Introduction

Oxidation of white wines with consequent browning and loss of typical aroma is a long-standing problem in white winemaking. Phenolics, being the major substrate for oxygen, are compounds of must and wine responsible for browning (Singleton, 1987). Oxidation can be enzymatic or non-enzymatic (chemical).

The enzymatic oxidation occurs in grape musts after pressing, and it is very fast; the enzymes involved are the polyphenol oxidases (PPO): natural grapes tyrosinase and, in grapes infected by Botrytis cinerea, laccase, which oxidise must phenols into the respective o-quinones (Singleton, 1987). The enzymatic browning of a grape must is highly related to the content of hydroxycinnamates such as caffeoyltartaric acid (caftaric acid) and para-coumaroyltartaric acid (coutaric acid) (Cheynier et al., 1990), and it is promoted by flavan-3-ols (Cheynier et al., 1995).

Non-enzymatic (chemical) oxidations occur during wine ageing. The cascade of the oxidative process starts with the oxidation of polyphenols containing an ortho-dihydroxybenzene (catechol) ring, such as (+)-catechin, (−)–epicatechin, caffeic acid and its esters, or a 1,2,3-trihydroxybenzene (galloyl) group, such as (–)–epigallocatechin, gallic acid and its esters, that are the most readily oxidisable compounds in wine (Singleton, 1987; Singleton, 2000; Kilmartin et al., 2001; Danilewicz, 2003; Li et al., 2008). These substrates are oxidised to semiquinones and quinones, while oxygen is reduced to hydrogen peroxide. Since oxygen cannot react directly with phenolic compounds, for the limited reactivity of triplet oxygen, the reaction is catalysed by transition metal ions, in particular by the redox cycle of Fe³⁺/Fe²⁺ together with Cu²⁺/Cu⁺ (Danilewicz, 2003; Danilewicz et al., 2008; Waterhouse and Laurie, 2006). Compounds with more isolated phenolic groups, such as malvidin, para-coumaric acid and resveratrol, are oxidised at higher potentials (Kilmartin et al., 2001).

Quinones formed from the oxidation of polyphenols are unstable and electrophilic, so they may react with nucleophilic compounds, such as phenols and thiols: in the first case form dimers or polymers, which have lower reduction potential than the initial phenols and, therefore, are much more readily oxidised (Li et al., 2008; Singleton, 1987).

Hydrogen peroxide (H₂O₂), in association with ferrous ions, generates hydroxyl radical (HO^.) (Fenton reaction). HO^. is a strong oxidant, capable of non-specifically oxidizing virtually all organic constituents in proportion to their abundance: first of all, ethanol and tartaric acid, but also glycerol, sugars and other organic acids (Danilewicz, 2003; Danilewicz, 2007; Waterhouse and Laurie, 2006; Li et al., 2008).

The oxidation products in wine are acetaldehyde from ethanol and keto-acids from organic acids: for instance, tartaric acid forms glyoxylic acid (Danilewicz, 2003; Li et al., 2008; Singleton, 2000), furfural and 5-hydroxymethyl furfural, which are both sugar degradation products (through caramelization or Maillard reaction). These aldehydes can react with flavanols and form yellow–orange xanthylium compounds (Es-Safi et al., 2000).

Furthermore, wine oxidation leads to the loss of aromas, especially fruity and floral notes, and to the appearance of a range of off-flavours that very often occur before the colour change becomes apparent (Escudero et al., 2002). If at low concentrations, these aromas might improve wine complexity; at certain levels, they are dangerous for aroma quality (Singleton et al., 1979).

Many studies were carried out to reproduce in the laboratory the taste of aroma degradation related to oxidative spoilage (Simpson, 1982; Escudero et al., 2002; Bueno et al., 2010; Ferreira et al., 1998; Silva Ferreira et al., 2003). The most important descriptors related to the typical aroma of “oxidative spoiled white wines” were reported as being “honey-like, farm-feed, hay, woody-like, nutty, spicy (Silva Ferreira et al., 2002), vegetal aroma resembling asparagus or straw, acetaldehyde (Noble et al., 1987); the appearance of bitterness was also reported (Rankine, 1995).

The attested antioxidant, antioxidasic and antimicrobial properties of SO₂ make sulphur dioxide the most common additive for the preservation of wines. However, it has been widely proven that a prolonged absorption of SO₂ can cause health problems and an allergenic effect in sensitive subjects (Ribéreau-Gayon et al., 2004). In the future, a decrease in the limits for SO₂ concentration in wine is expected, and, in some cases, the prospective is a completely SO₂-free wine.

Other molecules are now being studied for their antioxidant and antiradical properties, such as reduced glutathione (GSH) and oenological tannins (condensed, ellagic and gallic tannins).

Several works have been published (Elias et al., 2010; Danilewicz et al., 2008; Danilewicz et al., 2010; Danilewicz, 2011) that deeply address the mechanisms that regulate the oxidation reactions, with the aim of defining the theoretical basis for the reduction in the use of SO₂ in wines. However, these experiments were mostly performed on a laboratory scale with model solutions and only in a few cases with real wines. Therefore, to reduce/replace sulphites in wine, it is mandatory to investigate the effectiveness of other molecules added to different wine typologies in preserving wine from ageing oxidation.

This work, performed under oenological conditions, was aimed at studying the possibility of adding GSH and/or gallic tannins at bottling to limit the use of SO₂ in white wines.

To date, the studies on wine have been mainly focused on the effect of GSH on aroma evolution during bottle ageing of wines with volatile thiols, in particular, Sauvignon Blanc. On the other hand, little information is available on the influence of GSH on the oxidative evolution of wine colour.

Furthermore, since the level of dissolved oxygen is a critical parameter to consider during the winemaking process (Guaita et al., 2013), two different levels of oxygen were considered to study the effect of different bottling conditions on the oxidative evolution of white wine with different additives.

Materials and methods

Results and Discussion

1. Oxygen consumption rate (OCR)

The trend of the consumption of dissolved O₂ (oxygen consumption rate: OCR) in the wines of the different trials bottled in 135 mL bottles was monitored from bottling to its disappearance (concentration values around 0.1 mg/L) observed between 73 and 200 days from bottling.

The kinetics of oxygen consumption of the different trials was modelled based on the content of dissolved oxygen (Ln[O₂]) over time (from bottling up to the 73^rd day, when the oxygen concentration in the fastest oxygen consumer trial was lower than 0.1 mg/L) to find the order of reactions (Figure 1).

Figure 1. Regression lines of oxygen consumption kinetic in a Cortese white wine oxygenated at 5.5 ppm (135 mL bottles) and treated with different concentrations of SO2, GSH and gallotannins at bottling to obtain eight different trials for each dose of oxygen.

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(1) = Control = 20 mg/L of free SO₂; s = 40 mg/L of free SO₂; t = 20 mg/L of free SO₂ and 40 mg/L of gallic tannins; g = 20 mg/L of free SO₂ and 20 mg/L of GSH; st = 40 mg/L of free SO₂ and 40 mg/L of gallic tannins; sg = 40 mg/L of free SO₂ and 40 mg/L of gallic tannins, gt = 20 mg/L of GSH and 40 mg/L of gallic tannins, sgt = 40 mg/L of free SO₂, 20 mg/L of GSH and 40 mg/L of gallic tannins. Each sample has been prepared in duplicate.

The results show that the trends were always fitted by a first-order kinetic model with 0.91 2 < 0.99. Table 3 shows the first-order equations that describe the relationships between oxygen concentration and time according to the model: Ln[O₂]_t = -Kt + ln[O₂]₀, where [O₂]₀ was the concentration of dissolved oxygen at bottling (constant value of the equation), [O₂]_t the concentration of dissolved oxygen at time t and K the constant rate of oxygen consumption (representing the slope of the kinetic curve).

Table 3. First-order kinetic equations for the consumption of oxygen in Cortese white wines oxygenated, respectively, at 5.5 ppm (135 mL bottles) and 4.0 ppm (750 mL bottles) and treated with different concentrations of SO2, GSH and gallotannins at bottling to obtain eight different trials for each dose of oxygen.

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	135 mL bottles		750 mL bottles
	Equations of the regression lines	K value ± std error	Equations of the regression lines	K value ± std error
-1	y = –0.020X + 1.704 (R2 = 0.996)	0.02 ± 0.000	y = –0.049X + 1.461 (R2 = 0.984)	0.049 ± 0.002
-1	y = –0.026X + 1.740 (R2 = 0.997)	0.026 ± 0.000	y = –0.048X + 1.468 (R2 = 0.986)	0.048 ± 0.002
s	y = –0.051X + 1.900 (R2 = 0.988)	0.051 ± 0.001	y = –0.087X + 1.574 (R2 = 0.976)	0.087 ± 0.004
s	y = –0.053X + 1.958 (R2 = 0.974)	0.053 ± 0.002	y = –0.075X + 1.469 (R2 = 0.971)	0.075 ± 0.004
t	y = –0.017X + 1.725 (R2 = 0.993)	0.017 ± 0.000	y = –0.038X + 1.461 (R2 = 0.975)	0.038 ± 0.002
t	y = –0.020X + 1.729 (R2 = 0.996)	0.020 ± 0.000	y = –0.037X + 1.440 (R2 = 0.979)	0.037 ± 0.002
st	y = –0.043X + 1.864 (R2 = 0.984)	0.043 ± 0.001	y = –0.072X + 1.618 (R2 = 0.967)	0.072 ± 0.004
st	y = –0.042X + 1.874 (R2 = 0.976)	0.042 ± 0.002	y = –0.071X + 1.634 (R2 = 0.971)	0.071 ± 0.004
g	y = –0.032X + 1.802 (R2 = 0.993)	0.032 ± 0.001	y = –0.050X + 1.536 (R2 = 0.976)	0.050 ± 0.002
g	y = –0.021X + 1.744 (R2 = 0.997)	0.021 ± 0.000	y = –0.054X + 1.445 (R2 = 0.989)	0.054 ± 0.002
sg	y = –0.058X + 1.976 (R2 = 0.979)	0.058 ± 0.002	y = –0.095X + 1.482 (R2 = 0.935)	0.095 ± 0.008
sg	y = –0.065X + 1.957 (R2 = 0.976)	0.065 ± 0.003	y = –0.092X + 1.112 (R2 = 0.914)	0.092 ± 0.009
gt	y = –0.019X + 1.758 (R2 = 0.994)	0.019 ± 0.000	y = –0.042X + 1.441 (R2 = 0.983)	0.042 ± 0.002
gt	y = –0.019X + 1.746 (R2 = 0.994)	0.019 ± 0.000	y = –0.038X + 1.440 (R2 = 0.976)	0.038 ± 0.002
sgt	y = –0.046X + 1.987 (R2 = 0.930)	0.046 ± 0.003	y = –0.071X + 1.766 (R2 = 0.926)	0.071 ± 0.006
sgt	y = –0.064X + 1.848 (R2 = 0.958)	0.064 ± 0.003	y = –0.089X + 1.622 (R2 = 0.970)	0.089 ± 0.005

(1) = Control = 20 mg/L of free SO₂; s = 40 mg/L of free SO₂; t = 20 mg/L of free SO₂ and 40 mg/L of gallic tannins; g = 20 mg/L of free SO₂ and 20 mg/L of GSH; st = 40 mg/L of free SO₂ and 40 mg/L of gallic tannins; sg = 40 mg/L of free SO₂ and 40 mg/L of gallic tannins, gt = 20 mg/L of GSH and 40 mg/L of gallic tannins, sgt = 40 mg/L of free SO₂, 20 mg/L of GSH and 40 mg/L of gallic tannins. Each sample has been prepared in duplicate. K = angular coefficient of the equation = constant rate of oxygen consumption.

Our results agree with the observations of Jeremic et al. (2020) operating on model wine solutions and on Chianti red wines treated with tannins of different origins.

Boulton (2020), working with model catechin solutions, model wine with free SO₂ and white wines, proved that the trend of OCR, variable among wines, follows either first or pseudo-first order kinetics only if the concentration of the ferric ion is constant, that could happen if part of the ferrous ions is quickly oxidised back to the oxidised form.

Anyway, since the OCR is influenced by different parameters, the kinetics of oxygen consumption in wines can be more complex than in model solution and not always characterised as first or pseudo-first-order kinetic, as observed by some authors for red wines (del Alamo-Sanza et al., 2014; Ferreira et al., 2015).

The K values (constant rate of oxygen consumption), which express the average rate of oxygen consumption of the different trials, were processed with complete three-factor ANOVA to study the main effect of the three factors (SO₂, gallic tannins and GSH) on the OCR in wines, and their interactions. All three studied factors showed a significant effect on the OCR.

The most pronounced effect concerned SO₂: in the wines with 40 mg/L of SO₂, the K parameter increased by 2.4 times: from 0.022 (lower SO₂ concentration) to 0.053 (higher SO₂ concentration) unities (p ≤ 0.001). The same trend was observed in our previous work with white wines (Panero et al., 2015).

This result agrees with those obtained by Danilewicz et al. (2008) and by Danilewicz and Wallbridge (2010) with model solutions: samples with a higher level of SO₂ were significantly faster oxygen consumers than samples with lower SO₂.

Indeed, according to Danilewicz et al. (2008), the increase in OCR observed for higher SO₂ levels depends on the fact that when polyphenols are oxidised in the presence of SO₂, a part of the quinones formed reacts with bisulphite to produce sulfonic acid adducts, and most of the remainder is reduced back to the corresponding phenolic forms. Danilewicz (2012) observed that in model solutions without SO₂, the oxidation reaction of diphenols to quinones associated with the reduction of O₂ to hydrogen peroxide is very slow as the value of the redox potential of the two half-reactions is similar (E values ​​equal to 0.012 and G close to zero). The regeneration of orto-diphenols from quinones caused by SO₂, therefore, determines the rightward shift of the reaction with the consequent OCR acceleration (Danilewicz et al., 2008).

The addition of GSH also caused an acceleration of OCR, with a much lower efficacy (average increases in the K parameter equal to approximately 1.2 times from 0.034 to 0.049 unities, p ≤ 0.05). An increase in OCR was also observed by Danilewicz et al. (2008) when they added cysteine in model wine: the increase observed was much more evident than the one observed in our study by adding GSH to white wine. Fracassetti et al. (2013) observed a slightly faster consumption rate only when they added GSH (67.5 mg/L) to a clarified white wine and to a model wine with high SO₂ content (50 mg/L of total SO₂) but not in the model wine when the SO₂ content was low (17 mg/L of total SO₂). This could prove a slight synergistic effect of GSH when coupled with SO₂, which, however, was not observed in our study (no significant interactions between SO₂ and GSH). Our results are consistent with Nikolantonaki et al. (2014), who observed, working with model solution, a similar reactivity of SO₂ alone or coupled with GSH as regards the reduction of 4-methyl-1,2-benzoquinone to ortho-diphenol. This result could further confirm the hypothesis of Danilewicz et al. (2008) that the increase in OCR with increasing doses of SO₂, either in model solution or in wine, is due to the capacity of SO₂ to reduce quinones back to otho-diphenols.

Conversely, the addition of gallotannins (40 mg/L) caused a significant but modest reduction (–20 %) of the K parameter from 0.041 to 0.034 unities (p ≤ 0.05).

The same result was observed by Jeremic et al. (2020), who added 100 mg/L of different tannins (gallotannins, ellagitannins, condensed tannins from seeds and skins) to Chianti wine and measured the different OCRs after saturation: after the first saturation, only the thesis with gallotannins showed a reduction in OCR compared to the control.

Conversely, when working with model solutions (hydroalcoholic solutions at pH 3.5 containing transition metals), the addition of tannins always leads to an increase in OCR (Pascual et al., 2017; Vignault et al., 2018; Motta et al., 2020), probably because the added tannins provide an easily oxidizable substrate, previously absent. However, these works showed different OCRs related to the tannin typology: gallotannins resulted in the slowest oxygen consumers compared to the other classes of tannins.

During the oxidation process, the different typologies of tannins can also evolve into new compounds with different redox properties. Furthermore, the tannins could bind to the metals to create compounds less oxidizing than the metals themselves, reducing or eliminating the catalytic effect of metals and/or reducing the formation of free radicals and forming complexes more difficult to oxidise (Jeremic et al., 2020).

Finally, no significant interactions were observed between the factors SO₂, GSH and gallic tannin as regards the OCR of wines.

The OCR was also measured in the 750 mL bottles during storage, and the data were processed from bottling (DO = 4 mg/L) to the total consumption of oxygen in the fastest oxygen consumer sample (DO < 0.1 mg/L). In addition, in this case, the trend of oxygen consumption in the different samples was well-fitted by a first-order kinetic (Table 3). The K parameter values were processed with a complete three-factor ANOVA, as described above. The results were the same as those obtained in the previous experiment. The addition of SO₂ caused a highly significant (p < 0.001) increase in the K parameter from 0.045 to 0.082 unities, whereas the addition of GSH and gallotannins caused, respectively, a significant increase (from 0.060 to 0.066 unities) and a highly significant decrease (from 0.069 to 0.057 unities). Finally, no interactions between factors were observed.

2.5. Sensory analysis

After 15 months of bottle ageing, the wines were subjected to sensory analysis. The data relating to the 15 sensory descriptors (1 visual, 10 olfactory and 4 gustatory) were subjected to ANOVA: the main effects and the first-order interactions between the factors "wine", "assessor" and "sensory session" were calculated. The results are reported in Table 6.

Table 6. ANOVA results for the sensory data. Significativity of F index for main effects and first-order interactions of the factors “wine”, “assessor” and “sensory session”.

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	Assessor	Wine	Session	Assessor*Session	Assessor*Wine	Wine*Session
Straw yellow	***	***	*	***	*	ns
Acacia flowers	***	ns	*	ns	ns	ns
Lemon	***	***	*	ns	ns	ns
Pineapple	***	ns	***	*	*	ns
Golden apple	***	ns	ns	ns	ns	ns
Acetaldehyde	***	***	ns	*	*	ns
Honey	***	ns	ns	*	ns	ns
Liquorice	***	**	ns	*	ns	*
Walnut	***	**	ns	ns	ns	ns
Green beans	***	**	**	*	ns	ns
Hay/Straw	***	ns	*	**	ns	**
Acidity	***	ns	ns	ns	ns	ns
Bitterness	***	ns	*	ns	ns	ns
Softness	***	ns	ns	ns	ns	ns
Structure	***	ns	ns	*	ns	ns

(1) *,**,*** and ns indicate differences at p≥ 95 %; 99 %; 99.9 % and not significant, respectively.

Significant differences between assessors were observed for all descriptors and, between sessions, for 7 out of 15 descriptors.

These differences depend on the different use of the scale by the assessors and on the fact that the positioning on the measurement scale can vary between different sessions. The variability due to the main effect of these two factors (assessor and sensory session) is eliminated in the ANOVA calculation, and the comparisons between the different experimental trials are not affected by these differences.

Conversely, the presence of significant interactions between factors indicates the poor robustness of the considered descriptors. In particular, the presence of significant interactions between assessors and sessions highlights the existence of inconsistent assessments between the sensory sessions (this interaction was detected for the descriptors straw yellow, pineapple, acetaldehyde, honey, liquorice, green beans, hay/straw and structure).

The presence of significant interactions between wine and sensory session indicates a lack of consistency in the evaluation of wines during the two sensory sessions (this is the case of the descriptors hay/straw and liquorice). The presence of interactions between assessors and wine indicates the discrepancies between assessors in the evaluation of wines (these interactions were detected for the colour and the aroma of pineapple and acetaldehyde). Overall, the most robust sensory descriptors, for which no significant interactions were detected, were acacia flowers, lemon, golden apple, walnut, acidity, bitterness and softness.

The sensory analysis confirmed the positive role of SO₂ in protecting wine from oxidation during ageing, according to the results of physicochemical analyses. The average sensory profile for the +SO₂ and –SO₂ samples is reported in Figure 2A.

The samples with a higher level of SO₂ at bottling were described as significantly less coloured and with significantly more intense notes of lemon and acacia flowers (freshness descriptors) compared to the –SO₂ samples. Furthermore, the +SO₂ samples resulted statistically different from the –SO₂ samples for less intense notes related to oxidative evolution: acetaldehyde, liquorice, walnut and green beans. No differences were observed between the two samples for the taste descriptors.

The +GSH samples were similar to –GSH ones; they differed significantly from one another only for the more intense aroma of liquorice and the less intense aroma of pineapple (Figure 2B). The addition of gallotannins had no sensory effect (Figure 2C).

Figure 2. Sensory profiles of Cortese wines 15 months after bottling. Effect of SO2 (Figure A), GSH (figure B) and tannins (figure C).

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+SO2 (all the trials added with SO₂), −SO2 (all the trials not added with SO₂), +GSH (all trials added with GSH) and −GSH trials (all trials not added with GSH); +Tannins = all trials treated with tannins, –Tannins = all trials not treated with tannins.

* and *** indicate differences at p ≥ 95 % and 99.9 %, respectively.

Conclusion

The results confirmed the key role of SO₂ in the shelf life of bottled wines and in preserving their organoleptic characteristics during ageing. The addition of SO₂ led to an acceleration of OCR, which in all wines followed a first-order kinetic. The increase in OCR was the consequence of the acceleration of the first step of the oxidation process, that is, the oxidation of phenols, which is due to the reduction of quinones back to phenols or to the formation of additional compounds with quinones or the consumption of hydrogen peroxide.

The mechanism of action for GSH is supposed to be the same as for free SO₂. Anyway, the results showed a negligible effect of GSH compared to SO₂: no effect of GSH on colour intensity was observed during bottle ageing, and an increase in colour browning was observed in the +GSH samples after the browning test.

The initial free SO₂ concentration of 40 mg/L allowed one to preserve the organoleptic quality of Cortese wine, subjected to an important oxygen intake at bottling (4 mg/L) during 15 months of bottle ageing. On the contrary, medium-low quantities (20 mg/L) of free SO₂ were not sufficient to ensure adequate protection of the wines during the same storage period.

As it is well known, to choose the right amount of SO₂ to be added to the wine at bottling, it is mandatory to take into account the losses due to the reaction with oxygen dissolved into the wine during bottling and storage (type of closure used), and even the expected permanence in the bottle before the consumption. Regarding the other additives, neither gallotannins (40 mg/L) nor GSH (20 mg/L) improved the shelf life of wines. At the doses used, GSH caused a slight acceleration of OCR and a mild protective effect on SO₂ consumption.

Conversely, a slight slowdown in OCR was observed in +Tan, probably due to the increased initial consumption of SO₂. The effectiveness of GSH and/or gallotannins as partial substitutes for SO₂ should be evaluated for shorter storage times and for controlled oxygen intakes, possibly using higher doses, particularly in the case of GSH. From a practical point of view, to date, the best way to extend the shelf life of wines without adding too high concentrations of SO₂ at bottling is to control the oxygen uptake in bottled wine by improving the bottling systems to limit the amount of oxygen that enters in the bottle and is dissolved into the wine.

Acknowledgements

The authors thank the Hochschule Geisenheim University (Department of Microbiology and Biochemistry), especially Prof. Doris Rauhut, for having allowed to carry out some preliminary trials to this work.

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