Regional and cultivar comparison of Italian single cultivar olive oils according to flavor profiling

Research Article

Regional and cultivar comparison of Italian single cultivarolive oils according to flavor profiling

Debora Tura1, Osvaldo Failla1, Daniele Bassi1, Cristina Attilio2 and Arnaldo Serraiocco3

1 Dipartimento di Scienze Agrarie e Ambientali (DiSAA), Universita degli Studi di Milano, Milano, Italy2 CNR, IVALSA – Istituto per la valorizzazione del legno e delle specie arboree, Sesto Fiorentino (FI), Italy3 CRA-OLI – Consiglio per la ricerca e la sperimentazione in agricoltura, Centro di ricerca per l’olivicoltura e

l’industria olearia, Citta S. Angelo section, Citta S. Angelo (PE), Italy

Geographical origin, cultivar, and olive ripening stage are important factors which affect the typical flavor

profile of extra virgin olive oils. Aromatic compounds and sensorial profiles of ‘‘Casaliva’’, ‘‘Frantoio’’,

and ‘‘Leccino’’ olive oils from three different Italian production regions Abruzzo (eastern-central Italy),

Lombardy (northern Italy), and Tuscany (western-central Italy) were assessed in two cropping years and

at three olive ripening stages (green, veraison, and ripe). The chemical aromatic compounds were more

effective in discriminating the oils than their sensorial attributes. Oils showed peculiar aromatic and

sensorial profiles according to their region of origin. Genetically similar ‘‘Casaliva’’ and ‘‘Frantoio’’

showed also analogous profiles, but distinct from ‘‘Leccino’’. The interaction between regions of

cultivation and cultivars significantly affected the flavor profiling.

Practical applications: This research provides a sound proof that geographical origin, cultivar, and

fruit ripening stage, could play an important interactive role in shaping the flavor profiling of extra virgin

olive oils. This represents a scientific basis of the ‘‘typicality’’ concept, which should address the

marketing strategies for exploiting of the PDO products.

Keywords: Aroma / Olea europaea L. / Panel test / Phenol / Volatile

Received: March 10, 2012 / Revised: September 5, 2012 / Accepted: October 19, 2012

DOI: 10.1002/ejlt.201200104

1 Introduction

It is a common knowledge that a correct nutrition is the basis

for a good health. Already Hippocrates, father of modern

Medicine, claimed that ‘‘good health implies an awareness of

the powers of natural or processed food’’ (460–377 BC), and

also Leonardo da Vinci (1452–1519 AD) believed that

‘‘a man’s life depends on what he eats’’. Lipids are important

in nutrition and extra virgin olive oil plays a predominant role

in the Mediterranean diet, recognized for its high qualitative

composition (i.e., mono- and poly-unsaturated fatty acid,

phenols, tocopherols, etc.) and its nutraceutic proprieties

(i.e., reduction of coronary heart disease risk factor, preven-

tion of several types of cancer, modification of immune and

inflammatory responses, etc.), so it has been regarded for a

long time between a food and a drug [1].

In Europe, other than standard virgin and extra virgin

olive oils differing for anonymous cultivars blend (and region

of origin), following the EU legislation, the olive oils can be

further characterized by different production protocols

where also cultivars (e.g., for Protected Designation of

Origin and Protected Geographical Indication) or specific

cultivation procedures (i.e., for ‘‘organic’’ agriculture) are

regulated. In addition to well-grounded reasons for consid-

ering olive oil one of the best nutritional tool for improving

good health [2], it could be characterized by flavor profiles,

i.e., either light and delicate or with intense fruity notes,

slightly or intensely bitter and/or pungent, etc., which are

appreciated and considered for an adequate and better associ-

ation in foods preparation. Also, the volatile compounds in

Correspondence: Dr. Debora Tura, Universita degli Studi di Milano,

Dipartimento di Scienze Agrarie e Ambientali (DiSAA), via Celoria 2, 20133

Milano, Italy

E-mail: [email protected]

Fax: þ39 02 5031 6553

Abbreviations: C, olive cultivar; C T S, olive cultivar per ripening stage

interaction; LA, linoleic acid; LnA, linolenic acid; LOX, lipoxygenase

pathway; R, region of cultivation; R T C, region of cultivation per olive

cultivar interaction; R T S, region of cultivation per ripening stage

interaction; S, ripening stage; �, p � 0.05 (5%); ��, p � 0.01 (1%); ��,

p � 0.001 (0.1%)

196 Eur. J. Lipid Sci. Technol. 2013, 115, 196–210

� 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim www.ejlst.com

extra virgin olive oil play an important role not only for their

contribution to flavor, but also for place of production trace-

ability. To this end, the work of Zunin et al. [3] found that

three volatile terpenoid hydrocarbons (a-copaene, a-muur-

olene, a-farnesene) were fundamental for distinguishing

commercial oils of Liguria (northern Italy) from those pro-

duced in different Mediterranean regions, confirming the

important role of volatile compounds in olive oil character-

ization, although without taking into account the diverse

cultivar blend of the oils.

Environmental (climatic and soil) conditions, horticul-

tural practices, fruit ripening stage, and oil extraction pro-

cedures affect both the chemical composition and the

sensorial profile of monovarietal virgin olive oils [4].

Aguilera et al. [5], characterized two Italian cultivars,

‘‘Frantoio’’ and ‘‘Leccino’’, grown in two different areas in

Andalusia (Spain). The oils from the hilly location showed a

greater content of oleic acid and higher stability, while those

from the valley were characterized by higher tocopherols and

linoleic acid content. Moreover, the oils from Andalusia

showed higher concentration in antioxidants, greater oxi-

dative stability, and more marked sensorial characters than

oils of the same cultivars from Italy. Oils from three Italian

regions (Lombardy, Tuscany, and Abruzzo) were distin-

guished by composition of fatty acids, triacylglicerols, sterols,

phenols, tocopherols, and oxidative stability regardless the

four cultivars evaluated: ‘‘Casaliva’’, ‘‘Frantoio’’, ‘‘Leccino’’,

and ‘‘Pendolino’’ [6, 7]. Also Koprivnjak et al. [8] found

that five volatile compounds, hexanal among those, proved

to be useful to distinguish the oils from the three most

important cultivars in Istria (Croatia): ‘‘Leccino’’, ‘‘Buza’’,

and ‘‘Bjelica’’, although the influence of the year was also

highly significant.

In relation to the composition of the volatile fraction in

virgin olive oils and the activity of the enzymes involved in the

metabolic pathways, while the amount of enzymes strictly

depends on the genetic factor (cultivar), their activity is

mostly affected by the processing conditions [9].

Many analytical methods are available for the determi-

nation of the geographical origin of foods [10]. An unam-

biguous determination of the geographical origin seems

feasible when various parameters are measured in a food

product. Combining different analytical techniques and

applying chemometric procedure is possible to detect even

light difference between food samples. Many techniques are

available for assessing the geographical origin of oils, in

particular GC–MS for volatile compounds [11–13] and

sensory analysis for overall flavor.

Analyzing the oil headspace by direct MS without any

chromatographic separation, it was possible to classify the oils

in different commercial classes with an acceptable correlation

with the result an expert panel assessment [14]. Additionally,

it was possible to distinguish the different aromas of com-

mercial extra virgin oils from various cultivars harvested in

several areas (Liguria and Puglia in Italy, Spain, Greece, and

Tunisia) with a mean prediction ability of 80% [15]. The

accuracy of prediction was influenced both by region and

cultivar.

Another method assessed to discriminate the oil quality is

the electronic nose. By this technique it was possible not

only to distinguish among oils of different quality, but also

the cultivar and even the production area [16]. Furthermore,

applying a classification method based on a mathematic

model (CAIMAN) by chemical data from electronic tongue

and nose, several oil samples were characterized according to

their geographical origin, typicality, authenticity, and unique-

ness [17].

The combination of 1H NMR fingerprinting with chemo-

metric analysis provides an original approach to study the

identity of commercial oils from different cultivars in relation

to the country of origin (Italy, Tunisia, Turkey, Greece, and

Spain), to the different regions in the same country (Puglia,

Sicily, Lazio, Tuscany, Liguria, and Lombardy in Italy), or to

the year [18, 19].

Furthermore, several works classified extra virgin olive

oils according to their geographical origin by means of IR

spectroscopy. For example, Sinelli et al. [20] achieved highly

correct classification rates of olive oil samples from different

regions (Lombardy, Tuscany, and Calabria) by near-infrared

and mid-infrared spectroscopy combined with chemometric

analysis. In particular, it was possible to better classify about

90% of commercial oils (cultivar blends) on the basis of the

geographical origin by near-infrated, while by mid-ifrared it

was possible to classify both monovarietal (‘‘Casaliva’’,

‘‘Leccino’’, and ‘‘Frantoio’’) and commercial oils, allowing

a correct classification of more than 95% of the samples.

However, in both experiments the cultivar was not taken into

consideration for the classification of geographical origin.

Finally, it should be noted that in most of the above

studies aimed at oils discrimination by their geographical

origin, it is not possible to separate the environmental to

the genetic (cultivar) effect, since oils from different regions

most often derive from blend of local cultivars. Moreover,

differences in olive orchard management as well as the ripen-

ing stages of harvested fruit, and the processing techniques

for oil extraction may strongly affect the differences detected

in the oils.

Overall, there is a scant availability in the literature of

sound data related to the possibility to discriminate between

cultivar and environmental effect on olive oil quality, where

the specific contribution of both factors and their possible

interaction can be unambiguously ascertained.

The scientific aims of this work were: first, to estimate the

relative role of cultivar (C), region of cultivation (R), fruit

ripening stage (S), and their interactions (C � R, C � S, and

R � S) on the virgin oil flavor profile, expressed in term of

volatile compounds concentration and sensorial descriptors;

second, to examine which volatile compounds and sensorial

attributes have a major role in discriminating the different

sources of variation found in the experiment. From the

Eur. J. Lipid Sci. Technol. 2013, 115, 196–210 Regional olive oil cultivars comparison 197


practical point of view, it should be underlined that the

Protected Designation of Origin market policy is based on

a speculative assumption that the typicality of an agricultural

product is just based on irreproducible specific factors of

production. In the case of virgin olive oil, site of cultivation,

cultivars, and their interactions are presumed to play a major

role. Following the scientific literature, experiments to dem-

onstrate this assumption are not available. To fill this gap, the

present work has been carried out.

2 Materials and methods

A semi-orthogonal experimental plan was designed involving

three different Italian regions: Lombardy, at north, Abruzzo,

in the eastern-central and Tuscany in the western-central

part, respectively (Fig. 1). Three well-known olive cultivars

(‘‘Casaliva’’, ‘‘Frantoio’’ and ‘‘Leccino’’) were assessed at

three ripening stages (green, veraison, and ripe). The exper-

iment was repeated for two years (2009 and 2010). The

deviation from the orthogonality of the experimental plan

was due to the lack of ‘‘Casaliva’’ cultivar in Tuscany.

Moreover, additional unbalancing were due to the alternate

bearing of the olive tree, that in more than one occasion

reduced, to different extent, the crop load. Therefore, in

some occurrences, the experimental plan was adapted to

the circumstances by selecting less than three ripening stages

or omitting at all the year samplings. As a result, 33 exper-

imental oils were obtained in respect to the 54 expected by the

full orthogonal design. Chemical and sensorial data on oil

flavor profile were run in order to assess the relative import-

ance of the main possible sources of variability.

2.1 Oil sampling

All 33 oil samples were obtained each one from about 10 kg

of olives (Olea europaea L.) by a standard discontinuous

procedure within 1-day from picking. The olives, collected

on the bases of their ripening stage (green, veraison, and ripe)

in according to the maturity index suggested by Uceda [21],

were crushed with a stainless steel hammer crusher mill and

malaxed for 30 min at 288C. The oil was extracted by

hydraulic press (max 20 MPa) and separated by centrifu-

gation at 2000 rpm. The oils were classed as ‘‘virgin’’ because

the acidity, the peroxide number, K232, K270, and DK of all

Figure 1. Experimental design of oil sampling and environmental description of the growing areas characteristics.

198 D. Tura et al. Eur. J. Lipid Sci. Technol. 2013, 115, 196–210


oils were under the limits of the Commission Regulation

(UE) no. 1989/2003 [22].

2.2 Volatile compounds analysis

The volatile composition was determined following the

extraction procedure and GC analysis described in

Angerosa et al. [23].

2.2.1 Volatile compounds extraction

Fifty grams of oil was put into a 120 mL Drechsel gas

washing bottle with a porous distributor together with

10 mg of 1-nonanol (Sigma–Aldrich) as internal standard.

Volatile were stripped with nitrogen (1.2 L/min at 378C) for

2 h, trapped on 50 mg of activated charcoal and eluted with

1 mL of diethyl ether.

2.2.2 GC-flame ionisation detector analysis

0.5 mL of diethyl ether solution was injected on-column into

GC (HRGC 5160 Mega Series, Carlo Erba) fitted with a

fused silica capillary column (Supelcowax 10, Supelco; 60 m

length, 0.32 mm inner diameter, 0.5 mm film thickness) and

a CO2 cryogenic accessory to hold the oven at 258C. The

oven temperature program was: 258C for 6 min, increase of

18C/min until 468C for 0 min, increase of 4.28C/min until

708C for 0 min, increase of 3.38C/min until 2008C for 5 min.

The pressure of H2 carrier gas was at 30 kPa and the

flame ionisation detector detector was held at 2208C. The

volatile compounds were quantified by peak area integration

(Mega Series Integrator, Carlo Erba) and the results were

expressed in mg of 1-nonanol on kg of oil. Also, the aromatic

composition was summarized by chemical affinity (alcohols,

aldehydes, and ketons) and similar biosynthetic pathway

from lipoxygenase (LOX) of linoleic (LA) or linolenic acid

(LnA). As it is known, C5 compounds (1-penten-3-one,

trans-2-pentenal, 1-penten-3-ol and cis-2-penten-1-ol)

originate from LOX of LnA, whereas C6 compounds derive

both from LOX of LA (hexanal and hexan-1-ol) and from

LOX of LnA (trans-2-hexenal, cis-3-hexen-1-ol and trans-2-

hexen-1-ol).

2.3 Phenols analysis

The phenols composition was determined by modifying the

HPLC procedures described in Tura et al. [7].

2.3.1 Phenolic compounds extraction

Ten grams oil plus 5 mL hexane plus 6.25 mL methanol/

water solution (60:40) plus 0.5 mL 0.01% syringic acid as

internal standard (Fluka) in methanol were shaken for

15 min, then the mixture was centrifuged at 3000 rpm for

10 min. The methanol–water phase was recuperated in a

separator funnel, whereas the hexane-oil phase was extracted

again two times. The three united methanol–water phases

were washed two times with 7.5 mL hexane and 10 mL were

evaporated under vacuum at 358C and the residue was dis-

solved with 1 mL methanol–water solution before HPLC

injection.

2.3.2 HPLC analysis

Twenty microliters of dissolved residue was injected in

HPLC (CM 4000 – Milton Roy) with Spherisorb RP-18

column (25 cm � 4.6 mm, i.d. 5 mm – Merck), using a

mobile phase gradient of (A) acetonitrile/methanol solution

(50:50) and (B) 2% acetic acid in water (2% A at 0 min, 17%

A at 20 min, 30% A at 25 min, 30% A at 30 min, 35% A at

40 min, 52% A at 45 min, 52% A at 50 min, 75% A at

60 min, 100% A at 63 min, 100% A at 68 min, 2% A

at 70 min). The flow rate was 1 mL/min and the detector

was a photodiode spectrophotometer (DAD – Waters) at

270 nm. The results were expressed in mg of tyrosol on kg

of oil. For the purpose of the present work the phenols were

reported as a total, then the single compounds were not

considered.

2.4 Sensory analysis

The sensory evaluation was carried out following the pro-

cedures described in the enclosure XII of the Commission

Regulation (EC) no. 796/2002 [24], but modifying the sen-

sorial profile sheet according to a parametric non-structured

assessment based on many olfactory, gustatory, and tactile

descriptors. About 15–20 mL of oil were put in blue glasses

warmed at 28–308C. Eight trained tasters from three different

panel groups evaluated the sensory notes of all samples.

Data was expressed in arbitrary units (A.U.). ‘‘Green’’

notes include the following descriptors: ‘‘lawn’’, ‘‘leaf’’,

‘‘artichoke’’, ‘‘walnut’’, and ‘‘hay’’. ‘‘Floral’’ notes include

‘‘flowers’’ and ‘‘butter’’ descriptors. ‘‘Fruity’’ notes include

‘‘olives’’, ‘‘banana’’, ‘‘tomato’’, ‘‘almond’’, and ‘‘apple’’

descriptors. ‘‘Taste’’ notes include ‘‘bitter’’, ‘‘pungent’’

and ‘‘astringency’’. ‘‘Satisfaction’’ is the overall hedonistic

score considering all together the attributes of aroma, taste,

and flavor.

2.5 Statistical analysis

Normal distribution of chemical and sensory variables was

checked by the Kolmogorov–Smirnov test. When distri-

bution was not normal, the SD was not reported in tables.

In order to test the significance of the differences among

chemical and sensory variables in relation to geographical

origin, cultivar, and ripening stage, data were processed by

ANOVA, following the general linear model (GLM) pro-

cedure, which included these factors and their interaction

as sources of variation. To achieve more robust results,



according to the aim of this study, year was not included in

the model. To test the significance of the other source of

variation, the year effect was considered in the residual

variability. General linear model procedure was adopted

for its suitability to process unbalanced experimental designs.

Means were separated according to Duncan’s multiple com-

parison test. The magnitude of variability in oil composition

and sensory notes, attributable to the different sources of

variability (region, cultivar, ripening stage, and their inter-

actions) was quantified in terms of the expected components

of the variance. In order to evaluate the importance of the

chemical and sensory variables to distinguish oils from differ-

ent regions, cultivars, ripening stages and ‘‘region per culti-

var’’ interaction, discriminant analyses were performed by

step-wise method, separately for the two set of chemical and

sensory data, respectively.

Data were processed by an SPSS statistical package (version

14.0 for Windows – SPSS, Chicago, Illinois, 2006).

3 Results

3.1 Chemical aromatic profile

The aromatic composition and the total volatile compounds

with chemical affinity or similar biosynthetic pathway are

reported in Table 1. The total volatiles ranged from

452 mg/kg in ‘‘Leccino’’ from Tuscany at veraison stage in

2010, to 2591 mg/kg in ‘‘Casaliva’’ from Lombardy at green

stage in 2010. The same samples showed also minimum and

maximum values of total C6 volatile compounds (265 and

2410 mg/kg), in particular from lipoxygenase pathway

(LOX) of linolenic acid (LnA; 215 and 2277 mg/kg), and

for total aldehydes (203 and 2316 mg/kg), respectively. Total

alcohols ranged from 53 (‘‘Leccino’’ from Tuscany at ripe

stage in 2009) to 483 (‘‘Leccino’’ from Abruzzo at veraison

in 2010). Total ketons ranged from 5.7 (‘‘Frantoio’’ from

Lombardy at ripe stage in 2010) to 81 (‘‘Leccino’’ from

Table 1. Oil chemical aromatic profile (two years average): value range, mean, SD, and expected variance component due to region, cultivar,

ripening stage, and their interactions for 33 oil samples

Compound

Range

(mg/kg)

Mean

(mg/kg)

SD

(mg/kg)

Variance (%)

Region Cultivar Ripening R � C C � S R � S

n-Octane 1.16–313.38 35.09 n.r. 5.3 1.6 1.1 0.0 7.8 0.0

Ethyl acetate 4.84–28.57 9.40 n.r. 0.0 1.0 0.0 0.2 0.0 27.6

2-Methyl-butanal 0.82–34.23 6.00 n.r. 31.1 3.7 0.0 7.1 0.0 0.4

3-Methyl-butanal 0.99–39.28 8.04 8.44 22.7 7.0 0.0 9.7 0.0 0.6

Ethanol 2.40–41.27 10.84 n.r. 0.0 2.0 8.5 0.0 0.0 0.0

Pentan-3-one 3.19–70.14 14.84 12.18 0.0 0.0 0.0 4.0 1.6 33.7

1-Penten-3-one 1.66–15.57 7.77 4.35 7.8 0.0 11.6 4.6 1.9 35.9

Hexanal 15.23–227.76 67.66 46.20 1.1 0.0 7.0 24.1 0.0 0.0

2-Methyl-propan-1-ol 0.31–1.86 0.77 0.40 0.0 0.0 0.0 2.4 13.1 26.5

trans-2-Pentenal 2.33–12.21 7.18 2.78 0.0 12.6 0.0 0.0 0.0 34.0

1-Penten-3-ol 11.51–60.21 32.09 14.51 0.0 24.2 9.2 0.0 0.0 14.4

3-Methyl-butan-1-ol 3.57–133.70 15.00 n.r. 0.0 0.0 0.4 4.5 3.3 0.0

trans-2-Hexenal 85.87–2174.13 1073.40 472.18 8.6 32.0 13.6 25.7 0.0 1.4

Pentan-1-ol 0.25–17.23 1.91 n.r. 0.0 0.0 1.2 30.3 0.0 0.0

cis-2-Penten-1-ol 6.63–35.98 19.45 8.34 0.0 32.2 7.4 0.0 0.0 9.5

Hexan-1-ol 2.48–97.66 16.06 n.r. 3.0 6.8 9.1 0.0 0.0 6.3

cis-3-Hexen-1-ol 2.16–74.54 22.37 n.r. 12.0 0.0 0.0 1.0 6.3 9.6

trans-2-Hexen-1-ol 8.45–235.80 46.68 46.98 11.8 0.0 9.3 15.1 0.0 4.8

Acetic acid 0.12–14.25 1.52 n.r. 0.0 0.0 0.0 6.3 0.0 0.0

Octan-1-ol 0.21–14.72 1.28 n.r. 0.0 0.0 0.0 9.5 0.6 3.7

Total alcohols 53.17–482.88 166.45 91.31 8.8 0.0 0.7 14.5 0.0 0.0

Total aldehydes 203.14–2315.98 1162.28 483.52 10.7 32.9 15.4 2.6 0.0 1.3

Total ketons 5.67–81.04 22.60 14.27 0.0 0.0 0.0 5.9 2.9 38.4

Total C5 compounds 28.37–121.14 66.50 27.20 0.0 22.5 8.0 0.0 0.0 21.0

Total C6 compounds 265.02–2409.96 1226.16 476.56 16.9 27.9 11.6 5.4 0.0 2.1

Total C6 from LA 17.85–237.36 83.72 50.86 1.8 0.0 0.0 31.9 0.0 2.7

Total C6 from LnA 215.24–2276.53 1142.44 469.01 12.8 28.0 10.9 7.1 0.0 2.6

Total volatiles 451.77–2591.32 1397.35 504.61 15.2 27.2 13.0 14.0 0.0 6.5

Total phenols 37.13–477.70 270.40 99.81 49.6 0.0 0.0 16.7 4.1 2.8

n.r., not reported because frequency distributions were not normal according to Kolmogorov–Smirnov test (p ¼ 0.05); LA, linoleic acid;

LnA, linolenic acid; R, region; C, cultivar; S, stage of ripening.



Table 2. Oil chemical aromatic profile: comparison among 33 oils for region, cultivar, ripening stage, and ‘‘region T cultivar’’ interaction

Compound (mg/kg)

Region Cultivar Ripening stage

Abruzzo Lombardy Tuscany Casaliva Frantoio Leccino Green Veraison Ripe

n-Octane 56.63 aa) 33.73 a 16.46 a 44.41 aa) 53.92 a 14.98 a 68.59 aa) 20.03 a 7.81 a

Ethyl acetate 10.50 a 8.06 a 11.16 a 7.26 a 8.12 a 11.64 a 9.15 a 9.95 a 8.75 a

2-Methyl-butanal 13.67 b 2.76 a 5.20 a 4.27 a 3.96 a 8.59 a 6.56 a 6.32 a 4.39 a

3-Methyl-butanal 16.35 b 4.02 a 8.30 ab 5.52 a 5.26 a 11.68 a 8.15 a 8.94 a 6.07 a

Ethanol 10.13 a 10.02 a 13.31 a 10.17 a 8.64 a 12.96 a 6.88 a 14.51 a 10.32 a

Pentan-3-one 19.00 a 14.54 a 11.29 a 12.84 a 14.39 a 16.33 a 13.59 a 18.57 a 9.51 a

1-Penten-3-one 5.93 a 9.84 b 5.21 a 9.30 a 6.58 a 7.82 a 9.28 b 8.03 ab 4.66 a

Hexanal 92.01 b 69.12 ab 40.19 a 77.51 a 73.49 a 57.45 a 90.91 a 57.60 a 47.90 a

2-Methyl-propan-1-ol 0.71 a 0.84 a 0.66 a 0.69 a 0.70 a 0.86 a 0.85 b 0.85 b 0.44 a

trans-2-Pentenal 5.90 a 8.00 a 6.72 a 8.14 b 8.25 b 5.79 a 7.79 a 7.39 a 5.72 a

1-Penten-3-ol 30.20 a 35.33 a 27.11 a 39.37 b 38.58 b 22.84 a 38.90 b 31.51 ab 21.59 a

3-Methyl-butan-1-ol 25.50 a 10.67 a 13.69 a 11.19 a 11.82 a 19.67 a 10.80 a 21.66 a 8.87 a

trans-2-Hexenal 960.43 ab 1267.25 b 774.43 a 1428.79 b 1220.98 b 754.36 a 1304.01 b 982.80 ab 859.27 a

Pentan-1-ol 4.52 a 0.95 a 1.34 a 0.82 a 1.32 a 3.00 a 1.87 a 2.48 a 0.85 a

cis-2-Penten-1-ol 17.49 a 21.40 a 17.27 a 23.94 b 23.36 b 13.82 a 22.88 b 19.08 ab 14.32 a

Hexan-1-ol 17.10 a 19.84 a 6.98 a 14.01 a 9.99 a 22.00 a 6.99 a 16.52 ab 30.71 b

cis-3-Hexen-1-ol 13.60 a 31.48 b 11.77 a 31.31 a 19.74 a 19.32 a 21.23 a 18.86 a 31.31 a

trans-2-Hexen-1-ol 71.68 c 50.75 b 13.00 a 46.22 ab 32.84 a 57.80 b 30.89 a 62.62 b 41.85 ab

Acetic acid 3.68 a 0.45 a 1.65 a 0.57 a 1.28 a 2.26 a 1.62 a 1.97 a 0.46 a

Octan-1-ol 2.54 a 0.56 a 1.54 a 0.53 a 1.25 a 1.73 a 1.67 a 1.29 a 0.59 a

Total alcohols 193.48 b 181.85 b 106.67 a 178.24 a 148.23 a 174.02 a 142.96 a 189.38 a 160.84 a

Total aldehydes 1088.36 ab 1351.15 b 834.85 a 1524.22 b 1311.94 b 837.86 a 1417.40 b 1063.07 a 923.35 a

Total ketons 24.93 a 24.38 a 16.51 a 22.14 a 20.97 a 24.16 a 22.87 a 26.59 a 14.17 a

Total C5 compounds 59.52 a 74.57 a 56.32 a 80.75 b 76.78 b 50.28 a 78.85 b 66.02 ab 46.29 a

Total C6 compounds 1154.83 ab 1438.45 b 846.38 a 1597.85 b 1357.03 b 910.94 a 1454.03 b 1138.40 ab 1011.04 a

Total C6 from LA 109.12 b 88.96 ab 47.18 a 91.52 a 83.47 a 79.45 a 97.90 a 74.12 a 78.61 a

Total C6 from LnA 1045.71 ab 1349.49 b 799.20 a 1506.33 b 1273.56 b 831.48 a 1356.14 b 1064.28 ab 932.43 a

Total volatiles 1377.57 b 1599.62 b 987.30 a 1776.84 b 1544.46 b 1064.92 a 1662.60 b 1310.98 a 1115.38 a

Total phenols 254.02 a 220.17 a 393.52 b 266.93 a 271.20 a 271.74 a 278.73 a 270.53 a 255.85 a

Compound [mg/kg]

‘‘Region � cultivar’’ interaction

Abruzzo Lombardy Tuscany

Casaliva Frantoio Leccino Casaliva Frantoio Leccino Frantoio Leccino

n-Octane 88.79 aa) 76.59 a 30.57 a 29.61 a 71.52 a 6.34 a 20.58 a 12.35 a

Ethyl acetate 6.45 a 7.11 a 14.21 a 7.53 a 7.06 a 9.44 a 9.94 a 12.37 a

2-Methyl-butanal 11.10 bc 7.68 ab 17.96 c 1.99 a 1.53 a 4.57 ab 5.15 ab 5.26 ab

3-Methyl-butanal 13.22 ab 9.06 a 21.55 c 2.95 a 1.90 a 6.85 a 7.54 a 9.05 a

Ethanol 5.38 a 4.88 a 15.14 a 11.77 a 7.85 a 10.07 a 11.50 a 15.11 a

Pentan-3-one 10.21 a 11.53 a 27.13 a 13.71 a 15.91 a 14.24 a 13.91 a 8.68 a

1-Penten-3-one 4.95 a 6.54 a 6.11 a 10.75 a 8.86 a 9.74 a 3.77 a 6.66 a

Hexanal 55.79 ab 78.36 ab 116.95 b 84.75 ab 87.01 ab 38.58 a 54.14 ab 26.25 a

2-Methyl-propan-1-ol 0.70 a 0.65 a 0.74 a 0.69 a 0.80 a 1.03 a 0.59 a 0.72 a

trans-2-Pentenal 7.60 a 7.18 a 4.41 a 8.32 a 8.81 a 7.01 a 8.10 a 5.35 a

1-Penten-3-ol 36.51 a 35.53 a 24.38 a 40.32 a 41.84 a 24.92 a 36.03 a 18.20 a

3-Methyl-butan-1-ol 9.99 a 12.85 a 39.58 a 11.58 a 11.35 a 9.19 a 11.88 a 15.49 a

trans-2-Hexenal 1151.48 ab 1534.82 b 577.70 a 1521.23 b 1314.50 b 973.91 ab 947.18 ab 601.69 a

Pentan-1-ol 0.55 a 0.59 a 8.47 b 0.91 a 1.10 a 0.88 a 1.96 a 0.71 a

cis-2-Penten-1-ol 23.21 ab 24.12 ab 11.31 a 24.18 ab 24.73 b 15.85 ab 21.26 ab 13.29 ab

Hexan-1-ol 3.34 a 3.88 a 30.60 a 17.57 a 14.28 a 26.75 a 7.68 a 6.29 a

cis-3-Hexen-1-ol 10.27 a 17.13 a 13.50 a 38.32 a 29.91 a 25.94 a 8.32 a 15.22 a

(Continued )



Abruzzo at veraison stage in 2000). Total C5 volatile com-

pounds ranged from 28 (‘‘Leccino’’ from Abruzzo at green

stage in 2010) to 121 (‘‘Casaliva’’ from Lombardy at green

stage in 2010). C6 compounds from LOX of linoleic acid

(LA) ranged between 18 (‘‘Leccino’’ from Tuscany at ripe

stage in 2009) and 237 (‘‘Leccino’’ from Abruzzo at green

stage in 2010).

In general, as main of source of variability on chemical

composition, region of cultivation (R), and olive cultivar (C)

were more important than the ripening stage (S), while in

term of interaction, C � S showed no effect. Moreover, the

aromatic composition of the oil was affected by R, C, S, and

R � C interaction (Table 2). The following compounds were

peculiar in characterizing the region of origin: 2- and 3-

methyl-butanal (variance explained by R of 31.1%�� and

22.7%�, both higher in Abruzzo), 1-penten-3-one (7.8%�,

higher in Lombardy), trans-2-hexenal (8.6%�, higher in

Lombardy and low in Tuscany), cis-3-hexen-1-ol (12.0%�,

higher in Lombardy), trans-2-hexen-1-ol (11.8%��, lower in

Tuscany and higher in Abruzzo), total alcohols (8.8%�, lower

in Tuscany), aldehydes (10.7%�, higher in Lombardy and

lower in Tuscany), C6 compounds and C6 volatiles from

LnA (16.9%� and 12.8%�, lower in Tuscany and higher

in Lombardy), total volatiles and phenols (15.2%� and

49.6%��, respectively lower and higher in Tuscany).

The compounds affected by cultivar were: trans-2-pentenal,

1-penten-3-ol, trans-2-hexenal, cis-2-penten-1-ol, total

aldehydes, C5 and C6 compounds, total and from LOX of

LnA, and total volatiles (respectively 12.6%�, 24.2%�,

32.0%��, 32.2%��, 32.9%��, 22.5%�, 27.9%��, and

28.0%��, 27.2%��, all lower in ‘‘Leccino’’). The ripening

stage influence effected 1-penten-3-one, 1-penten-3-ol,

trans-2-hexenal and cis-2-penten-1-ol, total aldehydes, C5

and C6 compounds, both total and from LOX of LnA,

and on total volatiles as well (respectively 11.6%�, 9.2%�,

13.6%�, 7.4%�, 15.4%�, 8.0%�, 11.6%�, 10.9%�, and

13.0%�, all higher in ‘‘green’’ and lower in ‘‘ripe’’ stage)

which decreased during ripening. An opposite trend for

hexan-1-ol (9.1%�, lower in ‘‘green’’ and higher in ‘‘ripe’’

stage) and trans-2-hexen-1-ol (9.3%�, higher in ‘‘veraison’’

stage) were detected: the first one increased with olive

ripening while the second showed a bell-shaped trend, with

a maximum at ‘‘veraison’’ stage.

‘‘Region � cultivar’’ interaction affected: 2- and 3-

methyl-butanal, pentan-1-ol and trans-2-hexen-1-ol

(7.1%�, 9.7%�, 30.3%�, and 15.1%�, higher in ‘‘Leccino’’

from Abruzzo), hexanal (24.1%�, higher in ‘‘Leccino’’ from

Abruzzo and lower in ‘‘Leccino’’ from Lombardy and

Tuscany), trans-2-hexenal (25.7%�, lower in ‘‘Leccino’’ from

Abruzzo and Tuscany), total alcohols and C6 compounds

from LOX of LA (14.5%� and 31.9%�, higher in ‘‘Leccino’’

from Abruzzo and lower in ‘‘Leccino’’ from Tuscany), total

volatiles (14.0%�, higher in ‘‘Frantoio’’ from Abruzzo and

‘‘Casaliva’’ from Lombardy and lower in ‘‘Leccino’’ from

Tuscany) and total phenols (16.7%�, higher in ‘‘Leccino’’

from Tuscany). ‘‘Cultivar � stage of ripening’’ interaction

did not affect any compound in particular, whereas

‘‘region � stage of ripening’’ interaction was influenced

by ethyl acetate (27.6%�), pentan-3-one (33.7%�), 1-

penten-3-one (35.9%�), 2-methyl-propan-1-ol (26.5%�),

trans-2-pentenal (34.0%�), total ketons, and C5 compounds

(38.4%� and 21.0%�).

The oil classifications according to region, cultivar,

ripening stage, and ‘‘region � cultivar’’ interaction are

reported in Fig. 2 and Table 3. The oils from the three regions

were well separated (first two functions: eigenvalue 19.2

and 7.1; variance 73 and 27%; r ¼ 0.975�� and 0.936��),

mainly by the contribution of 2- and 3-methyl-butanale, 1-

penten-3-ol, 3-methyl-butan-1-ol, cis-2-penten-1-ol, cis-3-

Hexen-1-ol, trans-2-hexen-1-ol, acetic acid and octan-1-ol.

The ‘‘Casaliva’’ and ‘‘Frantoio’’ were well separated from

‘‘Leccino’’ by a linear function (eigenvalue 10.7, variance

92% and r ¼ 0.956�) mainly by the relative content of

pentan-1-ol, cis-2-penten-1-ol, acetic acid, octan-1-ol.

The ‘‘veraison’’ and ‘‘ripe’’ stages were not well separated

but clearly distinguished from the ‘‘green’’ stage (first

two functions: eigenvalue 11.8 and 2.2, variance 84

and 16%, r ¼ 0.960�� and 0.832�) according to the relative

trans-2-Hexen-1-ol 24.57 a 39.37 a 111.40 b 53.44 ab 44.89 ab 52.96 ab 14.52 a 11.48 a

Acetic acid 0.55 a 0.59 a 6.79 b 0.57 a 0.36 a 0.39 a 2.77 ab 0.53 a

Octan-1-ol 0.39 a 0.46 a 4.65 a 0.58 a 0.57 a 0.54 a 2.51 a 0.58 a

Total alcohols 114.92 ab 139.47 ab 259.77 b 199.35 ab 177.31 ab 168.14 ab 116.26 ab 97.09 a

Total aldehydes 1239.19 ab 1637.11 b 738.57 a 1619.23 b 1413.74 b 1030.91 ab 1022.10 ab 647.59 a

Total ketons 15.16 a 18.07 a 33.24 a 24.46 a 24.77 a 23.98 a 17.68 a 15.33 a

Total C5 compounds 72.28 a 73.38 a 46.20 a 83.57 a 84.24 a 57.52 a 69.16 a 43.49 a

Total C6 compounds 1245.45 abc 1673.57 c 850.15 a 1715.31 c 1490.58 bc 1118.14 abc 1031.83 ab 660.92 a

Total C6 from LA 59.13 a 82.24 ab 147.55 b 102.32 ab 101.29 ab 65.33 a 61.81 a 32.54 a

Total C6 from LnA 1186.32 abc 1591.32 c 702.60 a 1612.99 c 1389.29 bc 1052.81 abc 970.02 ab 628.38 a

Total volatiles 1465.05 bc 1878.95 c 1083.15 ab 1880.76 c 1694.76 bc 1239.20 abc 1189.34 ab 785.26 a

Total phenols 363.05 bc 255.74 ab 198.64 a 234.90 a 212.93 a 211.47 a 351.78 bc 435.26 c

a) Rows: values with the same letter are not statistically different at p ¼ 0.05 separately for region, cultivar, ripening stage, and

‘‘region � cultivar’’ interaction.

LA, linoleic acid; LnA, linolenic acid.



content of trans-2-pentenal, 1-penten-3-ol, 3-methyl-butan-

1-ol, pentan-1-ol, trans-2-hexen-1-ol, acetic acid and

octan-1-ol. ‘‘Casaliva’’ and ‘‘Frantoio’’ from Lombardy

and Abruzzo were well distinguished from ‘‘Leccino’’ from

all regions (first two functions: eigenvalue 112 and 62.4,

variance 55 and 31%, r ¼ 0.996�� and 0.992��) due to

the relative content of 2- and 3-methyl-butanal, 1-penten-

3-ol, 3-methyl-butan-1-ol, pentan-1-ol, cis-2-penten-1-ol,

cis-3-Hexen-1-ol, trans-2-hexen-1-ol, acetic acid and

octan-1-ol. Moreover, ‘‘Frantoio’’ from Tuscany was

more similar to ‘‘Leccino’’ from Lombardy and Tuscany

than from Abruzzo, the latter well distinguished from all

other oils.

3.2 Sensorial profile

The descriptors assessed for the sensorial profile, the sensory

notes, and the overall hedonistic ‘‘satisfaction’’ of oils are

shown in Table 4, expressed in arbitrary unites (A.U.). The

odor of ‘‘green’’, ‘‘floral’’, and ‘‘fruity’’ notes ranged from

17.4, 7.8, 19.3 (in ‘‘Leccino’’ from Abruzzo at veraison stage

in 2010) to 31.7 (in ‘‘Casaliva’’ from Abruzzo at green stage

in 2009), 16.9 (in ‘‘Leccino’’ from Lombardy at ripe stage in

2010), and 36.1 (in ‘‘Frantoio’’ from Lombardy at veraison

stage in 2010), respectively. The ‘‘taste’’ notes varied from

6.5 (in ‘‘Frantoio’’ from Lombardy at green stage in 2009)

to 25.3 (in ‘‘Leccino’’ from Tuscany at green stage in 2009),

Figure 2. Oil chemical aromatic profile: plots of the first two canonical functions for region, cultivar, ripening stage, and ‘‘region T cultivar’’

interaction (within brackets: percent of variance explained by function). See Table 3 for values and coefficients of functions. ^, centroid;

Ab, Abruzzo; Lo, Lombardy; Tu, Tuscany; Ca, Casaliva; Fr, Frantoio; Lc, Leccino; 1, green; 2, veraison; 3, ripe.



and the total sensorial satisfaction, from 0.8 (in ‘‘Leccino’’

from Tuscany at green stage in 2009) to 30.1 (in ‘‘Casaliva’’

from Lombardy at green stage in 2009).

Low levels in explained variability was found for the

majority of the assessed descriptors among regions, cultivars,

ripening stages, and among cultivar in each region (Table 5).

About the peculiarity among regions, worthy to be mentioned

are the flavors of ‘‘banana’’ (24.9%� of expected variance,

higher in Lombardy), ‘‘walnut’’ (14.3%�, lower in Abruzzo),

bitter and ‘‘astringency’’ (37.3%�� and 20.7%��, higher in

Tuscany), and the notes ‘‘fruity’’ (22.4%�, lower in Abruzzo

and higher in Lombardy) and ‘‘taste’’ (30.6%��, higher in

Tuscany). For the differences among cultivars, ‘‘lawn’’

(24.5%��) was higher in ‘‘Casaliva’’ and lower in ‘‘Leccino’’

and ‘‘green’’ notes (20.6%�) higher in ‘‘Casaliva’’. For the

ripening stages, ‘‘leaf ’’ (11.3%�) was higher in ‘‘green’’ stage,

‘‘hay’’ (11.5%�) scored higher in the ‘‘ripe’’ stage, ‘‘bitter’’

(11.0%�) was higher in ‘‘green’’ and lower in ‘‘veraison’’,

‘‘astringency’’ (11.8%�) was lower in ‘‘veraison’’ and higher

in ‘‘ripe’’ stage; finally, ‘‘satisfaction’’ (14.0%�) scored lower in

‘‘green’’ stage.

Five sensorial descriptors were significant in characterizing

each oil in each region: ‘‘lawn’’ (18.3%�, higher in ‘‘Casaliva’’

from Abruzzo), ‘‘olives’’ (8.0%�, lower in ‘‘Leccino’’ from

Tuscany), ‘‘bitter’’ (8.1%�, higher in ‘‘Leccino’’ from

Tuscany), ‘‘astringency’’ (25.0%�, higher in ‘‘Leccino’’ from

Tuscany) and ‘‘taste’’ notes (11.4%�, higher in ‘‘Leccino’’

from Tuscany). The other interactions affected the expected

variance for several descriptors: ‘‘olive’’ and ‘‘hay’’ (14.5%�

and 21.6%�) by ‘‘cultivar � stage of ripening’’; ‘‘apple’’,

Table 3. Oil chemical aromatic profile: function coefficients for region, cultivar, ripening stage, and ‘‘region T cultivar’’ interaction of plots in

Fig. 2

Model Function Eigenvalues % Variance % Cumulative Correlation l Wilks x2 df Sig.

Region 1 19.227 73.0 73.0 0.975 0.006 102 42 0.000

2 7.127 27.0 100.0 0.936 0.123 42 20 0.003

Cultivar 1 10.729 92.4 92.4 0.956 0.045 62 42 0.025

2 0.880 7.6 100.0 0.684 0.532 13 20 0.893

Ripening 1 11.845 84.1 84.1 0.960 0.024 75 42 0.001

2 2.244 15.9 100.0 0.832 0.308 24 20 0.050

Region � cultivar 1 112.055 55.4 55.4 0.996 0.000 284 147 0.000

2 62.357 30.8 86.3 0.992 0.000 202 120 0.000

3 16.645 8.2 94.5 0.971 0.001 129 95 0.012

Compound

Region Cultivar Ripening Region � cultivar

Fx 1 Fx 2 Fx 1 Fx 2 Fx 1 Fx 2 Fx 1 Fx 2 Fx 3

n-Octane �0.339 �0.041 �0.334 �1.605 0.530 �0.532 0.651 �0.242 0.293

Ethyl acetate �0.223 �.609 0.289 �1.320 1.422 1.283 1.729 1.997 �2.329

2-Methyl-butanal 5.164 6.343 0.217 1.055 0.378 0.129 �5.737 �9.859 3.185

3-Methyl-butanal �3.628 �7.611 .849 �.988 0.059 �0.005 12.472 11.171 �4.147

Ethanol �2.445 �0.537 �1.128 �0.084 �2.206 0.121 2.010 0.004 �1.560

Pentan-3-one �2.562 �2.363 0.234 �1.230 �0.016 �2.353 3.904 6.684 �3.881

1-Penten-3-one �1.030 1.179 1.446 0.912 2.299 0.330 �2.170 �0.727 3.683

Hexanal 1.058 0.238 �1.571 3.165 1.480 0.347 �0.153 �5.329 2.658

2-Methyl-propan-1-ol 0.559 0.044 2.257 0.975 1.529 0.076 0.570 4.070 �0.677

trans-2-Pentenal �1.375 0.099 �1.306 �1.137 �5.055 1.418 �1.775 �0.269 �1.528

1-Penten-3-ol �4.977 �1.195 1.437 �0.887 3.791 �0.726 0.096 5.272 2.926

3-Methyl-butan-1-ol 4.461 1.454 2.044 0.392 �3.465 3.863 �8.868 �6.165 11.819

trans-2-Hexenal 2.289 �0.062 0.916 0.386 �1.137 �0.283 0.767 1.465 �2.825

Pentan-1-ol 0.755 1.381 4.290 �2.448 0.189 �3.033 7.995 1.678 1.958

cis-2-Penten-1-ol 6.320 1.465 �3.114 1.123 0.855 1.760 0.318 �8.961 �3.261

Hexan-1-ol 1.916 0.539 1.971 2.126 1.663 �0.650 �1.161 1.543 �.148

cis-3-Hexen-1-ol �3.409 �1.510 0.879 �0.840 0.123 �2.085 0.622 6.250 0.006

trans-2-Hexen-1-ol 4.189 3.679 �2.224 1.010 �3.877 3.971 �5.805 �11.347 4.079

Acetic acid �5.764 �7.530 �6.512 3.654 7.972 �6.192 10.983 13.795 �22.143

Octan-1-ol 4.674 5.230 3.860 �3.596 �6.791 7.409 �12.052 �9.984 15.441

Total phenols 1.928 �0.167 1.573 2.422 0.498 0.140 �1.588 0.223 2.761

Fx, function.



‘‘walnut’’, and ‘‘bitter’’ (29.9%�, 57.3%�� and 23.3%�,

respectively) by ‘‘region � stage of ripening’’.

The sensorial assessment was not very efficient in dis-

criminating among regions, cultivars, ripening stages, and

‘‘region � cultivar’’ interactions (Fig. 3 and Table 6).

Lombardy and Tuscany were well separated while

Abruzzo was in between, according to correlations based

on ‘‘walnut’’, ‘‘butter’’, and ‘‘bitter’’ (eigenvalue 5.5,

variance 85% and r ¼ 0.920��). ‘‘Casaliva’’ was distinctively

separated from ‘‘Leccino’’, with ‘‘Frantoio’’ in between

according to ‘‘almond’’, ‘‘walnut’’, and ‘‘bitter’’ descriptors

(eigenvalue 1.7, variance 79% and r ¼ 0.792�). ‘‘Ripe’’ and

‘‘veraison’’ ripening stages were separated while ‘‘green’’ was

in between, mainly by ‘‘bitter’’, ‘‘pungent’’, ‘‘astringency’’

and ‘‘satisfaction’’ notes (eigenvalue 2.3, variance 59% and

r ¼ 0.833�).

About the interaction ‘‘region � cultivar’’, in Lombardy

there was not clear separation among cultivars according

to ‘‘apple’’, ‘‘walnut’’, ‘‘bitter’’, and ‘‘satisfaction’’ for

the first function (eigenvalue 9, variance 48% and

r ¼ 0.948��), and by ‘‘lawn’’, ‘‘banana’’, and ‘‘tomato’’ for

the second function (eigenvalue 5.7, variance 31% and

r ¼ 0.923�), while in Abruzzo and Tuscany the cultivars

were uniquely identified. However, there was no clear

distinction for ‘‘Frantoio’’ and ‘‘Leccino’’ between

Abruzzo and Lombardy.

4 Discussion

As a general overview, region of production, cultivars, fruit

ripening stage, and interaction between region and cultivar

were better characterized by the aromatic chemical compo-

sition then by the sensorial profile, showing that even for very

well trained panel the discrimination between samples needs

very large variability.

The ‘‘region’’ was the most important discriminating

factor: oils from Abruzzo, Lombardy, and Tuscany showed

peculiar aromatic and sensorial profiles. The chemical aro-

matic compounds and sensorial attributes, separately or in

relationship, were effective in characterizing the geographic

origin of oils, confirming a large body of findings so far based

on assessment were region and cultivar were confounded.

The oils from Lombardy were distinguished by the high

values of aldehydes and C6 compounds which give a good

‘‘fruity’’, light note, while those from Tuscany were differ-

entiated by a low volatile composition and a high content of

phenols conferred high sensation of strong taste notes. Oils

from Abruzzo scored in between.

Table 4. Oil sensorial profile (two years average): value range, mean, SD (expressed as arbitrary unites: A.U.) and expected variance

component due to region, cultivar, ripening stage, and their interactions for 33 oil samples

Descriptor

Range

(A.U.)

Mean

(A.U.)

SD

(A.U.)

Variance (%)

Region Cultivar Ripening R � C C � S R � S

Lawn 1.08–9.60 5.26 2.12 0.0 24.5 1.1 18.3 0.0 9.7

Leaf 2.07–8.89 5.25 2.10 0.4 4.1 11.3 0.0 0.0 2.8

Olives 0.69–11.91 5.05 2.67 2.7 4.2 9.6 8.0 14.5 0.0

Flowers 4.12–9.25 5.27 1.44 0.0 0.0 0.0 0.0 4.5 9.9

Banana 3.59–8.85 5.23 1.40 24.9 9.7 0.0 0.0 0.0 0.0

Tomato 3.66–10.19 5.24 1.54 5.7 1.7 0.0 0.0 0.0 0.0

Almond 3.15–8.68 5.24 n.r. 5.5 4.7 4.3 0.0 0.0 4.3

Artichoke 3.54–8.27 5.20 1.27 0.0 0.0 1.0 0.0 2.8 2.8

Apple 4.26–9.53 5.18 n.r. 0.0 0.0 0.0 5.6 3.8 29.9

Walnut 3.39–9.37 5.29 1.57 14.3 0.0 0.0 4.6 0.0 57.3

Hay 3.34–9.82 5.25 1.77 3.5 0.0 11.5 6.4 21.6 12.9

Butter 3.64–8.44 5.18 n.r. 0.0 11.7 7.9 0.0 0.0 18.5

Bitter 0.23–11.98 5.17 2.48 37.3 0.0 11.0 8.1 4.2 23.3

Sweet 2.29–9.87 5.19 1.95 0.0 0.0 0.4 5.4 4.6 0.4

Pungent 2.00–8.56 5.03 1.80 7.9 0.0 3.2 0.0 1.5 1.2

Astringency 3.41–9.23 5.11 1.52 20.7 0.0 11.8 25.0 0.0 6.1

Green notes 17.44–31.74 26.24 3.85 0.0 20.6 3.6 9.0 0.0 8.4

Floral notes 7.76–16.91 10.45 1.95 4.6 7.3 7.6 0.0 0.0 0.0

Fruity notes 19.26–36.14 25.94 3.99 22.4 3.7 6.7 0.0 4.5 0.0

Taste notes 6.49–25.31 15.31 4.78 30.6 0.0 2.4 11.4 1.5 14.2

Satisfaction 0.81–30.07 16.15 6.88 4.5 9.9 14.0 0.0 9.5 4.6

n.r., not reported because frequency distributions were not normal according to Kolmogorov–Smirnov test (p ¼ 0.05); R, region; C, cultivar;

S, stage of ripening.



Table 5. Oil sensorial profile: comparison among 33 oils for region, cultivar, ripening stage, and ‘‘region T cultivar’’ interaction

Descriptor

(A.U.)

Region Cultivar Ripening stage

Abruzzo Lombardy Tuscany Casaliva Frantoio Leccino Green Veraison Ripe

Lawn 5.28 aa) 5.17 a 5.42 a 6.43 ba) 5.74 ab 4.20 a 4.98 aa) 5.85 a 4.54 a

Leaf 5.05 a 5.26 a 5.40 a 5.81 a 5.17 a 4.98 a 6.36 b 4.65 a 4.53 a

Olives 4.84 a 5.51 a 4.28 a 6.02 a 5.86 a 3.86 a 4.39 a 5.99 a 4.32 a

Flowers 5.65 a 5.16 a 5.12 a 5.25 a 5.11 a 5.40 a 5.12 a 5.24 a 5.58 a

Banana 4.49 a 5.97 b 4.40 a 6.03 a 5.11 a 4.87 a 5.64 a 4.96 a 5.07 a

Tomato 4.85 a 5.56 a 4.94 a 5.64 a 5.10 a 5.11 a 5.16 a 5.44 a 4.98 a

Almond 4.45 a 5.69 a 5.07 a 5.57 a 4.89 a 5.32 a 4.73 a 5.39 a 5.80 a

Artichoke 4.34 a 5.69 a 5.03 a 5.39 a 5.31 a 5.01 a 5.24 a 4.89 a 5.76 a

Apple 4.90 a 5.04 a 5.77 a 4.66 a 5.34 a 5.36 a 4.89 a 5.30 a 5.45 a

Walnut 4.19 a 5.86 b 5.17 ab 6.06 a 4.80 a 5.23 a 5.40 a 4.94 a 5.81 a

Hay 5.66 a 5.45 a 4.41 a 5.64 a 4.64 a 5.50 a 5.05 a 4.61 a 6.85 b

Butter 4.73 a 5.38 a 5.19 a 4.59 a 5.12 a 5.56 a 4.74 a 5.12 a 6.03 a

Bitter 4.17 a 4.45 a 7.70 b 4.46 a 4.89 a 5.79 a 5.94 b 4.61 a 4.96 ab

Sweet 4.67 a 5.68 a 4.68 a 5.74 a 4.89 a 5.12 a 4.27 a 5.32 a 6.51 a

Pungent 4.06 a 5.02 a 6.01 a 5.15 a 5.06 a 4.92 a 4.82 a 4.72 a 5.99 a

Astringency 4.85 a 4.61 a 6.46 b 4.85 a 4.61 a 5.66 a 5.06 ab 4.75 a 5.94 b

Green notes 24.53 a 27.43 a 25.43 a 29.34 b 25.65 a 24.93 a 27.03 a 24.94 a 27.49 a

Floral notes 10.38 a 10.54 a 10.31 a 9.84 a 10.23 a 10.96 a 9.87 a 10.36 a 11.61 a

Fruity notes 23.53 a 27.77 b 24.47 ab 27.92 a 26.29 a 24.53 a 24.81 a 27.07 a 25.63 a

Taste notes 13.08 a 14.07 a 20.16 b 14.47 a 14.57 a 16.37 a 15.82 a 14.08 a 16.89 a

Satisfaction 13.92 a 18.31 a 13.80 a 20.41 b 17.22 ab 12.88 a 13.29 a 17.89 b 17.58 b

Descriptor

(A.U.)

‘‘Region � cultivar’’ interaction

Abruzzo Lombardy Tuscany

Casaliva Frantoio Leccino Casaliva Frantoio Leccino Frantoio Leccino

Lawn 9.47 ba) 5.05 a 3.31 a 5.42 a 5.76 a 4.42 a 6.06 a 4.77 a

Leaf 6.23 a 4.67 a 4.66 a 5.68 a 5.03 a 5.04 a 5.59 a 5.22 a

Olives 5.20 ab 5.45 ab 4.35 ab 6.29 b 5.21 ab 4.98 ab 6.87 b 1.70 a

Flowers 5.16 a 5.91 a 5.77 a 5.28 a 4.69 a 5.42 a 5.24 a 5.00 a

Banana 4.84 ab 4.14 a 4.49 ab 6.43 b 6.03 ab 5.47 ab 4.43 ab 4.36 ab

Tomato 5.25 a 5.22 a 4.47 a 5.77 a 5.58 a 5.33 a 4.45 a 5.43 a

Almond 4.34 a 4.34 a 4.55 a 5.98 a 5.07 a 5.90 a 4.93 a 5.21 a

Artichoke 4.29 a 4.29 a 4.40 a 5.76 a 5.47 a 5.79 a 5.61 a 4.46 a

Apple 4.42 a 5.17 a 5.01 a 4.74 a 5.56 a 4.90 a 5.16 a 6.39 a

Walnut 3.99 a 4.60 ab 4.09 a 6.75 b 5.06 ab 5.64 ab 4.58 ab 5.76 ab

Hay 6.63 a 6.08 a 4.97 a 5.31 a 4.46 a 6.41 a 4.14 a 4.68 a

Butter 4.29 a 5.09 a 4.77 a 4.69 a 5.31 a 6.14 a 4.90 a 5.47 a

Bitter 3.69 a 4.08 a 4.46 a 4.72 a 4.00 a 4.55 a 6.41 ab 8.98 b

Sweet 3.74 a 4.73 a 5.10 a 6.41 a 5.18 a 5.37 a 4.60 a 4.77 a

Pungent 4.92 a 4.53 a 3.39 a 5.23 a 4.64 a 5.12 a 5.86 a 6.16 a

Astringency 5.11 a 4.74 a 4.78 a 4.77 a 4.30 a 4.69 a 4.93 a 7.99 b

Green notes 30.60 b 24.69 ab 21.42 a 28.92 ab 25.78 ab 27.30 ab 25.97 ab 24.89 ab

Floral notes 9.44 a 11.00 a 10.54 a 9.97 a 10.00 a 11.56 a 10.15 a 10.47 a

Fruity notes 24.06 a 24.32 a 22.87 a 29.21 a 27.45 a 26.59 a 25.84 a 23.09 a

Taste notes 13.72 a 13.35 a 12.63 a 14.72 a 12.94 a 14.37 a 17.20 ab 23.12 b

Satisfaction 15.11 a 18.64 a 10.98 a 22.18 a 17.00 a 15.54 a 16.79 a 10.80 a

a) Rows: values with the same letter are not statistically different at p ¼ 0.05 separately for region, cultivar, ripening stage, and

‘‘region � cultivar’’ interaction.



The genetic origin was of course important in character-

izing the oils, as proved by previous works [11, 12, 25, 26]

although at a lesser extent than the region of cultivation. The

three cultivars were well identified, although ‘‘Casaliva’’ and

‘‘Frantoio’’ showed similar aromatic profile, a reasonable

explanation being their possible close genetic origin [27].

Oils from ‘‘Casaliva’’ and ‘‘Frantoio’’ confirmed a very

similar aromatic composition with high levels of volatile com-

pounds, while ‘‘Leccino’’ was characterized by a low content.

The oils from three cultivars had a sensorial profile slightly

different: more prominent in ‘‘Casaliva’’, less in ‘‘Leccino’’

and ‘‘Frantoio’’ in the middle.

The ripening stages affected both the aromatic and the

sensorial features of the oils, with slight differences. Also in

this case, the oils from ‘‘green’’ fruits were better identified

by the chemical rather than the sensorial assessment. The

volatile compounds were at the highest concentration at

this early stage and decreased during olives ripening, as also

found in other works [28]. The same trend was detected for

phenols. For this reason the oils from ‘‘green’’ olives were less

appreciated by the panel test, being evaluated as too ‘‘leafy’’

and bitter, due to particularly for highest concentration of

C6 compounds from LOX of LnA.

Also the interactions between region and cultivar showed

a much clear differentiation by chemical than by sensorial

attributes. ‘‘Casaliva’’ and ‘‘Frantoio’’ from Abruzzo showed

a similar composition except for trans-2-hexenal, C6 com-

pounds, total aldehydes and volatiles, that were higher in the

Figure 3. Oil sensorial profile: plots of the first two canonical functions for region, cultivar, ripening stage, and ‘‘region T cultivar’’ interaction

(within brackets: percent of variance explained by function). See Table 6 for values and coefficients of functions. Legend: ^, centroid;

Ab, Abruzzo; Lo, Lombardy; Tu, Tuscany; Ca, Casaliva; Fr, Frantoio; Lc, Leccino; 1, green; 2, veraison; 3, ripe.



second cultivar, while ‘‘Casaliva’’ scored high for ‘‘lawn’’ and

‘‘green’’ notes. A similar behavior was shown in Lombardy,

but in this case the above aromatic compounds were higher in

‘‘Casaliva’’. ‘‘Frantoio’’ from Tuscany, with high ‘‘olives’’

flavor, showed an ambiguous trend because for some volatiles

it was similar to ‘‘Casaliva’’ from Abruzzo, while for other it

was more similar to ‘‘Leccino’’ from Lombardy. ‘‘Leccino’’

from Abruzzo was quite different compared to the two other

regions, that were more comparable for low content of some

volatile compounds, particularly in ‘‘Leccino’’ from Tuscany.

The latter showed also a low flavor of ‘‘olives’’ and scored

high for strong sensorial notes, given its high content in total

phenols.

Overall, even if the place of production resulted as the

main discriminating factor for oil (chemical) characteriz-

ation, the influence of the cultivar, and the fruit ripening

stage should not be underestimated and a case by case assess-

ment should be regarded to the aim of a sound evaluation of

the overall quality of a virgin olive oil.

5 Conclusions

This study, carried out for two years on three olive cultivars

grown in three Italian regions at three different ripening

stages has clearly shown that the flavor profiles of oils depend

mainly from their geographical origin (environmental influ-

ence), than from cultivar (genetic influence) and finally from

fruit maturation at harvest (influence of the ripening stage).

Moreover, this research has confirmed that the chemical

aromatic composition is more effective in characterizing

the geographical origin of olive oil, the cultivar, the fruit

ripening stage, and the ‘‘region � cultivar’’ interactions than

the sensorial evaluation by a trained panel. Furthermore, the

oils from the three regions were well characterized by aro-

matic chemical and sensorial profiles. This brought out the

strong influence of macroclimatic environments on extra

virgin olive oil attributes.

The oils from ‘‘Casaliva’’ and ‘‘Frantoio’’, showed similar

aromatic and sensorial profile but were well differentiated

Table 6. Oil sensorial profile: function coefficients for region, cultivar, ripening stage, and ‘‘region T cultivar’’ interaction of plots in Fig. 3

Model Function Eigenvalues % Variance % Cumulative Correlation l Wilks x2 df Sig.

Region 1 5.511 85.1 85.1 0.920 0.078 56 34 0.010

2 0.964 14.9 100.0 0.701 0.509 15 16 0.535

Cultivar 1 1.684 79.3 79.3 0.792 0.259 30 34 0.050

2 0.438 20.7 100.0 0.552 0.695 8 16 0.949

Ripening 1 2.261 58.6 58.6 0.833 0.118 47 34 0.036

2 0.599 41.4 100.0 0.784 0.385 21 16 0.178

Region � cultivar 1 8.962 47.8 47.8 0.948 0.001 136 119 0.013

2 5.737 30.6 78.5 0.923 0.009 91 96 0.049

3 1.812 9.7 88.1 0.803 0.064 54 75 0.630

Descriptor

Region Cultivar Ripening Region � cultivar

Fx 1 Fx 2 Fx 1 Fx 2 Fx 1 Fx 2 Fx 1 Fx 2 Fx 3

Lawn �0.897 0.224 �0.854 �0.351 �0.515 0.091 0.296 �2.084 0.963

Leaf 0.772 0.186 �0.455 �0.509 �0.520 �0.761 �0.924 0.172 0.177

Olives 0.231 0.324 0.423 0.478 0.402 1.333 �0.050 0.633 �0.633

Flowers �0.939 0.216 0.299 �0.247 �0.019 �0.332 0.483 �0.958 �0.768

Banana 0.961 0.172 0.026 0.572 0.207 �0.131 �0.343 1.073 0.557

Tomato 0.569 0.611 0.787 0.306 �0.524 0.988 0.534 1.909 0.099

Almond �0.464 0.486 0.991 0.490 0.050 0.937 0.939 0.418 �0.525

Artichoke �0.289 0.708 0.021 �0.249 �0.315 �0.832 0.004 �0.868 �0.281

Apple �0.479 0.616 0.254 �0.353 0.180 0.291 1.203 0.182 0.759

Walnut 1.305 0.063 �1.205 0.318 0.084 �0.640 �1.658 0.011 0.639

Hay 0.033 �0.546 �0.210 0.790 0.557 �0.597 �0.478 �0.812 0.160

Butter 1.121 0.308 0.457 �0.209 0.435 �0.058 �0.655 0.877 �0.009

Bitter �1.965 0.526 0.905 0.016 �1.311 �0.038 1.877 �0.437 �0.926

Sweet �0.047 0.498 �0.080 �0.262 �0.081 0.524 0.544 0.846 0.102

Pungent �0.190 0.131 �0.229 �0.874 0.719 �0.214 �0.146 �0.450 �0.259

Astringency 0.210 �0.056 0.161 1.192 1.581 0.304 0.448 0.990 0.735

Satisfaction 0.255 �0.828 �0.855 0.041 0.750 �0.798 �1.004 �0.020 0.126

Fx, function.



from the more genetically distant ‘‘Leccino’’. Also the olive

ripening stage heavily affected the aromatic quality, the

‘‘green’’ stage being better characterized by the chemical

aromatic profile, while the ‘‘ripe’’ stage was better charac-

terized by the sensorial assessment. However, it has to be

taken in account that the influence of olive ripening on oil

quality is also related to seasonal conditions which could

affect minor compounds, e.g., volatiles, phenols, and toco-

pherols [28, 29]. Finally, the interactions ‘‘region � cultivar’’

and also ‘‘cultivar � year’’ [30] were significant in differen-

tiating the oils, particularly by chemical composition. By

these peculiar aromatic and sensorial profiles it was possible

to distinguish the oils based on their geographical and genetic

origin, and their possible interactions, confirming some

results by not-destructive methods, e.g., electronic nose,

NMR, IR [16, 19, 20] or by traditional analysis, e.g., anti-

oxidant compounds [7].

Therefore the differences induced by geographical origin,

cultivar, year (seasonal conditions), olive ripening stage at

harvest, and their interactions, could be effective factors in

addressing marketing of extra virgin olive oils, since they can

influence the inner quality and thus the consumer appreci-

ation in turn.

Furthermore, the growing information available on

monovarietal olive oils increase our knowledge in order to

get a better characterization of the commercial product,

either monovarietal or from a varietal blend. These findings,

that are also related to authentication and characterization,

are all possible tools for protecting olive oils against mislab-

eling and adulteration. This is also particularly relevant for a

better exploitation of the typicality of the products in the form

of Protected Designation of Origin protocols.

The research was funded by the EU Commission, Regulation EC

No. 528/99, in co-operation with the Agriculture Department of

Lombardy Region, Italy. The authors wish to thank the panel

groups of Pescara (CRA – Centro di ricerca per l’olivicoltura e

l’industria olearia), of Savona (O.N.A.O.O.) and Brescia

(A.I.P.O.L.).

Authors contribution:

� Experiment design and manuscript revision: all authors

� Oil analysis: Tura and Serraiocco

� Data processing: Tura and Failla

� Manuscript writing: Tura and Bassi

� English language revision: English native speaker and

professional proofreading

The authors have declared no conflict of interest.

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Regional and cultivar comparison of Italian single cultivar olive oils according to flavor profiling

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