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The effect of time and storage conditions on the phenolic composition and colour of white wine
Food Research International 39 (2006) 220–229 www.elsevier.com/locate/foodres
The effect of time and storage conditions on the phenolic composition and colour of white wine ´ ngeles F. Recamales a, Ana Sayago a, M. Lourdes Gonza´lez-Miret b, A Dolores Hernanz a,* b
a Department of Analytical Chemistry, Faculty of Experimental Science, University of Huelva, Spain Laboratory of Food Colour and Quality, Department of Nutrition and Food Science, Faculty of Pharmacy, University of Seville, Spain
Received 22 July 2005; accepted 24 July 2005
Abstract The influence of different storage conditions on the colour and phenolic composition of young white wine was evaluated along 12 months of storage. The wine was bottled, and stored using three different conditions: position of bottles illumination and temperature variations. The results indicate that the time of storage has a significant effect (p < 0.001) on colour parameters, the majority of the phenols studied and the total phenol content. A significant decrease of phenols is detected during storage, which result in a change in the colour of the wine from pale yellow to yellow-brown. However, it can be noted that their loss was significantly higher in the wine subjected to variable temperature than in the wine stored at a constant temperature after 12 months. The principal component analysis was applied to the wine analysis data measured throughout the storage time, and the scatter plot of the samples was obtained for visual inspection. The effect of the storage time was clearly reflected in this analysis. A good differentiation among wines according to the length of storage was also obtained using linear discriminant analysis. 2005 Elsevier Ltd. All rights reserved. Keywords: White wine; Storage; Colour; Phenolic composition
1. Introduction Phenolic compounds are important components of wine. They not only contribute to their sensory characteristics of wine, such as colour, flavor and astringency (Lee & Jaworsky, 1987), but may also act as antioxidants, with mechanisms involving both free-radical scavening and metal chelation (Benı´tez, Castro, Sa´nchez Pazo, & Barroso, 2002). The composition and concentration of phenolic in wine depend on the type of grape used for vinification, the procedures employed for wine-making and the chemical reactions that occur during the aging of wine (Pen˜a*
Corresponding author. Tel.: +34 959 219960; fax: +34 959 219942. E-mail address: [email protected] (D. Hernanz).
0963-9969/$ - see front matter 2005 Elsevier Ltd. All rights reserved. doi:10.1016/j.foodres.2005.07.009
Neira, Herna´ndez, Garcı´a-Vallejo, Estrella, & Suarez, 2000). Wine is subjected to continuous changes in composition during storage. Many studies have been performed in order to describe the chemical changes during bottle aging and their influence on the sensory perception of red wine. During storage and aging of red wine, polyphenolic compounds are gradually modified. Reactions among anthocyanins, flavan-3-ol, proanthocyanidins and other compounds, such as glyoxylic acid, piruvic acid, and acethaldehyde, and also between flavonols themselves have been observed. These reactions are responsible for the appearance of new pigments (Bakker & Timberlake, 1997; Dallas, Ricardo da Silva, & Laureano, 1996; Revilla, Pe´rez-Magarin˜o, Go´nzalez-San Jose´, & Beltra´n, 1999), and hence for the disappearance of oligomer
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proanthocyanidin from solution. These processes affect colour and colloidal stability (Saucier, Bourgeois, Christiane, Roux, & Glories, 1997) and also the nutraceutical properties (Chen & Ho, 1997; Kroon & Williamson, 1999). The rate of the progressive decline in anthocyan and the formation of new stable colour pigments is influenced by such factors as temperature, pH, sulphites and oxygen content. The most rapid changes in the colour characteristics of red wine occur during the first year of storage (Somers & Evans, 1986). During this time, temperature has a more important influence than oxygen concentration. Length of storage is the other factor influencing wine colour since most of the changes occurring during wine storage are time-dependent (Dallas & Laureano, 1994). In white wine, one of the main problems posed is its unstable colour after bottling. Essentially, browning results from the oxidation of phenols to quinones, which in turn polymerise to form macromolecules with a typical yellow-brown hue (Singleton, 1987). In particular, oxidative browning of white wines was shown to be especially related to flavanol content (Cheynier, Rigaud, Souquet, Barille´re, & Moutounet, 1989; Simpson, 1982). Browning usually starts at the early stages of winemaking by enzymatic reactions (Cheynier, Rigaud, Souquet, Barille´re, & Moutounet, 1990), where hydroxycinnamic acid esters play a crucial role (Singlenton, Timberlake, & Lea, 1978). Caffeoyltartaric acid and p-coumaroyl tartaric acid were both shown to be onverted to caffeoyltartaric acid o-quinone which then underwent further reduction and addition reactions involving other phenolic or non-phenolic compounds (Cheynier et al., 1989, 1990; Gunata, Sapis, & Moutounet, 1987; Singlenton et al., 1978). After fermentation, polyphenoloxidase activity decreases and oxidative browning is related to polyphenol chemical oxidation (Singleton, 1987). Flavonols were shown to play an important role in this regard (Cheynier et al., 1989; Simpson, 1982) and catechin autoxidation was shown to generate the same products as enzymatic oxidation (Oszmianski, Cheynier, & Moutounet, 1996). Recent studies demonstrated a new oxidate process, converting flavonols into yellow xanthylium pigments, potentially contributing to white wine browning (Es-Safi, Guerneve´, Fulcrand, Cheynier, & Moutounet, 2000), which is generally expressed in an increase of absorption in the 400–500 nm (Martinez & Whitaker, 1995). However, there is little reported about the evolution of the phenolic compounds and colour during storage, or the effects of different conditions during the wine white storage. Zafrilla et al. (2003) studied the change of the phenolic composition and antioxidant activity in ecological and conventional white wines during the first 7 months of storage in the dark. Other authors have considered the changes in some components of white
221
wine from Albillo grape variety during the years of storage (Pe´rez-Magarin˜o & Gonza´lez-San Jose´, 2001). The purpose of this study was to evaluate the influence of different storage conditions (temperature, illumination, position of bottles) on the colour properties and the phenolic content of white wine during 12 months. Statistical techniques, such as analysis of variance, principal component analysis and linear discriminant analysis were used to distinguish among wines with different lengths of storage.
2. Material and methods 2.1. Samples A total of 98 samples of bottled wine were analysed. This wine was elaborated with the white grape variety ‘‘Zalema’’ which is exclusively grown in ‘‘Condado de Huelva’’, a restricted wine-producing zone with CBOwines, situated in the southwest of Spain. The wines are produced according to traditional methods with fermentation to controlled temperatures. Due to the climatic conditions of the zone (a sunny region with warm temperatures and low rain fall), an early grape harvest was performed. After cold stabilization the wine was bottled in green glass bottles of a capacity with 750 mL and stored in two different conditions: (i) one set of bottles was stored in a partly open warehouse in which the bottles were subjected to temperature variations (both daily and seasonal), this process is referred to as ‘‘variable’’; (ii) the other set of bottles was stored in a cellar where the temperature varied between 15 and 20 C throughout the year, this process is referred to as ‘‘constant’’. In each set, half of the bottles were placed in a horizontal position and other half in a vertical position. Within each subset half of the bottles were left in the dark and the other half in conditions of variable light. The wine was stored for 12 months. Samples (two bottles of each set) were taken at the time of bottling, and then the same process was repeated every 2 months.
3. Methods 3.1. Chemical analyses Chemical parameters with enological meaning were measured according to the methods of analysis of the Office International de la Vigne et du Vin: ethanol, total sulphur dioxide, total acidity, pH, volatile acidity, total sugars, total polyphenols (AOAC Official MethodsSM, 2003). Analyses of all the samples were made in duplicate.
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3.2. Analysis of phenolic compounds All individual polyphenols were analysed by high performance liquid chromatography. An Agilent 1100 series (Palo Alto, CA, USA) chromatograph equipped with a diode-array detector was used. A gradient of solvent A (water–acetic acid, 98:2, v/v) and solvent B (water–acetonitrile–acetic acid, 58:40:2, v/v/v) was applied to a reversed-phase Nova-pack C18 column (30 cm · 3.9 mm I.D.) as follows: 0–60 min, 45% B linear; 60–70 min, 45% B isocratic; 70–75 min, 80% B linear; 75–100 min, washing and re-equilibration of the column. The method employed possesses sufficient selectivity and sensitivity to allow direct analysis of wines without prior sample preparation, except filtration before injection (0.45 lm filters). The flow was 1.0 mL/min and the temperature was set at 20 C. The volume injected was 100 lL. Detection was performed by scanning from 200 to 700 nm. Identification of chromatographic peaks were carried out by comparing their retention times and spectra with those of standards. Quantification of phenolic compounds was carried out by area measurements at 280 nm except rutin which was quantified at 320 nm. Quantitative assays were achieved using external calibration curves for all standard phenols by dissolution of the standard solution. All analyses were repeated three times and the results were expressed as mean values. Standards of phenolic compounds were from Merck (gallic acid, p-hydroxy benzoic acid, ferulic acid), Fluka (tyrosol, caffeic acid, p-coumaric acid, m-coumaric acid, catechin, protocatechuic acid) and Sigma (rutin). Phenolic compounds, which are not available in the market as standards, have been identified by their retention time and spectra according to the literature. These compounds have been assayed by assuming that their molar absorptivity is the same as that of the corresponding free standard molecule. 3.3. Colour measurement Colour was assessed by tristimulus colorimetry based on transmittance spectra with the application of the equations proposed by the Commission Internationale de lÕEclariage (CIE, 1986). The spectra were registered directly on the wine, using a diode array spectrophotometer (Unicam 5625 UV/Vis spectrophotometer) set to measure in the visible region (k = 380–770 nm) at constant intervals (Dk = 2 nm) and integrated using the ´ lvarez, Gonza´lezthe software CromaLab (Heredia, A Miret, & Ramı´rez, 2004), which take into account the CIE recommendations. The uniform colour space CIE 1976-(L*a*b*) (CIELAB) was used. As is required by the weighted-ordinate method, the visible spectra of the samples were weighted according to the characteristic factor of the selected visual reference conditions: 10 visual
field observer and standard illuminant D65, which corresponds to natural daylight (Wyszecki & Stiles, 1982). Within the approximately uniform colour space CIELAB, two colour coordinates, a* and b*, as well as lightness, L*, are defined. Coordinate a* takes positive values for reddish colours and negative values for the greenish ones, whereas b* takes positive values for yellowish colours and negative values for the bluish ones. L* is an approximate measurement of lightness, which is the property according to which each colour can be considered as equivalent to a member of the grey scale, between black and white, taking values within the range 0–100, respectively. From the CIELAB space, other parameters are defined, such as chroma ðC ab Þ and hue (hab): 2
2 1=2
C ab ¼ ½ða Þ þ ðb Þ
;
hab ¼ arctanðb =a Þ.
Chroma ðC ab Þ is the attribute which allows to determine for each hue its degree of difference in comparison to a grey colour with the same lightness, so it is considered the quantitative attribute of colourfullness. Hue (hab) is qualitative the attribute according to which colours have been traditionally defined as reddish, greenish, etc. It is the attribute which allows to distinguish a colour with reference to a grey colour with the same lightness. This attribute is related to the differences in absorbance at different wavelengths and is considered the qualitative attribute of colour. 3.4. Data analysis The factors affecting the stability of the bottled wines were investigated. The factors varied were storage temperature and time, position of the bottled, and illumination exposure and the levels were mentioned above. Analysis of variance was made using general linear model (GLM) to determine whether mean values for phenolic compounds and colour parameters differed with storage time and conditions. The means were compared by the least significant difference (LSD) test at a significance level of 0.05. Pattern recognition (PR) techniques including principal component analysis (PCA) and linear discriminant analysis (LDA) were applied on experimental standardized data to distinguish among wines with different lengths of storage. Statistical analyses were performed using the statistical package STATISTICA99 from Statsoft (1999).
4. Results The study of the storage of white wine was carried out over 12 months. Before the storage two samples were taken and analysed for chemical parameters with enological meaning. The mean values obtained in wines were: pH, 3.06; density, 0.9906 g/cm3; ethanol, 11.1%
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v/v; reducing sugars, 1.0 g/L; total acidity, 5.2 g tartaric acid/L; volatile acidity, 0.23 g acetic acid/L; SO2 total, 142.82 mg/L.
12
100˚
223
90˚
80˚
110˚
70˚
120˚
60˚
10
4.1. Colour changes 8
b*
For the study of the colour in this work the system CIE 1976-(L*a*b*) (CIELAB) has been selected. The analysis of variance was applied for testing the significance of the effects of storage time and conditions on these variables. The results showed that only the time of storage has a significant influence (p < 0.001) on the studied parameters (Table 1). Fig. 1 shows the distribution of the wines grouped according to the time of storage in the (a*b*) colour plane, in which the colour points are represented regarding the axes green-red (a* + a*) and blue-yellow (b* + b*). It can be observed that most of the samples are located inside a defined area between the 90 and the 120 of hue angle (hab) that belongs to the medium yellow or with a very slight tendency to the green. Also, this grouping is given in a very near area to the origin of coordinates, with low values of chroma ðC ab Þ, that is with a high proportion of white light transmitted by the samples. These data, besides the high levels of lightness (L*) near to 100% of quantity of transmitted global light, determine the final colour in the category of the pale yellow.
6
4 0 months 2 months 4 months 6 months
2
8 months 10 months 12 months
0
-6
-4
-2
0 a*
2
4
6
Fig. 1. Colour diagram (a*,b*).
The increases of the chroma ðC ab Þ and decreases of the hue (hab) are the characteristic changes in wines during storage. During the storage, an evolution in the values of the two colour coordinates (a* and b*) are observed. The value of a* (red component) displays initially a reduction from 0.86 to 1.47, but soon it
Table 1 Influence of conditions and storage time on colour parameters (CIELAB)a Source of variation
L*
a*
b*
C ab
hab
Storage period (months) 0 2 4 6 8 10 12 Significanceb
99.76c 98.41c 98.98c 99.28c 101.67d 99.69c 102.95d ***
0.86c 0.21c 0.91c 0.77c 1.49c 1.27c 4.07d ***
3.38c 3.32c 3.17c 3.61c 2.45c 3.40c 7.77d ***
3.49c 3.60c 3.29c 3.69c 2.91c 3.67c 8.81d ***
105.71c 102.70c 107.07c 104.11c 147.77d 112.10e 63.42f ***
Temperature Variable Constant Significanceb
99.79 100.54 ns
0.02 0.18 ns
4.06 3.85 ns
4.37 4.29 ns
108.82 103.58 ns
Exposition Light Dark Significanceb
100.27 100.05 ns
0.27 0.07 ns
3.83 4.08 ns
4.18 4.48 ns
102.91 109.48 ns
Position Horizontal Vertical Significanceb
99.90 100.43 ns
0.13 0.07 ns
4.06 3.85 ns
4.40 4.26 ns
100.90 111.49 ns
a b
Data followed by different letters for each column and source of variation are significantly different by LSD test. ns, *, **, ***, not significant and significance at p < 0.05, 0.01 and 0.001, respectively.
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increases sharply in the last two months of the test to reach value of 4.07. However, the values of b* practically remain constant until the 10th month in which it experiences a sharp increase, reaching the value 7.77. Therefore, the global result is an increase of the a* and b* values, resulting in a change in the colour of the wine from pale yellow to yellow-brown. 4.2. Changes in phenolic compounds during storage In the analysis of individual phenolic contents, 17 phenols were identified and quantified as follows: hydroxycinnamic acid (caftaric acid, p-coutaric acid, coutaric acid glucoside, fertaric acid, m-coutaric acid, caffeic acid, ferulic acid, p-coumaric acid, m-coumaric acid, ethyl caffeate, ethyl p-coumarate), benzoic acids (p-hydroxybenzoic acid, ethyl galate), flavonoids (catechin, rutin), tyrosol, as well as an unknown compound (compound 1), this phenol which has an absorption spectra similar to p-hydroxy benzoic acid spectra, so it was quantified as this acid. Table 2 shows the mean for the phenolic compound contents of the white wine. This table reports the effect of different conditions during the storage of the wine white. It can be seen that the temperature (variable/constant) has a significant influence on the total phenols content (expressed as mg/l gallic acid) and the light exposure on the tyrosol and caftaric acid concentration, at the 5% significance level. The factor of position (horizontal/vertical) of the bottles has no effect on any of the compounds studied, as can be observed in Table 2. With regard to the evolution of the total phenols, a significant decrease is detected during storage, as has been shown in earlier work (Benı´tez et al., 2002). This decrease occurred mainly in the last 4 months and is related to the changes of colour observed in the wine. However, it can be noted that their loss was significantly higher in the wine subjected to daily and seasonal temperature variations (8.26%) than in the wine stored at a constant temperature (4.42%) after 12 months. The study of individual behaviour of phenolic compounds indicates that the content of most of the phenolic compounds identified in the wines studied diminishes with time, with the exception of tyrosol, caffeic acid, ferulic acid, p-coumaric acid and compound 1. Recent experimental evidence indicates that storage conditions are expected to strongly affect the content of phenols, since they can undergo modifications during storage, mainly due to hydrolysis, oxidations and complexations (Zafrilla et al., 2003). Other factors such as light and temperature can contribute to the degradation of phenolic compounds (Cheynier & Fulcrand, 2003). Hydrolysis (enzymatic or not) is mainly responsible for the increase of simpler compounds, such as tyrosol and free phenolic acids. So, in the same conditions of light, the amount of tyrosol is 1.4 times higher in the wines stored at a vari-
able temperature than those stored at a constant temperature. Ferulic acid, caffeic acid, p-coumaric acid and compound 1 levels also increased with storage time, but in these cases the temperature effect is not significant. After 12 months of storage, the samples show significant losses of phenolic compounds relative to initial values. Caftaric acid, m-coutaric acid and ethyl caffeate are the compounds that exhibited a lower pronounced concentration reduction (14.67–9.32, 0.58–0.28, 0.69– 0.42 mg/L, respectively). Catechin levels also diminish with time which is according to other authors. This decrease occurred mainly in the last 2 months. Wine that was stored for 10 months has a mean concentration of catechin of 1.31 mg/L and after 12 months the catechin was not detected. Simpson (1982) has reported that catechins and procyanidins have a strong influence on the susceptibility of white wines to browning, because flavan-3-ols may suffer oxidations and polymerizations. The profiles of changes in the concentration of coutaric acid glucosides, as well as p-hydroxybenzoic acid and ethyl gallate were very similar. Their contents progressively decrease, and from the eighth month they increase slightly. With regard to the tartaric ester of the ferulic acid, their concentration decreases, and from the sixth month increases, this increase being slightly higher for samples stored at a constant temperature than at a variable temperature (32% and 7%, respectively). While m-coumaric acid and ethyl p-coumarate levels also diminish until the sixth month and after practically do not change. The decrease encountered for coutaric acid glucosides content (1.44–0.47 mg/L) may be due to the hydrolysis in the acidic wine medium, while oxidation processes may have been responsible for the decrease in concentration of hydroxycinnamic derivatives (Garcı´a Parrilla, Heredia, & Troncoso, 1999). Among the flavonols studied only the rutin could be detected and quantified in the wines. Their content also diminishes and could not be detected after 6 months of storage. 4.3. Multivariate analysis Another objective of this work was to check the ability of the phenolic compounds and colour variables to differentiate among wines with different lengths of storage. For this reason, several pattern recognition (PR) techniques including principal component analysis (PCA) and linear discriminant analysis (LDA) have been applied on experimental standardized data. Applied to our data set, PCA revealed that the first four principal components explain 70% of total variance (Table 3). A plot of the scores of PC1 versus PC2, i.e., the projection of the samples along the directions identified by the first two PCs, is reported in Fig. 2. It is apparent that samples are grouped in a similar way to
Table 2 Influence of conditions and storage time on phenolic compounds (mg/L)a Source of variation
Coutaric acid glucoside
p-Coutaric acid
Tyrosol
p-Hydroxybenzoic acid
Catechin
m-Coutaric acid
Fertaric acid
Storage period (months) 0 231.05c 2 220.00c 4 244.80d 6 234.86d 8 228.60c 10 216.41c 12 216.51c b Significance ***
14.67c 11.14c 11.11c 8.33d 8.33d 8.21d 9.32d ***
1.44c 1.59c 0.56d 0.44d 0.33d 0.37d 0.47d **
0.76c 1.83d 1.09d 0.95e 1.36e 1.04e 1.61e *
22.60c 8.88d 11.01d 10.78d 10.40d 11.20d 13.21e *
1.16c 1.25c 0.72cd 0.31e 0.26e 0.41e 0.79cf ***
1.42c 1.30c 1.52c 1.02c 0.98c 1.31c nd ***
0.58c 0.56cd 0.65d 0.32e 0.36e 0.33e 0.28e ***
1.19c 0.95c 0.93c 0.64d 0.71d 0.68d 0.85cd ***
Temperature Variable Constant Significanceb
220.89 232.84 **
9.29 9.53 ns
0.59 0.67 ns
1.24 1.39 ns
10.86 10.97 ns
0.69 0.56 ns
1.04 0.99 ns
0.44 0.40 ns
0.83 0.75 ns
Exposition Light Dark Significanceb
226.15 227.58 ns
8.76 10.05 *
0.58 0.67 ns
1.16 1.46 ns
9.72 12.11 *
0.61 0.64 ns
1.02 1.02 ns
0.39 0.44 ns
0.76 0.82 ns
Position Horizontal Vertical Significanceb
227.95 225.78 ns
9.51 9.31 ns
0.61 0.65 ns
1.17 1.45 ns
11.41 10.42 ns
0.66 0.60 ns
1.07 0.97 ns
0.42 0.42 ns
0.80 0.78 ns
Caffeic acid
Ethyl galate
Ferulic acid
Compound 1
p-Coumaric acid
m-Coumaric acid
Ethyl caffeate
Ethyl p-coumarate
Rutin
Storage period (months) 0 0.92c 2 1.85c 4 2.51d 6 1.52c 8 2.19e 10 2.08e 12 2.39e b Significance **
1.73c 1.35c 1.17d 0.99d 1.01d 1.10d 1.22d ***
0.54c 0.76c 1.11d 0.87cd 0.97cd 0.91cd 2.00e ***
199.49c 189.12c 202.44 c 159.67d 163.72d 162.20d 218.48e ***
0.06 0.20 0.41 0.30 0.37 0.77 0.20 ns
0.12c 0.53d 0.28d 0.15e 0.21e 0.20e 0.18e ***
0.69c 0.76d 0.65c 0.53c 0.56c 0.57c 0.42e ***
0.13c 0.36d 0.28de 0.16ef 0.17f 0.17f 0.15f ***
0.84c 0.82c 0.75d nd nd nd nd **
Temperature Variable Constant Significanceb
1.15 1.14 ns
1.08 1.13 ns
182.85 182.36 ns
0.47 0.28 ns
0.26 0.26 ns
0.58 0.59 ns
0.22 0.21 ns
2.12 2.06 ns
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Caftaric acid
Source of variation
Total polyphenols
0.27 0.26 ns (continued on next page) 225
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PC
Eigenvalue
Explained variance (%)
Cumulative variance (%)
1 2 3 4
8.13 3.96 2.43 1.54
35.35 17.25 10.59 6.70
35.35 52.60 63.19 69.90
0.57 0.59 ns
0.23 0.20 ns
0.26 0.26 ns
Table 3 Variance explained by the first PCs
a
b
Data followed by different letters for each column and source of variation are significantly different by LSD test. ns, *, **, ***, not significant and significance at p < 0.05, 0.01 and 0.001, respectively. Nd: not detected.
0.26 0.25 ns 0.45 0.30 ns 184.46 180.75 ns 1.07 1.13 ns 2.14 2.03 ns Position Horizontal Vertical Significanceb
1.16 1.13 ns
0.26 0.26 ns 0.22 0.20 ns 0.55 0.61 ns 0.25 0.26 ns 0.43 0.32 ns 176.15 189.06 ns 1.04 1.16 ns 1.09 1.19 ns 1.93 2.25 ns Exposition Light Dark Significanceb
Source of variation
Caffeic acid
Ethyl galate
Ferulic acid
Compound 1
p-Coumaric acid
m-Coumaric acid
Ethyl caffeate
Ethyl p-coumarate
Rutin
226
our classification. Moreover, an interesting feature can be pointed out: such groups are arranged along the direction of PC1, in a way that reflects their storage time, that is, samples that have been a shorter time in bottles have higher scores, and those which have been bottled for a longer time have lower scores on PC1. The loadings, i.e., the coefficients that define the weight of each original variable in the PCs, can then be investigated in order to understand which chemical compounds are responsible for the ranking of samples on the basis of storage time on the first PC. A comparison of scores and loadings for PC1 allows the identification of the compounds having a higher influence on this feature; analytes with highly positive loadings on PC1 should be regarded as compounds whose concentration decreases with storage time, while analytes with highly negative loadings tend to increase. The most important compounds are esters: caftaric acid, coutaric acid glucoside, m-coutaric acid, ethyl galate and ethyl-pcoumarate, and some acids: p-hidroxybenzoic acid, all with positive loading values on PC1. This assumption is in accordance with the literature. Phenolic compounds are directly related to the browning phenomenon of white wines (Singleton & Essau, 1969) because they can be easily oxidized to quinones and polymers (Cacho, 1997; Sapis, Macheix, & Cordonnier, 1983a; Sapis, Macheix, & Cordonnier, 1983b). The main phenols found in white grape juices and wines are hydroxycinnamic esters which can be both oxidation substrates and browning precursors (Cheynier, Osse, & Rigaud, 1988; Romeyer, Sapis, & Macheix, 1985). Also the second principal component seems to contain information on the difference between the seven groups. Wine from the first sample and from samples with 2, 4 and 6 months in a bottle is situated at the right of the plot with negative values of PC2. The most important variables in this case are b* value and chroma ðC ab Þ. In order to observe the contribution of the compounds and colour parameters studied to the differentiation among the wines with different lengths of storage, the results are subjected to a discriminant analysis. Matrix data are divided into training and evaluation set; the training set was used to build the model, and the evaluation set to test its performance. The cross validation method was used to test the computed model.
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2.5 2.0 1.5
PC 2 (19.78%)
1.0 0.5 0.0 control 2 months 4 months 6 months 8 months 10 months 12 months
-0.5 -1.0 -1.5 -2.0 -2.5
-2.0
-1.5
-1.0
-0.5
0.0
0.5
1.0
1.5
2.0
PC 1 (31.27%)
Fig. 2. Scores plot of the samples using the two first principal components obtained by PCA.
Table 4 Discriminant power (F-value) of the variables selected and coefficients of discriminant functions Variable
Rutin Coutaric acid glucoside Ferulic acid b* Eigenvalue Cum.Prop a
F-valuea
1480.774 39.778 10.623 7.702
Standardized coefficients Root 1
Root 2
Root 3
Root 4
1.192 0.622 0.159 0.293 461.131 0.978
0.114 0.537 0.868 0.279 5.918 0.991
0.825 0.810 0.145 0.684 4.062 0.999
0.032 0.253 0.699 0.750 0.131 1.000
Significant at p < 0.001.
Fig. 3. Scatterplot of canonical variates.
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Forward stepwise method selected rutin, coutaric acid glucoside, ferulic acid and b* as the variables of highest discriminant capacity (according to FisherÕs test). Table 4 lists the discriminant power and standardized coefficient for the five functions obtained, which allow to obtain a correct global classification of 100% using the training set and 87.5% using prediction set. Fig. 3 shows the graphical representation of the projections of the points of each group on the plane defined by the two principal canonical axes (functions 1 and 2). Discriminant function 1 is related mainly to rutin and coutaric acid glucoside (in this sequence) whereas function 2 is related to ferulic acid and b* component, both with negative sign. The sets of points show a distribution pattern in which four well-defined groups can be distinguished. It can be observed that the samples with 2 and 4 months of storage are situated at the right side of the plot well separated among them (positive and negative values of root 2, respectively) as well as from the rest. On the left side of Fig. 3, the samples with 6, 8, and 10 months are grouped forming a very homogeneous group at the top. The samples with 12 months appear grouped at the bottom, indicating that these samples are of a darker colour as a result of an oxidation process during storage.
Acknowledgements The authors thank Dr. Deryck Barker for his technical assistance with the English version of the manuscript. References AOAC Official MethodsSM (2003). Official Methods of Analysis of AOAC International (OMA) (17th Ed current through 2nd revision, 2003). Arling, VA: Association of Official Analytical Chemists. Bakker, J., & Timberlake, C. F. (1997). Isolation, identification and characterization of new color-stable anthocyanins occurring in some red wine. Journal of Agricultural and Food Chemistry, 45, 35–43. Benı´tez, P., Castro, R., Sa´nchez Pazo, J. A., & Barroso, C. G. (2002). Influence of metallic content of fino sherry wine on its susceptibility to browning. Food Research Internacional, 35, 785–791. Cacho, J. F. (1997). Oxidacio´n del vino. Factores que condicionan la vida de los vinos blancos jo´venes. Alimentacio´n, Equipos y Tecnologı´a, Diciembre 81–93. Chen, J. H., & Ho, C. T. (1997). Antioxidant activities of caffeic acid and its related hydroxycinnamic acid compounds. Journal of Agricultural and Food Chemistry, 45, 2374–2378. Cheynier, V. F., Osse, C., & Rigaud, J. (1988). Oxidation of grape juice phenolic compounds in model solutions. Journal Food Science, 53, 1729–1731. Cheynier, V., Rigaud, J., Souquet, J. M., Barille´re, J. M., & Moutounet, M. (1989). Effect of pomace contact and hyperoxida-
tion on the phenolic composition and quality of Grenache and Chardonnay wines. American Journal of Enology and Viticulture, 40, 36–42. Cheynier, V., Rigaud, J., Souquet, J. M., Barille´re, J. M., & Moutounet, M. (1990). Must browning in relation to the behaviour of phenolic compounds during oxidation. American Journal of Enology and Viticulture, 41, 346–349. Cheynier, V. F., & Fulcrand, H. (2003). Oxidacio´n de los polifenoles en los mostos y los vinos. In C. Flanzy (Ed.), Enologı´a: Fundamentos Cientı´ficos y Tecnolo´gicos (2nd ed.) (pp. 369–376). Madrid: AMV; Mundi-Prensa. CIE (1986). Colorimetry. Publication No. 15.2. (2nd ed.). Vienna: CIE. Dallas, C., & Laureano, O. (1994). Effects of pH, sulphur dioxide, alcohol content, temperature and storage time on colour composition of a young portuguese red table wine. Journal of the Science of Food and Agriculture, 65, 477–485. Dallas, C., Ricardo da Silva, J. M., & Laureano, O. (1996). Products formed in model wine solutions involving anthocyanins, procyanidin B2 and acetaldehyde. Journal of Agricultural and Food Chemistry, 44, 2402–2407. Es-Safi, N., Guerneve´, C. L., Fulcrand, H., Cheynier, V., & Moutounet, M. (2000). Xanthylium salts formation involved in wine colour changes. International Journal of Food Science and Technology, 35, 63–74. Garcı´a Parrilla, M. C., Heredia, F. J., & Troncoso, A. M. (1999). Sherry wine vinegars: phenolic composition changes during aging. Food Research International, 32, 433–440. Gunata, Z. Y., Sapis, J. C., & Moutounet, M. (1987). Substrates and carboxylic acid inhibitors of grape polyphenoloxidases. Phytochemistry, 26, 1573–1575. ´ lvarez, C., Gonza´lez-Miret, M. L., & Ramı´rez, A. Heredia, F. J., A (2004). CromaLab, ana´lisis de color. Registro General de la Propiedad Intelectual, SE-1052-04, Sevilla, Spain. Kroon, P. A., & Williamson, G. (1999). Hydroxycinnamates in plants and wood: current and future perspectives. Journal of the Science of Food and Agriculture, 79, 355–361. Lee, C., & Jaworsky, A. (1987). Phenolic compounds in white grapes in New York. American Journal of Enology and Viticulture, 38, 277–281. Martinez, M. V., & Whitaker, J. R. (1995). The biochemistry and control of enzymatic browning. Trends in Food Sciences and Technology, 6, 195–200. Pen˜a-Neira, A., Herna´ndez, T., Garcı´a-Vallejo, C., Estrella, I., & Suarez, J. A. (2000). A Survey of phenolic compounds in Spanish wines of different geographical origin. European Food Research and Technology, 210, 445–448. Pe´rez-Magarin˜o, S., & Gonza´lez-San Jose´, M. L. (2001). Influence of commercial pectolytic preparations on the composition and storage evolution of Albillo white wine. International Journal of Food Science and Technology, 36, 789–796. Oszmianski, J., Cheynier, V., & Moutounet, M. (1996). Iron-catalysed oxidation of (+)-catechin in model system. Journal of Agricultural and Food Chemistry, 44, 1712–1715. Revilla, I., Pe´rez-Magarin˜o, S., Go´nzalez-San Jose´, M. L., & Beltra´n, S. (1999). Identification of anthocyanin derivatives in grape skin extracts and red wines by LC-DAD-MS. Journal of Chromatography A, 847, 83–90. Romeyer, M. F., Sapis, J., & Macheix, J. (1985). Hydroxycinnamic esters and browning potential in mature berries of some grape varieties. Journal of Sciences and Food Agriculture, 36, 728–732. Sapis, C., Macheix, J. J., & Cordonnier, R. J. (1983a). The browning capacity of grapes. I. Changes in polyphenol oxidase activities during development and maturation of the fruit. Journal of Agricultural and Food Chemistry, 31, 342–345. Sapis, C., Macheix, J. J., & Cordonnier, R. J. (1983b). The browning capacity of grapes. II. Browning potential and polyphenol oxidase
A´.F. Recamales et al. / Food Research International 39 (2006) 220–229 activities in different mature grape varieties. American Journal of Enology and Viticulture, 34, 157–162. Saucier, C., Bourgeois, G., Christiane, V., Roux, D., & Glories, Y. (1997). Characterization of (+)-catechin-acetaldehyde polymers: a model for colloidal state of wine polyphenols. Journal of Agricultural and Food Chemistry, 45, 1045–1049. Simpson, R. F. (1982). Factors affecting oxidative browning of white wine. Vitis, 21(3), 233–239. Singleton, V. L. (1987). Oxygen with phenols and related reactions in musts, wines and model systems: observations and practical implications. American Journal of Enology and Viticulture, 38, 69–76. Singleton, V. L., & Essau, P. (1969). Quality and processing relationships in wine production. Phenolic substances in grapes and wine and their significance (Advances in Food Research 161). New York: Academic Press.
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Singlenton, V. L., Timberlake, C. F., & Lea, A. G. H. (1978). The phenolic cinnamates of white grapes and wines. Journal of Sciences and Food Agriculture, 29, 403–410. Somers, T. C., & Evans, M. E. (1986). Evolution of red wine: I. Ambient influences on colour composition during early maturation. Vitis, 25, 31–39. Statsoft, Inc., (1999). Statistica for Windows v. 5.5. Tulsa, OK: Statsoft, Inc. Wyszecki, G., & Stiles, W. S. (1982). Color science. Concepts and methods. Quantitative data and formulae (2a ed.). New York: Wiley. Zafrilla, P., Morillas, J., Mulero, J., Cayuelas, J. M., Martı´nezCacha´, A., Pardo, F., et al. (2003). Changes during storage in conventional and ecological wine: phenolic content and antioxidant activity. Journal of Agricultural and Food Chemistry, 51, 4694–4700.
The effect of time and storage conditions on the phenolic composition and colour of white wine ´ ngeles F. Recamales a, Ana Sayago a, M. Lourdes Gonza´lez-Miret b, A Dolores Hernanz a,* b
a Department of Analytical Chemistry, Faculty of Experimental Science, University of Huelva, Spain Laboratory of Food Colour and Quality, Department of Nutrition and Food Science, Faculty of Pharmacy, University of Seville, Spain
Received 22 July 2005; accepted 24 July 2005
Abstract The influence of different storage conditions on the colour and phenolic composition of young white wine was evaluated along 12 months of storage. The wine was bottled, and stored using three different conditions: position of bottles illumination and temperature variations. The results indicate that the time of storage has a significant effect (p < 0.001) on colour parameters, the majority of the phenols studied and the total phenol content. A significant decrease of phenols is detected during storage, which result in a change in the colour of the wine from pale yellow to yellow-brown. However, it can be noted that their loss was significantly higher in the wine subjected to variable temperature than in the wine stored at a constant temperature after 12 months. The principal component analysis was applied to the wine analysis data measured throughout the storage time, and the scatter plot of the samples was obtained for visual inspection. The effect of the storage time was clearly reflected in this analysis. A good differentiation among wines according to the length of storage was also obtained using linear discriminant analysis. 2005 Elsevier Ltd. All rights reserved. Keywords: White wine; Storage; Colour; Phenolic composition
1. Introduction Phenolic compounds are important components of wine. They not only contribute to their sensory characteristics of wine, such as colour, flavor and astringency (Lee & Jaworsky, 1987), but may also act as antioxidants, with mechanisms involving both free-radical scavening and metal chelation (Benı´tez, Castro, Sa´nchez Pazo, & Barroso, 2002). The composition and concentration of phenolic in wine depend on the type of grape used for vinification, the procedures employed for wine-making and the chemical reactions that occur during the aging of wine (Pen˜a*
Corresponding author. Tel.: +34 959 219960; fax: +34 959 219942. E-mail address: [email protected] (D. Hernanz).
0963-9969/$ - see front matter 2005 Elsevier Ltd. All rights reserved. doi:10.1016/j.foodres.2005.07.009
Neira, Herna´ndez, Garcı´a-Vallejo, Estrella, & Suarez, 2000). Wine is subjected to continuous changes in composition during storage. Many studies have been performed in order to describe the chemical changes during bottle aging and their influence on the sensory perception of red wine. During storage and aging of red wine, polyphenolic compounds are gradually modified. Reactions among anthocyanins, flavan-3-ol, proanthocyanidins and other compounds, such as glyoxylic acid, piruvic acid, and acethaldehyde, and also between flavonols themselves have been observed. These reactions are responsible for the appearance of new pigments (Bakker & Timberlake, 1997; Dallas, Ricardo da Silva, & Laureano, 1996; Revilla, Pe´rez-Magarin˜o, Go´nzalez-San Jose´, & Beltra´n, 1999), and hence for the disappearance of oligomer
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proanthocyanidin from solution. These processes affect colour and colloidal stability (Saucier, Bourgeois, Christiane, Roux, & Glories, 1997) and also the nutraceutical properties (Chen & Ho, 1997; Kroon & Williamson, 1999). The rate of the progressive decline in anthocyan and the formation of new stable colour pigments is influenced by such factors as temperature, pH, sulphites and oxygen content. The most rapid changes in the colour characteristics of red wine occur during the first year of storage (Somers & Evans, 1986). During this time, temperature has a more important influence than oxygen concentration. Length of storage is the other factor influencing wine colour since most of the changes occurring during wine storage are time-dependent (Dallas & Laureano, 1994). In white wine, one of the main problems posed is its unstable colour after bottling. Essentially, browning results from the oxidation of phenols to quinones, which in turn polymerise to form macromolecules with a typical yellow-brown hue (Singleton, 1987). In particular, oxidative browning of white wines was shown to be especially related to flavanol content (Cheynier, Rigaud, Souquet, Barille´re, & Moutounet, 1989; Simpson, 1982). Browning usually starts at the early stages of winemaking by enzymatic reactions (Cheynier, Rigaud, Souquet, Barille´re, & Moutounet, 1990), where hydroxycinnamic acid esters play a crucial role (Singlenton, Timberlake, & Lea, 1978). Caffeoyltartaric acid and p-coumaroyl tartaric acid were both shown to be onverted to caffeoyltartaric acid o-quinone which then underwent further reduction and addition reactions involving other phenolic or non-phenolic compounds (Cheynier et al., 1989, 1990; Gunata, Sapis, & Moutounet, 1987; Singlenton et al., 1978). After fermentation, polyphenoloxidase activity decreases and oxidative browning is related to polyphenol chemical oxidation (Singleton, 1987). Flavonols were shown to play an important role in this regard (Cheynier et al., 1989; Simpson, 1982) and catechin autoxidation was shown to generate the same products as enzymatic oxidation (Oszmianski, Cheynier, & Moutounet, 1996). Recent studies demonstrated a new oxidate process, converting flavonols into yellow xanthylium pigments, potentially contributing to white wine browning (Es-Safi, Guerneve´, Fulcrand, Cheynier, & Moutounet, 2000), which is generally expressed in an increase of absorption in the 400–500 nm (Martinez & Whitaker, 1995). However, there is little reported about the evolution of the phenolic compounds and colour during storage, or the effects of different conditions during the wine white storage. Zafrilla et al. (2003) studied the change of the phenolic composition and antioxidant activity in ecological and conventional white wines during the first 7 months of storage in the dark. Other authors have considered the changes in some components of white
221
wine from Albillo grape variety during the years of storage (Pe´rez-Magarin˜o & Gonza´lez-San Jose´, 2001). The purpose of this study was to evaluate the influence of different storage conditions (temperature, illumination, position of bottles) on the colour properties and the phenolic content of white wine during 12 months. Statistical techniques, such as analysis of variance, principal component analysis and linear discriminant analysis were used to distinguish among wines with different lengths of storage.
2. Material and methods 2.1. Samples A total of 98 samples of bottled wine were analysed. This wine was elaborated with the white grape variety ‘‘Zalema’’ which is exclusively grown in ‘‘Condado de Huelva’’, a restricted wine-producing zone with CBOwines, situated in the southwest of Spain. The wines are produced according to traditional methods with fermentation to controlled temperatures. Due to the climatic conditions of the zone (a sunny region with warm temperatures and low rain fall), an early grape harvest was performed. After cold stabilization the wine was bottled in green glass bottles of a capacity with 750 mL and stored in two different conditions: (i) one set of bottles was stored in a partly open warehouse in which the bottles were subjected to temperature variations (both daily and seasonal), this process is referred to as ‘‘variable’’; (ii) the other set of bottles was stored in a cellar where the temperature varied between 15 and 20 C throughout the year, this process is referred to as ‘‘constant’’. In each set, half of the bottles were placed in a horizontal position and other half in a vertical position. Within each subset half of the bottles were left in the dark and the other half in conditions of variable light. The wine was stored for 12 months. Samples (two bottles of each set) were taken at the time of bottling, and then the same process was repeated every 2 months.
3. Methods 3.1. Chemical analyses Chemical parameters with enological meaning were measured according to the methods of analysis of the Office International de la Vigne et du Vin: ethanol, total sulphur dioxide, total acidity, pH, volatile acidity, total sugars, total polyphenols (AOAC Official MethodsSM, 2003). Analyses of all the samples were made in duplicate.
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3.2. Analysis of phenolic compounds All individual polyphenols were analysed by high performance liquid chromatography. An Agilent 1100 series (Palo Alto, CA, USA) chromatograph equipped with a diode-array detector was used. A gradient of solvent A (water–acetic acid, 98:2, v/v) and solvent B (water–acetonitrile–acetic acid, 58:40:2, v/v/v) was applied to a reversed-phase Nova-pack C18 column (30 cm · 3.9 mm I.D.) as follows: 0–60 min, 45% B linear; 60–70 min, 45% B isocratic; 70–75 min, 80% B linear; 75–100 min, washing and re-equilibration of the column. The method employed possesses sufficient selectivity and sensitivity to allow direct analysis of wines without prior sample preparation, except filtration before injection (0.45 lm filters). The flow was 1.0 mL/min and the temperature was set at 20 C. The volume injected was 100 lL. Detection was performed by scanning from 200 to 700 nm. Identification of chromatographic peaks were carried out by comparing their retention times and spectra with those of standards. Quantification of phenolic compounds was carried out by area measurements at 280 nm except rutin which was quantified at 320 nm. Quantitative assays were achieved using external calibration curves for all standard phenols by dissolution of the standard solution. All analyses were repeated three times and the results were expressed as mean values. Standards of phenolic compounds were from Merck (gallic acid, p-hydroxy benzoic acid, ferulic acid), Fluka (tyrosol, caffeic acid, p-coumaric acid, m-coumaric acid, catechin, protocatechuic acid) and Sigma (rutin). Phenolic compounds, which are not available in the market as standards, have been identified by their retention time and spectra according to the literature. These compounds have been assayed by assuming that their molar absorptivity is the same as that of the corresponding free standard molecule. 3.3. Colour measurement Colour was assessed by tristimulus colorimetry based on transmittance spectra with the application of the equations proposed by the Commission Internationale de lÕEclariage (CIE, 1986). The spectra were registered directly on the wine, using a diode array spectrophotometer (Unicam 5625 UV/Vis spectrophotometer) set to measure in the visible region (k = 380–770 nm) at constant intervals (Dk = 2 nm) and integrated using the ´ lvarez, Gonza´lezthe software CromaLab (Heredia, A Miret, & Ramı´rez, 2004), which take into account the CIE recommendations. The uniform colour space CIE 1976-(L*a*b*) (CIELAB) was used. As is required by the weighted-ordinate method, the visible spectra of the samples were weighted according to the characteristic factor of the selected visual reference conditions: 10 visual
field observer and standard illuminant D65, which corresponds to natural daylight (Wyszecki & Stiles, 1982). Within the approximately uniform colour space CIELAB, two colour coordinates, a* and b*, as well as lightness, L*, are defined. Coordinate a* takes positive values for reddish colours and negative values for the greenish ones, whereas b* takes positive values for yellowish colours and negative values for the bluish ones. L* is an approximate measurement of lightness, which is the property according to which each colour can be considered as equivalent to a member of the grey scale, between black and white, taking values within the range 0–100, respectively. From the CIELAB space, other parameters are defined, such as chroma ðC ab Þ and hue (hab): 2
2 1=2
C ab ¼ ½ða Þ þ ðb Þ
;
hab ¼ arctanðb =a Þ.
Chroma ðC ab Þ is the attribute which allows to determine for each hue its degree of difference in comparison to a grey colour with the same lightness, so it is considered the quantitative attribute of colourfullness. Hue (hab) is qualitative the attribute according to which colours have been traditionally defined as reddish, greenish, etc. It is the attribute which allows to distinguish a colour with reference to a grey colour with the same lightness. This attribute is related to the differences in absorbance at different wavelengths and is considered the qualitative attribute of colour. 3.4. Data analysis The factors affecting the stability of the bottled wines were investigated. The factors varied were storage temperature and time, position of the bottled, and illumination exposure and the levels were mentioned above. Analysis of variance was made using general linear model (GLM) to determine whether mean values for phenolic compounds and colour parameters differed with storage time and conditions. The means were compared by the least significant difference (LSD) test at a significance level of 0.05. Pattern recognition (PR) techniques including principal component analysis (PCA) and linear discriminant analysis (LDA) were applied on experimental standardized data to distinguish among wines with different lengths of storage. Statistical analyses were performed using the statistical package STATISTICA99 from Statsoft (1999).
4. Results The study of the storage of white wine was carried out over 12 months. Before the storage two samples were taken and analysed for chemical parameters with enological meaning. The mean values obtained in wines were: pH, 3.06; density, 0.9906 g/cm3; ethanol, 11.1%
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v/v; reducing sugars, 1.0 g/L; total acidity, 5.2 g tartaric acid/L; volatile acidity, 0.23 g acetic acid/L; SO2 total, 142.82 mg/L.
12
100˚
223
90˚
80˚
110˚
70˚
120˚
60˚
10
4.1. Colour changes 8
b*
For the study of the colour in this work the system CIE 1976-(L*a*b*) (CIELAB) has been selected. The analysis of variance was applied for testing the significance of the effects of storage time and conditions on these variables. The results showed that only the time of storage has a significant influence (p < 0.001) on the studied parameters (Table 1). Fig. 1 shows the distribution of the wines grouped according to the time of storage in the (a*b*) colour plane, in which the colour points are represented regarding the axes green-red (a* + a*) and blue-yellow (b* + b*). It can be observed that most of the samples are located inside a defined area between the 90 and the 120 of hue angle (hab) that belongs to the medium yellow or with a very slight tendency to the green. Also, this grouping is given in a very near area to the origin of coordinates, with low values of chroma ðC ab Þ, that is with a high proportion of white light transmitted by the samples. These data, besides the high levels of lightness (L*) near to 100% of quantity of transmitted global light, determine the final colour in the category of the pale yellow.
6
4 0 months 2 months 4 months 6 months
2
8 months 10 months 12 months
0
-6
-4
-2
0 a*
2
4
6
Fig. 1. Colour diagram (a*,b*).
The increases of the chroma ðC ab Þ and decreases of the hue (hab) are the characteristic changes in wines during storage. During the storage, an evolution in the values of the two colour coordinates (a* and b*) are observed. The value of a* (red component) displays initially a reduction from 0.86 to 1.47, but soon it
Table 1 Influence of conditions and storage time on colour parameters (CIELAB)a Source of variation
L*
a*
b*
C ab
hab
Storage period (months) 0 2 4 6 8 10 12 Significanceb
99.76c 98.41c 98.98c 99.28c 101.67d 99.69c 102.95d ***
0.86c 0.21c 0.91c 0.77c 1.49c 1.27c 4.07d ***
3.38c 3.32c 3.17c 3.61c 2.45c 3.40c 7.77d ***
3.49c 3.60c 3.29c 3.69c 2.91c 3.67c 8.81d ***
105.71c 102.70c 107.07c 104.11c 147.77d 112.10e 63.42f ***
Temperature Variable Constant Significanceb
99.79 100.54 ns
0.02 0.18 ns
4.06 3.85 ns
4.37 4.29 ns
108.82 103.58 ns
Exposition Light Dark Significanceb
100.27 100.05 ns
0.27 0.07 ns
3.83 4.08 ns
4.18 4.48 ns
102.91 109.48 ns
Position Horizontal Vertical Significanceb
99.90 100.43 ns
0.13 0.07 ns
4.06 3.85 ns
4.40 4.26 ns
100.90 111.49 ns
a b
Data followed by different letters for each column and source of variation are significantly different by LSD test. ns, *, **, ***, not significant and significance at p < 0.05, 0.01 and 0.001, respectively.
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increases sharply in the last two months of the test to reach value of 4.07. However, the values of b* practically remain constant until the 10th month in which it experiences a sharp increase, reaching the value 7.77. Therefore, the global result is an increase of the a* and b* values, resulting in a change in the colour of the wine from pale yellow to yellow-brown. 4.2. Changes in phenolic compounds during storage In the analysis of individual phenolic contents, 17 phenols were identified and quantified as follows: hydroxycinnamic acid (caftaric acid, p-coutaric acid, coutaric acid glucoside, fertaric acid, m-coutaric acid, caffeic acid, ferulic acid, p-coumaric acid, m-coumaric acid, ethyl caffeate, ethyl p-coumarate), benzoic acids (p-hydroxybenzoic acid, ethyl galate), flavonoids (catechin, rutin), tyrosol, as well as an unknown compound (compound 1), this phenol which has an absorption spectra similar to p-hydroxy benzoic acid spectra, so it was quantified as this acid. Table 2 shows the mean for the phenolic compound contents of the white wine. This table reports the effect of different conditions during the storage of the wine white. It can be seen that the temperature (variable/constant) has a significant influence on the total phenols content (expressed as mg/l gallic acid) and the light exposure on the tyrosol and caftaric acid concentration, at the 5% significance level. The factor of position (horizontal/vertical) of the bottles has no effect on any of the compounds studied, as can be observed in Table 2. With regard to the evolution of the total phenols, a significant decrease is detected during storage, as has been shown in earlier work (Benı´tez et al., 2002). This decrease occurred mainly in the last 4 months and is related to the changes of colour observed in the wine. However, it can be noted that their loss was significantly higher in the wine subjected to daily and seasonal temperature variations (8.26%) than in the wine stored at a constant temperature (4.42%) after 12 months. The study of individual behaviour of phenolic compounds indicates that the content of most of the phenolic compounds identified in the wines studied diminishes with time, with the exception of tyrosol, caffeic acid, ferulic acid, p-coumaric acid and compound 1. Recent experimental evidence indicates that storage conditions are expected to strongly affect the content of phenols, since they can undergo modifications during storage, mainly due to hydrolysis, oxidations and complexations (Zafrilla et al., 2003). Other factors such as light and temperature can contribute to the degradation of phenolic compounds (Cheynier & Fulcrand, 2003). Hydrolysis (enzymatic or not) is mainly responsible for the increase of simpler compounds, such as tyrosol and free phenolic acids. So, in the same conditions of light, the amount of tyrosol is 1.4 times higher in the wines stored at a vari-
able temperature than those stored at a constant temperature. Ferulic acid, caffeic acid, p-coumaric acid and compound 1 levels also increased with storage time, but in these cases the temperature effect is not significant. After 12 months of storage, the samples show significant losses of phenolic compounds relative to initial values. Caftaric acid, m-coutaric acid and ethyl caffeate are the compounds that exhibited a lower pronounced concentration reduction (14.67–9.32, 0.58–0.28, 0.69– 0.42 mg/L, respectively). Catechin levels also diminish with time which is according to other authors. This decrease occurred mainly in the last 2 months. Wine that was stored for 10 months has a mean concentration of catechin of 1.31 mg/L and after 12 months the catechin was not detected. Simpson (1982) has reported that catechins and procyanidins have a strong influence on the susceptibility of white wines to browning, because flavan-3-ols may suffer oxidations and polymerizations. The profiles of changes in the concentration of coutaric acid glucosides, as well as p-hydroxybenzoic acid and ethyl gallate were very similar. Their contents progressively decrease, and from the eighth month they increase slightly. With regard to the tartaric ester of the ferulic acid, their concentration decreases, and from the sixth month increases, this increase being slightly higher for samples stored at a constant temperature than at a variable temperature (32% and 7%, respectively). While m-coumaric acid and ethyl p-coumarate levels also diminish until the sixth month and after practically do not change. The decrease encountered for coutaric acid glucosides content (1.44–0.47 mg/L) may be due to the hydrolysis in the acidic wine medium, while oxidation processes may have been responsible for the decrease in concentration of hydroxycinnamic derivatives (Garcı´a Parrilla, Heredia, & Troncoso, 1999). Among the flavonols studied only the rutin could be detected and quantified in the wines. Their content also diminishes and could not be detected after 6 months of storage. 4.3. Multivariate analysis Another objective of this work was to check the ability of the phenolic compounds and colour variables to differentiate among wines with different lengths of storage. For this reason, several pattern recognition (PR) techniques including principal component analysis (PCA) and linear discriminant analysis (LDA) have been applied on experimental standardized data. Applied to our data set, PCA revealed that the first four principal components explain 70% of total variance (Table 3). A plot of the scores of PC1 versus PC2, i.e., the projection of the samples along the directions identified by the first two PCs, is reported in Fig. 2. It is apparent that samples are grouped in a similar way to
Table 2 Influence of conditions and storage time on phenolic compounds (mg/L)a Source of variation
Coutaric acid glucoside
p-Coutaric acid
Tyrosol
p-Hydroxybenzoic acid
Catechin
m-Coutaric acid
Fertaric acid
Storage period (months) 0 231.05c 2 220.00c 4 244.80d 6 234.86d 8 228.60c 10 216.41c 12 216.51c b Significance ***
14.67c 11.14c 11.11c 8.33d 8.33d 8.21d 9.32d ***
1.44c 1.59c 0.56d 0.44d 0.33d 0.37d 0.47d **
0.76c 1.83d 1.09d 0.95e 1.36e 1.04e 1.61e *
22.60c 8.88d 11.01d 10.78d 10.40d 11.20d 13.21e *
1.16c 1.25c 0.72cd 0.31e 0.26e 0.41e 0.79cf ***
1.42c 1.30c 1.52c 1.02c 0.98c 1.31c nd ***
0.58c 0.56cd 0.65d 0.32e 0.36e 0.33e 0.28e ***
1.19c 0.95c 0.93c 0.64d 0.71d 0.68d 0.85cd ***
Temperature Variable Constant Significanceb
220.89 232.84 **
9.29 9.53 ns
0.59 0.67 ns
1.24 1.39 ns
10.86 10.97 ns
0.69 0.56 ns
1.04 0.99 ns
0.44 0.40 ns
0.83 0.75 ns
Exposition Light Dark Significanceb
226.15 227.58 ns
8.76 10.05 *
0.58 0.67 ns
1.16 1.46 ns
9.72 12.11 *
0.61 0.64 ns
1.02 1.02 ns
0.39 0.44 ns
0.76 0.82 ns
Position Horizontal Vertical Significanceb
227.95 225.78 ns
9.51 9.31 ns
0.61 0.65 ns
1.17 1.45 ns
11.41 10.42 ns
0.66 0.60 ns
1.07 0.97 ns
0.42 0.42 ns
0.80 0.78 ns
Caffeic acid
Ethyl galate
Ferulic acid
Compound 1
p-Coumaric acid
m-Coumaric acid
Ethyl caffeate
Ethyl p-coumarate
Rutin
Storage period (months) 0 0.92c 2 1.85c 4 2.51d 6 1.52c 8 2.19e 10 2.08e 12 2.39e b Significance **
1.73c 1.35c 1.17d 0.99d 1.01d 1.10d 1.22d ***
0.54c 0.76c 1.11d 0.87cd 0.97cd 0.91cd 2.00e ***
199.49c 189.12c 202.44 c 159.67d 163.72d 162.20d 218.48e ***
0.06 0.20 0.41 0.30 0.37 0.77 0.20 ns
0.12c 0.53d 0.28d 0.15e 0.21e 0.20e 0.18e ***
0.69c 0.76d 0.65c 0.53c 0.56c 0.57c 0.42e ***
0.13c 0.36d 0.28de 0.16ef 0.17f 0.17f 0.15f ***
0.84c 0.82c 0.75d nd nd nd nd **
Temperature Variable Constant Significanceb
1.15 1.14 ns
1.08 1.13 ns
182.85 182.36 ns
0.47 0.28 ns
0.26 0.26 ns
0.58 0.59 ns
0.22 0.21 ns
2.12 2.06 ns
A´.F. Recamales et al. / Food Research International 39 (2006) 220–229
Caftaric acid
Source of variation
Total polyphenols
0.27 0.26 ns (continued on next page) 225
A´.F. Recamales et al. / Food Research International 39 (2006) 220–229
PC
Eigenvalue
Explained variance (%)
Cumulative variance (%)
1 2 3 4
8.13 3.96 2.43 1.54
35.35 17.25 10.59 6.70
35.35 52.60 63.19 69.90
0.57 0.59 ns
0.23 0.20 ns
0.26 0.26 ns
Table 3 Variance explained by the first PCs
a
b
Data followed by different letters for each column and source of variation are significantly different by LSD test. ns, *, **, ***, not significant and significance at p < 0.05, 0.01 and 0.001, respectively. Nd: not detected.
0.26 0.25 ns 0.45 0.30 ns 184.46 180.75 ns 1.07 1.13 ns 2.14 2.03 ns Position Horizontal Vertical Significanceb
1.16 1.13 ns
0.26 0.26 ns 0.22 0.20 ns 0.55 0.61 ns 0.25 0.26 ns 0.43 0.32 ns 176.15 189.06 ns 1.04 1.16 ns 1.09 1.19 ns 1.93 2.25 ns Exposition Light Dark Significanceb
Source of variation
Caffeic acid
Ethyl galate
Ferulic acid
Compound 1
p-Coumaric acid
m-Coumaric acid
Ethyl caffeate
Ethyl p-coumarate
Rutin
226
our classification. Moreover, an interesting feature can be pointed out: such groups are arranged along the direction of PC1, in a way that reflects their storage time, that is, samples that have been a shorter time in bottles have higher scores, and those which have been bottled for a longer time have lower scores on PC1. The loadings, i.e., the coefficients that define the weight of each original variable in the PCs, can then be investigated in order to understand which chemical compounds are responsible for the ranking of samples on the basis of storage time on the first PC. A comparison of scores and loadings for PC1 allows the identification of the compounds having a higher influence on this feature; analytes with highly positive loadings on PC1 should be regarded as compounds whose concentration decreases with storage time, while analytes with highly negative loadings tend to increase. The most important compounds are esters: caftaric acid, coutaric acid glucoside, m-coutaric acid, ethyl galate and ethyl-pcoumarate, and some acids: p-hidroxybenzoic acid, all with positive loading values on PC1. This assumption is in accordance with the literature. Phenolic compounds are directly related to the browning phenomenon of white wines (Singleton & Essau, 1969) because they can be easily oxidized to quinones and polymers (Cacho, 1997; Sapis, Macheix, & Cordonnier, 1983a; Sapis, Macheix, & Cordonnier, 1983b). The main phenols found in white grape juices and wines are hydroxycinnamic esters which can be both oxidation substrates and browning precursors (Cheynier, Osse, & Rigaud, 1988; Romeyer, Sapis, & Macheix, 1985). Also the second principal component seems to contain information on the difference between the seven groups. Wine from the first sample and from samples with 2, 4 and 6 months in a bottle is situated at the right of the plot with negative values of PC2. The most important variables in this case are b* value and chroma ðC ab Þ. In order to observe the contribution of the compounds and colour parameters studied to the differentiation among the wines with different lengths of storage, the results are subjected to a discriminant analysis. Matrix data are divided into training and evaluation set; the training set was used to build the model, and the evaluation set to test its performance. The cross validation method was used to test the computed model.
A´.F. Recamales et al. / Food Research International 39 (2006) 220–229
227
2.5 2.0 1.5
PC 2 (19.78%)
1.0 0.5 0.0 control 2 months 4 months 6 months 8 months 10 months 12 months
-0.5 -1.0 -1.5 -2.0 -2.5
-2.0
-1.5
-1.0
-0.5
0.0
0.5
1.0
1.5
2.0
PC 1 (31.27%)
Fig. 2. Scores plot of the samples using the two first principal components obtained by PCA.
Table 4 Discriminant power (F-value) of the variables selected and coefficients of discriminant functions Variable
Rutin Coutaric acid glucoside Ferulic acid b* Eigenvalue Cum.Prop a
F-valuea
1480.774 39.778 10.623 7.702
Standardized coefficients Root 1
Root 2
Root 3
Root 4
1.192 0.622 0.159 0.293 461.131 0.978
0.114 0.537 0.868 0.279 5.918 0.991
0.825 0.810 0.145 0.684 4.062 0.999
0.032 0.253 0.699 0.750 0.131 1.000
Significant at p < 0.001.
Fig. 3. Scatterplot of canonical variates.
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A´.F. Recamales et al. / Food Research International 39 (2006) 220–229
Forward stepwise method selected rutin, coutaric acid glucoside, ferulic acid and b* as the variables of highest discriminant capacity (according to FisherÕs test). Table 4 lists the discriminant power and standardized coefficient for the five functions obtained, which allow to obtain a correct global classification of 100% using the training set and 87.5% using prediction set. Fig. 3 shows the graphical representation of the projections of the points of each group on the plane defined by the two principal canonical axes (functions 1 and 2). Discriminant function 1 is related mainly to rutin and coutaric acid glucoside (in this sequence) whereas function 2 is related to ferulic acid and b* component, both with negative sign. The sets of points show a distribution pattern in which four well-defined groups can be distinguished. It can be observed that the samples with 2 and 4 months of storage are situated at the right side of the plot well separated among them (positive and negative values of root 2, respectively) as well as from the rest. On the left side of Fig. 3, the samples with 6, 8, and 10 months are grouped forming a very homogeneous group at the top. The samples with 12 months appear grouped at the bottom, indicating that these samples are of a darker colour as a result of an oxidation process during storage.
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