Food Chemistry 172 (2015) 486–496
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The combined impact of vineyard origin and processing winery on the elemental profile of red wines Helene Hopfer a,b,⇑, Jenny Nelson a,c, Thomas S. Collins a,b, Hildegarde Heymann a, Susan E. Ebeler a,b a
Department of Viticulture and Enology, University of California-Davis, One Shields Avenue, Davis, CA 95616, USA Food Safety and Measurement Facility, University of California-Davis, One Shields Avenue, Davis, CA 95616, USA c Agilent Technologies, Inc., 5301 Stevens Creek Blvd., Santa Clara, CA 95051, USA b
a r t i c l e
i n f o
Article history: Received 23 May 2014 Received in revised form 8 September 2014 Accepted 19 September 2014 Available online 26 September 2014 Keywords: Wine Elemental composition Inductively-coupled plasma-mass spectrometry (ICP-MS) Vineyard Winery Determination of geographical origin
a b s t r a c t The combined effects of vineyard origin and winery processing have been studied in 65 red wines samples. Grapes originating from five different vineyards within 40 miles of each other were processed in at least two different wineries. Sixty-three different elements were determined with inductively coupledplasma mass spectrometry (ICP-MS), and wines were classified according to vineyard origin, processing winery, and the combination of both factors. Vineyard origin as well as winery processing have an impact on the elemental composition of wine, but each winery and each vineyard change the composition to a different degree. For some vineyards, wines showed a characteristic elemental pattern, independent of the processing winery, but the same was found for some wineries, with similar elemental pattern for all grapes processed in these wineries, independent of the vineyard origin. Studying the combined effects of grapegrowing and winemaking provides insight into the determination of geographical origin of red wines. Ó 2014 Elsevier Ltd. All rights reserved.
1. Introduction Determining the geographical origin of food products has gained increased research interest over the last decade, mostly due to growing concern and interest of consumers to know the origin of the food they eat (Drivelos & Georgiou, 2012; Kelly, Heaton, & Hoogewerff, 2005). The European Union (EU) established various food quality schemes based on geographical regions, thus, successfully classifying food products according to the geographical origin has also an economic component, as food products tend to sell for higher prices if associated with a certain geographical origin (Drivelos & Georgiou, 2012). Especially for specialty food products, with a strong reputation of and association to specific geographical areas (e.g. ham, cheese or wine), fraud with regards to geographical origin is expected, and various analytical strategies have been proposed. Besides untargeted profiling methods, such as nuclear magnetic, infrared and fluorescence spectroscopy, the use of stable isotope ratios, as well as multi-element profiles have been proposed for food authenticity (Drivelos & Georgiou, 2012; Kelly et al., 2005).
⇑ Corresponding author at: HM.Clause, 9241 Mace Blvd., Davis, CA 95616, USA. Tel.: +1 530 220 2116. E-mail address: [email protected] (H. Hopfer). http://dx.doi.org/10.1016/j.foodchem.2014.09.113 0308-8146/Ó 2014 Elsevier Ltd. All rights reserved.
From an analytical standpoint, the presence and/or absence of certain elements in a food product as well as ratios of certain element to each other could be used for elemental fingerprinting. However, before a successful determination of geographical origin of wines is possible, one needs to understand (i) how controlled studies correlate to real life grapegrowing and winemaking, (ii) which changes are possibly introduced during the whole production chain, (iii) how different varieties and/or wine styles vary, and finally (iv) how variable the impact of winery processes within and between different regions and countries is. The major elements in wine, present at levels between 10 and 1000 mg/L, are Ca, K, Na, and Mg, followed by minor elements, such as Al, Fe, Cu, Mn, Rb, Sr, and Zn, present in the range of 0.1–10 mg/L. Trace elements are present in the ppt range (0.1–1000 lg/L), and include Ba, Cd, Co, Cr, Li, Ni, Pb, and V among others (Pohl, 2007). The elemental composition of wine is the result of many factors, including the elemental composition of the soil the vine is growing on, the viticultural practices (application of fertilizers, pesticides, herbicides, and insecticides; irrigation), as well as winemaking processes, including storage and ageing (Aceto, 2003; Almeida & Vasconcelos, 2003a,b; Castiñeira Gómez, Brandt, Jakubowski, & Andersson, 2004; Cheng & Liang, 2012; Galani-Nikolakaki & Kallithrakas-Kontos, 2006; Hopfer, Nelson, Mitchell, Heymann, & Ebeler, 2013; Jakubowski, Brandt,
H. Hopfer et al. / Food Chemistry 172 (2015) 486–496
Stuewer, Eschnauer, & Görtges, 1999; Kristl, Veber, & Slekovec, 2002; Nicolini, Larcher, Pangrazzi, & Bontempo, 2004; Pereira, 1988; Pohl, 2007; Rossano, Szilágyi, Malorni, & Pocsfalvi, 2007; Tariba, 2011; Volpe et al., 2009). Volpe et al. (2009) categorise elements into so called (i) ‘‘natural’’ elements which are the result of their presence in the vineyard soil and their uptake by the vine plant (Al, B, Ba, Li, Mg, Mo, Si, Sr, Ti, rare earth elements (REEs), transition elements of the second and third period), (ii) ‘‘artificial’’ elements which result from human intervention (viticultural practices, winemaking procedures, environmental pollution; e.g. Pb, Co, Cr, Ni, V, Cd, Hg), and (iii) elements that are both ‘‘natural’’ and ‘‘artificial’’, and result from either endogenous or exogenous processes (e.g. Ca, Mg, Co, Zn, Fe, P, Na, K) (Pohl, 2007) (see also Fig. 1a).
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1.1. Viticultural changes in elemental composition From a plant perspective, elements like K, P, and N are essential for a plant’s health, thus, the presence of these elements in wine is expected. Elements, such as K, Ca, Cu, Cd, Mn, Zn, and Pb, are used in fertilizers, pesticides, and fungicides (Pohl, 2007), in some cases (e.g. Cd, Pb) due to anthropogenic pollution (Kment et al., 2005). Some elements have beneficial effects on the plant, higher yield, sugar accumulation, polyphenols and amino acids in wine grapes have been reported after the application of B, Cr, Mn, Mo, W, and Zn onto the vine or vineyard soil (Aceto, 2003; Pereira, 1988), thus, are most likely also found in the resulting wine. The proximity to an ocean has been reported to increased Na levels in the grapes resulting from marine sprays, while wines from vineyards closely
Fig. 1. (a) Elements that can be changed by grapegrowing and/or winemaking practices (Aceto, 2003; Almeida & Vasconcelos, 2003a,b; Castiñeira Gómez, Brandt et al., 2004; Cheng & Liang, 2012; Eschnauer et al., 1989; Jakubowski et al., 1999; Kristl et al., 2002; Nicolini et al., 2004; Pereira, 1988; Rossano et al., 2007; Tariba, 2011; Volpe et al., 2009). (b) Elements that have been used for the determination of geographical origin of wines from different regions within Australia (Martin et al., 2012), Canada (Greenough et al., 1997; Taylor et al., 2003), Czech Republic (Sperkova & Suchanek, 2005), Germany (Castiñeira Gómez, Feldmann et al., 2004; Thiel et al., 2004), Italy (Marengo & Aceto, 2003), New Zealand (Angus et al., 2006), South Africa (Coetzee et al., 2005), Spain (Baxter et al., 1997; Iglesias et al., 2007; Pérez Trujillo et al., 2011), Great Britain (Baxter et al., 1997), Turkey (Sen & Tokatli, 2013).
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located to roads or industrial areas tend to have higher levels of Cd and Pb (Pohl, 2007). The presence of elements in the soil is not necessarily directly correlated to the presence of these elements in the grapes or wine (Almeida & Vasconcelos, 2003a; Taylor, Longerich, & Greenough, 2003), as elements differ in their bioaccumulation behaviour (Kabata-Pendias, 2004). Elements like B, Cd, Cs, Ni, Rb, Sn, and Zn are more mobile than others, and thus, accumulate in the plant more easily. Elements are transported as ions to the plant roots, where their absorption rate is dependent on the ion concentration as well as the soil pH (Bañuelos & Ajwa, 1999; Kabata-Pendias, 2004). The accumulation of elements from the soil is also dependent on how strong they are chelated; B, Cd, Mn, Mo, Se, and Zn are weakly chelated, thus, are more easily absorbed by the plant. Other elements are strongly bound to the soil or are retained in the roots and not translocated into the other parts of the plant even if present in high concentrations in the soil (e.g., Ag, Al, Cu, Cr, Fe, Hg, Pb, Si, Sn, Zr) (Bañuelos & Ajwa, 1999). The absorption of elements into a plant is also dependent on the chemical properties, e.g. non-nutrient elements share similar chemical properties with nutritional elements (e.g. Cu and Ni, S and Se, Cd and Zn), thus these elements may also be assimilated by the plant (Bañuelos & Ajwa, 1999). Finally, the plant species itself may impact absorption. For example, it has been shown that different grape phenotypes exist for amino acid accumulation (Oungoulian, 2012); as the nitrogen source for these amino acids is taken up by the plant through its roots, similar phenotypic differences could exist for other elements as well, especially for elements that are either essential for the health of the plant and/or that share chemical properties with these nutrients. Besides the impact of viticulture and the environment the winemaking process has been shown to also affect the elemental composition of wine. Generally, the elemental content in wine decreases after fermentation is completed (Almeida & Vasconcelos, 2003a; Castiñeira Gómez, Brandt et al., 2004), due to precipitation of element complexes with tartrates, polyphenols, proteins and sugars (Eschnauer, Jakob, Meierer, & Neeb, 1989; Tariba, 2011), lower elemental solubility in the ethanolic solution compared to the grape juice, yeasts consuming elements during fermentation (Ca, Cu, Fe, K, Mg, Zn), and/or racking of sediments and precipitates at the end of fermentation (Pohl, 2007). However, the use of different materials in wineries, including stainless steel, brass, wood, and plastics, have been shown to introduce elements into the wine as well (Aceto, 2003; Almeida & Vasconcelos, 2003a; Castiñeira Gómez, Brandt et al., 2004; Kristl et al., 2002; Tariba, 2011). These elements include Al, Cr, Cd, Co, Fe, Mo, Mn, Ni, Pb, Sr, Ti, V, Zn from stainless steel and brass containers, oak barrels, tubes, fittings, and traps (Aceto, 2003; Almeida & Vasconcelos, 2003a; Almeida & Vasconcelos, 2003b; Castiñeira Gómez, Brandt et al., 2004; Kristl et al., 2002; Rossano et al., 2007; Tariba, 2011). Ageing in oak barrels was reported to increase the Al, Fe, and V content (Almeida & Vasconcelos, 2003a), while Cr and Ni levels remained constant once the wine was racked for solid removal, indicating contamination by the fermentation container (Almeida & Vasconcelos, 2003a). Besides winery equipment, also various winemaking practices have been identified as sources for elemental ‘‘contamination’’ of wine. During pressing and fermentation Pb was freed from grape skins and seeds and led to higher Pb levels in the resulting wine (Almeida & Vasconcelos, 2003b); monitoring Pb along the winemaking process Almeida and Vasconcelos (2003b) were able to divide the final content in the wine into 1/3 coming from contaminated soil and atmospheric deposition, and 2/3 coming from winemaking. The separation of grape berries from the rachises during destemming increased the Al, Cu, Fe, Zn, Mn and Sr levels, while crushing increased Cu and Zn levels (Cheng & Liang, 2012).
Clarification with bentonites, added either to grape must or finished wine, was identified as a source for Al, Cd, Hf, REEs, Pb, U, and Zr (Castiñeira Gómez, Brandt et al., 2004; Jakubowski et al., 1999; Kristl et al., 2002; Nicolini et al., 2004; Rossano et al., 2007), while different filtration practices (silica filters, cellulose filters, bed filtration) have been shown to increase the REE content (Rossano et al., 2007), as well as Co, Cr, Fe, and Ni levels (Eschnauer et al., 1989). On the other hand, during clarification and filtration some elements also decrease due to settling of protein, sulphate and amino acid metal complexes (Nicolini et al., 2004; Pohl, 2007). Lastly, also during ageing and storage various studies showed that the elemental composition of wine can be changed by the materials used (e.g. increasing Sn levels in screw-capped bottles (Hopfer et al., 2013), Cr from use of Cr oxides to colour glass bottles (Tariba, 2011), higher REEs when stored in glass bottles (Rossano et al., 2007)). 1.2. Determination of geographical origin of wines with multi-element fingerprints Several studies have evaluated the use of multi-element fingerprints for the determination of geographical origin of wines (Angus, O’Keeffe, Stuart, & Miskelly, 2006; Baxter, Crews, Dennis, Goodall, & Anderson, 1997; Castiñeira Gómez, Feldmann, Jakubowski, & Andersson, 2004; Coetzee et al., 2005; Greenough, Longerich, & Jackson, 1997; Iglesias, Besalú, & Anticó, 2007; Marengo & Aceto, 2003; Martin, Watling, & Lee, 2012; Pérez Trujillo, Conde, Pérez Pont, Câmara, & Marques, 2011; Sen & Tokatli, 2013; Sperkova & Suchanek, 2005; Taylor et al., 2003; Thiel, Geisler, Blechschmidt, & Danzer, 2004). The elements that were found to discriminate among different wine regions are summarised in Fig. 1b. The most discriminating elements in these studies include Sr, Mn, Mg, Li, Co, Rb, B, Cs, Zn, Al, Ba, Si, Pb, and Ca, which are reported in at least 4 different studies (Angus, O’Keeffe, Stuart, & Miskelly, 2006; Baxter et al., 1997; Castiñeira Gómez, Brandt et al., 2004; Coetzee et al., 2005; Greenough et al., 1997; Iglesias et al., 2007; Marengo & Aceto, 2003; Martin et al., 2012; Pérez Trujillo et al., 2011; Sen & Tokatli, 2013; Sperkova & Suchanek, 2005; Taylor et al., 2003; Thiel et al., 2004). There is quite some overlap in elements that have been used in the past for the determination of geographical origin (Fig. 1b) and elements that have been shown to change during various viticultural and/or enological processes (Fig. 1a). It seems that depending on the samples used, different elemental patterns emerge. The question is which elements could be useful in discriminating between different vineyards, despite the impact of the processing winery? This is the central question in this study, where we look at the combined effects of vineyard and winery on the elemental composition of red wines. By including wines that originated from the same vineyard but were processed in different wineries, and vice versa, we are able to separate the vineyard from the winery effect, and add to our understanding of how the elemental profile changes during the winemaking process. 2. Materials and methods 2.1. Samples and materials Sixty-five commercial red wine samples were included in this study. All samples came from five different vineyards (vineyard 1–5, Fig. 2) in Northern California (vineyard 1 near Cloverdale, vineyard 2 and 3 between Geyserville and Calistoga, vineyard 4 outside of St. Helena, and vineyard 5 outside of Sonoma), and were processed in five different commercial wineries (winery A–D, Fig. 2). Based on soil maps, each vineyard shows a range of different soils,
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clarification, racking, blending, etc.). Metal-free 50 mL plastic tubes (VWR, Radnor, PA, USA) were used for collecting the samples, and all samples were stored at 4 °C until analysis took place. All sampled wines were made for commercial use, and none of the samples were specifically made for this study (i.e. no specific research samples). Multi-element calibration standards (1, 2A, 3 and 4) were purchased from SPEX CertiPrep (Metuchen, NJ, USA), ultrapure concentrated nitric acid was obtained from Fisher Scientific (Optima grade, Pittsburgh, PA, USA), and an environmental spike mix was purchased from Agilent Technologies (Santa Clara, CA, USA). Ultrapure water (18 MXcm, EMD Millipore Bellerica, MA, USA) and 200 proof ethanol (GoldShield, Hayward, CA, USA) were used for the calibration solutions and dilutions. An internal standard (IS) mix (10 mg/L in 1% HNO3, SPEX CertiPrep) was diluted 1:10 in 1% HNO3 prior to use. 2.2. Instrumentation
Fig. 2. Sixty-five red wine samples originated from five different vineyards (1–5), and were processed in five different wineries, labeled A through E.
thus, we expect differences in soil metal composition between the 5 different vineyards, and probably, although this was not the scope of this study, also within each vineyard site. Vineyards showed a wide range of various gravelly and clay loams, as well as sandy alluvial land, clay and rock land. Grapes from one vineyard were processed in at least two different wineries (Suppl. Table 1). All wines were made from monovarietal grapes, and included Vitis vinifera cv. Cabernet Sauvignon, cv. Merlot, and cv. Pinot Noir. All wineries fermented all grapes from the individual vineyards in separate fermentation tanks. Similar to Coetzee et al. (2005), sampling took place in each winery directly from stainless steel fermentation vessels after fermentation was finished, but before any additional post-fermentation treatments took place (e.g. filtration,
An inductively coupled plasma-mass spectrometry (ICP-MS) instrument from Agilent (7700x, Santa Clara, CA, USA) was used for the elemental profiling of 63 trace elements in a mass range between 7 and 238 m/z. The IS mix was constantly fed into and mixed with the sample stream immediately before entering the spray chamber (quartz double wall, cooled to 2 °C), using a mixing tee (sample tubing inner diameter 1.02 mm, IS tubing inner diameter 0.25 mm). The peristaltic pump was operated at 0.1 rps. A concentric nebulizer (Micromist, Agilent) was used for sample transport into the plasma (RF power of 1550 W, RF matching 1.8 V, sampling depth 10 mm, carrier gas flow 1.05 mL/min). The instrument was calibrated and tuned daily, using a tuning mix (Li, Y, Ce, Tl, Co; Agilent) and the Pulse/Analog solutions (Zn, Be, Cd, As, Ni, Pb, Mg, Th, Ca, Co, Sr, V, Cr, Mn, 6Li, Sc, In, Lu, Bi, Y, Yb, Mo, Sb, Sn, Ge, Ru, Pd, Ti, Ir; Agilent). All wine were analysed in duplicate, and they were 1:3 dilutions in 5% HNO3. Elements were monitored in no gas, helium (He flow 4.3 mL/min) and/or high energy helium (He flow 10 mL/min) gas mode using the ORS3 system. A 6-point calibration between 0 and 500 lg/L was carried out for the elements listed in Table 1 in
Table 1 Monitored elements together with detection mode and limits of detection (LOD).
a b
Element
m/z
Modea
LODb [lg/L]
Element
m/z
Modea
LODb [lg/L]
Li Be B Na Mg Al Si P K Ca Ti V Cr Mn Co Ni Cu Zn Ga As Se Rb Sr Mo
7 9 11 23 24 27 28 31 39 43 47 51 52 55 59 60 63 66 69 75 78 85 88 95
ng ng ng ng ng ng ng ng He He He He He He He He He He He He HEHe ng He ng
2.25E 01 1.40E 02 1.12E 01 1.79E+00 4.03E 01 4.68E 01 4.23E 01 6.92E 01 1.16E+00 8.79E 01 5.43E 01 2.40E 02 7.70E 02 2.30E 02 9.00E 03 3.47E 01 2.30E 02 1.50E 02 5.00E 03 7.00E 03 5.20E 02 2.00E 03 1.00E 02 3.10E 02
Rh Cd Sn Sb Cs Ba La Ce Pr Nd Sm Eu Gd Dy Ho Er Tm Yb W Re Tl Pb U
103 111 118 121 133 137 139 140 141 142 147 153 157 163 165 166 169 172 182 185 205 208 238
He He He He ng He He He He He He He He ng He ng ng ng He He ng He He
1.00E 9.00E 2.10E 4.00E 5.00E 1.30E 6.00E 2.00E 3.00E 7.00E 2.00E 4.60E 1.00E 4.00E 6.00E 8.00E 3.00E 1.00E 1.90E 5.00E 2.00E 5.00E 6.60E
ng . . . no gas; He . . . helium; HEHe . . . high energy helium. Limit of detection (LOD); n = 10 calibration blank measurements; 99% confidence interval.
03 03 02 03 04 02 04 03 04 04 03 06 03 04 04 04 04 03 02 04 03 03 06
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matrix-matched calibration solutions (5% HNO3 and 4% Ethanol) to account for matrix interferences of the ethanolic wine solutions. Elements were detected using a 3-point peak pattern in triplicate with 100 sweeps per replicate. Previous studies have shown that a reduction of the ethanol content to around 5% is a good compromise between a stable plasma and sufficient sensitivity (Boorn & Browner, 1982; Dams, Goossens, & Moens, 1995; Goossens, Moens, & Dams, 1994; Rossano et al., 2007). Higher concentration elements (>500 lg/L; B, Na, Mg, Si, P, K, Ca, Mn, Cu, Rb, Sr, Ba) were measured after a 1:1000 dilution in 5% HNO3. Spiked samples were analysed throughout the analysis run to ensure validity of the analytical method. Continuous calibration blank verification (CCB) runs were performed every 10th sample. 2.3. Data analysis All monitored isotopes were calibrated using the MassHunter ICP-MS software (G7201B, version B.01.03, Agilent). Based on limits of detection (LOD), determined with 10 calibration blank measurements (Thomsen, Schatzlein, & Mercuro, 2003), detection limits (DL) and background equivalent concentrations (BEC), reported by the software, isotopes and gas modes were selected for each element, and used for further data analysis. For statistical significance testing as well as multivariate classification, elements that were detected below LOD were assigned a concentration of LOD/10. Multivariate and univariate analyses of variance (MANOVA and ANOVA) were carried out for the main effects winery, and vineyard, as well as for the winery-by-vineyard interaction, using logtransformed concentration data. Statistical significance was set at 5%. Canonical Variate Analysis (CVA) was chosen as a classification technique to study how individual wineries, vineyards as well as the winery–vineyard combinations differed from each other, using the respective one-way MANOVA models. Canonical variates (CVs) were tested for significance using the Bartlett’s test (homogeneity of variances) (Bartlett, 1937). All analyses were carried out in R (R Core Team, 2013), using RStudio (version 0.98.953, Boston, MA, USA) with the additional candisc package (Friendly & Fox, 2010). 3. Results and discussion 3.1. Elemental profiling Of the 63 monitored elements, 47 were detected in the 65 different wine samples at concentrations above their LODs, and thus, were included in the data analysis. For none of the elements was a significant replicate effect was found, indicating that the ICP-MS analysis method was repeatable (P 6 0.05). Recoveries for the spiked samples, measured throughout the analysis sequence, were between 93% (for Ba) and 103% (for Ca). Similar to Martin and coworkers (Martin et al., 2012) we found no significant elemental differences between different cultivars from one region. Significant differences for the winery, vineyard and the interaction effect were detected in the MANOVA (P 6 0.05). Individual ANOVAs revealed that all detected elements but 14 differed significantly among the wineries (33 significantly different elements, Suppl. Table 2a), while 26 out of the 47 detected elements differed significantly among the five different vineyards (P 6 0.05) (Suppl. Table 2b). Significant winery-by-vineyard interactions (i.e. the combination of both winery and vineyard impact) were found for 17 elements (Be, Na, P, Ti, Zn, As, Rb, Cd, Sb, Cs, La, Pr, Dy, Er, Tm, Yb, Tl) (P 6 0.05). In Suppl. Table 2a–b the detected elements are summarised for the five vineyards and five wineries. These results show that both
grapegrowing and winemaking have an effect on the elemental composition of the wine samples. Based on the ANOVA results it seems that more elements are affected by the winemaking, as more elements differ significantly in the wines across the different processing wineries compared to the different vineyard origins. Using the one-way MANOVA models for winery, vineyard and winery-by-vineyard effects, Canonical Variate Analysis (CVA) was conducted to establish a classification for each of these factors. 3.2. Vineyard effect Canonical Variate Analysis (CVA) was used to classify the samples according to their vineyard origin, using the log-transformed concentrations of the 26 elements that differed significantly among the vineyards (P 6 0.05). All four CVs were highly significant in the Bartlett’s test (P 6 0.05), and the first two CVs explain over 81% of the total variance ratio, as shown in Fig. 3. Along the first CV, capturing 55% of the total variance ratio, vineyards were separated based on the elemental differences between vineyard 1, and vineyards 2 and 5, with the remaining two vineyards located in between. Along the first CV vineyards line up according to their geographic north–south location (see also Fig. 1), except for vineyard 2 which showed more similarities to the most southern vineyard 5, while being the second most northern vineyard. Also, along the first CV the two neighbouring vineyards (2 and 3) were not close to each other (Fig. 3a). Wines from vineyard 1 showed higher levels in B, Mg, P, Ca, Ti, Cr, Ni, As, Mo, and to a lesser extent, Al, Co, Zn, and Sr, while wines from the more southern vineyards showed higher concentrations in Li, Be, Si, Mn, Rb, Cs, Er, Yb, Tl, and to a smaller extent, Ga, Se, Ba, and Eu (Fig. 3b-c). Boron, Mg, P, and Ti levels in wines from vineyard 1 were 1.5 times higher than in the wines from all other vineyards. Boron is an essential element for plants, but its precise role in the plant metabolism is not fully understood. Boron levels need to be managed in a very narrow range, to avoid either deficiency or toxicity, due to its easy mobilisation from the soil into the plant. Boron-rich soils are the result of either marine sediments or boron rich minerals, which enhances the danger of boron toxicity if combined with low rainfall and high salinity (Soilquality Pty Ltd., 2013; Yermiyahu, Ben-Gal, & Sarig, 2006). Potassium, N and P are essential plant elements, and are often added to the soil with fertilizers (Aceto, 2003), while Mg, Ti, Mo, Mn, and Si are mainly influenced by the mineral content of the soil and mineral grape uptake as reported by Marengo and Aceto (Marengo & Aceto, 2003) who successfully discriminated among Nebbiolo wines from different sub-regions within the Piemonte region in Italy. The second CV separates wines from the vineyards 1, 4, and 5 from those from the two neighbouring vineyards 2 and 3 (Fig. 3d). The former three vineyards are positively correlated to B, Si, Tl, Cs, and Se, while the levels in Cr, Mn, Co, Ni, Zn, As, and Mo were very similar in the wines from the two neighbouring vineyards 2 and 3, leading to a clear separation of these two vineyards from the others along CV 2 (Fig. 3e). All other elements (Li, Be, Mg, Al, P, Ca, Ti, Ga, Rb, Sr, Ba, Eu, Er, and Yb) contributed to a smaller degree to the separation of the different classes along CV 2. According to Pereira (Pereira, 1988) the application of B, Cr, Mo, Mn, Co, and Zn as grapevine, soil or foliage treatments or as fertilizers impact both grape yield and grape composition, especially the polyphenol, sugar, ester and amino acid levels. Any viticultural practices, such as fertilizer application, would most likely also affect the elemental composition of wine produced from such treated grapes, depending on how easily the element would be
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6
(a) 2 3
2
2
3 33
2
2
2
3
3
3 33 3 3
3
33 2
33 3 2
3
3 3 3 3 33 33 3 3
CV 2, 26% 0
3
3 3 3
5
5
4 5
5
5
5 5
5 5 55
1 1 1
4
11
1
1
−6
1
1
1
5
−8
0 CV 1, 55%
8
(b)
(d)
5
4
3
2
1
1
2
3
4
5
(e) 0.6
(c) Tl Yb
Zn
Cr
As
Er Eu Ba
Ni
Cs
Mo
Co Mn
Mo Sr Rb
BaEu
Se As
CV 2, 26% 0.0
Ga Zn Ni Co Mn Cr Ti
Ga
P
Mg
Ti
Rb Sr
Ca
Al
Li Be
Er Yb
Ca P
Se
Si Al
Si
Mg B
Tl
0.0 CV 1, 55%
0.8
−0.7
Be Li
−1.0
Cs
B
Fig. 3. Canonical Variate Analysis (CVA) plots for the vineyard effect. (a) Product plot showing the individual wine samples, coded according to their vineyard origin with different numbers (vineyard 1 (1), vineyard 2 (2), vineyard 3 (3), vineyard 4 (4), vineyard 5 (5)). Boxplots and total structures coefficients for the first (b-c) and second (d-e) dimension showing the contribution of each element to the separation along CV 1 and CV 2.
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6
(a) B B
B
B
B B B B
B B B B
B
B B
B A
A
A
A
A AA A AA AA
0
CV 2, 37%
A
A AA AA
A
A A A A A
A A
A A
C E
C
DD
C C C
E
C
C C
C
C
C
C
E E E
−8
E
−7
0
6
CV 1, 50%
(b)
(d) E
D
C
B
A
(c) Pb
Tl
Re
Yb Er Ho Dy
A
B
C
D
E
0.9
(e)
Zn As Gd Pr Ce La
K
Ba P
Cd
Rb
Sr Se
As
Zn Mn
CV 2, 37%
Mo
Ni
Co Cr
Ti
K
Ba Pb Gd Dy Pr HoEr
Ti Sr
Mn
Rh
Ca
La
Al Ce
Ca
Yb
Rb
P
Al
Mo CdSb
Co Ni
Mg
Rh
0.0
Cs Sb
Cr
Mg
B
B
−0.8
0.0 CV 1, 50%
0.7
−0.5
Re Se Cs
Tl
Fig. 4. Canonical Variate Analysis (CVA) plots for the winery effect. (a) Product plot showing the individual wine samples, coded according to their processing winery with different letters (winery A (A), winery B (B), winery C (C), winery D (D), winery E (E)). Boxplots and total structures coefficients for the first (b-c) and second (d-e) dimension showing the contribution of each element to the separation along CV 1 and CV 2.
H. Hopfer et al. / Food Chemistry 172 (2015) 486–496
mobilised in the soil. Elemental mobilisation is heavily dependent on the soil constitution, mainly pH and aeration status, the soil microbiota, as well as the element itself. While so called lithophile elements (e.g. geochemically stable Al, Rb, Sc, Ti, and Zr (Boës, Rydberg, Martinez-Cortizas, Bindler, & Renberg, 2011)) are bound to various minerals, and are thus, less mobile, the anthropogenic elements (e.g. B, Si) are typically present as ions, resulting in higher soil mobility and thus, bioavailability (Bañuelos & Ajwa, 1999; Kabata-Pendias, 2004). Based on these results, we hypothesise that the discrimination among the different geographic origins (i.e. vineyards) of the wines is the result of both soil elemental content and viticultural practices. Further studies are needed to directly relate the elemental composition of these vineyard soils to the composition in the wines. Additional studies relating the effects of viticultural practices on elemental composition of grapes are also needed. 3.3. Winery effect Similarly to the vineyard effect, the CVA on the winery effect as a classifier, using the 33 elements that differed significantly among the wineries in the ANOVA (P 6 0.05), led to a clear separation of all wines according to their processing winery. All four canonical variates (CVs) were significantly different from each other as determined by the Bartlett’s test (Bartlett, 1938; Friendly & Fox, 2010). Eighty-seven percent of the total variance ratio was explained within the first two CVs, thus only the first two dimensions are shown. Wine samples were grouped according to the winery they were processed as shown in Fig. 4a, where all wineries were well separated from each other. Wines from winery B are more different from the wines processed in all other wineries, as the remaining wineries (A, C–E) are closer to or overlap with each other. Along the first CV, 50% of the total variance ratio was explained, mainly driven by the elemental differences of wines processed in winery A, compared to wines processed in winery B or E, with the wines from winery C and D in between (Fig. 4b). Wines from winery A are separated from the other wineries based on the higher concentrations in Mg, P, Ca, Ti, Ni, Se, Sr, Rh, Re, while B, Cr, and Mo contribute to a smaller degree to the separation (Fig. 4c). The most likely source for Cr, Ti, Ni, and Mo are winery equipment and wine containers as reported previously (Almeida & Vasconcelos, 2003a; Galani-Nikolakaki, Kallithrakas-Kontos, & Katsanos, 2002; GalaniNikolakaki & Kallithrakas-Kontos, 2006; Pohl, 2007; Tariba, 2011; Volpe et al., 2009). Molybdenum and Ti are stainless steel alloy elements (http://www.ssina.com), but are also present in the soil, so their presence in the wines could be the result of both grapegrowing and winemaking practices. Magnesium, P, Ca, B, Sr, and Rh have been reported to come from vineyard soil by some authors (Pohl, 2007; Taylor et al., 2003), while others argue that P, Mg and Ca can also be influenced by winemaking processes (Volpe et al., 2009). Iglesias et al. (2007) report that Sr levels are not influenced by production, however, this is neither confirmed by our results nor by the results of Taylor et al. (2003) who found larger variation in Sr levels in wines than in the soil. Higher levels of Al, Mn, Zn, Rb, Cd, Sb, Cs, Tl, Pb, and the significantly different concentrations of REEs are contributing the most to the separation of the wines from wineries B and E from the other wineries, while K, Co, As, and Ba contribute to a lesser extent to this separation (Fig. 4c). Selenium, Rb and Cs are commonly reported elements used to differentiate the geographical origin of wines (Angus, O’Keeffe, Stuart, & Miskelly, 2006; Castiñeira Gómez, Feldmann et al., 2004; Coetzee et al., 2005; Martin et al., 2012; Pohl, 2007; Taylor et al., 2003), but in most of these previous studies, only finished wines have been analysed. Almeida and Vasconcelos (2003a) reported that the Rb levels remained constant throughout red wine making.
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The contents of Al, Mn, Cd, Co, and Pb in wines were reported previously to result from winery equipment and containers (Almeida & Vasconcelos, 2003a; Galani-Nikolakaki et al., 2002; Galani-Nikolakaki & Kallithrakas-Kontos, 2006; Pohl, 2007; Tariba, 2011; Volpe et al., 2009), and Almeida and Vasconcelos (2003a) were only able to find a significant correlation between vineyard soil and finished wine if they excluded Al and Ca from their model, indicating that these latter two elements were heavily influenced by the winemaking process. The presence of Zn in wines could be the result of various factors, such as industrial activity (Marengo & Aceto, 2003), the use of pesticides and fertilizers (Pohl, 2007; Tariba, 2011), as well as winery containers (Pohl, 2007; Tariba, 2011). Both Al and Zn have an impact on wine stability, and excess levels (
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Food Chemistry journal homepage: www.elsevier.com/locate/foodchem
The combined impact of vineyard origin and processing winery on the elemental profile of red wines Helene Hopfer a,b,⇑, Jenny Nelson a,c, Thomas S. Collins a,b, Hildegarde Heymann a, Susan E. Ebeler a,b a
Department of Viticulture and Enology, University of California-Davis, One Shields Avenue, Davis, CA 95616, USA Food Safety and Measurement Facility, University of California-Davis, One Shields Avenue, Davis, CA 95616, USA c Agilent Technologies, Inc., 5301 Stevens Creek Blvd., Santa Clara, CA 95051, USA b
a r t i c l e
i n f o
Article history: Received 23 May 2014 Received in revised form 8 September 2014 Accepted 19 September 2014 Available online 26 September 2014 Keywords: Wine Elemental composition Inductively-coupled plasma-mass spectrometry (ICP-MS) Vineyard Winery Determination of geographical origin
a b s t r a c t The combined effects of vineyard origin and winery processing have been studied in 65 red wines samples. Grapes originating from five different vineyards within 40 miles of each other were processed in at least two different wineries. Sixty-three different elements were determined with inductively coupledplasma mass spectrometry (ICP-MS), and wines were classified according to vineyard origin, processing winery, and the combination of both factors. Vineyard origin as well as winery processing have an impact on the elemental composition of wine, but each winery and each vineyard change the composition to a different degree. For some vineyards, wines showed a characteristic elemental pattern, independent of the processing winery, but the same was found for some wineries, with similar elemental pattern for all grapes processed in these wineries, independent of the vineyard origin. Studying the combined effects of grapegrowing and winemaking provides insight into the determination of geographical origin of red wines. Ó 2014 Elsevier Ltd. All rights reserved.
1. Introduction Determining the geographical origin of food products has gained increased research interest over the last decade, mostly due to growing concern and interest of consumers to know the origin of the food they eat (Drivelos & Georgiou, 2012; Kelly, Heaton, & Hoogewerff, 2005). The European Union (EU) established various food quality schemes based on geographical regions, thus, successfully classifying food products according to the geographical origin has also an economic component, as food products tend to sell for higher prices if associated with a certain geographical origin (Drivelos & Georgiou, 2012). Especially for specialty food products, with a strong reputation of and association to specific geographical areas (e.g. ham, cheese or wine), fraud with regards to geographical origin is expected, and various analytical strategies have been proposed. Besides untargeted profiling methods, such as nuclear magnetic, infrared and fluorescence spectroscopy, the use of stable isotope ratios, as well as multi-element profiles have been proposed for food authenticity (Drivelos & Georgiou, 2012; Kelly et al., 2005).
⇑ Corresponding author at: HM.Clause, 9241 Mace Blvd., Davis, CA 95616, USA. Tel.: +1 530 220 2116. E-mail address: [email protected] (H. Hopfer). http://dx.doi.org/10.1016/j.foodchem.2014.09.113 0308-8146/Ó 2014 Elsevier Ltd. All rights reserved.
From an analytical standpoint, the presence and/or absence of certain elements in a food product as well as ratios of certain element to each other could be used for elemental fingerprinting. However, before a successful determination of geographical origin of wines is possible, one needs to understand (i) how controlled studies correlate to real life grapegrowing and winemaking, (ii) which changes are possibly introduced during the whole production chain, (iii) how different varieties and/or wine styles vary, and finally (iv) how variable the impact of winery processes within and between different regions and countries is. The major elements in wine, present at levels between 10 and 1000 mg/L, are Ca, K, Na, and Mg, followed by minor elements, such as Al, Fe, Cu, Mn, Rb, Sr, and Zn, present in the range of 0.1–10 mg/L. Trace elements are present in the ppt range (0.1–1000 lg/L), and include Ba, Cd, Co, Cr, Li, Ni, Pb, and V among others (Pohl, 2007). The elemental composition of wine is the result of many factors, including the elemental composition of the soil the vine is growing on, the viticultural practices (application of fertilizers, pesticides, herbicides, and insecticides; irrigation), as well as winemaking processes, including storage and ageing (Aceto, 2003; Almeida & Vasconcelos, 2003a,b; Castiñeira Gómez, Brandt, Jakubowski, & Andersson, 2004; Cheng & Liang, 2012; Galani-Nikolakaki & Kallithrakas-Kontos, 2006; Hopfer, Nelson, Mitchell, Heymann, & Ebeler, 2013; Jakubowski, Brandt,
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Stuewer, Eschnauer, & Görtges, 1999; Kristl, Veber, & Slekovec, 2002; Nicolini, Larcher, Pangrazzi, & Bontempo, 2004; Pereira, 1988; Pohl, 2007; Rossano, Szilágyi, Malorni, & Pocsfalvi, 2007; Tariba, 2011; Volpe et al., 2009). Volpe et al. (2009) categorise elements into so called (i) ‘‘natural’’ elements which are the result of their presence in the vineyard soil and their uptake by the vine plant (Al, B, Ba, Li, Mg, Mo, Si, Sr, Ti, rare earth elements (REEs), transition elements of the second and third period), (ii) ‘‘artificial’’ elements which result from human intervention (viticultural practices, winemaking procedures, environmental pollution; e.g. Pb, Co, Cr, Ni, V, Cd, Hg), and (iii) elements that are both ‘‘natural’’ and ‘‘artificial’’, and result from either endogenous or exogenous processes (e.g. Ca, Mg, Co, Zn, Fe, P, Na, K) (Pohl, 2007) (see also Fig. 1a).
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1.1. Viticultural changes in elemental composition From a plant perspective, elements like K, P, and N are essential for a plant’s health, thus, the presence of these elements in wine is expected. Elements, such as K, Ca, Cu, Cd, Mn, Zn, and Pb, are used in fertilizers, pesticides, and fungicides (Pohl, 2007), in some cases (e.g. Cd, Pb) due to anthropogenic pollution (Kment et al., 2005). Some elements have beneficial effects on the plant, higher yield, sugar accumulation, polyphenols and amino acids in wine grapes have been reported after the application of B, Cr, Mn, Mo, W, and Zn onto the vine or vineyard soil (Aceto, 2003; Pereira, 1988), thus, are most likely also found in the resulting wine. The proximity to an ocean has been reported to increased Na levels in the grapes resulting from marine sprays, while wines from vineyards closely
Fig. 1. (a) Elements that can be changed by grapegrowing and/or winemaking practices (Aceto, 2003; Almeida & Vasconcelos, 2003a,b; Castiñeira Gómez, Brandt et al., 2004; Cheng & Liang, 2012; Eschnauer et al., 1989; Jakubowski et al., 1999; Kristl et al., 2002; Nicolini et al., 2004; Pereira, 1988; Rossano et al., 2007; Tariba, 2011; Volpe et al., 2009). (b) Elements that have been used for the determination of geographical origin of wines from different regions within Australia (Martin et al., 2012), Canada (Greenough et al., 1997; Taylor et al., 2003), Czech Republic (Sperkova & Suchanek, 2005), Germany (Castiñeira Gómez, Feldmann et al., 2004; Thiel et al., 2004), Italy (Marengo & Aceto, 2003), New Zealand (Angus et al., 2006), South Africa (Coetzee et al., 2005), Spain (Baxter et al., 1997; Iglesias et al., 2007; Pérez Trujillo et al., 2011), Great Britain (Baxter et al., 1997), Turkey (Sen & Tokatli, 2013).
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located to roads or industrial areas tend to have higher levels of Cd and Pb (Pohl, 2007). The presence of elements in the soil is not necessarily directly correlated to the presence of these elements in the grapes or wine (Almeida & Vasconcelos, 2003a; Taylor, Longerich, & Greenough, 2003), as elements differ in their bioaccumulation behaviour (Kabata-Pendias, 2004). Elements like B, Cd, Cs, Ni, Rb, Sn, and Zn are more mobile than others, and thus, accumulate in the plant more easily. Elements are transported as ions to the plant roots, where their absorption rate is dependent on the ion concentration as well as the soil pH (Bañuelos & Ajwa, 1999; Kabata-Pendias, 2004). The accumulation of elements from the soil is also dependent on how strong they are chelated; B, Cd, Mn, Mo, Se, and Zn are weakly chelated, thus, are more easily absorbed by the plant. Other elements are strongly bound to the soil or are retained in the roots and not translocated into the other parts of the plant even if present in high concentrations in the soil (e.g., Ag, Al, Cu, Cr, Fe, Hg, Pb, Si, Sn, Zr) (Bañuelos & Ajwa, 1999). The absorption of elements into a plant is also dependent on the chemical properties, e.g. non-nutrient elements share similar chemical properties with nutritional elements (e.g. Cu and Ni, S and Se, Cd and Zn), thus these elements may also be assimilated by the plant (Bañuelos & Ajwa, 1999). Finally, the plant species itself may impact absorption. For example, it has been shown that different grape phenotypes exist for amino acid accumulation (Oungoulian, 2012); as the nitrogen source for these amino acids is taken up by the plant through its roots, similar phenotypic differences could exist for other elements as well, especially for elements that are either essential for the health of the plant and/or that share chemical properties with these nutrients. Besides the impact of viticulture and the environment the winemaking process has been shown to also affect the elemental composition of wine. Generally, the elemental content in wine decreases after fermentation is completed (Almeida & Vasconcelos, 2003a; Castiñeira Gómez, Brandt et al., 2004), due to precipitation of element complexes with tartrates, polyphenols, proteins and sugars (Eschnauer, Jakob, Meierer, & Neeb, 1989; Tariba, 2011), lower elemental solubility in the ethanolic solution compared to the grape juice, yeasts consuming elements during fermentation (Ca, Cu, Fe, K, Mg, Zn), and/or racking of sediments and precipitates at the end of fermentation (Pohl, 2007). However, the use of different materials in wineries, including stainless steel, brass, wood, and plastics, have been shown to introduce elements into the wine as well (Aceto, 2003; Almeida & Vasconcelos, 2003a; Castiñeira Gómez, Brandt et al., 2004; Kristl et al., 2002; Tariba, 2011). These elements include Al, Cr, Cd, Co, Fe, Mo, Mn, Ni, Pb, Sr, Ti, V, Zn from stainless steel and brass containers, oak barrels, tubes, fittings, and traps (Aceto, 2003; Almeida & Vasconcelos, 2003a; Almeida & Vasconcelos, 2003b; Castiñeira Gómez, Brandt et al., 2004; Kristl et al., 2002; Rossano et al., 2007; Tariba, 2011). Ageing in oak barrels was reported to increase the Al, Fe, and V content (Almeida & Vasconcelos, 2003a), while Cr and Ni levels remained constant once the wine was racked for solid removal, indicating contamination by the fermentation container (Almeida & Vasconcelos, 2003a). Besides winery equipment, also various winemaking practices have been identified as sources for elemental ‘‘contamination’’ of wine. During pressing and fermentation Pb was freed from grape skins and seeds and led to higher Pb levels in the resulting wine (Almeida & Vasconcelos, 2003b); monitoring Pb along the winemaking process Almeida and Vasconcelos (2003b) were able to divide the final content in the wine into 1/3 coming from contaminated soil and atmospheric deposition, and 2/3 coming from winemaking. The separation of grape berries from the rachises during destemming increased the Al, Cu, Fe, Zn, Mn and Sr levels, while crushing increased Cu and Zn levels (Cheng & Liang, 2012).
Clarification with bentonites, added either to grape must or finished wine, was identified as a source for Al, Cd, Hf, REEs, Pb, U, and Zr (Castiñeira Gómez, Brandt et al., 2004; Jakubowski et al., 1999; Kristl et al., 2002; Nicolini et al., 2004; Rossano et al., 2007), while different filtration practices (silica filters, cellulose filters, bed filtration) have been shown to increase the REE content (Rossano et al., 2007), as well as Co, Cr, Fe, and Ni levels (Eschnauer et al., 1989). On the other hand, during clarification and filtration some elements also decrease due to settling of protein, sulphate and amino acid metal complexes (Nicolini et al., 2004; Pohl, 2007). Lastly, also during ageing and storage various studies showed that the elemental composition of wine can be changed by the materials used (e.g. increasing Sn levels in screw-capped bottles (Hopfer et al., 2013), Cr from use of Cr oxides to colour glass bottles (Tariba, 2011), higher REEs when stored in glass bottles (Rossano et al., 2007)). 1.2. Determination of geographical origin of wines with multi-element fingerprints Several studies have evaluated the use of multi-element fingerprints for the determination of geographical origin of wines (Angus, O’Keeffe, Stuart, & Miskelly, 2006; Baxter, Crews, Dennis, Goodall, & Anderson, 1997; Castiñeira Gómez, Feldmann, Jakubowski, & Andersson, 2004; Coetzee et al., 2005; Greenough, Longerich, & Jackson, 1997; Iglesias, Besalú, & Anticó, 2007; Marengo & Aceto, 2003; Martin, Watling, & Lee, 2012; Pérez Trujillo, Conde, Pérez Pont, Câmara, & Marques, 2011; Sen & Tokatli, 2013; Sperkova & Suchanek, 2005; Taylor et al., 2003; Thiel, Geisler, Blechschmidt, & Danzer, 2004). The elements that were found to discriminate among different wine regions are summarised in Fig. 1b. The most discriminating elements in these studies include Sr, Mn, Mg, Li, Co, Rb, B, Cs, Zn, Al, Ba, Si, Pb, and Ca, which are reported in at least 4 different studies (Angus, O’Keeffe, Stuart, & Miskelly, 2006; Baxter et al., 1997; Castiñeira Gómez, Brandt et al., 2004; Coetzee et al., 2005; Greenough et al., 1997; Iglesias et al., 2007; Marengo & Aceto, 2003; Martin et al., 2012; Pérez Trujillo et al., 2011; Sen & Tokatli, 2013; Sperkova & Suchanek, 2005; Taylor et al., 2003; Thiel et al., 2004). There is quite some overlap in elements that have been used in the past for the determination of geographical origin (Fig. 1b) and elements that have been shown to change during various viticultural and/or enological processes (Fig. 1a). It seems that depending on the samples used, different elemental patterns emerge. The question is which elements could be useful in discriminating between different vineyards, despite the impact of the processing winery? This is the central question in this study, where we look at the combined effects of vineyard and winery on the elemental composition of red wines. By including wines that originated from the same vineyard but were processed in different wineries, and vice versa, we are able to separate the vineyard from the winery effect, and add to our understanding of how the elemental profile changes during the winemaking process. 2. Materials and methods 2.1. Samples and materials Sixty-five commercial red wine samples were included in this study. All samples came from five different vineyards (vineyard 1–5, Fig. 2) in Northern California (vineyard 1 near Cloverdale, vineyard 2 and 3 between Geyserville and Calistoga, vineyard 4 outside of St. Helena, and vineyard 5 outside of Sonoma), and were processed in five different commercial wineries (winery A–D, Fig. 2). Based on soil maps, each vineyard shows a range of different soils,
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clarification, racking, blending, etc.). Metal-free 50 mL plastic tubes (VWR, Radnor, PA, USA) were used for collecting the samples, and all samples were stored at 4 °C until analysis took place. All sampled wines were made for commercial use, and none of the samples were specifically made for this study (i.e. no specific research samples). Multi-element calibration standards (1, 2A, 3 and 4) were purchased from SPEX CertiPrep (Metuchen, NJ, USA), ultrapure concentrated nitric acid was obtained from Fisher Scientific (Optima grade, Pittsburgh, PA, USA), and an environmental spike mix was purchased from Agilent Technologies (Santa Clara, CA, USA). Ultrapure water (18 MXcm, EMD Millipore Bellerica, MA, USA) and 200 proof ethanol (GoldShield, Hayward, CA, USA) were used for the calibration solutions and dilutions. An internal standard (IS) mix (10 mg/L in 1% HNO3, SPEX CertiPrep) was diluted 1:10 in 1% HNO3 prior to use. 2.2. Instrumentation
Fig. 2. Sixty-five red wine samples originated from five different vineyards (1–5), and were processed in five different wineries, labeled A through E.
thus, we expect differences in soil metal composition between the 5 different vineyards, and probably, although this was not the scope of this study, also within each vineyard site. Vineyards showed a wide range of various gravelly and clay loams, as well as sandy alluvial land, clay and rock land. Grapes from one vineyard were processed in at least two different wineries (Suppl. Table 1). All wines were made from monovarietal grapes, and included Vitis vinifera cv. Cabernet Sauvignon, cv. Merlot, and cv. Pinot Noir. All wineries fermented all grapes from the individual vineyards in separate fermentation tanks. Similar to Coetzee et al. (2005), sampling took place in each winery directly from stainless steel fermentation vessels after fermentation was finished, but before any additional post-fermentation treatments took place (e.g. filtration,
An inductively coupled plasma-mass spectrometry (ICP-MS) instrument from Agilent (7700x, Santa Clara, CA, USA) was used for the elemental profiling of 63 trace elements in a mass range between 7 and 238 m/z. The IS mix was constantly fed into and mixed with the sample stream immediately before entering the spray chamber (quartz double wall, cooled to 2 °C), using a mixing tee (sample tubing inner diameter 1.02 mm, IS tubing inner diameter 0.25 mm). The peristaltic pump was operated at 0.1 rps. A concentric nebulizer (Micromist, Agilent) was used for sample transport into the plasma (RF power of 1550 W, RF matching 1.8 V, sampling depth 10 mm, carrier gas flow 1.05 mL/min). The instrument was calibrated and tuned daily, using a tuning mix (Li, Y, Ce, Tl, Co; Agilent) and the Pulse/Analog solutions (Zn, Be, Cd, As, Ni, Pb, Mg, Th, Ca, Co, Sr, V, Cr, Mn, 6Li, Sc, In, Lu, Bi, Y, Yb, Mo, Sb, Sn, Ge, Ru, Pd, Ti, Ir; Agilent). All wine were analysed in duplicate, and they were 1:3 dilutions in 5% HNO3. Elements were monitored in no gas, helium (He flow 4.3 mL/min) and/or high energy helium (He flow 10 mL/min) gas mode using the ORS3 system. A 6-point calibration between 0 and 500 lg/L was carried out for the elements listed in Table 1 in
Table 1 Monitored elements together with detection mode and limits of detection (LOD).
a b
Element
m/z
Modea
LODb [lg/L]
Element
m/z
Modea
LODb [lg/L]
Li Be B Na Mg Al Si P K Ca Ti V Cr Mn Co Ni Cu Zn Ga As Se Rb Sr Mo
7 9 11 23 24 27 28 31 39 43 47 51 52 55 59 60 63 66 69 75 78 85 88 95
ng ng ng ng ng ng ng ng He He He He He He He He He He He He HEHe ng He ng
2.25E 01 1.40E 02 1.12E 01 1.79E+00 4.03E 01 4.68E 01 4.23E 01 6.92E 01 1.16E+00 8.79E 01 5.43E 01 2.40E 02 7.70E 02 2.30E 02 9.00E 03 3.47E 01 2.30E 02 1.50E 02 5.00E 03 7.00E 03 5.20E 02 2.00E 03 1.00E 02 3.10E 02
Rh Cd Sn Sb Cs Ba La Ce Pr Nd Sm Eu Gd Dy Ho Er Tm Yb W Re Tl Pb U
103 111 118 121 133 137 139 140 141 142 147 153 157 163 165 166 169 172 182 185 205 208 238
He He He He ng He He He He He He He He ng He ng ng ng He He ng He He
1.00E 9.00E 2.10E 4.00E 5.00E 1.30E 6.00E 2.00E 3.00E 7.00E 2.00E 4.60E 1.00E 4.00E 6.00E 8.00E 3.00E 1.00E 1.90E 5.00E 2.00E 5.00E 6.60E
ng . . . no gas; He . . . helium; HEHe . . . high energy helium. Limit of detection (LOD); n = 10 calibration blank measurements; 99% confidence interval.
03 03 02 03 04 02 04 03 04 04 03 06 03 04 04 04 04 03 02 04 03 03 06
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matrix-matched calibration solutions (5% HNO3 and 4% Ethanol) to account for matrix interferences of the ethanolic wine solutions. Elements were detected using a 3-point peak pattern in triplicate with 100 sweeps per replicate. Previous studies have shown that a reduction of the ethanol content to around 5% is a good compromise between a stable plasma and sufficient sensitivity (Boorn & Browner, 1982; Dams, Goossens, & Moens, 1995; Goossens, Moens, & Dams, 1994; Rossano et al., 2007). Higher concentration elements (>500 lg/L; B, Na, Mg, Si, P, K, Ca, Mn, Cu, Rb, Sr, Ba) were measured after a 1:1000 dilution in 5% HNO3. Spiked samples were analysed throughout the analysis run to ensure validity of the analytical method. Continuous calibration blank verification (CCB) runs were performed every 10th sample. 2.3. Data analysis All monitored isotopes were calibrated using the MassHunter ICP-MS software (G7201B, version B.01.03, Agilent). Based on limits of detection (LOD), determined with 10 calibration blank measurements (Thomsen, Schatzlein, & Mercuro, 2003), detection limits (DL) and background equivalent concentrations (BEC), reported by the software, isotopes and gas modes were selected for each element, and used for further data analysis. For statistical significance testing as well as multivariate classification, elements that were detected below LOD were assigned a concentration of LOD/10. Multivariate and univariate analyses of variance (MANOVA and ANOVA) were carried out for the main effects winery, and vineyard, as well as for the winery-by-vineyard interaction, using logtransformed concentration data. Statistical significance was set at 5%. Canonical Variate Analysis (CVA) was chosen as a classification technique to study how individual wineries, vineyards as well as the winery–vineyard combinations differed from each other, using the respective one-way MANOVA models. Canonical variates (CVs) were tested for significance using the Bartlett’s test (homogeneity of variances) (Bartlett, 1937). All analyses were carried out in R (R Core Team, 2013), using RStudio (version 0.98.953, Boston, MA, USA) with the additional candisc package (Friendly & Fox, 2010). 3. Results and discussion 3.1. Elemental profiling Of the 63 monitored elements, 47 were detected in the 65 different wine samples at concentrations above their LODs, and thus, were included in the data analysis. For none of the elements was a significant replicate effect was found, indicating that the ICP-MS analysis method was repeatable (P 6 0.05). Recoveries for the spiked samples, measured throughout the analysis sequence, were between 93% (for Ba) and 103% (for Ca). Similar to Martin and coworkers (Martin et al., 2012) we found no significant elemental differences between different cultivars from one region. Significant differences for the winery, vineyard and the interaction effect were detected in the MANOVA (P 6 0.05). Individual ANOVAs revealed that all detected elements but 14 differed significantly among the wineries (33 significantly different elements, Suppl. Table 2a), while 26 out of the 47 detected elements differed significantly among the five different vineyards (P 6 0.05) (Suppl. Table 2b). Significant winery-by-vineyard interactions (i.e. the combination of both winery and vineyard impact) were found for 17 elements (Be, Na, P, Ti, Zn, As, Rb, Cd, Sb, Cs, La, Pr, Dy, Er, Tm, Yb, Tl) (P 6 0.05). In Suppl. Table 2a–b the detected elements are summarised for the five vineyards and five wineries. These results show that both
grapegrowing and winemaking have an effect on the elemental composition of the wine samples. Based on the ANOVA results it seems that more elements are affected by the winemaking, as more elements differ significantly in the wines across the different processing wineries compared to the different vineyard origins. Using the one-way MANOVA models for winery, vineyard and winery-by-vineyard effects, Canonical Variate Analysis (CVA) was conducted to establish a classification for each of these factors. 3.2. Vineyard effect Canonical Variate Analysis (CVA) was used to classify the samples according to their vineyard origin, using the log-transformed concentrations of the 26 elements that differed significantly among the vineyards (P 6 0.05). All four CVs were highly significant in the Bartlett’s test (P 6 0.05), and the first two CVs explain over 81% of the total variance ratio, as shown in Fig. 3. Along the first CV, capturing 55% of the total variance ratio, vineyards were separated based on the elemental differences between vineyard 1, and vineyards 2 and 5, with the remaining two vineyards located in between. Along the first CV vineyards line up according to their geographic north–south location (see also Fig. 1), except for vineyard 2 which showed more similarities to the most southern vineyard 5, while being the second most northern vineyard. Also, along the first CV the two neighbouring vineyards (2 and 3) were not close to each other (Fig. 3a). Wines from vineyard 1 showed higher levels in B, Mg, P, Ca, Ti, Cr, Ni, As, Mo, and to a lesser extent, Al, Co, Zn, and Sr, while wines from the more southern vineyards showed higher concentrations in Li, Be, Si, Mn, Rb, Cs, Er, Yb, Tl, and to a smaller extent, Ga, Se, Ba, and Eu (Fig. 3b-c). Boron, Mg, P, and Ti levels in wines from vineyard 1 were 1.5 times higher than in the wines from all other vineyards. Boron is an essential element for plants, but its precise role in the plant metabolism is not fully understood. Boron levels need to be managed in a very narrow range, to avoid either deficiency or toxicity, due to its easy mobilisation from the soil into the plant. Boron-rich soils are the result of either marine sediments or boron rich minerals, which enhances the danger of boron toxicity if combined with low rainfall and high salinity (Soilquality Pty Ltd., 2013; Yermiyahu, Ben-Gal, & Sarig, 2006). Potassium, N and P are essential plant elements, and are often added to the soil with fertilizers (Aceto, 2003), while Mg, Ti, Mo, Mn, and Si are mainly influenced by the mineral content of the soil and mineral grape uptake as reported by Marengo and Aceto (Marengo & Aceto, 2003) who successfully discriminated among Nebbiolo wines from different sub-regions within the Piemonte region in Italy. The second CV separates wines from the vineyards 1, 4, and 5 from those from the two neighbouring vineyards 2 and 3 (Fig. 3d). The former three vineyards are positively correlated to B, Si, Tl, Cs, and Se, while the levels in Cr, Mn, Co, Ni, Zn, As, and Mo were very similar in the wines from the two neighbouring vineyards 2 and 3, leading to a clear separation of these two vineyards from the others along CV 2 (Fig. 3e). All other elements (Li, Be, Mg, Al, P, Ca, Ti, Ga, Rb, Sr, Ba, Eu, Er, and Yb) contributed to a smaller degree to the separation of the different classes along CV 2. According to Pereira (Pereira, 1988) the application of B, Cr, Mo, Mn, Co, and Zn as grapevine, soil or foliage treatments or as fertilizers impact both grape yield and grape composition, especially the polyphenol, sugar, ester and amino acid levels. Any viticultural practices, such as fertilizer application, would most likely also affect the elemental composition of wine produced from such treated grapes, depending on how easily the element would be
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(a) 2 3
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Fig. 3. Canonical Variate Analysis (CVA) plots for the vineyard effect. (a) Product plot showing the individual wine samples, coded according to their vineyard origin with different numbers (vineyard 1 (1), vineyard 2 (2), vineyard 3 (3), vineyard 4 (4), vineyard 5 (5)). Boxplots and total structures coefficients for the first (b-c) and second (d-e) dimension showing the contribution of each element to the separation along CV 1 and CV 2.
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Fig. 4. Canonical Variate Analysis (CVA) plots for the winery effect. (a) Product plot showing the individual wine samples, coded according to their processing winery with different letters (winery A (A), winery B (B), winery C (C), winery D (D), winery E (E)). Boxplots and total structures coefficients for the first (b-c) and second (d-e) dimension showing the contribution of each element to the separation along CV 1 and CV 2.
H. Hopfer et al. / Food Chemistry 172 (2015) 486–496
mobilised in the soil. Elemental mobilisation is heavily dependent on the soil constitution, mainly pH and aeration status, the soil microbiota, as well as the element itself. While so called lithophile elements (e.g. geochemically stable Al, Rb, Sc, Ti, and Zr (Boës, Rydberg, Martinez-Cortizas, Bindler, & Renberg, 2011)) are bound to various minerals, and are thus, less mobile, the anthropogenic elements (e.g. B, Si) are typically present as ions, resulting in higher soil mobility and thus, bioavailability (Bañuelos & Ajwa, 1999; Kabata-Pendias, 2004). Based on these results, we hypothesise that the discrimination among the different geographic origins (i.e. vineyards) of the wines is the result of both soil elemental content and viticultural practices. Further studies are needed to directly relate the elemental composition of these vineyard soils to the composition in the wines. Additional studies relating the effects of viticultural practices on elemental composition of grapes are also needed. 3.3. Winery effect Similarly to the vineyard effect, the CVA on the winery effect as a classifier, using the 33 elements that differed significantly among the wineries in the ANOVA (P 6 0.05), led to a clear separation of all wines according to their processing winery. All four canonical variates (CVs) were significantly different from each other as determined by the Bartlett’s test (Bartlett, 1938; Friendly & Fox, 2010). Eighty-seven percent of the total variance ratio was explained within the first two CVs, thus only the first two dimensions are shown. Wine samples were grouped according to the winery they were processed as shown in Fig. 4a, where all wineries were well separated from each other. Wines from winery B are more different from the wines processed in all other wineries, as the remaining wineries (A, C–E) are closer to or overlap with each other. Along the first CV, 50% of the total variance ratio was explained, mainly driven by the elemental differences of wines processed in winery A, compared to wines processed in winery B or E, with the wines from winery C and D in between (Fig. 4b). Wines from winery A are separated from the other wineries based on the higher concentrations in Mg, P, Ca, Ti, Ni, Se, Sr, Rh, Re, while B, Cr, and Mo contribute to a smaller degree to the separation (Fig. 4c). The most likely source for Cr, Ti, Ni, and Mo are winery equipment and wine containers as reported previously (Almeida & Vasconcelos, 2003a; Galani-Nikolakaki, Kallithrakas-Kontos, & Katsanos, 2002; GalaniNikolakaki & Kallithrakas-Kontos, 2006; Pohl, 2007; Tariba, 2011; Volpe et al., 2009). Molybdenum and Ti are stainless steel alloy elements (http://www.ssina.com), but are also present in the soil, so their presence in the wines could be the result of both grapegrowing and winemaking practices. Magnesium, P, Ca, B, Sr, and Rh have been reported to come from vineyard soil by some authors (Pohl, 2007; Taylor et al., 2003), while others argue that P, Mg and Ca can also be influenced by winemaking processes (Volpe et al., 2009). Iglesias et al. (2007) report that Sr levels are not influenced by production, however, this is neither confirmed by our results nor by the results of Taylor et al. (2003) who found larger variation in Sr levels in wines than in the soil. Higher levels of Al, Mn, Zn, Rb, Cd, Sb, Cs, Tl, Pb, and the significantly different concentrations of REEs are contributing the most to the separation of the wines from wineries B and E from the other wineries, while K, Co, As, and Ba contribute to a lesser extent to this separation (Fig. 4c). Selenium, Rb and Cs are commonly reported elements used to differentiate the geographical origin of wines (Angus, O’Keeffe, Stuart, & Miskelly, 2006; Castiñeira Gómez, Feldmann et al., 2004; Coetzee et al., 2005; Martin et al., 2012; Pohl, 2007; Taylor et al., 2003), but in most of these previous studies, only finished wines have been analysed. Almeida and Vasconcelos (2003a) reported that the Rb levels remained constant throughout red wine making.
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The contents of Al, Mn, Cd, Co, and Pb in wines were reported previously to result from winery equipment and containers (Almeida & Vasconcelos, 2003a; Galani-Nikolakaki et al., 2002; Galani-Nikolakaki & Kallithrakas-Kontos, 2006; Pohl, 2007; Tariba, 2011; Volpe et al., 2009), and Almeida and Vasconcelos (2003a) were only able to find a significant correlation between vineyard soil and finished wine if they excluded Al and Ca from their model, indicating that these latter two elements were heavily influenced by the winemaking process. The presence of Zn in wines could be the result of various factors, such as industrial activity (Marengo & Aceto, 2003), the use of pesticides and fertilizers (Pohl, 2007; Tariba, 2011), as well as winery containers (Pohl, 2007; Tariba, 2011). Both Al and Zn have an impact on wine stability, and excess levels (
