Optimization of the Temperature and Oxygen Concentration

Article pubs.acs.org/JAFC

Optimization of the Temperature and Oxygen Concentration Conditions in the Malaxation during the Oil Mechanical Extraction Process of Four Italian Olive Cultivars Roberto Selvaggini,* Sonia Esposto, Agnese Taticchi, Stefania Urbani, Gianluca Veneziani, Ilona Di Maio, Beatrice Sordini, and Maurizio Servili Dipartimento di Scienze Agrarie, Alimentari e Ambientali, Università degli Studi di Perugia, Via S. Costanzo, 06126 Perugia, Italy S Supporting Information *

ABSTRACT: Response surface modeling (RSM) was used to optimize temperature and oxygen concentration during malaxation for obtaining high quality extra virgin olive oils (EVOOs). With this aim, those chemical variables closely related to EVOO quality, such as the phenolic and the volatile compounds, have been previously analyzed and selected. It is widely known that the presence of these substances in EVOOs is highly dependent on genetic, agronomic, and technological aspects. Based on these data, the two parameters were optimized during malaxation of olive pastes of four important Italian cultivars using some phenols and volatile compounds as markers; the optimal temperatures and oxygen levels, obtained by RSM, were as follows for each cultivar: 33.5 °C and 54 kPa of oxygen (Peranzana), 32 °C and 21.3 kPa (Ogliarola), 25 °C and 21.3 kPa (Coratina), and 33 °C and 21.3 kPa (Itrana). These results indicate the necessity to optimize these malaxing parameters for other olive cultivars. KEYWORDS: extra virgin olive oil, quality, oil mechanical extraction process, phenols, volatile compounds, HS-SPME-GC/MS, optimization, response surface methodology

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INTRODUCTION

has a positive effect on EVOO quality, as it produces a good aroma and should be favored in the malaxation process.10,13−15 The results of several studies in this field have led experts to build new machines that can control these enzymatic activities by controlling the water temperature in the malaxer chamber and reducing the concentration of O2 in contact with the olive pastes (closed or confined malaxer); this allows on the one hand the limitation of PPO and POD activity and on the other the usual production of the aroma by the LPO;10,14,16−18 hence the choice of the optimal temperature and the amount of O2 during mixing is a strategy for the production of a high quality EVOO,19,20 even if these parameters must be correlated to the olive cultivar. RSM might be used for evaluating the relative importance of different influencing factors even in the presence of complex interactions. RSM is an empirical statistical modeling technique used for optimizing one or more responses (Y variables) influenced by several variables (X) using quantitative data gathered from properly designed experiments to solve multivariable equations simultaneously by using the method of leastsquares.21,22 When multiple variables might influence the outputs, RSM is an effective technique for exploring the relationships between the responses and the independent variables.23,24 Central composite design (CCD) is the most common form of design of experiments for minimizing the number of experiments required and suitable to perform RSM.25 It has been widely

Some extra virgin olive oil (EVOO) minor compounds highly influence its quality: in particular, aroma and taste (bitter and pungent) sensory notes are given by volatile and phenolic compounds, respectively.1,2 Furthermore, hydrophilic phenols are responsible for several health properties associated with virgin olive oil consumption.1,3,4 Many studies have demonstrated that the main causes responsible for the qualitative and quantitative presence of both these groups of substances in the final product are strictly correlated with the genetic origin of the olives (cultivar) and the agronomic and the technological production conditions.2,5−7 The wide variety of different cultivars used for the mechanical extraction process of monovarietal and blended EVOOs plays an important role in their sensory, nutritional, and health properties, even if the mean concentration of phenolic and volatile compounds of a single cultivar is necessarily influenced also by agronomic factors such as the growing area, fruit ripening, cultivation techniques, water resources, fertilization, and soil management and by the technological extraction system.7,8 From a technological point of view, malaxation represents a critical step in the EVOO extraction process, where the selective control of the oxidoreductase enzymes such as polyphenoloxidase (PPO), peroxidase (POD), and lipoxygenase (LPO) is very important.1,2,10−12 Indeed, all these oxidoreductases remain active after crushing, but since PPO and POD are responsible for the degradation of polyphenols, they should certainly be inhibited; on the contrary, LPO activity © 2014 American Chemical Society

Received: Revised: Accepted: Published: 3813

January 8, 2014 April 2, 2014 April 3, 2014 April 3, 2014 dx.doi.org/10.1021/jf405753c | J. Agric. Food Chem. 2014, 62, 3813−3822

Journal of Agricultural and Food Chemistry

Article

a central composite circumscribed design (CCC; see Table 1 for the trial temperatures and oxygen partial pressures). The EVOO samples were filtered and stored in the dark at 13 °C until analyzed.

utilized by several researchers to optimize various food processing methods such as fermentation,26 milling,27 extraction from vegetable matrices28 and virgin olive oil mechanical extraction;19 RSM has thus become one of the most popular optimization techniques in the field of food science.29,30 The objectives of this study were to systematically investigate the influence of temperature and oxygen concentration on the olive pastes belonging to four of the most important Italian olive cultivars during malaxation and to explore the best operative conditions for obtaining high quality EVOOs.

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Table 1. Temperature and Oxygen Content According to a Central Composite Circumscribed Design Used in the Optimization Study of the Malaxation Process

MATERIALS AND METHODS

Olives. In this research, olive drupes of Coratina, Peranzana, Itrana, and Ogliarola cultivars (cvs) were tested. Coratina and Ogliarola olive trees on a side and Peranzana by the other were planted in the Apulia Region, in the Province of Bari, and in the Province of Foggia, respectively. Instead, the growing area of Itrana olive trees was the Province of Latina (Lazio). All the cvs were harvested on the period October−November 2011 and the ripening stage of these olives, evaluated on the basis of the pigmentation index according to Pannelli et al.,31 was 0.95. The olives have been processed within 48 h after harvesting. Reference Compounds. The (p-hydroxyphenyl)ethanol (pHPEA) was purchased from Fluka (Milan, Italy), while the 3,4(dihydroxyphenyl)ethanol (3,4-DHPEA), produced by the Cayman Chemical Co. (Ann Arbor, MI, USA), was obtained from Cabru s.a.s. (Arcore, Milan, Italy). The dialdehydic forms of elenolic acid linked to 3,4-DHPEA and p-HPEA (3,4-DHPEA-EDA and p-HPEA-EDA, respectively), the isomer of oleuropein aglycon (3,4-DHPEA-EA), (+)-1-acetoxypinoresinol, and (+)-pinoresinol were extracted from virgin olive oil according to the method developed by Montedoro et al.32 In this method the phenolic compounds were extracted from the extra virgin olive oil using a mixture of methanol/water (80:20 (v/v)); then, after solvent evaporation and a partial purification of the crude extract obtained from EVOO, the phenols were separated by semipreparative high performance liquid chromatography (HPLC) analysis. The HPLC separation was conducted using a Whatman Partisil 10 ODS-2 column (500 mm × 9.4 mm i.d.). The mobile phase was 0.2% acetic acid (pH 3.1) in water (A) and methanol (B), and the elution was performed at a flow rate of 6.5 mL/min. The total running time was 150 min, and the gradient changed as follows: the starting composition was 95% A/5% B, then the percentage of B was increased to 74% A/26% B in 2.5 min, 64% A/36% B in 4.5 min, and this percentage was maintained for 33 min, 61% A/39% B in 35 min, 0% A/100% B in 35 min, and this percentage was maintained for 20 min, returning at the end to the initial conditions (95% A/5% B) in 20 min. The phenols were detected using a diode array detector (DAD) at a wavelength of 278 nm. The purity of these substances was tested by analytical HPLC,33 and their chemical structures were verified by NMR using the same operating conditions reported in previous papers by recording 1H and 13 C spectra.32,34 Pure analytical standards of volatile compounds Fluka and Aldrich were purchased from Sigma-Aldrich (Milan, Italy). Experimental Procedure. Virgin Olive Oil Mechanical Extraction Process. The experiments were conducted with an industrial plant using a TEM 200 system (Toscana Enologica Mori, Tavarnelle Val di Pesa, Florence, Italy) composed of a hammer mill, a malaxer with a gas controller system, and a working capacity of 200 kg of olives and a two-phase decanter; for the separation of olive oil, a UVPX 305 AGT 14 centrifuge (Alfa Laval S.p.A., Tavarnelle Val di Pesa, Florence, Italy) was used. The extraction was performed on a sample of 150 kg of olives, and malaxation was carried out for 40 min, a period commonly used in industrial plants, using a top-covered malaxing machine equipped with an O2 valve and a Mettler-Toledo O2 4100 sensor (Mettler-Toledo, Novate Milanese, Milan, Italy) for oxygen measurement.35 The trials were performed at malaxing temperatures (ranging from 20 to 40 °C) and initial oxygen partial pressures in the headspace of the malaxer chamber (ranging from 21.3 to 101.3 kPa) according to

trial

temp (°C)

oxygen content (kPa)

1 2 3 4 5 6 7 8 9 10 11

20 24 24 30 30 30 30 30 36 36 40

61.3 37.2 85.4 21.3 101.3 61.3 61.3 61.3 37.2 85.4 61.3

Analytical Methods. Extraction and HPLC Analysis of the Phenolic Compounds of Virgin Olive Oils. The extraction of EVOO phenolic compounds was performed in accordance with Montedoro et al.36 The HPLC analyses of the phenolic extracts were conducted according to Selvaggini et al.33 with a reversed-phase column using an Agilent Technologies system Model 1100 (Agilent Technologies, Santa Clara, CA, USA) which was composed of a vacuum degasser, a quaternary pump, an autosampler, a thermostated column compartment, a DAD, and a fluorescence detector (FLD). The C18 column used in this study was a Spherisorb ODS-1 250 mm × 4.6 mm with a particle size of 5 μm (Waters, Milford, MA, USA); the injected sample volume was 20 μL. The mobile phase was composed of 0.2% acetic acid (pH 3.1) in water (solvent A)/methanol (solvent B) at a flow rate of 1 mL/min and the gradient changed as follows: 95% A/5% B for 2 min, 75% A/25% B in 8 min, 60% A/40% B in 10 min, 50% A/50% B in 16 min, and 0% A/100% B in 14 min; this composition was maintained for 10 min and then returned to the initial conditions and equilibration in 13 min; the total running time was 73 min. Lignans were detected by using the FLD operated at an excitation wavelength of 280 nm and an emission of 339 nm; for the detection of all the other phenolic compounds a DAD was employed with the wavelength set at 278 nm. Volatile Compounds Analysis. The evaluation and quantification of volatile compounds in EVOOs were done by headspace−solid phase microextraction (HS-SPME) followed by gas chromatography−mass spectrometry analysis (HS-SPME-GC/MS) according to Servili et al.37 with few modifications. For sampling the headspace volatile compounds, SPME was applied as follows: 3 g of EVOO were placed in a 10 mL vial and thermostated at 35 °C, then the SPME fiber (a 50/30 μm divinylbenzene/ Carboxen/poly(dimethylsiloxane) (DVB/CAR/PDMS) with a length of 1 cm; StableFlex, Supelco, Inc., Bellefonte, PA, USA) was exposed to the vapor phase for 30 min to sample the volatile compounds. Afterward, the fiber was inserted into the GC injector set in splitless mode, using a splitless inlet liner of 0.75 mm i.d. for thermal desorption, where it was held for 10 min. All of the SPME operations were automated by using a Varian CP 8410 AutoInjector (Varian, Walnut Creek, CA, USA). GC/MS Analysis. The analysis of the volatile compound sampled with SPME was conducted as reported in Servili et al.37 with few modifications. A Varian 4000 GC/MS equipped with a 1079 universal capillary injector (Varian) was used. An Agilent J&W fused-silica capillary column was employed (DB-WAXetr, 50 m, 0.32 mm i.d., 1 μm film thickness; Agilent). The column was operated with helium at a constant flow rate of 1.7 mL/min maintained with an electronic flow controller (EFC). The GC oven heating program started at 35 °C. This temperature was maintained for 8 min, then increased to 45 °C at 3814

dx.doi.org/10.1021/jf405753c | J. Agric. Food Chem. 2014, 62, 3813−3822


Article

a rate of 1.5 °C/min, increased to 150 °C at a rate of 3 °C/min, increased to 180 °C at a rate of 4 °C/min, and finally increased to 210 °C at a rate of 3.6 °C/min; this temperature was then held for 14.5 min. The total time of analysis was 80 min. The injector temperature was maintained at 250 °C; the temperature of the transfer line was fixed at 170 °C. The mass spectrometer was operated in the electron ionization (EI) mode at an ionization energy of 70 eV, with scanning in the mass range of m/z 25−350 amu at a scan rate of 0.79 s/scan and a trap set point temperature of 150 °C. The GC-MS was operated with the Varian MS Workstation Software, Version 6.6 (Varian). The volatile compounds were identified by comparison of their mass spectra and retention times with those of authentic reference compounds. Integration of all the chromatographic peaks was performed by choosing the three masses with the highest intensities among those specific for each compound, to selectively discriminate them from their nearest neighbors. The volatile compound results were calculated on the basis of the calibration curves for each compound and expressed in micrograms per kilogram of oil.37 Statistical Analysis. Descriptive Statistics. To show the variability of data were employed box and whisker plots, in which the lower and the upper edges of the box indicate the 25th and the 75th percentile, respectively; the line within the box shows the median while the whiskers designate the 10th and 90th percentiles. In addition, on the graphs, are reported two points representing the fifth and 95th percentiles. These plots were elaborated using the statistical software SigmaPlot version 12.3 (Systat Software, Inc., San Jose, CA, USA). Principal Components Analysis. Principal component analysis (PCA) models were built to analyze the influence of processing parameters on the analytical data of EVOO. The SIMCA 13.0 chemometric package was used (Umetrics AB, Umeå, Sweden). To perform multivariate statistical analysis, the analytical data were put in a matrix with the samples (n objects) in rows and the analytical parameters (k variables) in columns. The raw data were normalized, with the subtraction of the mean, and autoscaled, dividing these results by the standard deviation. The number of significant components was found by applying cross-validation. The results of PCA modeling are presented in graphical form.38,39 First a PCA model with all data was built; then four SIMCA models, one for each cultivar studied in this work, were made for selecting a small number of variables (volatile and phenolic compounds), from among those with the highest absolute values of loadings, successively employed in the optimization study. When the distributions of these data were not normal (or Gaussian), the data were log-transformed. Optimization by Response Surface Modeling. Response surface model (RSM) was obtained with the chemometric package MODDE. 9.1 (Umetrics AB). To optimize the malaxation parameters in the mechanical extraction process, the original data (Y), phenols and volatile compounds chosen by previous PCA, were transformed into desirability functions (di), successfully used in RSM-based optimization when several response variables (several Y variables) are considered, so reducing the problem to the optimization of only one Y variable. di are dimensionless values, calculated using a linear transformation according to Derringer and Suich40 with a small modification, so as to obtain desirabilities ranging between 0.1 and 1 using the following equation:

D=

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RESULTS AND DISCUSSION The phenolic and volatile compounds of the EVOOs obtained in this study were determined according to the list given in Table 2. Table 2. List of the Variables Evaluated in Extra Virgin Olive Oils phenolic compounds hydroxytyrosol (3,4-DHPEA) tyrosol (p-HPEA) 3,4-DHPEA-EDA p-HPEA-EDA (+)-1-acetoxypinoresinol (+)-pinoresinol 3,4-DHPEA-EA total phenols volatile compounds ketones 3-pentanone 1-penten-3-one aldehydes pentanal hexanal octanal nonanal (E)-2-pentenal (E,E)-2,4-hexadienal 2,4-hexadienal (i) (Z)-3-hexenal (E)-2-hexenal (E)-2-heptenal (E)-2-octenal

phenols phenol

alcohols 2-methyl-1-butanol 1-pentanol 1-hexanol 1-heptanol 1-octanol 1-penten-3-ol (E)-2-penten-1-ol (Z)-2-penten-1-ol (E)-3-hexen-1-ol (Z)-3-hexen-1-ol (E)-2-hexen-1-ol esters ethyl acetate hexyl acetate (Z)-3-hexenyl acetate aromatic alcohols benzyl alcohol phenylethyl alcohol sum of classes of volatile compounds sum of ketones sum of saturated aldehydes sum of C6 unsaturated aldehydes sum of saturated alcohols sum of C5 unsaturated alcohols sum of C6 unsaturated alcohols sum of esters

The results from the combinations of temperature and O2 concentration applied during malaxation are shown, with respect to the phenolic compounds, as distributions in the box and whisker plots in Figure 1, while for volatile compounds the range and the average values contents are given in Table 3. From Figure 1 can be evidenced a strong variation of the phenolic concentration among the cultivars and, in addition, the distribution of the values obtained with different malaxation conditions is cultivar-dependent (cvs Peranzana and Coratina by a side and cvs Ogliarola and Itrana by the other show similar trends). The main phenolic compounds in all the cultivars were the oleuropein and the ligstroside derivatives, while the lignans showed the lowest concentrations and the lowest variability with the operating extraction conditions. It is important to note

0.9Y + 0.1Ymax − Ymin Ymax − Ymin

for phenolic compounds of EVOO that must be minimized:

di =

d1d 2 × ... × dn

The partial least-squares analysis (PLS) was used to estimate the coefficients of the terms in the models.41

for phenolic and volatile compounds of EVOO that must be maximized:

di =

n

−0.9Y + Ymax − 0.1Ymin Ymax − Ymin

Ymin and Ymax correspond to the minimum and the maximum variable values, respectively. The overall desirability (D) was calculated as the geometric mean of the individual di values: 3815



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Figure 1. Box and whisker plots of total phenols (A), derivatives of oleuropein (B), derivatives of ligustroside (C), and lignans (D) evaluated on EVOOs obtained from four Italian olive cultivars in different malaxing conditions. (Limits in percentile: box = lower 25th, upper 75th; whiskers = lower 10th, upper 90th; points = lower fifth, upper 95th. The line within the box represents the median.)

Table 3. Range and Average Values (μg/kg) of Volatile Compounds Evaluated on EVOOs Obtained from Peranzana, Ogliarola, Coratina, and Itrana Cultivars in Different Malaxation Conditions cv. Peranzana

aldehydes pentanal (E)-2-pentenal hexanal (E,E)-2,4-hexadienal 2,4-hexadienal (i) (Z)-3-hexenal (E)-2-hexenal sum of C6 unsaturated aldehydes alcohols 1-pentanol (E)-2-penten-1-ol (Z)-2-penten-1-ol 1-penten-3-ol 1-hexanol (E)-3-hexen-1-ol (Z)-3-hexen-1-ol (E)-2-hexen-1-ol sum of C6 unsaturated alcohols esters hexyl acetate (Z)-3-hexenyl acetate sum of esters

cv. Ogliarola

cv. Coratina

cv. Itrana

range

mean

range

mean

range

mean

range

mean

20−33 120−186 354−929 380−595 164−258 236−303 24,985−37,615 26,092−38,524

25 149 554 497 215 275 30,772 31,760

22−39 66−114 516−894 356−463 182−230 301−501 38,580−54,625 39,565−55,772

29 92 694 410 207 413 47,985 49,015

11−34 66−134 243−412 362−569 180−286 322−439 35,415−56,950 36,315−58,206

24 102 304 438 219 377 45,329 46,362

22−45 116−352 274−1,213 391−1,124 176−461 302−891 31,270−55,515 32,484−57,350

29 254 780 814 347 595 43,381 45,137

13−26 29−47 124−224 205−362 659−1,891 4−10 271−1,149 1,028−3,667 1,614−4,825

19 37 174 287 1,025 6 563 1,899 2,468

11−19 16−43 75−169 130−271 779−1,211 4−7 101−190 2,053−3,463 2,158−3,642

874−1,697 1,856−3,535 2,744−5,231

1,239 2,650 3,889

37−99 29−89 66−188

that the main contribution to the total phenols content was due

15 31 131 212 934 5 137 2,585 2,726 64 62 127

11−20 28−47 148−300 237−459 607−1,925 2−6 115−231 1,425−2,557 1,564−2,760 4−21 17−82 22−94

15 38 231 345 1,000 4 167 2,031 2,202 9 56 65

28−78 27−68 107−292 162−388 1,543−4,340 14−30 1,195−2,334 2,556−5,487 4,007−7,791 80−123 208−691 289−791

44 49 193 283 2,859 22 1,816 3,743 5,581 95 488 583

By the data analysis, the highest average value of total phenols was found in cv. Coratina (992 mg/kg) and the lowest in cv. Peranzana (337 mg/kg); the EVOOs obtained from cv.

to the oleuropein derivatives. 3816



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Figure 2. Score plot and loading plot of the first two principal components (a) and of the first and third components (b) of the PCA of EVOOs obtained from four Italian olive cultivars in different malaxation conditions. Abbreviations used: P = Peranzana; O = Ogliarola; C = Coratina; I = Itrana.

related to the EVOO flavor evaluated in this work are highly affected by the operative conditions. The maximum range of variability for the C6 unsaturated aldehydes corresponding to 24,866 μg/kg was found in cv. Itrana; on the contrary, cv. Peranzana shows the minimum value with 12,432 μg/kg. The mean amounts of the C6 unsaturated alcohols have the highest content in cv. Itrana (5,581 μg/kg), about twice the average amount of the other three cultivars; with respect to the range of variability for this class of compounds, cv. Itrana has the maximum value, 3,784 μg/kg, and cv. Coratina shows the minimum, with 1,196 μg/kg. Regarding the esters concentration, cv. Peranzana has the highest average value (3,889 μg/ kg), about seven times the nearest value found in cv. Itrana, and even in this case the operative conditions of malaxation greatly affect their content: the maximum range of variability was found in cv. Peranzana, with 2,487 μg/kg, while the minimum value was found in cv. Coratina, with 72 μg/kg. Multivariate statistical methods were used to better interpret all the data collected from the EVOO samples obtained by varying the combination of two malaxing parameters, the O2 concentration in the olive pastes and the processing temperature, and to optimize these two variables. A PCA model was first built with the whole data set, which included the EVOOs evaluated for all four Italian cultivars studied using the list of compounds given in Table 2. The model, built with some variables log-transformed so as to obtain a distribution closer to a Gaussian, explains 93% of the total variance with seven significant principal components (37%, 22%, 15%, 9%, 5%, 3%, and 2%, respectively) and the results for the first two components are shown in Figure 2. A clear discrimination of

Itrana contained an average total phenols amount of 364 mg/ kg, while that of cv. Ogliarola was 480 mg/kg. The phenolic variation among the cultivars, in agreement with the literature, indicates that genetic biodiversity is one of the most important parameters that affects the phenolic concentration in EVOOs.1,2,42 So far, however, the impact on the bioactive phenols of the operative conditions of malaxation, such as O2 concentration in the olive pastes and the processing temperature, was very strong in all the cultivars studied. This is demonstrated by the ranges of variability between the extreme values of the total phenols, corresponding to 1,241 mg/kg in cv. Coratina, 488 mg/kg in cv. Ogliarola, 387 mg/kg in cv. Itrana, and 351 mg/kg in cv. Peranzana. High variability was observed also for the volatile compounds according to the cultivar and the operative conditions of malaxation, with the main variations found in the compounds, related to the lipoxygenase pathway, that include hexanal, (E)2-hexenal, 1-hexanol, (E)-3-hexen-1-ol, (Z)-3-hexen-1-ol, and (E)-2-hexen-1-ol, together with esters such as hexyl acetate and (Z)-3-hexenyl acetate. The significant differences in terms of cultivar impact in the C6 unsaturated aldehydes show the lowest average value in cv. Peranzana (31,760 μg/kg) and the highest concentration in cv. Ogliarola (49,015 μg/kg); with regard to the C6 unsaturated alcohols, these range between 2,202 and 5,581 μg/kg for the Coratina and the Itrana cvs, respectively. The most important variation in the volatile composition related to cultivar origin is, however, shown by the ester mean concentrations having the lowest value in cv. Coratina (65 μg/kg) and the highest in cv. Peranzana (3,889 μg/kg). All the classes of volatile compounds 3817



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the EVOOs in four clusters, corresponding to the olive cvs, is observed in the first three principal components, and in particular in the first component the oils most differentiated are Itrana (on the left side) and Coratina (on the right side), while in the second component there are the Coratina and Itrana EVOOs (on the upper side) opposite to the Peranzana and Ogliarola oils (Figure 2a). The loading plot in Figure 2a shows that the Itrana oils are characterized by higher concentration of ketones, C6 saturated and unsaturated alcohols, (E)-2-pentenal, hexanal, and (Z)-3-hexenal; on the contrary, the Coratina EVOOs have a higher secoiridoids content, while Peranzana and Ogliarola EVOOs have lower contents of C5 unsaturated alcohols and secoiridoids (in comparison with cv. Coratina) and higher concentrations of some saturated alcohols. In the score plot of the third component vs the first, there is a very good separation of Ogliarola (on the upper side) compared to Peranzana EVOOs and the former has higher levels of C6 unsaturated aldehydes; on the other hand, Peranzana is very rich in esters (Figure 2b). For the data set for each cultivar without the two lignans, due to very little differences in the samples, preliminary PCA models were built to establish the variables (with regard to the volatile compounds, those substances originated by the lipoxygenase pathway were chosen, significant in defining the flavor of EVOOs) that play an important role in the quality of this food product and that undergo the most variations under the different mechanical oil extraction conditions, temperature and oxygen concentration during malaxation, fixed with the CCC design (for a detailed description of these PCA models see the Supporting Information). For the RSM optimization, only a few analytical variables must be selected in order to define the overall desirability starting with the partial desirability functions (for the list of the variables chosen for each olive cultivar see Table 4). The RSM models explain with two PLS components for all the cultivars analyzed 98%, 97%, 94%, and 85% of the total variance for Peranzana, Ogliarola, Coratina, and Itrana, respectively. The results for Peranzana, given in Figure 3, show a response surface with a maximum located at about 33.5 °C and 54 kPa of oxygen. The most important effect is due to temperature, although oxygen also plays a significant role. For cv. Ogliarola, the surface shows a saddle shape and the best operative conditions can be found at the temperature of 32 °C and the lowest oxygen concentration (Figure 3); in this case, both temperature and oxygen are important in the optimization model. In the case of cv. Coratina, when transformed into desirability functions, due to very high concentration of the phenolic substances (for total phenols up to 1,690 mg/kg), a maximum total phenols value of 1,000 mg/kg was chosen for these compounds, and for secoiridoids proportional values to their original concentrations were calculated, above which the equation for the minimization of the desirability was used, because EVOOs with higher phenolic contents are unpleasant due to their bitter and pungent sensory notes.43,44 The RSM model gave the best results with a temperature of 25 °C and an oxygen concentration of 21.3 kPa, even if in this case a high desirability function value can be obtained at a temperature of 36 °C and an oxygen concentration of 101.3 kPa with the two factors both influencing the model (Figure 4). The best malaxing conditions for cv. Itrana are a temperature of 33 °C and the lowest oxygen concentration, and as for cv. Coratina, very high response values were obtained at a temperature of 37

Table 4. List of the Phenolic and Volatile Compounds Transformed into Desirability Function for Each Cultivar for the RSM Peranzana

Ogliarola

Coratina

3,4-DHPEA-EDA

3,4-DHPEA

3,4-DHPEA

p-HPEA-EDA 3,4-DHPEA-EA

p-HPEA total phenols

(Z)-3-hexen-1-ol hexanal

hexanal (E)-2-pentenal

(E)-2-pentenal (E)-2-hexenal hexyl acetate (E)-2-hexen-1-ol

(E)-2-hexenal 1-pentanol 1-hexanol sum of C5 unsaturated alcohols sum of C6 unsaturated alcohols sum of esters

p-HPEA 3,4-DHPEAEDAa p-HPEA-EDAa 3,4-DHPEAEAa total phenolsa hexanal (E)-2-pentenal (E)-2-hexenal

(Z)-3-hexenyl acetate sum of saturated alcohols sum of C5 unsaturated alcohols

Itrana 3,4-DHPEAEDA p-HPEA-EDA 3,4-DHPEAEA total phenols hexanal (E)-2-pentenal (Z)-3-hexenal (E)-2-hexenal (Z)-3-hexen-1ol

(Z)-3-hexen-1ol

(E)-2-hexen-1ol

(E)-2-hexen-1ol

sum of C5 unsaturated alcohols

(Z)-3-hexenyl acetate sum of C5 unsaturated alcohols

a

Compounds maximized and minimized in the cv. Coratina (for details see the text).

°C with the highest oxygen content; between the two factors now the temperature plays an important role in the modeling process (Figure 4). The results of the optimization models show that the optimal malaxing conditions are strongly affected by genetic biodiversity. These results confirm, as found in previous works,1,2,7,8,42 that cultivars have a significant impact on the chemical and biochemical characteristics of olive fruits and the EVOOs obtained from them. The total amount of phenols in the fruit and the activities of several endogenous enzymes that are involved in phenolic oxidation and aroma generation, such as polyphenoloxidases, peroxidases, and lipoxygenases, are influenced by the genetic origins of the cultivars. As a consequence, to obtain high quality EVOOs, the operative conditions of malaxation, such as the O2 concentration in the pastes and the processing temperature, which both affect the activities of endogenous enzymes, must be optimized according to the cultivar. In this context it is very important to stress that the EVOOs obtained from Itrana and Peranzana among the cultivars studied, rich mainly in esters among the aromatic compounds, formed in the lipoxygenase pathway, but relatively poor in phenolic substances, show the highest malaxation temperatures for obtaining the maximum response values in the optimization models. The high temperatures (near 40 °C) reduce the activity of hydroperoxide lyase responsible for the formation of C6 aldehydes and, consequently, of the other classes of compounds originated by these, but, at the same time, improving the cell wall degradation, due to the endogenous depolymerizing enzymes, and enhancing the solubility of these substances in the oils, they increase the release of phenols in the EVOOs and in the vegetation waters.45,46 On the basis of these results, to improve the health and the sensory properties of EVOOs for cultivars poor in phenols and characterized by high 3818



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Figure 3. RSM and contour plots obtained in the PLS model built to optimize the temperature and oxygen concentration during malaxation in the Peranzana and Ogliarola cultivars.

Figure 4. RSM and contour plots obtained using the PLS model built to optimize the temperature and oxygen concentration during malaxation in the Coratina and Itrana cultivars.

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LPO activity, the optimal malaxing conditions are obtained at temperatures ranging between 30 and 36 °C and low to mid O2 concentrations. In this context the esters production seems to be increased by medium O2 levels in the pastes, which is particularly apparent in cv. Peranzana, probably due to intense alcohol acetyltransferase activity, the last step in the lipoxygenase pathway formation of the volatile compounds. Cv. Coratina, on the contrary, which was characterized by the highest amount of phenols in the EVOOs,33,47,48 shows that the operative conditions for obtaining the highest response value is located to quite low malaxation temperature of (25 °C) among the cultivars studied. Moreover, the results showed that the low O2 amount in cv. Coratina seems to be in contrast with the reduction of the phenolic compounds content, which should be promoted in all cultivars extremely rich in these substances to improve the oil consumer acceptability by reducing the bitterness and the pungent sensory notes.43,49 It is important to note, however, that this result has been obtained with the limit set at 1,000 mg/kg of total phenols content for obtaining pleasant EVOOs. Moreover, cv. Coratina is not only characterized by a high amount of phenols but, at the same time, shows a low polyphenoloxidase and peroxidase activity.13 The low activity of these enzymes can explain why an increase of O2 in the pastes produces a small reduction of the phenolic content in the oils, lower than that connected with the malaxing temperature; as a consequence, in cv. Coratina optimization model, low processing temperatures seem to be more important than high O2 concentrations in the reduction of the phenolic compounds in the oils. This phenomenon could be explained by reduced activity of the depolymerizing enzymes in the pastes that decrease the release of phenols from the cell wall into the olive oil. The optimization of the malaxing parameters of the four Italian cultivars conducted in this study pointed out the different results of the operative conditions, thus requiring specific investigations of the optimal setting for the oil mechanical extraction process for each individual cultivar due to the different influence of the temperature and oxygen concentration during malaxation. However, it is important to note that the malaxing parameters here investigated heavily modify the concentrations of both the phenolic and volatile compounds independently by olive cultivar.10,14,15,19,50

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ACKNOWLEDGMENTS

We thank Michele Giglioni and Roberto Santibacci for their technical assistance during this study.

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ABBREVIATIONS USED RSM, response surface modeling (or response surface methodology); EVOOs, extra virgin olive oils; PPO, polyphenoloxidase; POD, peroxidase; LPO, lipoxygenase; CCD, central composite design; p-HPEA, (p-hydroxyphenyl)ethanol; 3,4DHPEA, (3,4-dihydroxyphenyl)ethanol; 3,4-DHPEA-EDA, dialdehydic form of decarboxymethyl elenolic acid linked to (3,4-dihydroxyphenyl) ethanol; p-HPEA-EDA, dialdehydic form of decarboxymethyl elenolic acid linked to (phydroxypheny1)ethanol; 3,4-DHPEA-EA, isomer of the oleuropein aglycon; HPLC, high-performance liquid chromatography; DAD, diode array detector; NMR, nuclear magnetic resonance; CCC, central composite circumscribed design; FLD, fluorescence detector; HS-SPME-GC/MS, headspace−solid phase microextraction−gas chromatography−mass spectrometry; DVB/CAR/PDMS, divinylbenzene/carboxen/poly(dimethylsiloxane); EFC, electronic flow controller; PCA, principal component analysis; PLS, partial least-squares analysis

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REFERENCES

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ASSOCIATED CONTENT

S Supporting Information *

Text describing PCA models, one for each cultivar, utilized to select the few analytical variables for the RSM optimization and figures showing score and loading plots of the first two principal components of the PCA models of EVOOs. This material is available free of charge via the Internet at http://pubs.acs.org.

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AUTHOR INFORMATION

Corresponding Author

*Phone: +39 075 5857903. Fax: +39 075 5857916. E-mail: [email protected]. Funding

This study was kindly supported by the Consorzio Olivicolo Italiano UNAPROLItaly (Projects Reg. UE 1220/2011). Notes

The authors declare no competing financial interest. 3820



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