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Olive Oil Laboratory Guidance Document

March 2021


By Rodney J. Mailer, PhD,a and Stefan Gafner, PhDb
aAustralian Oils Research, Lambton, NSW 2299, Australia
bAmerican Botanical Council, Austin, TX 78723, USA

Correspondence: email

Citation (JAMA style): Mailer RJ, Gafner S. Olive oil laboratory guidance document. Austin, TX: ABC-AHP-NCNPR Botanical Adulterants Prevention Program; 2020.

Keywords: Olea, Olea europaea, olive, olive oil, huile d'olive, virgin olive oil, extra virgin olive oil, EVOO, adulteration, fraud, traceability, laboratory analysis, methods of analysis

1.  Purpose

Extra virgin olive oil is often described as the healthiest of all commercially available edible oils. Olive oil has a high percentage of monounsaturated fat and because it is generally consumed in the unrefined (virgin) crude state, the oil contains natural compounds which would otherwise be removed in refining. The high value of the virgin oil compared to refined seed oils make it highly susceptible to adulteration. This laboratory guidance document provides a review of (1) analytical methods used to determine whether olive products have been adulterated and, if so, (2) methods to identify the adulterants. As olive oil is frequently diluted with undeclared refined olive oil or degraded virgin olive oil, methods have been established to determine the quality of the oil’s freshness and compliance with international standards. Adulteration has also been observed in various vegetable oils including canola (Brassica napus, Brassicaceae), sunflower (Helianthus annuus, Asteraceae), and other oils. This document should be viewed in conjunction with the corresponding Botanical Adulterants Prevention Bulletin1 on olive oil published by the ABC-AHP-NCNPR Botanical Adulterants Prevention Program.

2.  Scope

The name olive oil relates to a wide range of materials, all originating from the extraction of the oil from olive fruit. However, different methods of extraction will result in different oil qualities and hence produce a variety of grades of oil, some which are considered unfit for human consumption. The main classes, virgin and refined olive oil, and their subclasses have been described in detail in the Botanical Adulterants Prevention Bulletin on olive (Olea europaea) oil.1 The focus of this document is on olive oil used for food, especially extra virgin olive oil (EVOO), since previous analyses and reports suggest that it is the product most likely to be adulterated.

Due to the wide range of possible adulterants, there are many analytical methods used to evaluate virgin olive oil purity; these will be discussed below as part of this laboratory guidance document. For the purpose of this publication, the methods described have been limited to measuring those components which are useful for determining authenticity. For chemometric methods, selection criteria included the publication date (after 2000), and the ease of access.

The evaluation of a specific analytical method or methods in this Laboratory Guidance Document for testing of olive oil does not reduce or remove the responsibility of laboratory personnel to demonstrate adequate method performance in their own laboratory using accepted protocols outlined in various domestic (in the United States) or international legal and/or regulatory documents. Such documents include, for example, the standards developed by AOAC International, International Standards Organization (ISO), World Health Organization (WHO), and the International Council on Harmonisation (ICH).

3.  Common and Scientific Names

3.1 Common name of the plant: Olive

3.2 Other common names:2 

Chinese: Gan lan (橄榄)
Danish: Oliven
Dutch: Olijf
French: Olive
German: Olive
Hindi: Zaitoon (ज़ैतून)
Italian: Oliva
Japanese: Oribu (オリーブ)
Portuguese: Oliva
Russian: Olivka (оливка), bot: oliva (олива)
Spanish: Aceituna, oliva
Swedish: Oliv

3.3 Accepted Latin binomial name: Olea europaea L.

3.4 Synonyms: none

3.5 Botanical family: Oleaceae

4.  Botanical Description and Geographical Range

Olea europaea L., was traditionally and still is predominantly grown in the Mediterranean Basin but its commercial cultivation has spread globally. The olive tree is a fruit-bearing evergreen tree, ranging from 3 to 20 meters in height. Traditional orchards still exist in many countries with trees growing on uneven terrain and often requiring hand harvesting due to the inaccessibility by mechanical harvesters. However, with modern techniques, such as high-density farming, most orchards today are managed to produce a variety of shapes and sizes of trees, including trellising methods, to suit automated harvesting equipment. The tree is robust and can be grown under adverse conditions such as high salinity. It can also be grown in arid regions but, for consistent quality and good yields, irrigation is generally required. There are several hundred cultivars ranging from high oil-producing fruit to types better suited as edible table fruit.3 The fruit is the main focus of farming although leaf extract is becoming more widely recognized for potential cardiovascular health benefits, particularly due to two major biophenols found in the olive leaf, namely oleuropein and hydroxytyrosol.4,5

5.  Adulterants and Confounding Materials

Table 1: Scientific names, family, and common names of plants used as vegetable oil sources of olive oil adulterants.*

Speciesa

Synonym(s)a

Family

Common nameb

Other common namesc

Brassica napus L.

Brassica napus subsp napus

Brassicaceae

Canolad

Colza, rape, rapeseed

Corylus avellana L.

 

Betulaceae

Hazelnut

European filbert, European hazel, filbert, hazel

Helianthus annuus L.

H. aridus Rydb.

H. jaegeri Heiser

H. lenticularis Douglas

H. macrocarpus DC

H. ovatus Lehm.

Asteraceae

Sunflower

 

Glycine max (L.) Merr.

Dolichos soja L.

G. gracilis Skvortsov

G. hispida (Moench) Maxim.

G. soja (L.) Merr.

Soja hispida Moench

S. max (L.) Piper

Fabaceae

 

Soy bean

Soy, soya bean

 aThe Plant List6 and the Kew Medicinal Plant Names Services database.7 A comprehensive list of synonyms can be accessed through both websites.
bAmerican Herbal Products Association’s Herbs of Commerce, 2nd ed.8
cAmerican Herbal Products Association’s Herbs of Commerce, 2nd ed.,8 and the USDA GRIN database.9
dAccording to the Canadian Food Inspection Agency, canola oil may also be obtained from Brassica rapa and B. juncea. 

*Note: Species other than those listed in Table 1 used for production of edible fatty oils may also be used as olive oil adulterants.

6.  Identification and Distinction using Physical Characteristics of Fruit

6.1 Fruit quality

Olive fruit needs to be processed within the shortest possible time after harvest to maintain oil quality. Poor quality fruit results in low quality oil, so the assessment of fruit quality is an important step for manufacturers to ensure that the oil obtained meets the highest grade (see sections 1 and 2). The fruit should be inspected to ensure that (1) the skin is intact, (2) the fruit is not infested by insects or other plant pathogens, and (3) there is no discoloration as a result of frost damage.

Figure 1. Olives should be stored in open containers and storage time should be kept to a minimum to avoid fruit damage. Image courtesy of Rodney J. Mailer.

Olives should be transported from the grove to the factory in open containers (Figure 1) which allow heat to dissipate. Without proper storage conditions, the heat generated during storage will result in fruit fermentation leading to poor quality fruit and oil.

Free fatty acids will increase as the fruit ages and this is accelerated at higher temperatures.10,11 Storage in inappropriate containers such as hessian bags (Figure 2; bags made predominantly of jute fiber) will impart a musty flavor to the oil which will ultimately be recorded as a defect in the oil.

Figure 2. Storage of olive fruit in inappropriate containers such as hessian bags will impart flavors recorded as a ‘defective’ to the oil. Image courtesy of Rodney J. Mailer.

6.2 Fruit maturity

EVOO quality relies heavily on the quality and the maturity of the fruit. Olives may be harvested at any stage throughout the fruiting months. The ripeness (maturity) at which the fruit (green to black) is harvested will determine the ultimate color, sensory characteristics, and chemical composition of the oil.12 Harvesting olives at a later stage (ripened) increases the risk of fruit damage which will result in reduced oil quality as the fruit is softer and more prone to damage.

Fruit maturity determines not only the quality but also the quantity of olive oil obtained.13 Oil content increases rapidly as olives mature but the rate slows as the fruit begins to change color. Growers often begin harvesting when oil content is close to its maximum without entering the stage where fruit quality starts to deteriorate. Figure 3 illustrates the different stages of fruit maturity or “fruit maturity index”.

Figure 3. Olive fruit at different stages of maturity as described by the internationally accepted “olive fruit maturity index14

7.  Identification and Distinction using Physical Characteristics of the Oil

There are many assays such as density, refractive index, smoke point, melting point, and others, which can be used to determine the physical characteristics of an oil under examination. However, overlapping values among other edible oils render these identification approaches ineffective to determine olive oil quality and purity (See Table 2).  Nevertheless, some physical characteristics such as color and clarity may provide useful information about the authenticity of the product.

7.1 Color

The color of freshly extracted olive oil may range from dark green to pale yellow (Figure 4).  Young green olives produce a more intensely green-colored oil whereas mature, black olives tend to be more yellow. Colors of dark brown or red tints may be an indication that the oil has been heated, as part of the refining process, or blended with other oils. Refined oils are generally colorless or straw colored due to removal of pigments during the bleaching/refining process. However, the evaluation of color alone is not sufficient to establish the authenticity or quality of olive oil.

7.2 Clarity

The oil will be clear if it has been filtered or allowed to settle but may be cloudy when it is fresh (Figure 4). The oil will also be cloudy if it contains moisture, but this will separate and settle to the bottom after standing for a period of time. Any water should be discarded from contact with the oil as soon as possible to avoid enzymatic activity from water-soluble lipases on triacylglycerides. The visual assessment of oil clarity will not provide information about olive oil adulteration.

Figure 4. Freshly extracted oil is generally green and cloudy due to the presence of solids and moisture. Image courtesy of Rodney J. Mailer.

8.  Organoleptic Identification

Perhaps the most unique characteristic of olive oil is its sensory quality. Trained sensory experts can identify attributes such as fruitiness and bitterness, as well as defects such as fusty and musty flavors. These characters can, in turn, identify the age and/or storage conditions to which the oil has been exposed. In some cases, a sensory panel can determine the fruit cultivar and even trace the origin of the oil.

Compliance with organoleptic or sensory analysis limits is necessary to meet the EVOO criteria. A positive level of fruitiness is an essential attribute, and the oil must be free of defects. The observation of defects can point towards specific shortcomings in chemical compliance on the basis of the particular defect. The presence of defects will also determine if the oil has passed its useful age and if the oil has been stored or treated correctly.

Sensory analysis is dependent on the ability of experts to correctly interpret the oil characteristics. For this reason, sensory analysis has been criticized for being not robust enough to be used as evidence for legal challenges to an oil’s quality or authenticity. The International Olive Council (IOC) has developed strict guidelines for the training of sensory tasters and for the design of specific facilities for carrying out sensory analysis.15 These guidelines include the need for a panel of 8–12 tasters in environmentally-controlled tasting rooms. The competency of IOC-accredited sensory panels is routinely evaluated to ensure they meet strict requirements.

The IOC methodology includes a general basic vocabulary for oil tasting, a description of the apparatus (Figure 5) for tasting, installation of a test room, guide for training and monitoring olive oil tasters, and methods for oil assessment.15

Despite the accuracy and consistency of well-trained panels, the decisions made by the panel in cases where adulteration or fraud are prosecuted continue to face challenges. If a panel determines the oil is lampante (unfit for human consumption), it must be reanalyzed by a second panel and even a third if the results are still unfavorable.

Between December 1, 2018 and November 30, 2019, the IOC accredited only 80 panels in 23 countries. Not only is accessing a panel difficult, but the test is also expensive and time-consuming. If the samples need to be transported to another country, the risk of sample degradation is a possibility. Moreover, an oil may be found to be acceptable on the basis of the organoleptic test but may still fail to meet chemical limits required to be classified as EVOO.

Attempts have been made to develop laboratory-based methods such as the electronic nose16 to overcome the limitations of human sensory analysis although the methods have not been successful to date. In general, sensory analysis remains a useful tool but is deemed not suitable in many cases for determining authenticity of EVOO.

Figure 5. IOC specifications for glasses17 (a) and image of compliant glassware (b) used for tasting olive oil.

9.  Genetic Identification and Distinction

Although the IOC has published a World Catalogue of Olive Varieties3 describing 139 cultivars across 23 countries, there are in fact, many unidentified cultivars. Olives are generally outcrossing and current olive cultivars include numerous, and presumably undocumented, wild types.

In an Australian study of two olive groves in Wagga Wagga (96 named cultivars) and Yanco (four cultivars) using random amplified polymorphic DNAs (RAPDs) analysis, the level of heterogeneity suggests that many, if not all cultivars, are comprised of varietal populations often with considerable genetic overlap between cultivars.18 Many subsequent studies on cultivars have been undertaken using molecular markers, including the use of microsatellites.19 Other techniques include amplified fragment length polymorphisms (AFLPs), simple sequence repeats (SSRs), and single nucleotide polymorphisms (SNPs).20 However, some authors concluded that RAPD marker analysis produces unreliable results in authenticating olive oils.21

More recently, DNA analysis has progressed from the identification of olive cultivars to the measurement of olive oil authenticity by identifying foreign DNA within olive oil. For example, the matK and psbA-trnH regions were used to detect the presence of sunflower and canola oil in olive oil at levels of 5% or higher despite the low yield of DNA from vegetable oils.22 Analysis of polymerase chain reaction (PCR) products of the trnL genetic region by capillary electrophoresis (CE) proved equally suitable as gas chromatography (GC) analysis in detecting admixture of 5% or more of soybean, palm, rapeseed, sunflower, sesame, cottonseed, and peanut oils.23 However, this methodology is limited by the fact that oil is generally adulterated with refined oil in which DNA is basically destroyed and the majority of any DNA in the oil sample will be contributed by the EVOO itself.

10.  Physicochemical Tests

Several physical and chemical tests are available for olive oil analysis.24 These include specifications for specific gravity, refractive index, iodine value, saponification value, percentage unsaponifiable constituents, and melting point. A comparison of physical characteristics is provided in Table 2.

These tests have little value in detecting the presence of foreign oil which may have been used to dilute the original product. Many edible oils have very similar physical characteristics. This has become even more complex with genetic modifications of plant types to mirror olive oil quality due to the perceived nutritional benefits of olive oil. Within each plant species there are now several categories of oil types. For example, soybean oil is now available with a range of fatty acid profiles including traditional types, high saturated, low linolenic, and low saturated types.

Other simple chemical parameters, including peroxide value and acid value, are dependent on the harvesting and storage conditions, and, therefore, do not provide any helpful information for determination of authenticity. Furthermore, the relative density and refractive index of olive oil and common vegetable oils do not differ substantially, and thus are also not useful in determining adulteration.

Table 2: Physicochemical tests of olive oil and vegetable oils used as potential adulterants.25

Physicochemical test

Olive oil

Hazelnut oil

Canola oil

Coconut oil

Palm oil

Soybean oil

Sunflower oil

Specific gravity

0.910-0.916 at 20oC

0.914-0.920 at 15.5oC

0.914-0.920 at 20oC

0.908-0.921 at 40oC

0.891-0.899 at 50oC

0.919-0.925 at 20oC

0.918-0.923 at 20oC

Specific gravity

 

0.908-0.915 at 25oC

 

 

 

 

 

Refractive index (20-25oC)

1.468-1.471 at 20oC

1.469-1.476 at 25oC

 

 

 

 

1.472-1.476 at 25oC

Refractive index (40oC)

1.460-1.463

1.456-1.463

1.465-1.467

1.448-1.450

1.454-1.456

1.466-1.470

1.467-1.469

Iodine value

75-94

83-90

110-126

5-13

49-55

118-139

118-145

Saponification value

184-196

188-197

182-193

248-265

190-209

189-195

188-194

Melting point (oC)

-3-0

 

 

23-26

33-40

 

 

11.  Chemical Identification and Distinction

11.1 Composition of olive oil

Extra virgin olive oil is composed of approximately 98% triacylglycerols (TAGs), with the remaining 2% consisting of a large number of other constituents referred to as the minor compounds. The proportions of the different triacylglycerols, as well as the proportion of the total fatty acids which make up those triacylglycerols, are both strong characteristics of olive oil. Therefore, they can often be used to distinguish olive oil from other edible oils.

The minor components include phytosterols, pigments, and phenolic compounds, the fingerprint of which can serve as a means for oil quality and authenticity determination.

11.2 Fatty acids

The major fatty acids in common edible oils are C14 to C24 fatty acids. The structure of the most common fatty acids in olive oil is illustrated in Figure 6. The olive oil fatty acid composition and that of possible adulterants are provided in Table 3. Although the fatty acid profile is useful as a fingerprint to distinguish the different species, several issues can render this approach unsuitable. Blended oils have a fatty acid profile which is something in between the profile of the oils which have been used for blending. Additionally, and as previously discussed, plant breeding has seen the development of a whole range of different fatty acid profiles within each species such as soybean, which can be, for example, high or low in concentrations of saturated fatty acids, high in stearic acid, or low in linolenic acid. Many of these are genetically modified organisms (GMOs) which have been engineered to achieve the required fatty acid pattern. The undeclared blending of GMO oil with olive oil is another case of adulteration which affects consumers that prefer non-GMO products.

Figure 6. Chemical structures of the three major fatty acids in olive oil.

Table 3. Relative fatty acid composition (%) of olive oil and potential adulterants, taken from Firestone.25

Fatty acid

Olive

Hazelnut

Canolaa

Coconut

Palm

Soybean

Sunflowerb

Sunflowerc

Caprylic C8:0

n.d.

n.d.

n.d.

0.91-9.4

n.d.

n.d.

n.d.

n.d.

Capric C10:0

n.d.

n.d.

n.d.

3.8-7.8

n.d.

n.d.

n.d.

n.d.

Lauric C12:0

n.d.

n.d.

n.d.

45.1-50.9

≤ 0.2

≤ 0.1

≤ 0.1

n.d.

Myristic C14:0

≤ 0.1

n.d.

≤ 0.2

16.8-21.1

0.5-2.0

≤ 0.2

≤ 0.2

≤ 0.1

Palmitic C16:0

7.5-20

4.1-7.2

3.3-6.0

7.7-10.2

39-48

9.7-13.3

5.0-7.6

2.6-5.0

Palmitoleic C16:1 (9)

0.3-3.5

0.1-0.3

0.1-0.6

n.d.

n.d.

Tr.

1-0.3

0.1-0.2

Stearic C18:0

0.5-5.0

1.5-2.4

1.1-2.5

2.3-4.9

3.5-6.0

3.0-5.4

2.7-6.5

2.9-6.2

Oleic C18:1 (9)

55-83

71.9-84.0

52-67

5.4-9.9

36-44

17.7-28.5

14-39

75-90

Linoleic C18:2 (9,12)

3.5-21

5.7-22.2

16-25

0.6

9.0-12

53.7

48-74

2.1-17

Linolenic C18:3 (9,12,15)

≤ 1.5

0-0.2

6-14

≤ 0.2

≤ 0.2

5.5-9.5

≤ 0.3

≤ 0.3

Arachidic C20:0

≤ 0.8

0.1

0.2-0.8

≤ 0.2

≤ 0.2

0.1-0.6

0.1-0.5

0.2-0.5

Eicosenoic C20:1 (11)

n.d.

0.1-0.3

0.1-3.4

≤ 0.2

≤ 0.2

≤ 0.3

≤ 0.5

0.1-0.5

Behenic C22:0

≤ 0.2

0.1

≤ 0.5

n.d.

n.d.

0.3-0.7

≤ 0.7

0.5-1.6

Lignoceric C24:0

≤ 1.0

n.d.

≤ 0.2

n.d.

n.d.

≤ 0.4

≤ 0.5

≤ 0.5

aLow erucic acid canola oil, bRegular (= linoleic-type) sunflower oil, cHigh-oleic acid sunflower oil, n.d.: not determined

There are further limitations of using fatty acid profiles as purity indicators. Significant variations within olive oil cultivars have been reported due to environmental differences among the growing regions. Studies on cultivars, harvest timing, and environmental effects have shown the fatty acid profile for olives to be inconsistent, therefore limiting the value for authenticity testing.14,26

Despite these limitations, there are some unique characteristics of olive oil in relation to fatty acids which can be useful. The linolenic acid content of olive oil is generally less than 1% (w/v) of the total fatty acids. This is in contrast to canola oil (6-14%) and soybean oil (5.5-9.5%). This difference is useful to identify possible substitution from two of the most likely adulterants.

11.3 Triacylglycerols

From the 13 or more fatty acids present in olive oil, theoretically a large number of TAGs may exist. However, the actual number of variants is much lower than expected. Data for European oils indicate that those which predominate contain linoleic (L), oleic (O), palmitic (P), and stearic (S) acids in the following concentration ranges: OOO (40-59%), POO (12-20%), OOL (12.5-20%), POL (5.5-7%), and SOO (3.7-7%).24 Some combinations of fatty acids are never found, including fully saturated TAGs, such as PPP, SSS, PSP, or SPS.12 Data for Australian and New Zealand oil27 show slightly different proportions but the same order of prevalence (Table 4).

Table 4: Mean composition of TAGs present in Australian (n=1200) and New Zealand (n=141) EVOO’s.27

 

POP

PLP

POS

POO

POL

PLL

SOO

OOO

OOL

LLO

LLL

Mean

Australia

4.2

1.4

1.0

27.6

7.2

1.0

3.7

42.4

9.4

1.5

0.4

Mean

New Zealand

3.1

0.8

0.6

26.5

4.9

0.6

3.3

50.9

7.8

1.1

0.4

The unique TAG composition of olive oils has been proposed as a useful tool in detecting the presence of seed oils within olive oil blends.28 In a recent study, a database of TAG and fatty acid profiles for Australian and New Zealand olive oils was established for 1200 individual Australian and 141 New Zealand oil samples across the growing regions.27 The relationship of oleic acid to dioleoylpalmitin (C18:1 and POO) was useful in discriminating among olive oils and most seed oils (Figure 7).27

Figure. 7. Discrimination of oil types based on the relationship of oleic acid (C18:1) and dioleoylpalmitin (POO).27

The discrimination among blends of seed oils and olive oil, using various combinations of individual triacylglycerols and fatty acids, is useful but not always precise. For example, using the relationship of oleic acid and dioleoylpalmitin, for canola oil/olive oil blends show that blends containing high concentrations of canola oil (95%, 75%, 50% canola oil) were easily distinguishable from 100% EVOOs (Figure 8). However, low, mid, and high oleic acid canola oils showed that blends of canola oil and EVOO which were 50% canola oil or less, were indistinguishable using this method of analysis.

Figure 8. Comparison of canola oil (low oleic)/olive oil blends against the Australian and New Zealand TAG and FAP database.27

11.4 Minor Compounds

The minor compounds in vegetable oils are generally referred to as unsaponifiable matter. This is the fraction that remains after the oil has been treated with alkaline reagents to cause saponification of the TAGs and subsequent removal of this fraction by solvent extraction. Although this unsaponifiable group of compounds may exclude some minor compounds, it is commonly used to isolate non-glyceridic components. These minor compounds include sterols, pigments, and squalene.

For the purpose of this document, the discussion of minor compounds will be limited to those substances that are useful in determining product quality and authenticity. This discussion will also include some degradation products obtained from minor compounds when the oil has aged or has been heated and/or refined.

11.4.1 Phytosterols

Phytosterols, like fatty acids, provide a characteristic fingerprint of olive oil. The sterols are present in free form (14-73% of total sterols) or as fatty acid esters (27-86% of total sterols).29 The major sterols (Figure 9) in olive oil (listed in Table 5), show “apparent β-sitosterol” as the sum of β-sitosterol, Δ-5-avenasterol, Δ-5-23-stigmastadienol, clerosterol, and sitostanol. β-Sitosterol is the most predominant. Campesterol, although significant in olive oil at 2-4%, is considerably less than that of oilseed crops such as soybean and sunflower (Table 6). It is therefore useful in screening for the presence of those oils. Olive oil shows only a trace of brassicasterol, the major sterol of brassica crops such as canola/rapeseed, and it is therefore a suitable screening tool for adulteration of oil from that species.

Table 5. 4-Desmethylsterol composition (% of total sterols) of olive oil.

 

International
Olive Council30

Boskou et al.24

Guillaume et al.31

β-Sitosterol

Δ5-Avenasterol

Cholesterol

Brassicasterol

Campesterol

Stigmasterol

Δ7-Stigmastenol
Apparent β-sitosterola

n.a.

n.a.

≤  0.5

≤  0.1b

≤  4.0

< campesterol in edible oils

≤  0.5

≥ 93.0

75-90

5-20

n.a.

n.a.

≤  4.0

≤  2.0

n.a.

n.a.

84-87

4-7

0.1-0.2

n.a.

3-4

0.7-0.8

0.3-0.4

93-94

 aß-Sitosterol, Δ5-avenasterol, Δ5,23-stigmastadienol, clerosterol, sitostanol, and Δ5,24-stigmastadienol
bLimit raised to < 0.2 for olive pomace oils; Although there is a peak for brassicasterol, it is considered to be an artifact.
n.a.: not available

                                                                                   
Figure 9. The major phytosterols in olive oil.

Table 6. Relative 4-desmethylsterol composition (%) of olive oil and potential adulterants taken from Codex Alimentarius32 and Benitez-Sánchez et al.33

4-Desmethylsterol

Olive

Hazelnut

Canolaa

Coconut

Palm

Soybean

Sunflowerb

Sunflowerc

Δ5-Avenasterol

5-20

1.5-4.9

2.5-6.6

20.0-40.7

≤ 2.8

1.5-3.7

≤ 6.9

1.5-6.9

Brassicasterol

≤ 0.1

n.a.

5.0-13.0

≤ 0.3

≤ 0.05

≤ 0.3

≤ 0.2

≤ 0.3

Campesterol

≤ 4.0

4.3-5.7

24.7-38.6

6.0-11.2

18.7-27.5

15.8-24.2

6.5-13.0

5.0-13.0

Cholesterol

≤ 0.5

≤ 1.1

≤ 1.3

≤ 3.0

2.6-6.7

0.2-1.4

≤ 0.7

≤ 0.5

β-Sitosterol

75-90

72.2-85.2

45.1-57.9

32.6-50.7

50.2-62.1

47.0-60.0

50.0-70.0

42.0-70.0

Δ7-Stigmastenol

≤ 0.5

0.5-3.3

≤ 1.3

≤ 3.0

0.2-2.4

1.4-5.2

6.5-24.0

6.5-24.0

Stigmasterol

≤ 2.0

0.7-1.0

0.2-1.0

11.4-15.6

8.5-13.9

14.9-19.1

6.0-13.0

4.5-13.0

aLow erucic acid canola oil
bRegular (= linoleic type) sunflower oil
cHigh-oleic acid sunflower oil
n.a.: not available

11.4.2 Waxes

Waxes, the esters of fatty acids and fatty alcohols, are predominant on the skin surface of olives. Little of the wax is removed during mechanical extraction of the oil in compliance with EVOO processing. However, the use of solvents to remove residue oil from the pomace will also remove the wax esters. Hence, the presence of waxes in EVOO therefore provides a clear indication of the presence of pomace oil.

11.4.3 Aromatic and phenolic compounds

Phenolic compounds play a very important part of the minor components of olive oil. In addition to providing a considerable contribution to the flavor, bitterness, and pungency of olive oil, their contents also determine the oil stability and shelf life.34,35 Depending on the method of extraction, the phenolic compounds may be considerably reduced in the oil.

Phenolic compounds include a wide range of structures, including cinnamic acid derivatives (caffeic acid, cinnamic acid, coumaric acid, ferulic acid), simple phenols (gallic acid, p-hydroxybenzoic acid, homovanillic acid), tyrosol and hydroxytyrosol, secoiridoids (oleuropein and its aglycone, ligstroside and its aglycone, oleacein, oleocanthal, oleokoronal, oleomissional, and ligstrodial), flavonoids (apigenin, luteolin, cyanidin-3-O-glucoside, cyanidin-3-O-rutinoside), and lignans (pinoresinol).36 From a quantitative perspective, secoiridoids are by far the most abundant phenolic compounds in olive oil (Figure 10).37-39

Figure 10. Selected secoiridoids in olive oil.

11.4.4 Pigments

Olives and olive oil contain several pigments. The color of the oil may range from grey/green to straw yellow depending on the stage of maturity at which the olives are harvested. The major pigments in olive oil are chlorophylls and carotenoids.

The chlorophylls include chlorophyll a, chlorophyll b, and chlorophyll derivatives such as pheophytin. Carotenoids include several compounds including β-carotene, violaxanthin, and lutein. As the fruit ripen, chlorophyll and carotenoids decrease.12 When the fruit has matured, it becomes violet or purple as the chlorophyll is replaced by anthocyanins.30  Data on the levels of anthocyanins in olive oil are lacking, but concentrations are likely to be very low.  

Pigments have been shown to provide a measure of oil quality. The green color of the oil extracted from green olives is an indication of freshness. As chlorophyll is converted to pheophytin, the oil color changes from green to yellow. The measurement of pheophytin and pheophytin a can be used to measure the level of degradation.

11.4.5 Pyropheophytin

A recent study highlights the value of pyropheophytin as an indicator of olive oil quality and freshness.40 The measurement of pyropheophytins helps detect deodorized olive oils and is effective in determining oil storage conditions and ageing (Figure 11). A method for the measurement of pyropheophytin, published by the International Organization for Standardization (ISO), involves the determination of the proportions of pyropheophytins to the total pheophytins in virgin olive oil by high-performance liquid chromatography with ultraviolet detection (HPLC-UV).41 There is also a strong correlation with organoleptic defects and increased levels of pyropheophytin.

A.  EVOO without heating

B.  EVOO exposed to 160°C for 60 minutes

Figure 11. Vegetable fats and oils – Determination of the degradation products of chlorophylls a and a' (pheophytins a and a' and pyropheophytins). ISO 29841:2009.41 Images provided by Rodney J. Mailer.

11.5.1 Minor secondary compounds

During processing, particularly where heat has been used, as in refining, bleaching, and deodorizing, several secondary products other than pyropheophytins, particularly polycyclic aromatic hydrocarbons (PAHs),42 may be formed. These are often useful markers to detect the presence of refined oils, be it olive oil or blended seed oils.

11.5.2 1,2-Diacylglycerol content

The ISO has published a method for the analysis of 1,2 and 1,3-diacylglycerols.43 When a fatty acid molecule is cleaved from a triacylglycerol, the hydrolysis takes place at the sn-1* position forming a 1,2-diacylglycerol. Eventually, some of the 1,2-diacylglycerols will be converted by acyl migration into 1,3-diacylglycerols, which are more stable.44 The proportions of 1,2-diacylglycerols to 1,3-diacylglycerols have been shown to indicate oil freshness and quality.40

11.5.3 Stigmastadienes

Sterenes are a group of molecules formed during olive oil refining through the dehydration of sterols. A major member of this group is stigmasta-3,5-diene, which is formed from the dehydration of ß-sitosterol.45 Small amounts of stigmasta-2,4-diene can also be present. The occurrence of stigmasta-3,5-diene is evidence of the use of bleaching clay or high temperature applications used in deodorizing. This is the most important and sensible parameter to detect the undeclared addition of refined oils to olive oil.

11.5.4 Triterpene dialcohols and aliphatic alcohols

Triterpene dialcohols, such as erythrodiol and uvaol, are analyzed simultaneously with sterols. Erythrodiol and uvaol are generally at less than 4.5% of total sterols in EVOO but are much higher in the olive skin. Solvent extraction of olive paste pulls these chemical compounds out from the ground seed and, therefore, excessive amounts of these compounds indicate the presence of pomace oil.

A range of aliphatic alcohols are present on the skin of olives as well as in the oil itself. The presence of these alcohols, which range from C20 – C32, may indicate the presence of solvent-extracted oil as they are collected from the skin during extraction of pomace oil.

12.  Methods for chemical analysis

Undoubtedly, olive oil has been the most studied of all edible oils due to its diversity, the perceived health benefits, and the risks for fraudulent products due to its relatively high value. The number of methods for evaluating olive oil is, therefore, exceedingly large and covers multiple purposes. Over the years, numerous organizations have presented alternative methodologies in determining the components of interest. In order for a laboratory to efficiently screen large numbers of samples, the methods need to be accurate, fast (high-throughput technology), economical to carry out, and be within the capability of other laboratories, throughout the world, to reproduce. New methods are continually being developed, particularly with current technologies and instrumental methods that increase the speed and accuracy of the analysis. Since the evaluation of each published method for the determination of olive oil quality and authenticity in the context of a laboratory guidance document would be overwhelming, a number of criteria have been used to select the most pertinent analytical methods. For example, the methods described have been limited to those measuring components which are useful for determining authenticity. For chemometric methods, the selection criteria included the publication date (after 2000) and ease of access.

Gas chromatography (GC) and high-performance liquid chromatography (HPLC) methods predominate as the techniques of choice for analysis for olive oil and its minor components. Some more traditional methods, including column and thin-layer chromatography (TLC) continue to be used in current laboratory settings.

In recent years, numerous instrumental techniques have evolved, such as near infra-red spectroscopy (NIR) and instruments to rapidly predict oxidative stability or shelf life. These instruments are considered secondary methods, often requiring verification with materials analyzed by traditional primary methods.

Several international organizations publish methods for analysis of olive oil — in some cases — along with the limits for each of the constituents. The most widely quoted methods are those of the IOC (represented in Figures 5, 11, and 12).30 The IOC was set up in Madrid, Spain, in 1959, under the auspices of the United Nations. Its mission statement declares that it “contributes to the sustainable and responsible development of olive growing and it serves as a world forum for discussing policy-making issues.”

However, different countries have their own definition of standards for olive oil along with their respective parameter limits. Generally, these standards are based on the IOC standards30 although frequently with some slight modifications. Table 7 lists some of the standards set by different bodies across the globe.

Table 7: Standards Established by Authoritative Bodies.

Standard

Title/Revision

Codex Alimentarius46

Standard for Olive Oils and Olive Pomace Oils. CXS 33-1981. Adopted in 1981. Revised in 1989, 2003, 2015. Amended in 2009, 2013

European Union47

Commission Regulation (EEC) No 2568/91 of 11 July 1991 on the characteristics of olive oil and olive-residue oil and on the relevant methods of analysis. Consolidated version: 04/12/2016

International Olive Council30

Trade Standard. COI/T.15/NC No 3/Rev. 11. 2016

United States48

United States Standards for Grades of Olive Oil and Olive-Pomace Oil

State of California49

Grade and Labelling Standards for Olive Oil, Refined-Olive Oil and Olive-Pomace Oil

Argentina50

Código Alimentario Argentino. Capítulo VII. Alimentos Grasos. Aceites Alimenticios. Artículos 535 y 536

Australia51

Australian Standards: Olive oils and olive-pomace oils. AS 5264—2011

Brazil52

Instrução normativa No 1, 30 de Janeiro de 2012

South Africa53

South African National Standard. Olive oils and olive-pomace oils. SANS 1377:2015 Edition 1

Due to the variations that exist among the standards, in some situations an olive oil may be acceptable as EVOO in some countries but rejected in others. The lack of an agreed-upon standard creates further complications in fighting fraud on the international and national level.

12.1 General methods to determine quality and purity

Refining generally requires the application of heat, which can cause detectable changes in olive oil. Poor storage conditions and storage of oil over long periods of time can also produce similar undesired chemical changes. These deviations from EVOO provide marker compounds to detect poor quality EVOO.

12.1.1 UV absorption

Heating olive oil can result in the formation of conjugated dienes and trienes which can be detected by changes in the absorbance value by ultraviolet (UV) spectroscopy. A number of standard-setting bodies have adapted UV spectrophotometry as one of their quality tests, e.g., COI/T.20/Doc. No 19/Rev.4,54 ISO 3656,55 or the American Oil Chemists’ Society (AOCS) Ch 5-91.56 However, such measurements at individual wavelengths, i.e., at 232 nm, and 268 nm or 270 nm, are not specific and any results from such tests can be useful only in combination with other analytical methods.

12.1.2 2-Glyceryl monopalmitate

Extra virgin olive oil has a low concentration of palmitic acid in the sn-2 position of the triacylglycerols. The IOC standard30 indicates EVOO must be < 1% whereas pomace oil must be < 1.4%. 2-Glyceryl monopalmitate may be determined after enzymatic hydrolysis of TAGs using a lipase according to COI/T.20/Doc. No 23/Rev.1,57  or to ISO 12872.58

12.1.3 Free fatty acids

An elevated level of free fatty acids indicates poor quality fruit were used during the olive oil extraction process. High free fatty acids will result in poor quality oil with organoleptic defects. Determination of the free acidity may be carried out using acid-base titration according to COI/T.20/Doc. No 34/Rev.1.59

12.1.4 Peroxide value

Peroxide is a measure of oxidation (rancidity) in oil. High peroxide content may be a result of poor processing or prolonged exposure to air. Oil should be stored in sealed containers or under a blanket of inert gas, such as nitrogen or argon. Peroxide value is determined according to COI/T.20/Doc. No 35/Rev.1,60 ISO 3960,61 or AOCS Cd 8b-90.62

12.1.5 Equivalent carbon number (ECN) value

The ECN value in a TAG is the difference between the equivalent carbon number as determined by RP-HPLC analysis and GC analysis and the theoretical ECN number calculated from the fatty acid composition. It is obtained using the number of fatty acid carbons in a TAG minus two times the number of double bonds. For example, the ECN for trilinolein (see Section 12.2), which has three linoleic acids (C18:2) attached to the glycerin molecule, is 42 (3 x 18 – 2 x 6). The method for the determination of the difference between the actual and theoretical ECN 42 triacylglycerol content is described in detail by the IOC63 and by AOCS.64

12.2 Gas chromatography and high-performance liquid chromatography

12.2.1 Fatty acid methyl ester analysis

Gas chromatography is the traditional method of analysis for fatty acids following saponification of the triacylglycerols and methylation of the fatty acids to create fatty acid methyl esters (FAME). The FAMEs are most often created by dissolving the olive oil sample in hexane, heptane, or other appropriate solvent, and reacting it with 2N methanolic potassium hydroxide solution.47,65-69 ISO allows transmethylation using sequential alkaline and acidic conditions, boron trifluoride,70 or a base-catalyzed transesterification with trimethylsulfonium hydroxide.71 However, the use of boron trifluoride is not recommended due to its toxicity. Capillary gas chromatography with flame ionization detector (GC-FID) is a simple and quick method for easy and efficient separation of fatty acid methyl esters, even in complex matrices (Figure 12). Several organizations have created official methods to analyze fatty acids in olive oil, or vegetable oils in general, e.g., the European Commission Regulation EC 2015/1833,68 the AOCS standard 2-91,72 the ISO standard 12966-4:2015,73 or the IOC method for fatty acid methyl ester analysis (Figure 12).69


Figure 12. GC/FID chromatogram of fatty acids in olive oil based on IOC method COI/T.20/Doc. No 33/Rev.169 Image courtesy of Rodney Mailer.

Several research papers detailed additional conditions to determine FAMEs in olive oil by GC-FID. A majority of the papers retrieved used cyanopropyl polysiloxane stationary phases with various modifications for the separation.65-67,74-77 Starting temperatures were generally between 120oC – 160oC, with a temperature change of 3-5oC/min.65-67,74,75

12.2.2 Sterols, triterpene dialcohols and aliphatic alcohols

Sterol analysis by capillary GC simultaneously determines sterols, triterpene dialcohols, and aliphatic alcohols. The method requires the saponification of the oil sample in a suitable solvent, extraction of the unsaponifiable matter in diethyl ether, and the separation of the sterol fraction by thin-layer chromatography. The sterols are then separated by GC. Various modifications of this method have been attempted to remove the need for TLC. However, this method remains the official IOC technique. The IOC method of analysis is COI/T.20/Doc. No26/Rev.3 June 2018.78 The ISO 12228:2009 method replaces the solvent-extraction in the sample preparation with solid-phase extraction (SPE) on aluminum oxide. However, the authors caution that results obtained by ISO 12228:2009 can lead to different results from those obtained using the IOC method.

A number of additional methods have been developed to measure sterols in olive oils and other vegetable oils, either by GC or HPLC. Vichi et al.79 separated sterols from the fatty acid fraction using SPE. The sterol fraction was further purified on silica gel by TLC according to EU method 2568/91. Free sterols were eventually determined after silylation by GC-FID. While individual sterols were not sufficient to determine adulteration with hazelnut oil, the Δ7-stigmastenol/Δ7-avenasterol ratio allowed detection of the addition of 10% hazelnut oil. Mariani et al.80 proposed the evaluation of free and esterified sterols to highlight the presence of 6-8% hazelnut oil in olive oil.

In order to simplify the sample preparation, several authors have developed HPLC-GC combination methods.81,82 For the analysis of free sterols, diluted oils were injected directly into the liquid chromatograph to separate free sterols from triglycerides. The sterol fraction is automatically transferred to the gas chromatograph using the through oven transfer adsorption desorption (TOTAD) interface.82 For the determination of total sterols, olive oil samples were saponified with potassium hydroxide in ethanolic solution and the unsaponifiable fraction was extracted with diethyl ether. The extract was then analyzed by reversed phase HPLC-GC,82 avoiding the laborious TLC step used in the official European Union (EU) method.47 In another method, saponification and extraction were performed by an autosampler before separation of sterols by normal phase HPLC using a silica column and further separation and quantification of sterols using GC-FID.81 Quantitative results obtained were comparable to the IOC and ISO methods.81

12.2.3 Stigmastadienes

Refined oil contains stigmasta-3,5-diene, and other minor sterenes as a result of the dehydration of sterols, particularly β-sitosterol, during refining. The process of analysis requires separation of the unsaponifiable matter from the olive oil, which is done by extracting the saponified olive oil with hexane, followed by fractionating the sample on silica gel columns. The eluent is analyzed by GC, as per the IOC method COI/T.20/Doc. No 11/Rev. 3.83 The laborious sample preparation requirement in the IOC method has prompted researchers to look for alternative ways to analyze these sterenes, e.g., by HPLC.84 More recently, a method combining HPLC and GC has been proposed. The sample is dissolved in hexane, then the sterene fraction is separated by normal phase HPLC before an HPLC-GC transfer occurs using the retention gap technique with concurrent solvent evaporation. Sterenes are separated by GC on a phenyl polydimethylsiloxane column and detected by FID.85

12.2.4 Triacylglycerols

HPLC with a refractive index (RI) or evaporative light scattering detector (ELSD) has been used in the past to separate TAGs.86 Trilinolein was proposed as a possible marker for adulteration with other vegetable oils since olive oil contains very low concentrations of this TAG. However, separation by HPLC is poor, leading to difficulties in accurately quantifying the TAGs. In addition, the use of the RI detector prevents running HPLC in a gradient system, leading to peak broadening in the later eluting peaks. More reliable results can be obtained using a mass spectrometer (MS) as the detector, e.g., a charged aerosol detector (CAD),87-90 atmospheric pressure chemical ionization (APCI)-MS,91-93 or a matrix laser desorption ionization-time-of-flight (MALDI-TOF) detector.91 Using a MS detector allows the simplification of the sample preparation to a one-step dilution, and the quantification of trilinolein even if the peak co-elutes with other TAGs. When combined with statistical methods, HPLC-MS methods can distinguish olive oil from similar oils such as hazelnut and camellia oils, and have demonstrated the ability to detect admixture with sunflower oil starting at concentrations of 1%.93 The main disadvantage of an HPLC-MS method is the comparatively high equipment cost.

In 2013, IOC developed a method using capillary GC-FID (COI/T.20/Doc. No 32 November 2013) for TAG analysis.94 The basis of the method is to dissolve the sample in a suitable solvent such as n-heptane, along with an internal standard and silylating reagent, and directly inject the mixture into the GC. Triacylglycerols are resolved based on their carbon atom number. Very high temperatures are required for separation, and as a result column life is short. The method also allows evaluation of diacylglycerols with the same injection. In 2017, IOC published another approach,63 combining an HPLC-RI method with a GC-FID to determine the fatty acid methyl esters according to COI/T.20/Doc. No 33/Rev.1.69 While this method provides a better quantitative assessment of the fatty acids, the sample preparation is cumbersome, and the need for two methods is not very practical in a quality control laboratory.

In a recent study, GC has been used with a modification of the operating conditions27 using a Restek Rtx 65TG 30m column. Good separation was achieved with a runtime of only 13 minutes (Figure 13). Using this method, over 500 injections were possible before needing to replace the column. A comparison of the various methods is provided in Table 8. 

 

Figure 13. Chromatogram of TAGs in EVOO: Restek Rtx 65TG column, 0.25mm ID, 0.1μm, 30m; 300°C to 370°C at 15°C/min; hold for 8.33 min at 370°C; injector temperature: 320°C; detector temperature: 370°; flow rate: 2ml/min; Split : 100:1; Injection volume: 1.5-2µL.27

Table 8: Comparison among methods to measure triacylglycerols in vegetable oils.

Author

Method

Sample preparation

Run time

Comments

IOC No. 3294

GC-FID

Multiple steps, including silylation

31 min.

Complex sample preparation, low peak resolution; analysis of di-and triacylglycerides

Ayton27

GC-FID

Dissolution of olive oil in isooctane

13 min.

Quick and simple sample preparation, some peak overlap but overall acceptable resolution

IOC No. 2063,69

EC 2472/9795

HPLC-RI + GC-FID

Multiple steps, including column chromatography or SPE for HPLC, and transesterification for GC-FID

55 min (HPLC)

22.5 min. (GC-FID)

Complicated & time-consuming sample preparation; low peak resolution

Moreda86

HPLC-RI (three methods, including EC 2472/97)95

Multiple steps, including SPE

55-60 min

Time-consuming sample preparation; low peak resolution

Guerfel96

HPLC-ELSD

Dilution in isopropanol/acetonitrile/hexane

37 min.

Low peak resolution, no information on trilinolein

De la Mata Espinosa87,90

HPLC-CAD

Dilution in hexane

45 min.

Validated method; peak overlap, but quantification possible with CAD; expensive equipment

Green88

UHPLC-CAD

Dilution in methanol/chloroform

45 min.

Validated method; peak overlap, but quantification possible with CAD; expensive equipment

Holčapek93

Lisa92

HPLC-APCI-MS & PCA

Dilution in isopropanol/acetonitrile/hexane

110 min.

Peak overlap, but quantification possible with MS; distinction of olive oil with 59 other vegetable oils using PCA; long run time; expensive equipment; no validation

Jakab91

HPLC-APCI-MS & LDA;

MALDI-TOF & LDA

Dilution in acetone/acetonitrile (APCI-MS)

Dilution in chloroform (MALDI-TOF)

47.5 min. (APCI-MS)

No separation (MALDI-TOF)

Peak overlap, but quantification possible with MS; distinction of olive oil with 13 other vegetable oils using LDA; expensive equipment; No validation

Lucci89

UHPLC-CAD

Multiple steps, including SPE

27 min.

Peak overlap, but quantification of trilinolein possible even without CAD; expensive equipment; partly validated

SPE: Solid phase extraction
PCA: Principal component analysis
LDA: Linear discriminant analysis

12.2.5 Wax esters

Wax esters in olive oil include, e.g., phytyl-, geranylgeranyl-, and benzyl-esters of fatty acids, such as phytyl linoleate and phytyl stearate,97,98 esters of fatty acids with long-chain aliphatic alcohols in the range C22−C28, and fatty acid esters with sterols.98 IOC has established wax limits of ≤ 150 mg (sum of waxes containing 42, 44, or 46 carbon atoms) per kg EVOO and of >350 mg (sum of waxes containing 40, 42, 44, and 46 carbon atoms) per kg for olive pomace oils.30 The presence of esters with carbon numbers between C40-C46 at levels greater than 250 mg/kg is a good indication of adulteration with pomace oil due to solvent extraction.99 In the method published by IOC, the wax is separated from other olive oil components using silica gel chromatography. The sample is eluted with hexane:diethyl ether 99:1 and subsequently analyzed by capillary GC-FID. The IOC method of analysis is COI/T.20/DOC. 28/Rev.2, which allows for the determination of waxes, and fatty acid methyl and ethyl esters in a single run.100  

An improvement over the IOC method COI/T.20/DOC. No 28/Rev.2 was adopted by ISO in 2010.101 In this method, the sample preparation involves column chromatography on a mixture of silica gel and silver nitrate-impregnated silica gel with n-hexane/dichloromethane as eluent. The separation of the samples is done by GC with FID detector. Overall, the ISO method provides an improved peak resolution, allowing for a more accurate determination of C40–C46 esters.101 

Vichi et al. used direct electrospray (ESI) high-resolution mass spectrometry to profile olive oil wax components. Samples were injected into the HPLC-ESI-MS instrument after dilution in dichloromethane/methanol. The analysis time was only 6 minutes.98 The drawbacks of this method are the expensive equipment and the lack of data on other vegetable oils. However, the approach, combined with chemometric data analysis, will likely provide a robust method to detect adulteration with lower-grade olive oils or vegetable oils from other sources. 

12.3 Chemometric methods

At the core, chemometric assays for authentication classify sets of chemical data obtained with analytical methods using mathematical/statistical models. Vibrational spectroscopy, such as mid infrared (IR), near infrared (NIR), and Raman spectroscopy, mass spectrometry, and nuclear magnetic resonance (NMR) spectroscopy are commonly used analytical techniques that can be explored using multivariate statistics.102 These mathematical/statistical models can be supervised, which means that the identity of the samples used to build the model is known, or unsupervised, in which case the similarity of samples is assessed without prior knowledge about the category of which they are a part. Qualitative chemometric methods answer the question if an unknown sample is similar enough to a set of representative olive oils to classify it as olive oil, or as olive oil from a specific cultivar or geographic region, while quantitative chemometric methods try to determine how much of an adulterating oil has been mixed with genuine olive oil.102

The use of chemometric methods to distinguish olive oil from its adulterants started over 20 years ago and was initially driven by academic research groups. Despite a number of advantages, especially in the area of sample preparation, none of the published chemometric methods has been included as an official method, e.g., by IOC, or by other organizations in Australia, the European Union, or the United States.102 Reviews on chemometric methods for olive oil authentication have been published by Gómez-Caravaca et al.102 and Avramidou et al.103 A review of spectrometric and spectroscopic methods in combination with (or in rare cases without) multivariate statistical methods is provided in sections 12.3.1 – 12.3.4 below.

12.3.1 Raman, near infrared, and mid infrared spectroscopy

Raman, NIR, and IR spectroscopy are all measuring vibrations in molecules that have been exposed to an energy source, usually light in the infrared, near-infrared, and — in case of Raman — sometimes also in the ultraviolet and visible range. Advantages of infrared methods are the easy sample preparation, desirable environmental footprint, speed and versatility of modern NIR instruments, and relatively affordable equipment costs. A comparison of infrared methods used for olive oil authentication is provided in Table 9.

While NIR and IR measure the energy absorbed by the sample constituents, Raman measures changes in the energy of photons that are scattered after the interaction of energy with the sample.104,105 One advantage of NIR and Raman spectroscopy is the lack of interference by certain packaging materials, e.g., glass, allowing to measure samples stored in bulk containers.105 Although less of an issue with olive oil, particle size and water content do not have a major impact on Raman spectra. Among the three methods, infrared spectroscopy provides the most useful qualitative information, and is therefore widely used to determine the identity of the sample, especially with lipophilic samples where water content is very low.104,105 But Raman and NIR methods can also be used for determining authenticity if appropriate chemometric methods are applied. NIR has been used for oil analysis for many years, and studies in 2004 illustrated the potential to use this instrumentation to characterize olive oil.106,107 

Comments: Partial least square (PLS) regression is the method most often used to calibrate the chemometric models to predict the concentration of an adulterant in olive oil. The published infrared methods usually allow the detection and quantification of adulteration with a specific vegetable oil at low concentrations, and robust quantitative data can be obtained provided the adulterant is known, and the olive oil used to calibrate is the same as the one used in the adulterated material. However, there are less data on the usefulness of infrared methods to detect adulteration in commercial samples. Two publications listed in Table 9 reported the results from an evaluation of commercial samples. In one paper, the authors used vegetable oils with known concentrations of oleic, linoleic, and linolenic acids as calibrants. Subsequently, adulteration was based on the concentrations of these three fatty acids measured by infrared spectroscopy.115 The other investigation used blends provided by Aydin Commodity Exchange Laboratories (Aydin, Turkey) and the California Olive Oil Council (Berkeley, CA). The latter study used IR and Raman spectroscopy to measure the fatty acid profile, free fatty acids, peroxide value, pyropheophytins, and total polar compounds, which provided accurate classifications of all the authentic and adulterated oils.117 However, the concentrations of the adulterants are unknown, and, hence, it is unclear just how well these models work. One advantage for NIR is the availability of commercial software packages to measure fatty acids contents in edible oils, which is a helpful tool that allows the detection of adulteration with some undeclared edible oils.116 While the technique has many advantages, data generated from the infrared methods do not carry much significance alone and act as supplementary data to support results from other analytical methods, producing a more robust process for the determination of olive oil authenticity. 

Table 9: Comparison among infrared methods to authenticate olive oil.

Author

Method

Frequency

(cm-1)

Statistics

Comments

Muik108

Raman

1200-1800

PLS for calibration

Classification of olive oil quality based on free fatty acid content; 0.29-1.04% error of prediction; screening method-accuracy needs improvement

Christy107

NIR

4550-9000

PLS for calibration

PCA for classification

0.56-1.32% SEP in quantifying mixtures of olive oil and corn, hazelnut, soybean, sunflower, or walnut oils at ≥2% adulterant

Gurdeniz109

IR

675-1876

2520-3620

 

PLS for calibration

PCA and SIMCA for classification

1.04-1.40% SEP in quantifying mixtures of olive oil and corn/sunflower, cottonseed, or canola oils at ≥5% adulterant

Öztürk110

NIR

4000-10000

GILS & PLS for calibration

2.93-5.86% SEP using GILS

4.64-8.30% SEP for PLS for quaternary mixtures of olive oil with canola, corn, or sunflower oils; adulterant concentrations below 5% yield questionable results

Azizian111

NIR

5780-5830

PLS for calibration

No classification

Acceptable quantitative data on adulterant concentrations of ≥3-4% for canola, corn, hazelnut, palm olein, peanut, safflower, soybean, and sunflower oils. Detection of dilution with refined olive oil at ≥11.5% 

Vasconcelos112

IR

600-1800

2750-3050

PLS & PCR for calibration

PCA and LDA for classification

PLS: 1.04-1.26% SEP

PCR: 1.49-1.72% SEP

Ability to detect peanut oil adulteration at 1%

Georgouli113

IR

 

Raman

690-1875

2750-3100

800-1800

Multiple

Comparison among 10 chemometric methods for classification of olive-hazelnut oil mixtures at 4 or 10 ranges of adulterant concentration.

CLPP-kNN best prediction model with 40.97% and 79.19% correct assignments with 10 and 4 adulteration ranges, respectively.

Rohman114

IR

Grape seed & soybean oil:

1000-1200

3002-3018

 

Walnut oil:

667-1125

2954-3029

PLS & PCR for calibration

DA for classification

PLS: 0.93-1.49% SEP

PCR: 0.91-1.72% SEP at adulterant concentrations of 1-50%.

Filoda115

IR

1068-1225

2648-2726

2806-3042

PLS for calibration

0.62-4.44% SEP for fatty acids

0.86% SEP for adulteration concentration;

Method allows detection of canola, corn, soybean, and sunflower oil using one calibration set

Vanstone116

NIR

4551-9130

PCA for classification

Method allows detection of  adulteration with ≥10% canola oil, ≥15% soybean oil, and ≥20% of corn and sunflower oils; detection limit at 2.7% when unadulterated olive oil control sample available

Aykas117

IR

Raman

700-4000

250-1850

PLS for calibration

SIMCA for classification

 

IR: 0.02-1.46% SEP

Raman: 0.01-1.78% SEP

Multi-class models show 100% accuracy of product classification of adulteration with VOO/OO and vegetable oil blends; concentration of adulterants not indicated

CLPP: Continuous locality preserving projections
DA: Discriminant analysis
GILS: Genetic inverse least squares
kNN: k nearest neighbor
LDA: Linear discriminant analysis
PCA: Principal component analysis
PCR: Principal component regression
PLS: Partial least squares
SEP: Standard error of prediction
SPE: Solid phase extraction

12.3.2 Nuclear magnetic resonance spectroscopy

As with infrared methods, the ease of sample preparation and short analysis time makes NMR an appealing technology for olive oil authenticity determination. Table 10 lists some of the published methods to detect vegetable oil adulteration or country/region of origin determinations by NMR. One-dimensional 1H NMR appears to be the most widely used approach for discriminating olive oil and other vegetable oils. Particularly relevant are the signals for the olefinic fatty acid protons, and certain methyl protons of squalene and β-sitosterol.118,119 An interesting approach is the use of 31P-NMR after phosphitylation of diacylglycerides. However, the relatively long sample preparation steps for the reaction make this approach less advantageous than other NMR methods that require only simple dilutions.

Comments: Similar to the infrared methods, NMR works well in cases where the adulterant is known, and the olive oil is chemically well defined, although the concentrations at which known adulterants can be detected appear to be higher than what has been reported for IR/NIR methods. The development of methods using benchtop NMR instruments,128 where the ease of use and speed of analysis can be combined with affordable equipment, holds some promise for use in routine testing. Nevertheless, more data on the suitability of NMR to detect unknown types of adulteration in commercial bulk and finished product olive oils are needed to give this technique a more prominent role in the detection of fraud.

Table 10: Comparison among NMR methods to authenticate olive oil. 

Author

Experiment

Statistics

Comments

Royer120

SNIF-2H-NMR

ANOVA

Classification of olive oil based on geographical origin; no data on ability to detect adulteration.

Fauhl121

1D 1H-NMR

DA for classification

Discriminant analysis allows distinction of olive oil and oils adulterated with ≥25% hazelnut and ≥10% sunflower oils.

Mavromoustakos122

1D 13C-NMR

DA for classification

Method can distinguish between olive oil and olive oil adulterated with ≥5% corn, cottonseed, soybean, and sunflower oil based on olefinic signals for oleic and linoleic acids; 21.5% of authentic olive oil samples classified as adulterated.

Vigli123

1D 31P-NMR

1D 1H NMR

DA for classification

Complex sample preparation (reaction with 2-chloro-4,4,5,5-

tetramethyldioxaphospholane) for 31P NMR; Using 8 discriminant functions, adulteration of fresh olive oil with ≥5% of 12 different vegetable oils detectable. Adulterant detection conc. depends on olive oil age.

Fragaki124

1D 31P-NMR

 

HCA and DA for classification

Complex sample preparation (reaction with 2-chloro-4,4,5,5-

tetramethyldioxaphospholane) for 31P NMR; Using 5 discriminant functions, adulteration of extra virgin olive oil with ≥5% of lampante or refined olive oils can be detected

Mannina118

1D 1H NMR

LDA and multiple regression model for calibration

PCA for classification

0.65-0.88% SEP in quantifying mixtures of refined hazelnut and olive oils using 600 MHz instrument; detection of ≥10% refined hazelnut oil in refined olive oil; 400 MHz instrument does not allow quantitative analysis due to overlapping signals

Šmejkalová125

Diffusion coefficients for 1H-NMR peaks

DA for classification

Ability to detect ≥10% adulteration with sunflower and soybean oils, ≥30% adulteration with hazelnut and peanut oils

Agiomyrgianaki126

1D 31P-NMR

1D 1H NMR

CDA and CBT for classification

Complex sample preparation:

  • MeOH-water extraction for phenolic compounds
  • Reaction with 2-chloro-4,4,5,5-tetramethyldioxaphospholane) for 31P NMR

The limit of detection for refined hazelnut oil in refined olive oil is ≥5% with CDA, and ≤5% for CBT

Del Coco127

1D 1H NMR

PCA for classification

Method to establish olive oil origin; no data on adulteration with vegetable oils; small sample set

Parker128

1D 1H NMR

PLS for calibration

Method for 60 MHz benchtop NMR; detection of adulteration with hazelnut oil at ≥13% using olefinic:glyceride proton ratio, at ≥11% using PLS regression

Rongai129

1D 1H NMR

PCA and OPLS-DA for classification

Large sample set to establish a model for distinguishing oils from different country/region of origin; successful separation among Tunisian olive oils and oils from Australia, Chile, Italy, Portugal, and Spain. Some overlap between olive oils from Spain and Italy; no data on ability to detect adulteration

Girelli130

1D 1H NMR

PCA and OPLS-DA for classification

Same approach as Rongai et al.129 but with EVOOs of Tuscan origin; only limited capability to distinguish among cultivars and geographic location with both, PCA and OPLS-DA models; no data on ability to detect adulteration

Gouilleux119

1D-1H-NMR

COSY

 

PLS for calibration

PCA and SIMCA for classification

COSY allows to distinguish olive oil from canola, corn, hazelnut, sesame, and sunflower oils; SEP: 6.75% for quantitative determination of hazelnut in olive oils. Quantitative model not accurate below 20% hazelnut oil as adulterant.

CBT: Classification binary trees
CDA: Canonical discriminant analysis
DA: Discriminant analysis
HCA: Hierarchical cluster analysis
LDA: Linear discriminant analysis
OPLS-DA: Orthogonal partial least squares discriminant analysis
PCA: Principal component analysis
PCR: Principal component regression
PLS: Partial least squares
SEP: Standard error of prediction
SIMCA: Soft Independent Modeling of Class Analogy
SNIF: Site-specific natural isotope fractionation 

12.3.3 Mass spectrometry (stand-alone) 

In addition to HPLC-MS methods described in section 12.2, researchers have also applied mass spectrometry directly, i.e., without prior separation by liquid chromatography, to detect adulteration of olive oil (Table 11). Due to the high sensitivity of MS, it allows for the detection of adulterations at low concentrations provided that suitable distinction criteria can be found. Among the three methods evaluated, the direct analysis in real time – time-of-flight (DART-TOF) MS method can detect the broadest range of adulterants when using a methanol-water extraction to prepare the samples. This method uses some of the polar metabolites as parameters in the chemometric models, e.g., tyrosol, hydroxytyrosol, sinapic acid, and elenoic acid, which are much lower or altogether absent in lower-quality olive oils or adulterating vegetable oils.131 Of interest is the flow injection analysis – magnetic resonance mass spectrometry (FIA-MRMS) method, since it combines a simple sample preparation with a 2-minute analysis time. Using multivariate statistics, this method allowed classification of EVOO from three regions of Greece, and to distinguish among conventional, integrated, and organic oil production.132 The main drawbacks of these methods are the high equipment costs and the relatively complex setup of the chemometric models. In addition, there are no data on the usefulness of the method in mixtures of EVOO with lower quality olive oils. As with the other chemometric methods — e.g., IR/NIR, Raman, and NMR — direct MS is a commendable screening tool but should be combined with other methods to rule out the possibility of adulteration.

Table 11: Comparison among direct mass spectrometric methods to authenticate olive oil.

Author

Experiment

Statistics

Comments

Lorenzo133

Headspace-MS

LDA for classification

Classification based on ion intensity of volatiles; 99% successful prediction rate for adulteration with sunflower and olive pomace oils at concentrations of ≥5% adulterant

Vaclavik131

DART-TOFMS

LDA for classification

2 sample sets (TAG ions obtained by dilution in toluene, polar compounds by methanol-water extraction);

Toluene dilution: 100% accurate prediction at hazelnut oil concentrations of ≥15%

Methanol-water extraction: 100% accurate prediction at hazelnut oil concentrations of ≥6%;

Both sample sets allow distinction between olive oil and olive pomace oil

Da Silveira134

ESI-QQQMS

No statistics

Adulteration with soybean oil detected at ≥1% using 1-oleyl-2-linoleyl-3-margaroleylglycerin as marker

Nikou132

FIA-MRMS

PCA

OPLS-DA

Good prediction of geographic origin and processing method; No data on ability to detect adulteration with other vegetable oils

LDA: Linear discriminant analysis
OPLS-DA: Orthogonal Projections to Latent Structures Discriminant Analysis
PCA: Principal component analysis 

12.3.4 Stable isotope ratio (SIR) analysis

Stable isotope ratio analysis for the authentication and determination of geographic origin of olive oil has been used by several researchers, either alone or in combination with other analytical methods and subsequent multivariate statistical analysis.135-143 

Comments: Variations in the SIRs in plants can be used to distinguish among species or determine the environment in which a plant was grown. For olive oil, the 13C/12C ratio has been the most widely used factor for the authentication and country/region of origin determination. The 13C/12C ratio in plants depends on the type of photosynthesis a plant utilizes. While most plants exclusively use the Calvin cycle, some plants (e.g., corn [Zea mays, Poaceae] or sugar cane [Saccharum officinarum, Poaceae]) have additional photosynthetic pathways, leading to a slightly higher 13C/12C ratio. As such, the undeclared admixture of corn oil is readily detected by SIR. In addition, environmental factors, such as temperature and precipitation, have an impact on the 13C/12C ratio, which is why this ratio can be used to determine the geographic region in which a plant was grown. The 18O/16O ratio depends on the temperature, freshwater input, and other climatic factors. Similarly, the 2H/1H ratio in plants is influenced by the geographical origin of the local water.

SIR determinations in olive oil are usually obtained by GC-IRMS. Spangenberg et al. used the 13C isotope composition of oleic versus palmitic acid to detect adulteration with canola, corn, hazelnut, peanut, sunflower, walnut, and mixed vegetable oils, as well as olive pomace oil.135 Subsequent investigations mainly focused on determining the country/region of origin with SIR alone,136,139,140 or SIR in combination with metal profiling by ICPMS,138,141 or NMR,137,143 HPLC-MS,143 or Raman analysis.142 SIR is a unique approach that can resolve some of the more challenging types of olive oil fraud, particularly the determination of the country/region of origin. Drawbacks are the relatively large number of samples needed to establish a robust statistical model, and the expertise and costs involved in performing the analysis. While SIR is still mainly used in academic settings, there are a few contract analytical laboratories that offer the service on a routine basis.

13.  Conclusion

Adulteration of EVOO and VOO comes in many shapes and forms, such as the dilution with lower-grade olive oils, undeclared vegetable oils, or the undeclared addition of pigments such as chlorophyll or β-carotene.1 The selection of the analytical method of choice is dependent on the type of adulteration, but in all cases, authenticity can be established only by combining several orthogonal methods.

The large range of components in EVOO allows for multiple methods of authenticity testing. The triacylglycerol and fatty acid profile are unique in some characteristics, particularly in the high concentration of oleic acid and minimal amounts of linolenic acid. But the best approach to distinguish olive oil from adulterants is within the minor compounds, e.g., some of the phenolics, or the unsaponifiable fraction. Sterols offer clear differences with possible adulterants, such as the limited concentration of campesterol and brassicasterol related to other vegetable oil-providing species. More recently, the acceptance of the use of pyropheophytin to detect refined oil and 1,2 and 1,3-diacylglycerol as measures of freshness have further increased the ability to detect fraud.

Besides the likes of official methods established by IOC, AOCS, ISO, or government agencies in many countries, spectrometric and spectroscopic approaches combined with multivariate statistical analysis have shown great promise in detecting adulteration in many “olive oils”. These methods are advantageous with regards to the ease of sample preparation and speed of analysis, but often require a substantial investment in equipment and expertise in order to perform the work. Nevertheless, methods based on IR, NIR, Raman, NMR, and MS data have proven highly useful in detecting olive oil adulteration. Based on the comparatively lower equipment cost, infrared-based chemometric approaches may be the first choice for an industry laboratory.

The need to screen large numbers of samples and the expense of such testing make detection of fraud more difficult. Further development in instrumental techniques, particularly in the area of spectrometry and spectroscopy, should overcome these limitations. 

* Stereospecific Numbering. To designate the configuration of glycerol derivatives, the carbon atoms of glycerol are numbered specifically to the configuration the glycerol carbons. The carbon atom that appears on top in the Fischer projection that shows a vertical carbon chain with the hydroxyl group at carbon-2 to the left is designated as C-1. To differentiate this from numbering without steric information, the prefix ‘sn’ (for stereospecifically numbered) is used.

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