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ISSN: 2155-9600
Journal of Nutrition & Food Sciences
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Preliminary Results on the Influence of Carbonic Snow Addition during the Olive Processing: Oil Extraction Yield and Elemental Profile

Zoani C1, Zappa G1, Venturi F2*, Sanmartin C2 and Zinnai A2

1ENEA-Italian National Agency for New Technologies, Energy and Sustainable Economic Development - Technical Unit for Sustainable Development and Innovation of Agro- Industrial System (UTAGRI), Casaccia Research Centre - Via Anguillarese, 301- 00123 Roma, Italy

2University of Pisa – Department of Agriculture, Food and Environment (DAFE) - Via del Borghetto 80 - 56124 Pisa, Italy

*Corresponding Author:
Francesca Venturi
DAFE – University of Pisa, Italy
Tel: +39 0502216632
Fax: +39 0502216636
E-mail: [email protected]

Received Date: April 16, 2014; Accepted Date: May 28, 2014; Published Date: May 30, 2014

Citation: Zoani C, Zappa G, Venturi F, Sanmartin C, Zinnai A (2014) Preliminary Results on the Influence of Carbonic Snow Addition during the Olive Processing: Oil Extraction Yield and Elemental Profile. J Nutr Food Sci 4: 277. doi: 10.4172/2155-9600.1000277

Copyright: © 2014 Zoani C, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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Abstract

The compositional profile of olive oil is strictly connected to the raw material characteristics, nevertheless technological processes utilized to extract the oil fraction can deeply impact on its final chemical composition. Trace quantities of elements are naturally present in olive oil. To make objective and measurable food quality and traceability, it is necessary to develop analytical methods useful to detect contaminants potentially coming from any phases of the supply chain and define characteristic markers and patterns for the authenticity verification and origin demonstration. The objective of the paper is twofold: a) to verify the influence of the addition of cryogen (CO2,s), directly to olives during pre-milling phase, on the yield of the oil production; b) to develop specific analytical methods for evaluating the elemental profile of olive oil and to collect some preliminary data about the possibility to use these methods in order to put in evidence the possible influence of different process conditions on the olive oil elemental profile. The experimental evidences show as the addition of cryogen directly to the olives during pre-milling phase seem induce a general increase in the oil extraction yield, ranging from 2 to 12,4%. While preliminary results show a rather homogeneous elemental content among all the analyzed samples of olive oil, samples of olive oil obtained by the “traditional” process showed - in general - a higher content of Ca, Cr, Mg, Si and Zn, compared to those obtained by the addition of “carbonic snow”. The analytical methods for evaluating the olive oil elemental profile by ICP-AES and ICP-MS were set up and the methodologies for data processing and statistical analysis were developed, so they could be applied during the next crop season to study in depth the influence of different process conditions on the olive oil elemental profile.

Keywords

Olive oil; Cryogen; Elemental profile; Oil extraction yield

Introduction

Olive oil is a premium vegetable oil highly appreciated and consumed [1]. It constitutes the main lipid source in the Mediterranean diet due to its sensory and healthy properties [2]. The compositional profile of olive oil is strictly connected to the raw material characteristics but the operative conditions adopted to extract the oil fraction can deeply impact on its final chemical composition [3]. Several studies have pointed out the importance of the different virgin olive oil processing stages on the extraction yield as well as the minor composition found in the final product. The technological operations that most affect the composition and quality of oil during the manufacturing process are crushing and malaxation [4].

Although the public demand for adequate and sustainable quantities of good-quality food throughout the food chain stimulated the study and application of promising new and emerging food technologies [5], the entire virgin olive oil (VOO) process has changed very little over the last twenty years [1]. With the aim to contribute to advance in VOO technology, at DAFE of University of Pisa, an innovative VOO extraction technology (Patent n° RM2010A000617) involving the addition of a cryogen (solid CO2) to the olives [6] were developed, in order to increase the extraction yield and to obtain an oil characterized by higher concentration of phenolic compounds and a stronger link with the raw material and its production area [7].

As a function of the temperature adopted, at atmospheric pressure carbon dioxide (CO2) can be present only in a solid (CO2,S = carbonic snow; T < -78,5°C) and/or in a gaseous state (T > -78,5°C) [8]. The pre-milling addition of solid carbon dioxide CO2,s (carbonic snow) to the olives, causes a partial solidification of endocellular water as a consequence of the direct contact between the cryogen (carbonic snow) and the olives. Because of the volume occupied by the same amount of water in the solid state is greater than that in the liquid phase, a corresponding increase of endocellular volume occurs and the consequent laceration of cellular membranes (cellular crash) promotes the immediate diffusion in the liquid phase of many cellular compounds like phenols and oil. In this way, it could be possible to obtain extra virgin olive oils characterized by a greater amount of metabolic compounds deriving from the olives even because the relevant amount of gas (gaseous CO2,G), which evolves during the direct contact between olives and cryogen, decreases the amount of atmospheric oxygen diffused in the liquid phase and than inhibits the possible oxidation of the phenolic substances.

To verify if there are compositional differences between the cryomacerated oils and the traditional ones which make it possible to ensure the traceability and safety of these new products, it’s important to develop analytical methods useful for protecting producer and consumers’ interests [9,10]. Suitable traceability systems are needed to document the history of a product along the entire supply chain (from primary production to the final use), to protect high quality productions from frauds and sophistications and contain health safety risks [11-13].

Trace quantities of elements are naturally present in olive oil. Natural composition of olive fruit, natural contamination from soil, use of fertilizers, industrial applications or highways near the plantations are the main sources of toxic or potentially toxic elements in olive oils. Contamination can also occurs during the production process and contact with storage materials.

In this context, the objective of the paper is twofold:

a) The first goal was to verify the influence of the addition of cryogen (CO2,s), directly to olives during pre-milling phase, on the yield of the oil production, in order to obtain a preliminary evaluation of the suitability of the new proposed methodology for VOO production;

b) The second goal was to develop specific analytical methods for evaluating the elemental profile of olive oil and to collect some preliminary data about the possibility to use these methods in order to put in evidence the possible influence of different process conditions (extraction with or without addition of carbonic snow) on the olive oil elemental profile. In particular, olive oil samples were submitted - after appropriate pre-treatments - to chemical analyses focused to establish the elemental composition (macro-, micro- and trace elements) and to define characteristic elemental patterns. The following analytical techniques were applied and compared: Inductively Coupled Plasma Atomic Emission Spectroscopy (ICP-AES), and Inductively Coupled Plasma–Mass Spectroscopy (ICP-MS). These techniques allow the determination (also simultaneously) of nutritional elements (e.g.: Fe, Zn, Cu), environmental contaminants and contaminants from transformation processes, storage and packaging (e.g.: Pb, Cd, Ni), as well as of trace elements to be used for the definition of characteristic fingerprints linked to the territorial product origin.

The accurate determination of trace elements in olive oil is an analytical challenge due to their low concentration and the difficulties arising from the high organic content of the oil matrix. In particular, the high organic content imply that sample pre-treatment could represent a critical step in the olive oil analysis [14].

Materials and Methods

The study was conducted on samples of olive oil produced from monovarietal and polyvarietal (mix) olives collected in two different Italian regions (from Tuscany and Basilicata) during the same season (Table 1). In each experimental runs, olive oil samples obtained from the same raw material were submitted or not to the treatment with carbon dioxide in the solid state (“carbonic snow”) and were analyzed, so to compare the oil yield as well as the elemental profiles obtained as a function of different process conditions.

Sample ID Geographical origin Cultivar
"Traditional" "Cryo"
A 1 Tuscany (GR) frantoio
B 2 Tuscany (SI) mix (frantoio, leccino, corregiolo)
C 3 Tuscany (SI) mix (frantoio, leccino, corregiolo)
D 4 Tuscany (SI) mix (frantoio, leccino, corregiolo)
E 5 Basilicata coratina
F 6 Basilicata coratina
G 7 Basilicata coratina

Table 1: Experimental runs: origin and cultivar of the raw matter.

Determination of oil extraction yield

The extraction runs were carried out utilising a micro oil mill (Oliomio Baby®, Toscana Enologica Mori), which is able to mill 2030 kg of olives, and it was suitably modified to allow the addition of carbonic snow directly to olive fruits and/or to their paste.

The main process steps followed by this micro oil mill, can be so schematically presented: olives properly cleaned and washed, are poured into the receiving hopper, where a screw feeds the crusher equipped with a hollow knife impeller. The produced paste falls into the lower mixer, where an helicoidally shaped stirrer promotes its malaxation, the temperature reached by the paste is maintained in the wished range by a thermal regulation system (temperature sensor put inside the olive paste, connected with an heat exchanger). The wished flow of the olive paste is then sent to a biphasic decanter by a pump equipped with a speed change gear. The decanter (4200 rpm) promotes the separation of oil from the solid parts of olive mixed with vegetable water plus the fraction possibly added to allow an efficient separation of these two phases.

The separation efficiency of this decanter can be enhanced by a suitable regulation of its nozzles, which determine the point of oil picking and then also the purity degree of the product.

To allow a suitable comparison between the results obtained in the presence or in the absence of solid CO2 during the oil extraction process, the olive fruits utilised in each experimental runs (~ 60 kg) were preliminary and suitably mixed to ensure homogeneous feeds.

In all the experimental run the ratio “mass of cryogen”/“mass of fruits” was maintained constant, close to 0,2.

With the aim to avoid that the differences in the composition of olives (i.e. cultivar and/or ripening stage as well as water content) utilised in different experimental runs can influence determination of the oil extraction yield, this parameter has been expressed as “extractability” according to the following equation:

Extractability index E = kg of extracted oil /(kg of milled olives ) x% of oil inside the olives      (1)

Determination of oil elemental profile

All reagents used were of analytical grade. High-purity water (resistivity > 18MΩ cm) was used in all dilutions. The elemental standard solutions were prepared by diluting stock solutions (TraceCERT® Fluka Standards) of 1000 mg/l.

ICP-AES and ICP-MS analysis:

Dissolution of the test material: Olive oil dissolution was performed by acid attack in a Microwave High Pressure Digestion System MILESTONE MLS 1200 MEGA. Different reagent mixtures were tested in order to define the better conditions for obtaining a total dissolution with a complete destruction of the organic component of the matrix. In particular the use of different reagent mixtures was investigated: 0,5 g of olive oil was treated with concentrated H2O2 (30%v/v) and concentrated HNO3 (69.9%v/v) in different proportions (H2O2 ranged from 1 ml up to 2 ml while HNO3 ranged from 2 ml up to 6 ml). Complete dissolution of oil was obtained by employing 6 ml HNO3+2 ml H2O2 and applying the following digestion cycle: 1 min for 250 W, 1 min at 0 W, 5 min at 400 W, 5 min at 650 W and 5 min vent (with free pressure rise). The obtained solutions were filled up to the 25 ml final volume with high-purity water in PP flasks and submitted to ICP-AES and ICP-MS analysis. Process blank solutions were prepared and submitted to elemental analysis under identical conditions.

ICP-AES analysis: Solutions obtained by olive oil dissolution were analyzed as it were (TQ) using a Varian VISTA MPX (Axial Configuration; simultaneous 1.12 Mpixel CCD detector).

First of fall tests to optimize gas flows basing on signal-tobackground ratio (S/B) were conducted. Then samples were analyzed with a method allowing to perform the study of spectral interferences and the preliminary qualitative analysis (simultaneous detection of the presence of 72 elements). Finally quantitative analysis was carried out, under the conditions reported in Table 2.

Instrumental conditions
RF Frequency 40 MHz (free running, air-cooled)
RF Power 1.2 kW
Gas (plasma, auxiliary, nebulizer) Argon
Plasma flow 15.0 l/min
Auxiliary flow 1.5 l/min
Nebulizer flow 1.10 l/min
Replicates 5
Replicate read time 5 s
Analytical wavelengths (nm)
Al - 396.152 nm K  - 766.491 nm Rb - 780.026 nm
As - 188.980 nm Li - 670.783 nm S  - 181.972 nm
B  - 249.772 nm Mg - 279.553 nm Sb - 206.834 nm
Ba - 455.403 nm Mn - 257.610 nm Si - 251.611 nm
Ca - 396.847 nm Na - 589.592 nm Sr - 407.771 nm
Cr - 267.716 nm Ni - 231.604 nm Ti - 334.941 nm
Cu - 327.395 nm P  - 213.618 nm V  - 311.837 nm
Fe - 238.204 nm Pb - 220.353 nm Zn - 206.200 nm

Table 2: Operating parameters for ICP-AES quantitative analysis.

ICP-MS analysis: Solutions obtained by olive oil dissolution were 1:10 diluted with high-purity water and then analyzed using a Bruker Aurora M90 (90 degree ion mirror ion optics; Collision Reaction Interface). The ICP-MS was tuned with a with a 5 μg/l Be, Mg, Co, In, Ba, Ce, Ti, Pb and Th solution for sensitivity and resolution optimization and mass calibration. The level of oxide ions were checked by the CeO+/ Ce+ ratio (< 2%), while double charged ions were monitored by the signal 137Ba++/137Ba+ (< 3%).

The isotopes to be investigated were selected basing on potential interferences and relative abundances. In order to check/correct the presence of interferences, for some elements the method was optimized by analyzing more isotopes (e.g.: Rb85 and Rb87; Sr88 and Sr87; Nd142, Nd146 and Nd144; Se77 and Se78; Sm147, Sm148 and Sm152; Gd157 and Gd154; Er166 and Er168; Yb170 and Yb172), even applying correction equations with respect to isotopes of other elements potentially interfering (e.g.: (e.g.: Nd142 corrected by analyzing Ce140, Nd144 by Sm147, Sm152 by Gd157, Rb87 by Sr88). For lead, considering the great variability of the relative abundances of its isotopes in nature, a mathematical combination of the results obtained for the three stable isotopes Pb206, Pb207 and Pb208 was employed. The dwell time was optimized for each element in order to obtain the best sensitivity.

For some elements, analyses were performed operating both in Normal and in High Sensitivity Mode, so to focus the ion beam enhancing sensitivity.

Tables 3 and 4 show the analyzed isotopes and the instrumental conditions for the ICP-MS analysis, in Normal Sensitivity Mode and in High Sensitivity Mode respectively. In addition, for As and Se a specific method in Normal Sensitivity Mode was developed in order to reduce interferences by using the Collision Reaction Interface (Skimmer gas: H2; Skimmer flow = 60 ml/min); the potentials of ion optics, Ar flows and dwell time (100 ms) were appropriately optimized.

Instrumental conditions
Gas flow parameters
(Argon)
Plasma flow 17.00 l/min
Auxiliary flow 1.80 l/min
Nebulizer flow 0.94 l/min
Sheat flow 0.25 l/min
Plasma power RF power 1.40 kW
Sample introduction Sampling depth 7.50 mm
Pump rate 2 rpm
Ion optics First extraction lens - 1.00 V
Second extraction lens - 176.00 V
Third extraction lens - 210.00 V
Corner lens - 213.00 V
Mirror lens left 42.00 V
Mirror lens right 24.00 V
Mirror lens bottom 26.00 V
Fringe bias - 2.40 V
Quadrupole scan Scan mode Peak hopping
Dwell time 30 ÷ 60 ms
Points per peak 1
Scans/Replicate 10
Replicates/Sample 5
Analyzed isotopes
As75 Cu65 La139 Ni60 Sc45 Sr88
Cd114 Er166 Mg32 Pb(206,207,208) Se78 Th232
Ce138 Er168 Mn55 Pr141 Sm147 Y89
Ce140 Eu153 Nd142 Rb85 Sm148 Yb170
Co59 Gd154 Nd144 Rb87 Sm152 Yb172
Cr53 Gd157 Nd146 Sb121 Sr87 V51

Table 3: Operating parameters for ICP-MS analysis Normal Sensitivity Mode (without CRI).

Instrumental conditions
Gas flow parameters
(Argon)
Plasma flow 17.00 l/min
Auxiliary flow 1.70 l/min
Nebulizer flow 1.00 l/min
Sheat flow 0.16 l/min
Plasma power RF power 1.40 kW
Sample introduction Sampling depth 6.50 mm
Pump rate 15 rpm
Ion optics First extraction lens - 456.00 V
Second extraction lens - 826.00 V
Third extraction lens - 600.00 V
Corner lens - 544.00 V
Mirror lens left 69.00 V
Mirror lens right 48.00 V
Mirror lens bottom 51.00 V
Fringe bias - 3.00 V
Quadrupole scan Scan mode Peak hopping
Dwell time 40 ÷ 60 ms
Points per peak 1
Scans/Replicate 10
Replicates/Sample 5
Analyzed isotopes
Ce138 Eu153 Nd142 Sc45 Th232
Ce140 Gd154 Nd144 Sm147 Y89
Er166 Gd157 Nd146 Sm148 Yb170
Er168 La139 Pr141 Sm152 Yb172

Table 4: Operating parameters for ICP-MS analysis High Sensitivity Mode.

As internal standard, Y89 (except when Y was an analyte) and In115 were employed.

External calibration was performed by employing 5 standard solution and a blank solution; working ranges were:

• 0.05 ÷ 5 μg/l – for As, Cd, Ce, Er, Eu, Gd, La, Mn, Nd, Pb, Pr, Rb, Sb, Sc, Se, Sm, Sr, Th, V, Y, Yb

• 0.1 ÷ 10 μg/l – for Co, Cr, Cu, Mg, Ni

Results and Discussion

Determination of oil extraction yield indexes: preliminary results

In Table 5 are reported the different indexes of extractability calculated for each experimental run according to eq. 1, with (EC) or without (ET) the addition of cryogen during pre-milling phase.

Run EC ET (EC-ET) · 100
              ET
1/A 85.8 82.5 4.0%
2/B 85.5 77.2 10.8%
3/C 91.2 82.7 10.3%
4/D 84.1 74.8 12.4%
5/E 80.8 79.3 1.9%
6/F 73.6 68.9 6.8%
7/G 84.4 77.4 9.0%

Table 5 : Oil extraction yield. EC = extractability with cryogen; ET =extractability without cryogen.

In order to evaluate the effect induced by the addition of cryogen on the oil extraction yield, it was determined the Extractability Index Variation (EIV) as the percentage of the variation of oil extractability using CO2,s compared with the same parameter obtained by a traditional extraction process:

EIV = (EC-ET) /ET n 100                   (2)

The experimental values (Table 5) showed as the direct addition of cryogen to the olives during pre-milling phase could induce a general increase in the oil extraction yield, ranging from 2 to 12,4%.

Even if the number of experimental runs carried out until now could appear quite reduced, the data obtained have given a positive indication about the suitability of the new proposed method for the oil extraction so that it will be used during the next crop season. In order to individuate the best working conditions which have to be adopted to obtain the best oil extraction yield as a consequence of the addition of cryogen, it will be necessary to apply the new extraction process to a greater number of experimental runs adopting several combinations of the working parameters (i.e. amount of cryogen/amount of olives, fruit ripening stage, etc.).

Moreover, in order to define the best working conditions, it will be taken into account the values of the concentrations of high quality components (such as phenols and aromatic compounds) diffused from the solid parts of the olives into the lipid phase during the different experimental runs.

Because of the cellular crash induced by the cryogen addition, it would be possible to move up the olive harvest time in order to greatly reduce the damages due to the third fly attack of Bactrocera oleae that can induce a significant loss in oil production (up to 60%) as well as a decrease in oil quality. In fact the extent of the changes was much greater when the olives were attacked and harvested at the advanced stage of maturity [15].

Determination of oil elemental profile: preliminary results

The analytical methods for evaluating the olive oil elemental profile by ICP-MS and ICP-MS were set up. ICP-AES and ICP-MS techniques are particularly advantageous for the application in the definition of the elemental profiles of olive oil, since they allow simultaneous multielemental analysis and are characterized by wide linear ranges and (especially ICP-MS) very low Detection Limits. Main analytical issues are related to the hard organic content of the oil matrix, which requires appropriate sample pre-treatments. Microwave-assisted digestion permitted to obtain a complete dissolution of olive oil samples, but resulted in the obtainment of highly acidic solutions not directly detectable by ICP-MS, with a consequent reduction of sensitivity (due to the preliminary 1:10 dilution of the mineralized olive oil). To address this issue, it is possible to apply matrix modification procedures (e.g. solvent extraction – also ultrasound assisted -, addition of organic solvents, or emulsification) or to employ systems for direct oil sample introduction in torch (e.g.: Flow Injection Analysis systems). In the next experimental campaign, it will be then possible to apply these methodologies for the analysis of a higher number of samples, so to study in depth the influence of different process conditions on the olive oil elemental profile. Additional experimental tests have been planned also in order to evaluate the possibility to employ a Laser Ablation (LA) system or an ElectroThermal Vaporization (ETV) system for direct sample introduction in ICP-AES and ICP-MS.

Table 6 shows the elemental content in olive oil samples. Preliminary results show a rather homogeneous elemental content among all the analyzed samples of olive oil. Generally, samples of olive oil obtained by the “traditional” process showed a higher content of Ca, Cr, Mg, Si and Zn, compared to those obtained by the addition of “carbonic snow”. However also in this case it will be necessary to increase the number of experimental runs and vary the operating conditions adopted during the extraction with “carbonic snow” (i.e. ratio “cryogen”/”olives”; ripening stage; etc.).

Sample Al B Ba Ca Fe K Li Na P S Si Ti Zn
mg/kg
1 Trad 0.9 24 0.02 7.9 0.50 0.6 0.25 2.9 1.4 20 16 0.12 1.4
A Cryo 0.9 26 0.01 5.5 0.28 < 0.4 0.26 2.9 1.3 25 10 0.21 1.4
2 Trad 2.8 26 0.13 21 1.3 1.1 0.25 2.8 1.6 24 25 0.21 1.4
B Cryo 1.0 24 0.01 7.1 0.40 0.5 0.24 2.7 1.5 24 15 0.27 1.2
3 Trad 1.1 26 0.01 7.3 0.32 < 0.4 0.27 3.0 2.6 15 8 0.10 1.5
C Cryo 0.9 25 < 0.01 6.2 0.26 0.5 0.25 2.8 2.0 30 7 0.11 1.4
4 Trad 0.8 26 0.01 11 0.28 0.5 0.25 2.8 1.1 29 84 0.12 1.4
D Cryo < 0.8 25 < 0.01 3.8 0.62 0.4 0.26 2.8 1.4 25 14 0.08 1.3
5 Trad 1.2 25 0.02 9.5 0.42 0.5 0.26 2.8 2.7 30 16 0.11 1.4
G Cryo 2.3 23 0.01 10 0.43 0.4 0.26 3.0 2.0 28 20 0.11 1.4
6 Trad 2.3 24 0.04 13 1.0 1.1 0.26 2.9 1.6 23 18 0.14 1.7
F Cryo 1.0 23 0.02 12 0.39 0.8 0.26 2.9 1.8 25 21 0.11 1.5
7 Trad 1.2 24 0.02 7.7 0.49 0.5 0.24 2.8 1.2 28 13 0.14 1.4
G Cryo 1.3 24 0.03 12 0.58 1.2 0.26 2.9 1.5 < 10 19 0.13 1.5

Table 6a: Elemental content in olive oil (mg/kg).

Sample As Cd Ce Co Cr Cu Er Eu Gd La Mg Mn Nd Ni Pb Pr Rb Sb Sc Se Sm Sr Th V Y Yb
µg/kg
1 Trad 24 < 5 < 2.5 18 283 < 100 < 2.5 < 2.5 < 2.5 < 2.5 306 < 25 < 2.5 < 250 10 < 2.5 < 25 < 15 448 < 25 < 2.5 < 25 36 214 < 2.5 4
A Cryo 35 28 < 2.5 < 5 119 106 < 2.5 < 2.5 < 2.5 < 2.5 858 < 25 < 2.5 < 250 126 < 2.5 78 < 15 428 < 25 < 2.5 32 36 192 < 2.5 4
2 Trad < 15 < 5 6 < 5 133 < 100 4 < 2.5 4 12 1040 41 9 < 250 3255 < 2.5 < 25 < 15 580 38 < 2,5 27 288 222 3,0 12
B Cryo 40 < 5 < 2.5 < 5 99 120 < 2.5 < 2.5 < 2.5 < 2.5 523 < 25 5 < 250 70 < 2.5 < 25 < 15 538 < 25 < 2.5 < 25 53 243 < 2.5 10
3 Trad 29 10 < 2.5 < 5 61 173 < 2.5 < 2.5 < 2.5 < 2.5 789 < 25 < 2.5 < 250 64 < 2.5 65 < 15 261 < 25 < 2.5 34 108 83 < 2.5 5
C Cryo < 15 < 5 < 2.5 < 5 54 437 < 2.5 < 2.5 < 2.5 < 2.5 164 < 25 < 2.5 < 250 139 < 2.5 < 25 < 15 395 < 25 < 2.5 < 25 54 161 < 2.5 4
4 Trad 43 < 5 < 2.5 < 5 230 201 < 2.5 < 2.5 < 2.5 < 2.5 1467 < 25 < 2.5 < 250 93 < 2.5 < 25 < 15 205 < 25 < 2.5 32 41 118 < 2.5 4
D Cryo 44 < 5 < 2.5 < 5 190 288 < 2.5 < 2.5 < 2.5 < 2.5 611 < 25 < 2.5 < 250 1028 < 2.5 < 25 < 15 448 < 25 < 2.5 < 25 49 123 < 2.5 4
5 Trad < 15 < 5 < 2.5 < 5 < 50 125 < 2.5 < 2.5 < 2.5 < 2.5 244 < 25 < 2.5 < 250 8 < 2.5 < 25 < 15 588 < 25 < 2.5 < 25 39 < 50 < 2.5 4
G Cryo 25 < 5 < 2.5 < 5 401 < 100 < 2.5 < 2.5 < 2.5 < 2.5 218 < 25 < 2.5 < 250 54 < 2.5 < 25 < 15 258 < 25 < 2.5 47 45 56 < 2.5 4
6 Trad 63 < 5 < 2.5 6 539 < 100 < 2.5 < 2.5 < 2.5 5,7 581 < 25 3 < 250 109 < 2.5 < 25 < 15 431 < 25 < 2.5 50 189 116 < 2.5 6
F Cryo 30 < 5 < 2.5 < 5 725 < 100 < 2.5 < 2.5 < 2.5 < 2.5 303 < 25 < 2.5 < 250 163 < 2.5 < 25 < 15 320 < 25 < 2.5 < 25 41 81 < 2.5 4
7 Trad 30 < 5 < 2.5 < 5 149 < 100 < 2.5 < 2.5 < 2.5 < 2.5 334 31 < 2.5 < 250 39 < 2.5 < 25 < 15 386 < 25 < 2.5 < 25 37 173 < 2.5 4
G Cryo 51 < 5 < 2.5 < 5 680 320 < 2.5 < 2.5 < 2.5 14 661 28 < 2.5 < 250 42 < 2.5 < 25 < 15 436 < 25 < 2.5 42 48 118 < 2.5 4

Table 6b: Elemental content in olive oil (μg/kg).

Table 6: Elemental profile of olive oil samples.

As showed in Figure 1, experimental concentrations fell within the ranges reported in literature [16] for all elements. In respect to these ranges, analyzed samples showed a high content of B, S and Si, while Fe, Na, Pb, Ba, Cr and Cu contents are quite low.

nutrition-food-sciences-ranges-weight

Figure 1: Elemental concentration ranges and Detection Limits.

Although in this first stage of our work the main purpose was to develop the analytical methods for elemental analysis of olive oil by ICP-AES and ICP-MS, the results obtained on this first set of samples have been submitted to multivariate statistical analysis in order to better interpret the data and perform a preliminary evaluation about the possibility to differentiate the samples in respect to the process.

Principal Component Analysis (PCA) was performed with XLStat 2014 Software package (Addinsoft) used as a Microsoft Excel plug-in. Considering that below DL values are unreadable when using XLSTAT, PCA was applied to the elemental concentration of each sample by using the approximation to the DL value (set of 39 observations for 14 variables). The first 5 principal components extracted account together for 80.64% of the variability in the original data. The elements that mainly describe the first two variables (accounting together for 55.84% of the variability of the original data) are: Ba, Er, Gd, Se, Ce, Y, Nd, Mn and Pb for F1 (40.02%); Zn, Sr, Cr, Na, Li, K and V for F2 (15.82%). A further data processing was performed by considering only the elements present at detectable concentrations in at least 50% of the olive oil samples (set of 23 observations for 14 variables). Also in this case the first 5 variables extracted account together for 80.65% of the variability in the original data, but with the F1 (26.87%) mainly described by Ba, Fe, Th, Yb, Pb, Ca, Al and K and the F2 (22.18%) mainly described by Zn, Sr, Na, Cr, Li and V (F1 and F2: 52.04%). The results of the PCA showed a rather homogeneous distribution of samples, in accordance with the rather homogeneous elemental content previously highlighted. This is also due to the reduced number and type of the samples analyzed in this first experimental crop season (suitable to the development of methodologies, in accordance with the aim of our work). In any case, this elaboration allowed to define, in addition to the analytical methods, also the methodologies for data processing and statistical analysis. Further tests conducted on a larger number of olive oil samples, with characteristics as homogeneous as possible in respect to their geographical and botanical origin, differentiated in respect to the production process (addition or not of “carbonic snow” during the extraction, different operating conditions), will allow to better evaluate the effect of the different process conditions on the olive oil elemental profile.

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