1 Geographical Traceability of Virgin Olive Oils from South-Western 2 Spain by Their Multi-Elemental Composition 3 4 María Beltrán1, María Sánchez-Astudillo1, Ramón Aparicio2*, Diego L. García-González2 5 6 1 Department of Chemistry and Science of Materials, Faculty of Experimental Sciences, 7 8 University of Huelva, Avda. Tres de Marzo S/N. 21071, Huelva, Spain 2 Instituto de la Grasa (CSIC), Padre García Tejero 4, 41012, Sevilla, Spain 9 10 11 12 13 14 15 16 17 *Author to whom correspondence should be sent. 18 E-mail: aparicio@cica.es; Tel: +34 954 61 15 50; Fax: +34 954 61 67 90 19 1 20 21 ABSTRACT 22 The geographical traceability of virgin olive oil can be controlled by chemical species 23 that are linked to the production area. Trace elements are among these species. The hypothesis 24 is that the transfer of elements from the soil to the oil is subjected to minor variations and 25 therefore this chemical information can be used for geographical traceability. In order to 26 confirm this hypothesis, the trace elements of virgin olive oils from south-western Spain were 27 analyzed, and the same elements were determined in the corresponding olive-pomaces and 28 soils. The differences in the concentration were studied according to cultivars and locations. 29 Results show some coincidences in the selection of elements in soils (W, Fe, Na), olive- 30 pomace (W, Fe, Na, Mg, Mn, Ca, Ba, Li) and olive oils (W, Fe, Mg, Mn, Ca, Ba, Li, Bi), 31 which supports their utility in traceability. In the case of olive oils, 93% of the samples were 32 correctly classified in their geographical origins (96% for Beas, 77% for Gibraleón, 91% for 33 Niebla, and 100% for Sanlúcar de Guadiana). 34 35 Keywords: Virgin olive oil, Geographical traceability, Trace elements, Inductively coupled 36 plasma-mass spectrometry 37 2 38 39 1. Introduction 40 The quantitative determination of trace elements in foodstuffs has always been a 41 challenge in analytical chemistry since they have evident nutritional (Boufleur, Dos Santos, 42 Debastiani, Yoneama, Amaral & Dias, 2013), safety (Zand, Chowdhry, Wray, Pullen & 43 Snowden, 2012) and quality implications (Benedet & Shibamoto, 2008). Although there is 44 extensive literature concerning the analysis of other materials, such as some lubricants and 45 fuels (Maryutina & Soin, 2009), the information concerning food analysis is relatively scarce. 46 In regards to edible oils, elemental analysis has received little attention so far and, on the 47 contrary, other major (e.g. fatty acids) or minor components (e.g. sterols) has been the targets 48 of the analytical effort in the last decades for solving authenticity/quality issues. However, it 49 is a well-known fact that certain metallic contaminants (e.g. Cu and Fe) speed up the 50 oxidation processes of edible oils thereby having a negative effect on their sensory quality 51 (Benedet & Shibamoto, 2008). The unimpeachable importance of metals in olive oil stability 52 explains that the International Olive Council (IOC) established concentration limits of Cu and 53 Fe, and also contaminants such as Pb and As, in olive and olive-pomace oils (IOC, 2013). 54 Other elements (e.g. Ca, Mg, Mn) are also present in a wide concentration range in olive oils 55 (Benincasa, Lewis, Perri, Sindona & Tagarelli, 2007). Other elements can be found and they 56 might be transfer into the oil from the metallic surfaces of the processing equipment or 57 storage material. They might be also incorporated into de oil from the soil although their 58 concentrations are modulated by biochemical pathways of each cultivar (Chatzistathis, 59 Therios & Alifragis, 2009). 60 As olive trees are closely linked to land, the importance of the chemical species 61 coming into virgin olive oils (VOOs) from the soil is taking on special relevance day by day, 62 as it is the case of elements. The importance of the elements lies in their potential use in 63 geographical traceability, in particular in the characterization of protected designations of 64 origin (PDOs) or protected geographical indications (PGIs) (EU, 2012), and they can also 3 65 contribute to determine VOO geographical provenance of non PDO oils. Thus, a complete 66 element characterization may back up a hypothetical warfare against illicit practices as 67 consequence of the financial benefits associated with these prestigious labels. Thus, a non- 68 PDO product may be labelled as a PDO one and also it may be adulterated with olive oils that 69 do not fulfil the PDO/PGI requirements. The use of elemental analysis for detecting these 70 frauds can be an alternative to other approaches to tackle VOO geographical traceability 71 based on chromatographic, spectroscopic, isotopic, and in-tandem analytical techniques, 72 (Alonso-Salces et al. 2010; Aparicio, 1988; Benincasa, Lewis, Perri, Sindona & Tagarelli 73 2007; Camin et al., 2010a; García-González, Tena & Aparicio, 2011; Woodcock, Downey, 74 O’Donnell, 2008). 75 The needs of characterizing the trace elements of olive oil, and other edible oils, has 76 led researcher to optimize methodologies with the most sensitive techniques. Thus, edible oils 77 have been analysed for different elements using potentiometry (Dugo, La Pera, La Torre & 78 Giuffrida, 2004), inductively coupled plasma atomic emission spectrometry (ICP-AES) 79 (Zeiner, Steffan & Cindric, 2005), electrothermal vaporization inductively coupled plasma 80 mass spectrometry (Huang & Jiang, 2001) and mostly atomic absorption spectrometry (AAS) 81 (Mendil, Uluözlü, Tüzen & Soylak, 2009), which is included in some official methods (IOC 82 2011; Codex Alimentarius, 2009). Since some elements are present at very low concentration, 83 the inductively coupled plasma-mass spectrometry (ICP-MS) is the most suitable tool because 84 of its low detection limits, multi-elemental capacity and wide linear range that result of 85 combining the remarkable characteristics of ICP for atomising and ionising samples with the 86 sensitivity and selectivity of mass spectrometry (Castillo et al., 1999). Thus, the number of 87 papers dealing with the analysis of organic samples by ICP-MS has increased in recent years, 88 particularly in the analysis of olive oil (Benincasa et al., 2007; Jiménez, Velarte, Gomez & 89 Castillo, 2004; Llorent-Martínez, Ortega-Barrales, Fernández-de Córdova, Domínguez-Vidal 4 90 & Ruiz-Medina, 2011a; Llorent-Martínez, Ortega-Barrales, Fernández-de Córdova & Ruiz- 91 Medina, 2011b). 92 In this paper, we analyse the availability of elements, determined by ICP-MS, for 93 implementing a reliable method of geographical traceability of olive oils . As elements can 94 come from other sources than soil, samples of soils, wet olive-pomaces (“alperujo”) (WOP) 95 and virgin olive oils from diverse geographical places have been analyzed. The presence and 96 concentration of some elements in VOOs and WOPs in comparison with the results of 97 analysing the soils of the orchards will help to understand the usefulness of this technique for 98 explaining the olive oil geographic provenance, and hence for protecting virgin olive oils 99 from PDOs and PGIs against false copies. A geographical zone of Southern Spain was 100 selected for its diversity of cultivars that are cultivated in modern irrigated orchards with 101 different characteristics of soils. 102 103 2. Materials and Methods 104 2.1. Samples 105 Table 1 summarizes the number of samples of virgin olive oils (VOOs) and olive- 106 pomaces according to cultivars (var. Arbequina, Picual and Verdial de Huévar) and their 107 geographical provenances in terms of the municipalities of the Huelva province, and the 108 samples of the orchards of those municipalities where olive trees are cultivated. 109 Seventeen orchards of olive trees located in four municipalities of the Southern 110 Spanish province of Huelva - Beas (3), Gibraleón (2), Niebla (8), and Sanlúcar de Guadiana 111 (4) - were selected because cultivars are harvested in orchards with diverse soil characteristics 112 (REDIAM, 2013). Soil samples (40) were collected in each orchard at two depths, 30 cm and 113 60 cm, because the depth of the roots can vary among the olive trees of cultivars and also in 114 order to study the possible variability of the element concentrations with the depth. The 115 number of samples per orchard is two (one per depth) with the exception of the orchards 5 116 located at Beas as their size are larger and their soil compositions are very diverse in 117 comparison with the orchards of the other municipalities (REDIM, 2013). The orchards can 118 have more than one cultivar depending on the orchard size and its geographical location. 119 The samples of VOOs and olive-pomaces were 82, which can be clustered in terms of 120 cultivars (40 for Arbequina, 29 for Picual and 13 for Verdial de Huévar) or geographical 121 provenance (28 from Beas, 14 from Gibraleón, 21 from Niebla and 19 from Sanlúcar de 122 Guadiana). 123 Olives were harvested by mechanical means at the same step of ripeness, according to 124 the classification of Hermoso, Uceda, García, Morales, Frías and Fernández (1991). All the 125 olive oils were processed by two-phase centrifugation systems in cooperative societies of 126 farmers under similar conditions of milling and malaxation. The resulting products of this 127 extraction system were VOO and olive-pomace (“alperujo”). The latter is a by-product that 128 consists of vegetation water and solids (stone and pulp of the olives) and a small percentage 129 of olive oil. 130 2.2. Sample preparation and digestion 131 Virgin olive oils and olive-pomaces (“alperujo”) resulting of processing olives 132 from the different orchards as well as samples from their soils were prepared for digestion. 133 The number of elements quantified in the samples were 34 although some of them were not 134 detected (e.g., Strontium) or at trace level in the samples of VOOs and olive-pomaces. The 135 samples were digested in an Anton Paar (multiwave 3000 SOLV) oven with programmable 136 power control (10 W increments, maximum power 1000 W) with segmented rotor XQ80 (35 137 bar of maximum operating pressure and 260 ºC of maximum operating temperature). 138 139 2.2.1. Olive oil samples 140 Microwave-assisted acid decomposition was performed to dissolve the oil sample for 141 elemental analysis. The digestion was carried out with 0.5 g aliquot of sample, weighed 6 142 directly into the digestion vessel, to which were added 5 mL of nitric acid at 65% v/v, 3 mL 143 of hydrogen peroxide at 30% v/v, and 1 mL of hydrochloric acid (Sigma-Aldrich, Madrid, 144 Spain) (Acar, 2012). The microwave operation parameters of the Anton Paar oven were firstly 145 a ramp of 15 minutes to reach 280 ºC and 80 bar that was maintained for 20 minutes with 146 minimum level of ventilation, and later, the samples were vented for 15 minutes. 147 After digestion, samples were stored at 25 ºC for 12 h and finally, all the digestion 148 liquors were diluted to 25 mL with ultrapure water (Llorent-Martínez et al., 2011a). Samples 149 were thoroughly shaken prior to analysis by ICP-MS. 150 151 2.2.2. Olive-pomace samples 152 The olive-pomace (alperujo) samples were frozen and lyophilized in a laboratory 153 freeze-dryer Cryodos 80 (Telstar, Tarrasa, Spain) at -80 ºC. Two subsequent digestions were 154 performed to dissolve the freeze-dried alperujo for elemental analysis. The first digestion was 155 carried out as follows: 5 mL of nitric acid at 65%, 1 mL of hydrogen peroxide at 30%, 1mL of 156 hydrofluoric acid at 40% and 1 mL of hydrochloric acid at 30% were added to 0.20 g of 157 lyophilized alperujo. An Anton Paar Microwave-Assisted oven was used under the condition 158 described for olive oil with a ramp of 12 min to reach 210ºC and 40 bar, and this conditions 159 were maintained for 20 min. 160 The second digestion was carried out as follows: 6 mL of boric acid were added to the 161 residue of the previous digestion. The program of microwave operation parameters were a 162 ramp of 5 minutes to reach 210ºC and 40 bar and these conditions were maintained during 15 163 minutes with a minimum level of ventilation, and then the sample was vented for 15 minutes. 164 After digestion, samples were stored at 25ºC for 12 h and finally, the residues were diluted in 165 25 ml with ultrapure water. 166 167 7 168 2.2.3. Soil samples 169 The method described by De la Rosa et al. was applied for the digestion of soil 170 samples (De la Rosa, Chacón, Sánchez de la Campa, Carrasco & Nieto, 2001). The soil 171 samples, previously frozen, were grounded many cycles in a special vibrating mill using 172 titanium rods under cryogenic conditions. An aliquot of 0.1 g of each sample was placed into 173 a 60 mL PTFE/PFA bomb (Savillex, Eden Prairie, MN) where 8 mL of hydrofluoric acid 174 (HF) and 3 mL of nitric acid were added. The mixture was heated at 90 ºC in the closed bomb 175 for 24 h. Soil samples were homogenized in the titanium mill and a complete digestion with 176 HF would release more titanium and zirconium in to the digest which could affect the 177 determination of copper and cadmium by ICP-MS through the formation of oxide ions. Bomb 178 was opened for the evaporation of acids, and the mixture was heated at 130º C. Then, 3 mL of 179 nitric acid were added, the bomb was closed and the mixture was heated at 90º C for 12 h. 180 Then the acids were re-evaporated and 3 mL of hydrochloric acid were added, the bomb was 181 closed and the mixture was heated at 90º C for 12 h. The residue was recovered with nitric 182 acid at 2 % into a 100 mL volumetric flask once total dryness was achieved. 183 184 In all samples (soils, olive-pomaces, virgin olive oils) Rh (103) was added as internal standard in a 5 μg/L concentration. 185 186 2.3. ICP-MS Analyses 187 The concentration of 34 elements (Table 2) were determined by a quadrupole 188 inductively coupled plasma mass spectrometer (ICP-MS) (Agilent 7700X Model G3281A, 189 Agilent Technologies, CA, USA) working under the following operating conditions: RF 190 power, 1.5kW; plasma Ar flow rate, 15 L/min; auxiliary Ar flow rate, 0.9 L/min; carrier Ar 191 flow rate, 1.1 L/min; sample depth, 9.0 mm; spray interface temp. 2 ºC; sample flow rate, 400 192 μL/min. The sampler and skimmer cones were of nickel. The instrument was run under a 193 linear multipoint calibration 1-200 μg/L. Analyses were carried in duplicate. 8 194 Glassware was not used to avoid metal releases and all the plastic containers, like 195 PFA Teflon digestion vessels, were checked for contamination. Vessels were cleaned using 196 the same microwave operating program for digestion but adding 7 mL HNO3 to each 197 digestion vessel after each analytical batch. Later, all the vessels were thoroughly rinsed with 198 Milli-Q water. Ultrapure deionised water was obtained from Milli-Q system (Millipore, 199 Bedford, MA). 200 201 2.4 Calibration procedure 202 The calibration standard solution was prepared from a multi-element standard solution 203 (SCP Science, Paris, France) by dilution with HNO3 in ultrapure water (Llorent-Martínez et 204 al., 2010b). For the quantitative analysis of oils calibration curves were built at five different 205 concentrations (Benincasa et al., 2007). The concentration range was 0.2-60 ng/mL for all the 206 elements excepting Ba, Ca, Sr, V, Zr, which were calibrated in a wider concentration range 207 (10-200 ng/mL). The recoveries were determined by analysing spike solutions (Boqué, 208 Maroto, Riu & Rius, 2002), and the values were within the range 78-218%, being 50% of 209 them in the range 90-110%. These recoveries were inside the range described by other authors 210 (Arunachalam, Mohl, Ostapczuk & Emons, 1995; Benincasa et al., 2007; Llorent et al., 211 2011a-b). 212 213 2.5 Data analysis 214 The data matrix (elements × samples) was analyzed by uni and multi-variate 215 mathematical procedures. Brown-Forsythe test (Brown & Forsythe, 1974) was used to 216 determine homogeneity of the variances and to select variables (elements) with univariate 217 discriminate ability. Stepwise linear discriminant analysis (SLDA), a supervised statistical 218 procedure, was applied under the strictest conditions (F-to-Enter ≥ 4.0). Principal Component 219 Analysis (PCA), an unsupervised statistical procedure, was used as it allows reducing the 9 220 dimensionality of the original data by means of equations (principal components) that are 221 linear combination of the elements and encapsulate their variability. All statistical data 222 treatments were performed by Statistica 6.0 (StatSoft, Tulsa, OK). 223 224 3. Results and discussion 225 The trace elements that are incorporated to the olive tree from the soil are partially 226 transferred to the olives (Bakircioglu, Kurtulus & Yurtsever, 2013). In consequence, trace 227 elements are determined in olive oil and/or olive-pomace samples, the only two materials 228 resulting of processing the olives. The province of Huelva (Southern Spain) is an excellent 229 geographical zone to study the importance of the soil composition in geographical traceability 230 because it provides different cultivars planted in the same land. The orchards of var. Verdial 231 de Huévar, which meant more than 90% of the whole production only a few years ago, have 232 gradually been substituted by var. Arbequina and Picual cultivated in irrigated intensive 233 plantations. Thus, in this area it is possible to analyze the concentration of elements in olive 234 oil and olive-pomace of several cultivars with respect to their availability in the soils. 235 As the root depth in olive trees varies in accordance with the soil characteristics and 236 the olive tree age (Fernández, Moreno, Cabrera, Arrue & Martín-Aranda, 1991), the soil 237 samples were collected at 30 cm and 60 cm depth because the plantations are in its juvenile 238 step –with the exception of var. Verdial de Huévar – and the tree roots were estimated to be 239 around 40-50 cm depth. Table 2 shows the mean and standard deviation of the concentrations 240 of 34 elements at those two depths. The half of them was quantified at concentrations higher 241 than 10 mg/kg. In regards to elements quantified at low concentrations, it is remarkable the 242 low concentrations of Mn that were lower than 1 mg/kg in all cases. 243 The concentrations of eighteen elements are higher in the samples of soils collected at 244 60 cm depth (Table 2) (p<0.05) while thirteen of them (As, Ga, Hf, Mn, Na, Nb, Pb, Sc, Th, 245 Ti, U, Y, Zn) do not show any significant difference (p<0.05) between the two depths after 10 246 applying the Brown-Forsythe test. Only three elements (Cu, Sn, Mo) are in higher 247 concentrations in the samples collected at 30 cm. The accumulation of copper in the soils 248 might be as consequence of the extensive application of fungicides composed of a mixture of 249 copper (II) sulphate (CuSO4) and calcium hydroxide (Ca(OH)2) (e.g. Bordeaux mixture). 250 The availability of elements being incorporating into the olive trees varies from an 251 orchard to another, and this variability support the hypothesis that trace elements can be use to 252 determine the geographical provenance of virgin olive oil. In order to confirm this hypothesis, 253 the differences in element composition between the soils of the four selected zones (Beas, 254 Gibraleón, Niebla and Sanlúcar de Guadiana) need to be checked. Thus, the first statistical 255 study of the soil samples was focused on the analysis of the possible differences in the 256 concentration of the trace elements in these zones. 257 Table 3 shows the concentrations of the 34 elements in the four selected zones (mean 258 and standard deviation) although not all of them were selected for showing differences in their 259 concentrations when applying Brown-Forsythe test. The data indicated that, in general terms, 260 the highest concentrations of the elements were determined in the samples from Beas 261 followed by Sanlúcar de Guadiana, which is far from the other three regions. The use of 262 Brown-Forsythe test indicated that five (Mg, Na, Sc, Ta, U) had a p-value>0.05 for the 263 simultaneous characterisation of the samples from the four geographical locations. Other 264 elements were able to distinguish two or three geographical origins simultaneously (e.g. Ba, 265 Cs, Cr, Ga, Hf, Fe, K, W). Fig. 1 shows that only three elements - Fe, Na and W – were able 266 to distinguish the soils -including the two depths- from the four locations by applying LDA. 267 Most of the variance was explained by the first canonical equation (81%). An overlap 268 between the samples collected in the orchards of Beas and Gibraleón was observed. These 269 two municipalities are adjacent to each other, which explains that some classification 270 problems may arise when distinguishing those samples. The differences are much clearer 271 when the other elements selected by the Brown-Forsythe test are taken into account. Thus, the 11 272 concentrations of Ba, Fe, K, Na, Ta and W can distinguish the soils from the four 273 geographical origins whichever the depth of the samples collected. 274 As the olive trees would get the elements from the soil, it is expected that the olive-pomaces 275 resulting from extracting olive oils contain the elements present in soils but in lower 276 concentrations. In this regards, the hypothesis is that the olive oil production is simple enough 277 for not altering in great extent the concentration of the remaining paste. The olive-pomace or 278 “alperujo” is the byproduct resulted from virgin olive oil production. Virgin olive oil is 279 obtained solely from the fruit of the olive tree (Olea europaea L.) in a process that begins by 280 milling the olives , and is followed by stirring the olive paste, and separating the oil from the 281 vegetable matter and the water by direct continuous centrifugation and dual decanters 282 (Vossen, 2013). Once the oil is separated, the remaining paste -olive-pomace- contains a 283 small quantity of oil (2-6%), and it is expected that some elements also remains in this paste. 284 Table 3 confirms that the elements quantified in the olive-pomaces are those quantified in the 285 soils but at lower concentrations, with some exceptions. Some of these exceptions can be 286 explained by the composition of the foliar fertilizers, which are widely used in the olive 287 orchards. The chemical composition of the foliar fertilizers contains K, Fe, Mg, Mn, P and Zn 288 in different proportions, together with other elements (i.e. B, Ca), which can be presented 289 complexed with amino acids such in the cases of Ca, Fe, Mg, Mn and Zn (Barranco, Ercan, 290 Muñoz-Díez, Belaj & Arquero, 2010). It might explain the higher concentration of K and Mg, 291 while the high concentration of Cu might be due to the use of copper fungicides (Soares, 292 Pereira & Bastos, 2006). The use of foliar vs. soil fertilizers and also copper fungicides 293 depends on the cultivar and the level of expertise of farmers (Sistani, Ramezanpour & 294 Nasrollanejad, 2009) as detected when analyzed the concentration of these elements from the 295 different olive groves studied in this work. We have not found, however, plausible 296 explanations for the high concentration of Sc in all the olive-pomace samples, and of Cr in 297 almost all the olive-pomace extracted in the groves of Niebla and Sanlúcar de Guadiana. 12 298 The first study of olive-pomace samples was centered on the influence of the cultivars 299 (Arbequina, Picual and Verdial de Huévar) in the concentrations of the elements. The analysis 300 of the cultivars of each location independently showed that four elements (Ba, Cu, Rb and Zn) 301 are enough to distinguish them with no misclassification. The concentration of Cu was higher 302 in Arbequina, whichever the geographical origin of the olive-pomaces, so pointing out that 303 this cultivar was much more protected against diseases by means of fungicides based on 304 copper than the other cultivars. Thus, the mean concentration of Cu in Arbequina was double 305 than in Picual and five times than in Verdial de Huévar. Table 4 points out that Arbequina 306 cultivar was much more efficient obtaining elements from soils than Picual in all the 307 locations. The higher percentages of Zn for cultivar Arbequina was also remarkable and can 308 be explained by the use of fertilizers that help in increasing the olive production. Some of the 309 olive trees cv. Arberquina were planted in intensive/super intensive mode, which requires 310 more amounts of fertilizers and fungicides (Beaufoy, 2002). 311 312 No explanation has been found for the highest percentages of Rubidium determined in the Arbequina olive-pomace from orchards situated in Niebla and Sanlúcar de Guadiana. 313 The determination of the geographical origin of olive-pomaces, whichever their 314 cultivar is more complex than analysing the soils. Thus, eight elements (W, Mg, Mn, Ca, Fe, 315 Ba, Li and Na) were used by SLDA up to reach a full classification with three canonical 316 equations. Fig. 2 shows the results with first two canonical equations. Three of the selected 317 elements (W, Fe and Na) were already used for classifying soils (Fig. 1). 318 Ideally, any traceability system based on chemical compounds should be based in 319 determinations in the olive oils, which origin sometimes is unknown or need to be confirmed. 320 The main objective of traceability is to determine the geographical provenance of olive oils by 321 the analysis of their chemical composition, elements in our case. Following the same 322 procedure applied for olive-pomace, the differences in the concentration of elements 323 determined in olive oils from different cultivars were analyzed. Grubbs test (Grubbs, 1969) 13 324 pointed out that six samples were outliers and they were removed. Table 3 shows the 325 concentrations of the elements determined in virgin olive oils clustered by the geographical 326 origins. The concentration of the elements agrees with values of some of them previously 327 published by other authors (Camin et al., 2010b; Benincasa et al., 2007; Llorent-Martínez et 328 al., 2011b). Furthermore, in order to check the safety of VOOs obtained for this study, the 329 maximum concentrations of the elements, which are cited in the EC Regulation (EU, 2006) 330 and IOC trade standards (IOC, 2013), are lower than the maxima admitted for edible oils in 331 those regulations (0.10 mg/kg for As, Cu and Pb; 3.0 mg/kg for Fe; and 50 mg/kg for Sn). 332 The analysis of the cultivars (Arbequina, Picual and Verdial de Huévar) of each zone 333 independently showed that the elements selected for characterizing olive oils by their cultivars 334 were K, Cu, Fe, Mg. Some elements, such as Cu or K, could be directly related with the 335 fertilizer and fungicides applied to the olive trees (Soares et al., 2006). As showed in the 336 olive-pomaces (Table 4), the concentration of the elements more related with external 337 addition of agricultural products (K and Cu) is higher in Arbequina, whichever the 338 geographical origin. Thus, the ratios of concentrations for Arbequina to those for Picual were 339 higher than 1 in all cases for K, Cu, Fe, Mg, with an average ratio of 2.28 (standard deviation, 340 1.36). 341 If the classification of the olive-pomaces in accordance with their geographical 342 provenance required more elements than classifying the soils of the orchards, the study of the 343 olive oils needed even more elements to obtain classification rates higher than 90%. Seven of 344 the elements selected for the classification of olive oils (W, Mg, Mn, Li, Fe, Ca, Ba) were 345 already selected in the study of olive-pomace although SLDA procedure needed to add two 346 more (Bi and Cu) to arrive a total correct classification of 93% of the analyzed samples (96% 347 for Beas, 77% for Gibraleón, 91% for Niebla, and 100% for Sanlúcar de Guadiana). The 348 results are not as good as those showed working with soils and olive-pomace where no 349 misclassifications were observed. In the case of olive oils, the classification rate was lower 14 350 probably due to the very low concentrations of elements in olive oils that may cause 351 sensitivity problems. Fig. 3 shows the SLDA result, which points out that the classification 352 was not influenced by the cultivars of the orchards despite the selection of Cu, K and Mg. 353 354 4. Conclusions 355 The coincidence in the selection of the elements for classifying soils (W, Fe, Na), 356 olive-pomace (W, Fe, Na, Mg, Mn, Ca, Ba, Li) and olive oils (W, Fe, Mg, Mn, Ca, Ba, Li, Bi) 357 in accordance with the geographical provenance indicates that some elements present in the 358 soils of the orchards might also be detected in the olives and olive oils from the olive trees 359 planted there, though at very lower concentrations. In conclusion, the analysis of elements by 360 ICP-MS might be a good technique for performing the backward traceability of olive oils. 361 Further studies are required to gain in knowledge about to what extent the natural 362 concentration of some elements can be modified by the use of fertilizers (with either foliar or 363 soil application) and fungicides prior to normalizing the methodology and its proposal as a 364 possible standard for olive oil traceability in future. 365 366 367 Acknowledgements 368 369 370 Authors would like to express gratitude to Andalusian Government (Project FQM6185) and European Union (Project 0042_I2TEP_5_E) for funding support. 371 15 372 References 373 374 Alonso-Salces, R.M., Héberger, J., Holland, M.V., Moreno-Rojas, J.M., Mariani, C., Bellan, 375 G., Reniero, F. & Guillou, C. (2010). Multivariate analysis of NMR fingerprint of the 376 unsaponifiable fraction of virgin olive oils for authentication purposes. 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Applying linear discriminant analysis (LDA) to the concentration of three elements 493 (Fe, Na and W) determined in the soils of orchards collected at two depths (30 cm and 60 cm) 494 from four geographical origins (Beas, Gibraleón, Niebla and Sanlúcar de Guadiana). 495 496 Fig. 2. Applying linear discriminant analysis (LDA) to the concentration of eight elements 497 (Fe, Na, W, Mg, Mn, Ca, Li, Ba) determined in the olive-pomace of cultivars (Arbequina, 498 Picual and Verdial de Huévar) from four geographical origins (Beas, Gibraleón, Niebla and 499 Sanlúcar de Guadiana). 500 501 Fig. 3. Applying linear discriminant analysis (LDA) to the concentration of eight elements 502 (Ba, Bi, Ca, Cu, Fe, Li, Mg, Mn, Sn, W) determined in the olive oils of var. Arbequina, Picual 503 and Verdial de Huévar from four geographical origins (Beas, Gibraleón, Niebla and Sanlúcar 504 de Guadiana). 505 21