Elemental characterisation of Andalusian wine vinegars with protected designation of origin by ICP-OES and chemometric approach

Food Control xxx (2016) 1e8

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Elemental characterisation of Andalusian wine vinegars with protected designation of origin by ICP-OES and chemometric approach
n b P. Paneque a, *, M.L. Morales b, P. Burgos c, L. Ponce a, R.M. Callejo

lez nº1, E-41012, Seville, Spain Area de Edafología y Química Agrícola, Facultad de Química, Universidad de Sevilla, C/P. García Gonza

lez nº2, E-41012, Seville, Spain
n y Bromatología, Facultad de Farmacia, Universidad de Sevilla, C/P. García Gonza Area de Nutricio c Instituto de Recursos Naturales y Agrobiología de Sevilla (IRNAS), CSIC, Avda. de Reina Mercedes 10, P.O. Box 1052, E-41080, Seville, Spain a

b

a r t i c l e i n f o

a b s t r a c t

Article history: Received 15 July 2016 Received in revised form 2 December 2016 Accepted 3 December 2016 Available online xxx

Wine vinegars from three Protected Designations of Origin (PDO), Vinagre de Jerez (J), Vinagre de Montilla-Moriles (MM) and Vinagre del Condado de Huelva (CH) from Andalusia, Southern Spain, were investigated for their mineral elements content. Al, As, B, Ba, Ca, Cd, Co, Cr, Cu, Fe, K, Mg, Mn, Na, Ni, P, Pb, S, Sr, V and Zn were determined by inductively coupled plasma optical-emission (ICP-OES). Jerez vinegars had a statistically significant higher Sr content than the others, while with respect to B the same was true for Montilla-Moriles vinegars. Moreover, the ageing time of the vinegars clearly played a role in vinegar mineral content, with higher mineral levels found in aged vinegars than in young ones, especially in samples from Condado de Huelva. Multivariate analysis was performed in order to assess if the vinegars' geographical classification was possible through their elemental profile. Classification models were obtained by LDA and SVM, achieving good prediction abilities, 73 and 80%, respectively. © 2016 Elsevier Ltd. All rights reserved.

Keywords: Wine vinegar Multi-elemental analysis ICP-OES Multivariate statistic Support vector machine

1. Introduction Currently, there is a growing demand for high-quality food products in the market. Hence, quality vinegar, practically only appreciated in haute cuisine and gastronomy, has been in great demand and is a highly-appreciated condiment. Wine vinegar is the most commonly-used vinegar in Central European and Mediterranean countries. It is the result of two fermentation processes (alcoholic fermentation and acetous
n ~ ez, Callejo
n, Morales, & García Parrilla, 2013). fermentation) (Ordo From a technological point of view, there are two methods for vinegar production: fermentation with a submerged or surface culture. In the first, the acetic acid bacteria are submerged in the acetifying liquid, and it is vigorously aerated to obtain the desired acetic degree (>6% w/v) within 24e36 h. In the second method, the acetic acid bacteria are placed on the aireliquid interface in direct contact with atmospheric air. Oxygen availability to the acetic acid bacteria is, therefore, more limited, and, to obtain a high acetic degree, a long time period is required (Tesfaye, Morales, GarcíaParrilla, & Troncoso, 2009). This latter process usually takes place

* Corresponding author. E-mail address: [email protected] (P. Paneque).

in wooden barrels, resulting in high-quality vinegars with excellent organoleptic characteristics. In addition, some vinegars are aged in wooden barrels using different systems, which also contribute to increasing the vinegars' quality (Marrufo-Curtido et al., 2012). Some wine vinegars, traditionally linked to a certain geographical area, have been protected by the European Union with a legislative system known as Protected Designation of Origin (PDO) which protects the specifications of their chemical and sensory features and their production system, as well as endowing them with a certification (Chinnici et al., 2009). In Andalusia there are three wine vinegars that, due to their unique characteristics, benefit of PDO protection: Vinagre de Jerez, Vinagre del Condado de Huelva and, recently, Vinagre de MontillaMoriles. Furthermore, there are different categories within each PDO according to the ageing time in wooden barrels and the type of ageing, dynamic or static. These vinegars have different prices in the market according to their quality, the price rising as ageing time and, consequently, production costs increase. Consequently, they
n et al., 2012). In addition, are frequently subject to fraud (Callejo the growing demand as well as the increasing diversity of wine vinegars due to their different production processes, has generated a need to characterise them in order to ensure an adequate quality control that enables the different denominations to demonstrate

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P. Paneque et al. / Food Control xxx (2016) 1e8

and defend their identity (Cerezo et al., 2008; Liu, He, & Wang, 2008; Marrufo-Curtido et al., 2012). Vinegar characterisation and differentiation has been performed by different methods and perspectives, mainly to differentiate vinegars produced from different raw materials or by different production process (Boffo, Tavares, Ferreira, & Ferreira,
pez, & 2009; Chen et al., 2014; De la Haba, Arias, Ramírez, Lo
n Sanchez, 2004; Dong, Zheng, Jiao, Lang, & Zhao, 2016; Dura Guerrero, Castro Mejías, Natera Martín, Palma Lovillo, & García
nz Gonzalez, & Barroso, 2010; Pizarro, Esteban-Díez, Sae Gonzalez-S
aiz, 2008; ). Different analytical parameters, such as phenolic composition, volatile compounds, organic acid contents, and different analytical techniques (H NMR spectra, NIRS spectroscopy, olfactory and sensory sensors, etc.) were all used by the above authors with that aim in mind. Furthermore, several authors have performed studies to characterise and differentiate high-quality PDO wine vinegars. García
lez, Heredia, and Troncoso (1997) differentiated Parrilla, Gonza Andalusian vinegars according to their provenance and production method (quick or slow acetification process) by determining their phenolic composition. General chemical composition has been used to characterise and differentiate Jerez (Sherry) and Rioja vin~ iguez, 1999); whereas egars (Benito, Ortiz, Sanchez, Sarabia, & In Chinnici et al. (2009) and Marrufo-Curtido et al. (2012) used volatile compounds to differentiate Sherry vinegars from Modena Balsamic vinegars. In addition, mineral composition can also be used as a tool to differentiate vinegars produced from different raw materials (Acosta, Diaz, Hardisson, & Gonzalez, 1993; Akpinar-Bayizit, Ali Turan, Yilmaz-Ersan, & Taban, 2010), different production pro
n, cesses and geographical origin. Guerrero, Herce-Pagliai, Camea
lez (1997) determined Ca, Mg, Cu, Zn, Fe, Mn Troncoso, and Gonza and As contents in Andalusian wine vinegars, and characterised them according to their production process (quick and slow acetification). Moreover, some attempts were made to differentiate Andalusian slow acetification process vinegars from different geographical areas within the region using these same elements
n, (Guerrero, Herce-Pagliai, Gonz
alez, J. Heredia, Troncoso, & Camea 1996). Procedures followed for wine vinegar production and ageing are similar in the three existing Andalusian wine vinegar PDOs (Ministerio de Medio Ambiente y Medio Rural y Marino, 2009a, b, c), yet there are differences in grape variety in each PDO and also in the characteristics of the soils where the vines are grown

n, & Gonz
(Alvarez, Moreno, Jos, Camea alez, 2007; Paneque,

mez, 2009). Accordingly, soil differAlvarez-Sotomayor, & Go ences and, to a lesser extent, differences in grape varieties could be reflected in the mineral composition of the three PDO vinegars. Major elements found in wine vinegars, such as Ca, K, Mg, Na, P and S are natural components of grape juice, K being the predominant cation. Therefore, K is also the most abundant element in wine vinegars, although its content may increase due to the addition of metabisulphite for wine and vinegar preservation (Marengo & Aceto, 2003). Deacidification treatments during the oenological process may also raise Ca and Mg concentration in wine and the resulting wine vinegars (Hopfer, Nelson, Collins, Heymann, & Eberler, 2015; Marengo & Aceto, 2003; Tariba, 2011). Although Na is found naturally in the soil, the exposure of the grapevines to marine influence may affect its content in wines (Frias, Conde,
rez-Trujillo, 2003). Rodríguez-Bencomo, Garcia-Montelongo, & Pe P concentration in wine is determined by its content in the soil and the capacity of the vine to assimilate it, but it is also added to wine as a calcium or ammonium salt (Volpe et al., 2009). The minor elements Cu and Zn occur naturally in the soil, but their contents are

influenced by agricultural practices and direct contact with tank surfaces and metallic tubing during winemaking (Guerrero et al.,
n, 1988). Al is 1996; Marengo & Aceto, 2003; Troncoso & Guzma an element whose presence in grape juice is affected by natural factors such as soil mineral contribution or the vine's uptake capacity (Marengo & Aceto, 2003); however the use of bentonite for fining treatments and, to a lesser extent, Al surface contact may raise its content in wines (Stafilov & Karadjova, 2009). Co, Cr, Ni and V content in wines is related almost exclusively to artificial sources, primarily due to interaction with metal containers (Marengo & Aceto, 2003). B and Sr are natural elements which originate from its presence in the soil and its uptake by the vine (Volpe et al., 2009). In relation to toxic elements, As may be present in wines and in the resulting vinegars as a consequence of the use of pesticides, soil type and vinification process (Tariba, 2011); while Cd is considered an artificial element (Hopfer et al., 2015) which may originate either from the use of fertilisers, fungicides and pesticides in the vineyard (Pohl, 2007) or from atmospheric pollution (Kment et al., 2005; Volpe et al., 2009). Finally, Pb content in wines is primarily related to fungicidal treatments, container materials and vehicular traffic, the soil contribution being minimal (Marengo & Aceto, 2003), although nowadays the reduction of natural Pb content in fuels means the contribution made by traffic combustibles is minimal (Tariba, 2011). Vinegar mineral composition has been determined primarily through flame atomic absorption spectroscopy (FAAS), flame atomic emission spectrometry (FAES) (Acosta et al., 1993; Guerrero et al., 1997, 1996; Saei-Dehkordi, Fallah, & Ghafari,
n, 1988), and, in the case of the element 2012; Troncoso & Guzma As, by hydride generation atomic absorption spectroscopy (HGAAS) (Troncoso & Guzm
an, 1988). Saei-Dehkordi et al. (2012) used FAAS together with stripping chronopotentiometry for determining Pb, Cd, Cu and Zn in Iranian vinegars. In the last decade, inductively coupled plasma optical-emission (ICP-OES) has also been used for determining mineral constituents in vinegar samples (Akpinar-Bayizit et al., 2010; Da Silva, Cadore, Nobrega, & Baccan, 2007). ICP-OES is a multi-elementary technique that enables FAAS and FAES (both mono-elementary) analysis times to be shortened, considerably reducing laborious and time-consuming techniques. The aims of this paper are to characterise the mineral composition of Andalusian Protected Designation of Origin wine vinegars using the ICP-OES technique; and, subsequently, to check if the mineral composition of the vinegars could be a suitable tool for discriminating among Andalusian PDO wine vinegars according to their geographical origin by chemometrics. Additionally, the influence of ageing time on the element content was studied. 2. Materials and methods 2.1. Reagents and materials All reagents used were of analytical grade or better. For sample dilution and preparation of standards we used <18 MU/cm ultrapure water supplied from a Milli-Q Millipore system (Bedford, MA, USA) and Tracepure™ HNO3 from Merck (Darmstadt, Germany). Calibration and Quality Control (QC) solutions were prepared from an ICP multi-element standard solution IV Certipur obtained from Merck and Spectrascan certified reference solution from LGC Standards GmbH (Wesel, Germany). Single-element solutions from SPEX CertiPrep (Metuchen, NJ, USA) were used to prepare calibration solutions for phosphorus and sulphur. To prevent contamination of the samples with traces of any metal, all material used for sample storing and treatments and all

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P. Paneque et al. / Food Control xxx (2016) 1e8

labware was soaked in 4% v/v HNO3 solution followed by two washes with Milli-Q water. 2.2. Samples Twenty-eight samples of wine vinegars from three Andalusian PDOs were used. The distribution of samples was as follows: 10 samples from Condado de Huelva (CH); 10 samples from Jerez (J); and 8 samples from Montilla-Moriles (MM). In all cases, half of the samples corresponded to young vinegars and the rest to aged vinegars (known as Reserva in the three PDOs), except the Jerez samples, in which the distribution was 4 and 6, respectively. To ensure the geographical origin of the vinegars, all samples were kindly provided during 2014e2015 by each PDO's Consejo Regulador, or Regulatory Council. The samples were produced by different wineries in each PDO: 6, 10 and 4 in CH, J and MM PDOs, respectively. Acetic acid content ranged from 7 to 9.7 g/100 mL of vinegar, according to the supplier. 2.3. Samples and standard preparation Following Selih, Sala, & Drgan (2014), vinegar samples were analysed without preliminary treatment. However, to minimise possible matrix effects, samples were diluted 1:2.5 (v/v) with 8% v/v HNO3. Each vinegar sample was diluted in triplicate as indicated and analysed; accordingly, we have used the average value from the triplicate as the sample's element content. The calibration and QC solutions were diluted with 8% v/v HNO3. The calibration blank was prepared with 8% v/v HNO3. Y was used as an internal standard and prepared from a Merck single-element 1000 mg/L solution. All solutions, including diluted samples and calibration blank, were filtered using a 0.45 mm nylon membrane. 2.4. Analytical procedure For ICP-OES measurements a Varian 720-ES axial inductively coupled plasma atomic emission spectrometer equipped with a standard axial torch and a seaspray nebulizer was used. Detailed instrumental settings for ICP-OES technique used and elements measured are presented in Tables 1 and 2. The method was validated by spike recovery studies. For each element, limit of detection (LOD) estimation consisted of measuring 10 replicates of the blank sample, determining the mean value (Y10) and standard deviation (SD), and calculating LOD as the mean plus 3 SD (LOD ¼ Y10 þ 3SD); while limit of quantification (LOQ) was calculated as LOQ ¼ Y10 þ 10SD. Table 1 Instrument operating conditions. Condition

Setting

Power Plasma gas flow Auxiliary gas flow Spray chamber type Torch Nebulizer type Nebulizer gas flow Replicated read time Number of replicates Sample delay time Stabilization time Rinse time Fast pump Background correction

1.30 kW 16.5 L/min 1.50 L/min Glass cyclonic Standard axial torch Seaspray 0.95 L/min 10 s 3 40 s 15 s 10 s On Fitted

3

2.5. Statistical analysis A data matrix with 19 columns (determined elements) and 28 rows (analysed samples) was built for chemometric calculations. ANOVA and multivariate analysis (cluster analysis, CA; linear discriminant analysis, LDA; and support vector machine, SVM) were performed. CA was applied as an unsupervised technique in which objects are grouped in clusters in terms of their similarity. The initial assumption is that the nearness of objects in the space defined by the variable reflects the similarity of their properties (Massart & Kaufmann, 1983). We used as a criterion of similarity Ward's hierarchical method and City's block (Manhattan) distance. LDA linearly combines the original variables to obtain discriminant functions which separate categories by means of the minimization of the within-class and between-class ratio of the sum of squares (Massart et al., 1998). LDA was carried out by forward stepwise procedure to select the most relevant variables; and standard LDA method in LDA external validation, in this case, the variables used were those included in the classification functions obtained by forward stepwise LDA. Support vector machines (SVM) are revolutionary methods for pattern recognition based on statistical learning theory and kernel
berger, latent variables (Abe, 2005; Berrueta, Alonso-Salces, & He 2007; Burges, 1998). The purpose of SVM is separate the classes in a vectorial space independently on the probabilistic distribution of pattern vectors in the data set. This separation is performed with the particular hyperplane which maximizes a quantity called margin. The margin is the distance from a hyperplane separating the classes to the nearest point in the data set. The training pattern vectors closest to the separation boundary are called support vectors. When dealing with a non-linear boundary, the kernel method is applied. The key idea of kernel method is a transformation of the original vectorial space (input space) to a high dimensional Hilbert space (feature space), in which the classes can be separated linearly. SVM was performed using the same variables considered in LDA external validation. The classification models obtained by LDA and SVM were externally validated using the same training set (80% of the samples) and test set (20% of the samples), manually randomly selected. Statistical analysis was carried out by using the STATISTICA 7 package of Statsoft (2005); and elements with content levels lower than the LOQ were not considered. 3. Results and discussion The first aim of our work was the characterisation of the mineral content of Andalusian PDO wine vinegars by ICP-OES (section 3.1); and, subsequently, on the one hand, to assess if mineral content could be a suitable tool for the vinegars' classification according to their geographical origin (section 3.2); and, on the other hand, if ageing time of the vinegars could influence on the vinegar classification due to their mineral content (section 3.3). Steps followed for data analysis are summarised in Fig. S.1 (see Supplementary Materials). 3.1. Mineral content in Andalusian PDO wine vinegars In the present study, a total of 21 elements (Al, As, B, Ba, Ca, Cd, Co, Cr, Cu, Fe, K, Mg, Mn, Na, Ni, P, Pb, S, Sr, V and Zn) were analysed by ICP-OES in Andalusian wine vinegars with PDO. Results are listed in Table 3. Among the results obtained, the variability of values obtained for each element in the samples is outstanding, showing a wide range of values for each element e even in vinegars from the same

Please cite this article in press as: Paneque, P., et al., Elemental characterisation of Andalusian wine vinegars with protected designation of origin by ICP-OES and chemometric approach, Food Control (2016), http://dx.doi.org/10.1016/j.foodcont.2016.12.006

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P. Paneque et al. / Food Control xxx (2016) 1e8

Table 2 Wavelength, calibration range, limit of detection (LOD) and limit of quantification (LOQ) for each element. Element

Wavelength (nm)

Calibration range (mg/L)

LOD (mg/L)

LOQ (mg/L)

Al As B Ba Ca Cd Co Cr Cu Fe K K Mg Mn Na Na Ni P Pb S Sr V Zn

396.152 188.980 249.772 493.408 318.127 226.502 228.615 267.716 324.754 259.940 766.491 404.721 285.213 293.931 589.592 568.821 231.604 213.618 220.353 182.562 407.771 311.837 213.857

0e10 0e10 0e10 0e10 0e500 0e10 0e10 0e10 0e10 0e10 0e50 50e500 0e250 0e10 0e50 10e500 0e10 0e100 0e10 0e500 0e10 0e10 0e10

0.020 0.005 0.002 0.006 0.016 0.0003 0.0007 0.0007 0.002 0.005 0.005 2.00 0.005 0.0003 0.003 0.200 0.002 0.010 0.003 0.009 0.0003 0.002 0.002

0.050 0.020 0.005 0.002 0.050 0.001 0.002 0.002 0.007 0.020 0.020 6.20 0.020 0.001 0.010 0.080 0.005 0.030 0.009 0.030 0.001 0.005 0.008

geographical area. The mean content of the major elements Ca, Mg, Na and K, was consistent with the values range previously reported for Andalusian wine vinegars (Guerrero et al., 1996, 1997; Troncoso & Guzm
an, 1988). To our knowledge, the major-elements P and S have not previously been determined in Andalusian vinegars. In our study, contents ranged from 50 to 200 mg/L for P and from 155 to 700 mg/L for S, approximately. Mean P content in our samples was higher than that reported in Turkish wine vinegars (mean content, 74.72 mg/L) (Akpinar-Bayizit et al., 2010). The Spanish Government regulates the maximum permitted contents of some heavy metals in vinegars (Ministerio de la

Presidencia, 1993). Accordingly, toxic metals as Hg, Pb and the metalloid As, should not exceed 0.05 mg/L (for Hg) and 0.5 mg/L (for Pb and As); whereas the total content of Cu and Zn should not exceed 10 mg/L. Cu and Zn are considered essential metals, but in high concentrations they could become toxic. The mean Cu content found in our samples was similar to those already reported in Andalusian wine vinegars; whereas Zn contents were slightly lower
n, 1988). Only two (Guerrero et al., 1996, 1997; Troncoso & Guzma samples (10.6 and 10.7 mg/L) of the 28 analysed exceeded the maximum value of 10 mg/L allowed for CuþZn, both samples corresponding to aged vinegars (in addition to endogenous and

Table 3 Range of element contents (mg/L) in Andalusian wine vinegars from the PDOs Condado de Huelva (n ¼ 10), Jerez (n ¼ 10) and Montilla-Moriles (n ¼ 8), and mean and standard deviation in young and aged wine vinegars within each PDO. Element

Condado de Huelva Range*

Al As*** B Ba Ca Cd*** Co Cr Cu Fe K Mg Mn Na Ni P Pb S Sr V Zn

1.17e5.77 A <0.020 1.47e10.09 B 0.040e0.103 A 44.41e459 A <0.001 0.003e0.077 A 0.017e2.09 A 0.018e4.47 A 1.37e16.21 A 372e1814 A 29.99e137 A 0.171e1.66 A 22.69e284 A 0.012e0.903 A 51.32e219 A 0.035e0.813 A 155e714 A 0.196e1.57 A 0.011e0.035 B 0.141e6.12 A

Jerez

Mean ± SD**

Range*

Young (n ¼ 5)

Aged (n ¼ 5)

1.36 ± 0.13 b <0.020 1.8 ± 0.3 b 0.090 ± 0.010 70 ± 29 b <0.001 0.020 ± 0.010 0.4 ± 0.9 a 0.15 ± 0.14 b 3±4b 459 ± 54 b 49 ± 12 b 0.28 ± 0.11 b 148 ± 122 a 0.2 ± 0.4 a 92 ± 53 a 0.050 ± 0.010 230 ± 63 b 0.41 ± 0.16 b 0.024 ± 0.010 0.27 ± 0.11 b

4.0 ± 1.2 a <0.020 5±3a 0.080 ± 0.020 282 ± 124 a <0.001 0.03 ± 0.03 a 0.070 ± 0.020 2.4 ± 1.8 a 10 ± 4 a 1281 ± 398 a 87 ± 34 a 0.9 ± 0.6 a 157 ± 107 a 0.050 ± 0.020 125 ± 61 a 0.4 ± 0.3 a 553 ± 98 a 1.1 ± 0.3 a 0.024 ± 0.004 2.8 ± 2.0 a

a

a

b

a

a

a

a

a

0.85e5.57 A <0.020 3.26e9.25 B 0.045e0.117 A 144e393 A <0.001 0.009e0.060 A 0.023e0.108 A 0.032e8.58 A 1.98e17.46 A 771e1452 A 60.55e104 A 0.239e1.32 A 50.73e211 AB 0.007e0.117 A 84.58e205 A 0.038e2.20 A 408 -692 A 0.880e1.72 B 0.013e0.147 AB 0.079e4.75 A

Montilla-Moriles Mean ± SD**

Range*

Young (n ¼ 4)

Aged (n ¼ 6)

2.9 ± 1.6 a <0.020 3.37 ± 0.10 a 0.090 ± 0.020 a 231 ± 111 a <0.001 0.025 ± 0.007 a 0.06 ± 0.04 a 0.4 ± 0.6 a 7±5a 928 ± 142 b 66 ± 6 a 0.78 ± 0.21 a 72 ± 12 a 0.040 ± 0.026 a 150 ± 48 a 0.14 ± 0.12 a 447 ± 28 a 1.2 ± 0.3 a 0.05 ± 0.06 a 0.7 ± 0.6 a

3.3 ± 1.1 a <0.020 5.4 ± 2.2 a 0.080 ± 0.020 a 190 ± 46 a <0.001 0.028 ± 0.018 a 0.059 ± 0.018 a 3±3a 7±6a 1303 ± 236 a 85 ± 15 a 0.7 ± 0.5 a 93 ± 61 a 0.06 ± 0.04 a 134 ± 42 a 0.7 ± 0.8 a 563 ± 102 a 1.52 ± 0.17 a 0.04 ± 0.05 a 1.5 ± 1.8 a

1.91e7.11 A <0.020 3.47e8.74 A 0.048e0.164 A 86.68e236 A <0.001 0.007e0.041 A 0.038e0.063 A 0.017e2.60 A 1.18e19.02 A 567e1668 A 58.63e107 A 0.049e1.49 A 42.64e82.38 B 0.002e0.043 A 73.85e196 A 0.083e0.217 A 292e644 A 0.676e1.83 A 0.015e0.055 A 0.040e1.74 A

Mean ± SD** Young (n ¼ 4)

Aged (n ¼ 4)

3.2 ± 1.6 a <0.020 5.9 ± 2.3 a 0.11 ± 0.05 a 179 ± 66 a <0.001 0.019 ± 0.015 0.044 ± 0.007 0.9 ± 1.2 a 8±8a 1015 ± 337 a 79 ± 21 a 0.8 ± 0.6 a 57 ± 17 a 0.026 ± 0.019 117 ± 44 a 0.15 ± 0.06 a 410 ± 141 a 1.1 ± 0.5 a 0.037 ± 0.020 0.8 ± 0.6 a

5.5 ± 1.8 a <0.020 7.8 ± 0.8 a 0.11 ± 0.06 a 189 ± 33 a <0.001 0.013 ± 0.022 0.059 ± 0.003 0.3 ± 0.3 a 7.8 ± 2.5 a 1339 ± 329 a 95 ± 8 a 0.9 ± 0.3a 56 ± 12 a 0.028 ± 0.008 166 ± 28 a 0.110 ± 0.020 544 ± 80 a 1.03 ± 0.19 a 0.040 ± 0.008 1.0 ± 0.6 a

a b

a

a

a a

a a

a

* Different capital letter in the same row indicates statistical differences (p  0.05) among the three PDOs. ** Different lowercase letter in the same row, within each PDO, indicates statistical differences (p  0.05) between young and aged vinegars. *** Values below the LOQ (As, 0.020 mg/L; Cd 0.001 mg/L).

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P. Paneque et al. / Food Control xxx (2016) 1e8

exogenous sources of these metals, ageing in oak barrels may produce an increase in the vinegars' mineral content). Fe and Mn, other essential elements, showed mean contents which ranged from 1.2 to 19 mg/L, and from less than 0.1e0.2 mg/L, respectively, lower than mean values previously reported (Guerrero
n, 1988). According to these et al., 1996, 1997; Troncoso & Guzma authors, Fe contents exceeding 10e15 mg/L could be related to hazy phenomena in vinegars. In this case, vinegars, as it occurs in wines, could become turbid as a consequence of a ferric casse related to an
reau-Gayon, Glories, Maujean, & Dubourdieu, iron excess (Ribe 2006). In our study, 5 samples exceeded this range for Fe, 3 of them corresponded to aged vinegars. Despite this, none of the samples showed hazy phenomena. Because of their toxic effects, the heavy metals Cd and Pb and the metalloid As require special attention. The As and Cd contents found were lower than their LOQ (Table 2).; whereas the mean Pb content was 0.28 mg/L (ranging from 0.03 to 2.20 mg/L), lower than
n (1988), but higher than values reported by Troncoso and Guzma those of Turkish wine vinegars (Akpinar-Bayizit et al., 2010) and Iranian red and white wine vinegars (Saei-Dehkordi et al., 2012). Pb may present a real health hazard, affecting the nervous system and the biosynthesis of haemoglobin (reviewed in Pyrzynska, 2004). Because of this risk to health, there is a maximum Pb limit in vinegars (0.5 mg/L in Spain). Two vinegar samples out of 28 exceeded this value; one of them was an aged vinegar. Thus, special attention to the vinegars' initial Pb content, as well as their evolution during ageing, together with possible sources of Pb that could increase its content need to be taken into consideration. However, the daily intake of vinegar is very low; in the case of the vinegar with the highest Pb value (2.2 mg/L), and considering an average daily vinegar consumption of 5 mL (Da Silva et al., 2007), the daily Pb intake would be 11 mg. The EFSA Panel on Contaminants in the Food Chain's scientific opinion on lead in food (EFSA, 2010), identified developmental neurotoxicity in children and cardiovascular effects and nephrotoxicity in adults as the three critical effects for lead exposure risk assessment. Moreover, the EFSA pointed out that the daily exposure to the following amounts of Pb are associated with these adverse effects on health: for a child of 20 kg of weight, 10 mg/ day increases developmental neurotoxicity by 1%; for an adult of 60 kg of weight, 37.5 mg/day increases the effects on systolic blood pressure by 10% and 90 mg/day increases the effects on the prevalence of chronic kidney disease by 10%. Therefore, the amount of Pb of our samples does not pose a health problem, especially in the case of children, since consumption of this vinegar is usually lower than 5 mL due to its intense flavour. Finally, Al, B, Co, Cr, Ni, Sr and V were determined in Andalusian vinegars for the first time. Hence, references of their content do not exist in the related scientific literature and even, for some of them, in vinegars produced from other raw materials. Acosta et al. (1993) reported a mean Ni content of 0.21 mg/L in Spanish wine vinegars, whilst Akpinar-Bayizit et al. (2010) found mean values of 0.05 mg/L in marketed Turkish wine vinegars. Mean Ni content in MM vinegars was lower than that of Turkish vinegars, this value was higher in some J vinegar samples; while only one CH sample exceeded the mean value of 0.21 mg/L reported by Acosta et al. (1993) in Spanish vinegars. 3.2. Effect of geographical origin on the vinegars' mineral content 3.2.1. Andalusian PDO vinegars' geographical classification Although the multi-elemental profile of wines has already been used extensively as chemical descriptors for PDO classification, little information is available in relation to its discriminant power among wine vinegars from different geographical PDOs. Model building is extremely important because it allows us to establish,

5

one to one, a relationship between the chemical measurements obtained and complex concepts such as denomination of origin, ageing and type of processing (Benito et al., 1999). In order to assess the influence of the geographical origin upon the vinegar's mineral content, an ANOVA test was carried out. Results revealed significant statistical differences (p  0.05) for the elements B, Na, Sr and V (Table 3) among vinegars of some of the PDOs. CH samples achieved the highest Na content, whereas the lowest contents were observed in MM vinegars, significant differences existing between them. Higher Na content in CH samples could be attributed to the fact that these vinegars are produced in a geographical region where vines are exposed to a marine influence. A similar trend for Na content was observed in Andalusian oloroso wines from the same PDOs (Paneque et al., 2009). B and Sr are both “natural” elements that come from the vineyard soil (Volpe et al., 2009). MM vinegars achieved statistically significant higher B values than CH and J; and Sr content was higher in J vinegars, indicating differences between Jerez and the other two PDOs. Sr has been reported to be one of the most discriminating elements of wines in relation to their origin (Hopfer et al., 2015). Thus, Paneque et al. (2009) also reported statistically significant higher Sr content in Jerez oloroso wines than in CH and MM olorosos. Finally, the “artificial” element V (which originates from different materials used in wineries) differentiated CH vinegars from MM. Forward stepwise LDA was performed, taking the PDO vinegar (CH, J or MM) as the grouping variable. There were ten variables in the model, Sr, B, Na, Mg, P, Pb, Zn, Mn, Ba and Ca; two discriminant functions were obtained where the most important variables were Mg and Sr in the first function and B in the second. A good differentiation between the CH and J categories can be visualised according to function 1, whereas the MM category can be differentiated according to function 2 (Fig. 1). The percentage of correct classification or recognition ability (cases number (%) correctly classified in model calibration) was 100% for category J, and 90% and 87.5% for CH and MM, respectively. Total recognition ability was 92.86% (Table 4). In the external validation, prediction ability obtained (cases number (%) correctly classified in model validation) was 73.3%. When SVM was performed, 80% of the tests set samples were well classified. Accordingly, it seems that the vinegars' mineral content could be useful for PDO differentiation. 3.2.2. Effect of the geographical origin on young and aged vinegars An ANOVA test was performed on the young vinegars from different PDOs to explore significant differences among them and also on the aged vinegars for the same reason. Results for young vinegars indicated no significant differences between vinegars from J and MM. CA showed two main clusters: the first included young samples from J and MM, whereas all CH vinegars are included in the second cluster. In fact, CH vinegars showed significantly different lower B, Ca, K, Mg, S and Sr contents. This could be related to the existence of CH young, non-aged vinegars in the market, as explained later. A forward stepwise LDA was carried out considering only significant variables, obtaining 100% recognition ability; variables in the model were B, Ca, Pb and S. External validation results indicated a good discrimination among PDOs, with prediction ability of 80% in LDA; same result was achieved with SVM analysis. When considering aged vinegars, J samples presented significant differences to CH and MM with regard to Sr; while Al and V showed significant differences between MM-J and MM-CH, respectively. CA gave three clusters, in which samples from CH and J were mixed in the first two clusters, whereas MM samples, together with one sample from CH, were included in the third. Forward LDA sets out a total recognition ability of 80%, including

Please cite this article in press as: Paneque, P., et al., Elemental characterisation of Andalusian wine vinegars with protected designation of origin by ICP-OES and chemometric approach, Food Control (2016), http://dx.doi.org/10.1016/j.foodcont.2016.12.006

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5 4 3

Root 2

2 1 0 -1 -2 -3 -4 -5

-4

-3

-2

-1

0

1

2

3

4

5

CH J MM

Root 1 Fig. 1. Discriminant scatter plot of 28 vinegar samples of the three PDOs: Vinagres del Condado de Huelva (CH), Vinagres de Jerez (J) and Vinagres de Montilla-Moriles (MM).

Table 4 Classification of the samples in the PDOs (CH, J, MM) and recognition ability using forward LDA technique.

Condado de Huelva Jerez Montilla-Moriles Total

CH

J

MM

Recognition ability (%)

9 0 0 9

0 10 1 11

1 0 7 8

90.0% 100.0% 87.5% 92.86%

the variables Al, Sr and V in the model; the best recognition ability being for J vinegars (100%). External validation by LDA and SVM analysis gave 86.7% of correctly classified samples. These results point out a good discrimination among vinegars in relation to geographical origin regardless the ageing time.

3.3. Effect of ageing time on the vinegars' mineral content 3.3.1. Vinegars' classification according to ageing time Possible differences between samples with different ageing times, regardless of their geographical origin, were investigated. Fig. 2 represents mean element contents in young and aged vinegars. In most of the cases, the mineral content in aged vinegars was higher than that of young ones; there being statistically significant differences (p < 0.05) for elements Al, B, Cu, K, Mg, Pb, S, Sr and Zn. Ageing in oak barrels is accompanied by a gradual water loss by evaporation, implying an increase in dry extract content, mineral salts and ashes (Ministerio del Medio Ambiente, y Medio Rural y Marino, 2009a). Taking into account the variables Al, B, Cu, K, Mg, Pb, S, Sr and Zn (those which revealed statistical differences between both groups), the CA revealed two main clusters (Fig. 3) and a good differentiation between young and aged vinegars: 93.3% of the aged vinegars were grouped in the first cluster, and 84.6% of young samples were in the second one. Accordingly, it seems that these variables have sufficient explanatory power to detect different ageing time. When forward stepwise LDA was performed the variables in the model

were S, Al, Mn, Zn, Ca, K, Na and Fe. A total recognition ability of 92.86% was achieved (92.3 and 93.3% of the samples correctly classified into young and aged vinegars, respectively). Results obtained in external validation were 86.7% and 90% for test set in LDA and SVM, respectively.

3.3.2. Effect of the ageing time on the mineral content within each PDO ANOVA was performed to explore differences between young and aged vinegars within each PDO. Differences were observed between both types of samples (Table 3), with especially outstanding results obtained in CH vinegars. With regard to these samples, significant differences in a high number of elements (Al, B, Ca, Cu, Fe, K, Mg, Mn, Pb, S, Sr and Zn) were observed between young and aged vinegars. CA revealed two main clusters, each containing young or aged samples only. Significant differences between young and aged vinegars were only achieved for K and for Cr in J and MM vinegars, respectively. In both PDOs, sample aggrupation by CA according to ageing time was not clear. Best classification results were obtained when using SVM analysis. In the all the PDOs recognition ability was 100%. However, external validation indicated only a good classification between young and aged in the case of CH (100% well classified); whereas for J samples, total prediction ability was 66.7%, and only 33.33% for MM samples. It is clear, therefore, that CH vinegars presented a different behaviour to J and MM vinegars, with a clear differentiation between young and aged vinegars. This may be due to the different regulation for young vinegars in the CH PDO; young vinegars are allowed to be marketed without a minimum period of storage in wooden barrels. In the case, therefore, of young CH vinegars, the mineral concentration typical of aged vinegars due to water loss simply does not occur. This could explain why there are a greater number of elements that showed statistically different contents between young and aged vinegars, contrary to J and MM vinegars.

Please cite this article in press as: Paneque, P., et al., Elemental characterisation of Andalusian wine vinegars with protected designation of origin by ICP-OES and chemometric approach, Food Control (2016), http://dx.doi.org/10.1016/j.foodcont.2016.12.006

P. Paneque et al. / Food Control xxx (2016) 1e8

7

14

350

A

300

B

12 10

250

8

200

6

150

4

100

2

50

0

0 Ca

K

Mg

Na

P

-2

S

Al

B

Cu Young vinegars

Young vinegars

Fe

Sr

Zn

Aged vinegars

Aged vinegars 1

C

0.8 0.6 0.4 0.2 0 -0.2

Ba

Co

Cr

Mn

Ni

Pb

V

-0.4 -0.6 Young vinegars

Aged vinegars

Fig. 2. Mean element content and standard deviation (mg/L) in young (n ¼ 13) and aged (n ¼ 15) vinegars from the three PDOs. 2A: Ca, K, Mg, Na, P and S. 2B: Al, B, Cu, Fe, Sr and Zn. 2C: Ba, Co, Cr, Mn, Ni, Pb and V. Striped bars (K, S and Mn) indicate values divided by ten.

70

60

Linkage Distance

50

40

30

20

10

0

A A A A A A A A Y A Y A A A A A A Y Y Y Y Y Y Y Y Y Y Y

Fig. 3. Dendrogram of cluster analysis of vinegar samples from Andalusian PDOs according to ageing time: Y: young vinegars; A: aged vinegars. (Only statistically significant different variables were considered).

4. Conclusions The nineteen elements quantified in wine vinegars from Andalusian PDOs showed a wide variation in their contents. Only 2 vinegars samples exceeded the maximum Pb (a toxic heavy metal) content (0.5 mg/L). However, according to the EFSA, and taking into account the low daily consumption of wine vinegar,

the amount of Pb consumed via these vinegars would not cause adverse effects on health. The highest Sr and B contents were obtained in J and MM samples, respectively, these differences being statistically significant. These elements occur naturally in the soil from the weathering of their parent rocks and their presence in wine vinegars is due to uptake by the vines.

Please cite this article in press as: Paneque, P., et al., Elemental characterisation of Andalusian wine vinegars with protected designation of origin by ICP-OES and chemometric approach, Food Control (2016), http://dx.doi.org/10.1016/j.foodcont.2016.12.006

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For vinegar sample classification according to geographical origin, the mineral composition could be a suitable tool. Finally, the ageing time has been shown to influence the mineral composition, with higher mineral content in aged vinegars compared to young ones. Furthermore, differences with respect to the vinegars' provenance are observed regardless the ageing time. Acknowledgements We express our gratitude to the Denominations of Origins'
n (IRNAS-CSIC) for providing Consejos Reguladores and to E. Madejo the facilities for ICP-OES analysis. This work was supported by the
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Please cite this article in press as: Paneque, P., et al., Elemental characterisation of Andalusian wine vinegars with protected designation of origin by ICP-OES and chemometric approach, Food Control (2016), http://dx.doi.org/10.1016/j.foodcont.2016.12.006