA cork. The variation of the potential from about 580 mV (15 days of extrac- tion time) to 530 mV is certainly related to the higher pH of the 1-day extract solutions as well as to relative changes in the individual compounds contributing the overall oxidation band. 0 200 400 600 800 potential (mV) MA S 1μA
Fig. 2.22. Cyclic voltammograms of cork extracts with 1 day of extraction time, diluted in NaCl, without pH adjustment (pH extracts S = 4.9, and pH extracts MA = 5.6), for corks S and MA. Thin line curves are the background voltammogram. Scan rate of 100 mV/s (Rocha et al. 2005).
Methodologies for Improved Quality Control Assessment of Food Products 41
Validation of this model showed that 80 percent of the data set was correctly classi- fied as S samples, whereas 90 percent of the data set was correctly classified as MA cork samples. Being a natural product and due to the various degrees of contamination, the observed classification rates can be accepted as high.
In conclusion, voltammetric methods based on the redox properties of compounds could be successfully used to establish the voltammetric signature of S and MA corks. The major difference between samples S and MA is the occurrence of an important peak at about 580 mV in the MA cyclic voltammograms. This peak at more positive potential may be assigned to lignin-related phenolics; thus it can be proposed as a possible marker to follow lignin degradation. Furthermore, the comparative analysis of the cyclic voltammograms for extraction times of 1 day and 15 days points to the existence of a population of easily oxidizable phenolics (oxidation peak at about 380 mV), which seems to be common to both cork samples S and MA. On the other hand, the class of phenolic compounds char- acteristic of the MA cork presented a relatively low kinetics of extraction. The application of a hierarchical clustering analysis (DiPLS_Cluster) allowed the classification of each type of cork, which allows predicting if the cork stoppers would be able to contaminate a wine. Therefore, the cyclic voltammetry associated with multivariate analysis allowed the development of a fast methodology for screening corks.