Honeydew honeys: a review on characterization and authentication of

Review pubs.acs.org/JAFC

Cite This: J. Agric. Food Chem. 2018, 66, 2523−2537

Honeydew Honeys: A Review on the Characterization and Authentication of Botanical and Geographical Origins Consuelo Pita-Calvo and Manuel Vázquez* Department of Analytical Chemistry, Faculty of Veterinary Science, University of Santiago de Compostela, 27002 Lugo, Spain ABSTRACT: The commercial interest in honeydew honeys (from the secretions of plants or the excretions of plant-sucking insects found on plants) is increasing because of their higher therapeutic properties compared with those of most blossom honeys (from nectar). However, honeydew honeys have been less studied than blossom honeys. In this work, studies carried out to characterize and authenticate honeydew honeys by their botanical and geographical origins have been reviewed. The identification of honey origins has been approached by two ways: by the analysis of chemical markers and by the development of analytical methodologies combined with multivariate analyses. Some compounds have been suggested as specific botanical markers of several honeydew honeys, such as quercitol and trans-oak lactone for oak honey, 2-aminoacetophenone and propylanisol for holm oak honey, and 1-chloro-octane and tridecane for pine honey. The presence of 3-carene and an unidentified compound in samples was proposed as a way discriminate between Greek and Turkish pine honeys. Chemometric analyses have been applied on chemical compositions and on physicochemical, microscopic, and spectral parameters and have proved to be valuable methods for authenticating honeydew honeys. Analytical methods based on spectral information are suitable for the routine control of honeydew-honey origins because they are fast and require easy sample preparations. KEYWORDS: honey, honeydew, chemical characterization, botanical authentication, geographical authentication, botanical chemical markers, geographical chemical markers, classification, multivariate analysis

1. INTRODUCTION Honey is a natural, sweet substance produced by bees (Apis mellifera). It is a compound blend primarily consisting of carbohydrates (70−80%, w/w) and water (10−20%, w/w). The most abundant carbohydrates are glucose (∼31%, w/w), fructose (∼38%, w/w), and their disaccharides.1 Honey also contains a large number of minor components. It possess health-promoting properties, such as antioxidant, antibacterial, free radical-scavenging, and anti-inflammatory activities, and has shown antitumoral efficacy, all of which depend on the flora from which the honey was produced.2−4 Honey has been reported to have inhibitory effects on monoamine oxidase5 and carbonic anhydrase6,7 which are considered to be derived mostly from the honey polyphenols. Honey is rich in both enzymatic (catalase, glucose oxidase, and peroxidase) and nonenzymatic antioxidant substances (phenolic compounds, ascorbic acid, α-tocopherol, carotenoids, organic acids, amino acids, proteins, and Maillard reaction products).8,9 Honey can be used as a topical antibacterial agent for surface-wound infections. The antimicrobial activities of honey have been attributed to its high osmolarity (resulting from its high sugar concentration) and low pH and the presence of hydrogen peroxide, bee defensin-1, and methylglyoxal.10 The strong antibacterial activities of Leptospermum honeys, which include New Zealand manuka honey (Leptospermum scoparium) and Australian jelly bush honey (Leptospermum polygalifolium), are attributed to their high concentrations of methylglyoxal.11 Bee defensin-1 has been identified in the honey used as the source for Revamil, a medical grade honey, and it substantially contributes to its antibacterial properties.12 Along with methylglyoxal and defensin-1, phenolic compounds are considered partially © 2018 American Chemical Society

responsible for honey’s antibacterial activities. A honey’s phenolic composition and the consequent antibacterial and antioxidant properties depend on the botanical origin of the honey.2 Honey can be classified according to the original raw plant as a (i) blossom (floral) or (ii) honeydew honey. Bees make blossom honey from the nectar of flowers of blossoming plants. In contrast, honeydew honey is produced from the secretions of plants (genera Pinus, Abies, Castanea, and Quercus, among others) or the excretions on plants of plant-sucking insects mostly from the family Aphididae.13 The honeydew secreted by insects cannot be considered excrement because the plant sap is not digested in the insect’s stomach.14 The commercial interest in honeydew honeys is increasing because honeydew honeys have higher therapeutic properties than blossom honeys. Higher antibacterial and antioxidant properties have been found in honeydew honeys than in blossom honeys.8,15,16 Furthermore, the food industry appreciates the strong flavor of this kind of honey.17 Therefore, discrimination between honeydew and blossom honeys is of great interest for the avoidance of adulterations and frauds. Honeydew honeys and blossom honeys have different chemical compositions and physicochemical and biochemical properties, as concluded in recently reviewed studies.11,18 Honeydew honeys are darker than most blossom honeys. They are also usually described as having higher values of several physicochemical variables evaluated in the routine quality Received: Revised: Accepted: Published: 2523

December 11, 2017 February 1, 2018 February 20, 2018 February 20, 2018 DOI: 10.1021/acs.jafc.7b05807 J. Agric. Food Chem. 2018, 66, 2523−2537

Review

Journal of Agricultural and Food Chemistry Table 1. Proposed Botanical Chemical Markers of Honeydew Honeys botanical origin

a

chemical marker

analytical technique

geographical origin

ref

oak

quercitol

oaka holm oak pine fir

trans-oak-lactone 2-aminoacetophenone and propylanisol 1-chloro-octane and tridecane protocatechuic acid

GC-FID NMR spectroscopy SDE/GC-MS SDE/GC-MS purge-and-trap/GC-MS HPLC-DAD

Spain Bulgaria and Serbia Spain Spain Greece and Turkey Poland

22 35 17 17 14 42

The authors did not include holm oak.

Table 2. Proposed Botanical Chemical Markers inside Honeydew Honeys botanical origin pine vs oak

pine vs fir

distinguishing characteristic

chemical marker gallic acid

only detected in oak honey

rutin and protocatechuic acid

much higher amounts in oak honey only detected in pine honey only detected in fir honey higher amounts in fir honey

1-nonanol and β-thujone 3,4,5-trimethyl-phenol, 6-methyl-5-hepten-2-one, 2-hydroxy-3,5,5trimethylcyclohex-2-en-one, and geranyl acetone ethyl esters of hexanoic, heptanoic, octanoic, nonanoic, decanoic, dodecanoic, and tetradecanoic acids; nonanal; nonane; 1-(2-furanyl)-ethanone; and (Z)-5-methyl4-nonene octane

geographical origin

ref

RP-HPLC-UV detection (liquid− liquid extraction)

Turkey

26

HS-SPME/GC-MS

Greece

49


higher amounts in pine honey

Studies on the authentication of honeydew honeys have been approached in two ways: The first way involves the isolation and identification of specific chemical markers that identify the the honey’s botanical or geographical origin. The second way involves the development of analytic methods joined to the chemometric processing of data for the authentication of honeydew-honey origins. In the next sections, these two approaches will be discussed.

control of honeys, such as the electric conductivity (EC), acidity, pH, and ash content. EC is used in quality control to discriminate between the two types of honeys. The European legislation (EU Directive 110/2001)13 states that blossom honeys and blends of these honeys must have EC values ≤ 0.8 mS/cm. This rule does not apply to certain honeys, such as bell heather (Erica), strawberry tree (Arbutus unedo), manuka or jelly bush (Leptospermum), ling heather (Calluna vulgaris), tea tree (Melaleuca sp.), lime (Tilia sp.), or eucalyptus honey. Honeydew and chestnut honeys and combinations of them with blossom honeys (except those cited) must have EC ≥ 0.8 mS/cm. An extremely high EC value, 3.07 mS/cm, was found in Salix sp. honeydew honey.19 Another important physical property that can be used to differentiate blossom honeys from honeydew honeys is optical rotation. Honey exhibits the property of rotating the polarization plane of polarized light. Its specific optical rotation depends to a large extent on the types and relative amounts of carbohydrates present in the honey. Honeydew and adulterated honeys are generally dextrorotatory, whereas blossom honeys are levorotatory.20 Honeydew honeys also have higher oligosaccharide contents, including mainly melezitose and raffinose, and lower contents of monosaccharides than blossom honeys.18 Melezitose (a trisaccharide) is considered a distinguishing feature of honeydew honeys.21 Oligosaccharides from honey show probable prebiotic activities because they increase the populations of bifidobacteria and lactobacilli in the human gut.22 Honeydew honeys have been less studied than blossom honeys. Given the growing interest in honeydew honeys, especially for their superior therapeutic properties, it is interesting to summarize the studies that have been carried out on the characterization and authentication of the botanical and geographical origins of these kinds of honeys. To our knowledge, no review articles exist about this subject.

2. CHARACTERIZATION OF HONEYDEW HONEYS BY BOTANICAL AND GEOGRAPHICAL ORIGINS: CHEMICAL MARKERS Honeydew honeys of several botanical and geographical origins have been characterized on the basis of their physicochemical parameters and chemical compositions. In the last few years, there has been great interest in characterizing honeydew honeys using specific markers to authenticate their origins. Marker compounds have been identified among the phenolic and volatile constituents of these honeys. Finding reliable chemical markers of botanical origins is rather difficult because a honey’s chemical composition depends not only on the species of plant that produces honeydew or nectar but also on other factors such as the geographical area, bee species, collection season, weather conditions, time of honey ripening, nature of the bee pastures, storage mode, and harvest conditions and technology, among others.8,23,24 Moreover, honey of the same botanical origin may provide different chemical-composition results depending on the analytical techniques and sample preparation procedures employed. The following subsections are dedicated to different categories of compounds: carbohydrates, volatile constituents, and phenolic compounds. Compounds suggested as botanical chemical markers of several honeydew honeys are listed in Table 1. Several compounds have been proposed to 2524

DOI: 10.1021/acs.jafc.7b05807 J. Agric. Food Chem. 2018, 66, 2523−2537

Review

Journal of Agricultural and Food Chemistry

Table 3. Proposed Chemical Markers and Analytical Methods with Multivariate Analyses to Authenticate the Geographical Origins of Honeydew Honeys botanical origin 3-carene and an unidentified compound (only detected in Turkish pine honey)

pine

geographical origin Chemical Marker Greece and Turkey

volatile composition

Analytical Methods (Parameter Types) pine Greece and Turkey

free amino acids

bracatinga

physicochemical parameters and volatile composition

pine

Brazil: areas in the state of Santa Catarina Greece: Halkidiki, Evia, Thassos, and Samos


discrimination or classification techniquea

ref

purge-and-trap/ GC-MS



14

purge-and-trap/ GC-MS GC-MS

ANN/KSOM

14

PCA and CA

81

LDA

48

HS-SPME/GCMS

a ANN, artificial neural network; KSOM, Kohonen self-organizing map; PCA, principal-component analysis; CA, cluster analysis; LDA, linear discriminant analysis.

Table 4. Characterization of Honeydew Honeys of Different Botanical and Geographical Origins Based on Their Carbohydrate Compositions no. of samples

main carbohydrates (%, w/w)

Quercus sp.

botanical origin

geographical origin Spain

19

Quercus ilex

Spain

2

Quercus robur L.

Turkey

3

Pinus L.

Turkey

4

Abies sp.

France

57

Abies sp.

Spain

1

Nothofagus sp. Metcalfa

New Zealand Italy

1 

fructose (32.80) glucose (27.22) fructose (38.3) glucose (26.3) maltose (2.3) turanose (2.1) maltulose (1.9) kojibiose (2.0) fructose (43.28) glucose (21.73) trehalose (0.42) melezitose (0.94) maltose (0.19) fructose (39.80) glucose (23.67) trehalose (0.23) melezitose (0.62) maltose (0.54) melibiose (0.35) fructose (33.37) glucose (25.63) erlose (0.82) raffinose (1.56) melezitose (2.22) sucrose (0.45−2.59) fructose (33.1) glucose (24.2) turanose (4.56) maltulose (3.48) isomaltose (3.1) kojibiose (2.95) trehalose (2.15) isomaltose, melezitose, panose, and maltotriose maltotriose and dextrins

discriminate several honeydew honeys from each other. They are shown in Table 2. Compounds suggested as geographical chemical markers of honeydew honeys of the same botanical origin are shown in Table 3. 2.1. Carbohydrates. Honey carbohydrates are the result of the actions of several bee saliva enzymes on the sugars in nectar or honeydew. Honeydew honeys of different countries and botanical origins were characterized on the basis of their


ref

HPLC-RID

29

GC-MS

25

HPLC-RID

26

HPLC-RID

26

HPAEC-PAD

27

GC-MS

25

HPAEC-PAD

28 30, 31

carbohydrate compositions. However, no chemical markers have been found within this category of compounds. Results regarding carbohydrate compositions are shown in Table 4. Cyclitols (carbohydrate-related compounds) were studied to investigate their possible use as markers of Quercus sp. honeydew honeys. Chromatographic techniques are widely used to isolate, identify, and quantify carbohydrates in honeys. Such techniques 2525


Review


Table 5. Characterization of Honeydew Honeys of Different Botanical and Geographical Origins Based on Their Volatile Compositions

botanical origin

geographical origin

no. of samples

analytical technique and extraction method

main volatile compounds phenylacetaldehyde, isophorone, ketoisophorone, epoxylinalool, linalool oxide, αterpineol, eugenol, car-2-en-4-one, hotrienol, p-cymen-8-ol, 2-hydroxycineol, and 3hydroxy-2-butanone dimethyl sulfide, 3-methyl-1-butanol, 3-methyl-3-buten-1-ol, cis-linalool oxide, isophorone, and acetic acid cis- and trans-linalool oxides, hotrienol, epoxylinalool, and aliphatic acids (octanoic, nonanoic, decanoic, and hexadecanoic acids) phenylacetic acid, benzoic acid, 4-hydroxybenzoic acid, 4-hydroxybenzyl alcohol, 4hydroxycinnamic acid, and methyl syringate esters, alcohols, carboxylic acids, aldehydes, ketones, hydrocarbons, etc.

holm oak, oak, and forest (blend of holm oak and oak) Quercus ilex

Spain

9

Spain

2

Quercus f rainetto

Croatia

2

Quercus f rainetto

Croatia

2

Pinus sp.

Greece

39

Abies sp.

Poland

5

4-hydroxy-3,5,6-trimethyl-4-(3-oxobut-1-enyl)cyclohex-2-en-1-one, coniferyl alcohol isomers, borneol, and benzaldehyde

Abies sp.

Spain

1

butanoic acid, methyl butyrate, α-pinene, α-phellandrene, and 1,8-cineole

Salix sp.

Croatia



Salix sp.

Croatia



nonan-1-ol, hotrienol, dimethyl sulfide, benzaldehyde, 2-phenylethyl acetate, 3methylbutanoic acid, isophorone, hexanoic acid, benzyl alcohol, and 2-phenylethanol high amounts of benzoic acid, phenylacetic acid, 2-hydroxybenzoic acid, and 4hydroxyphenylacetic acid with minor percentages of 4-hydroxy-2-phenylethanol, 4methoxybenzoic acid, and 4-hydroxybenzoic acid

ref

microscale SDE/ GC-MS

17

HS-SPME/GCMS HS-SPME/GCMS USE/GC-MS

25

HS-SPME/GCMS HS-SPME/GCMS, USE/GCMS HS-SPME/GCMS HS-SPME/GCMS USE/GC-MS

40 40 48 42 25 19 19

0.94, and 0.19% (w/w), respectively; melibiose was not detected. Sucrose was not detected in either of the honeys studied.26 However, this sugar was detected by GC-MS in Spanish honeys from Quercus ilex (0.79%, w/w) and Abies sp. (0.13%, w/w)25 and by high-performance anion-exchange chromatography (HPAEC-PAD) in 57 samples of French Abies sp. honey (0.45−2.59%, w/w)27 and in New Zealand Nothofagus sp. (beech) honey (n = 1)28. This could be explained by the higher sensitivities of the techniques. The average amounts of fructose, glucose, erlose, raffinose, and melezitose found in Abies sp. honey (n = 57) of French origin were 33.37, 25.63, 0.82, 1.56, and 2.22% (w/w), respectively, with wide concentration ranges for erlose (0.320−1.11%, w/w), raffinose (0.920−2.860%, w/w), and melezitose (0.960−3.120%, w/w).27 In Quercus sp. honey (n = 19) of Spanish origin, the amounts of fructose and glucose found were 32.80 and 27.22% (w/w), respectively.29 Isomaltose was the most abundant disaccharide found in the Nothofagus sp. honey (n = 1) from New Zealand, whereas melezitose, panose, and maltotriose were the significant trisaccharides.28 Metcalfa honey is a type of honeydew honey produced mainly in Italy. It is rich in maltotriose and contains particularly high amounts of dextrins.30,31 As far as we know, very few studies on the carbohydrate compositions of different honeydew-honey types have been carried out. Moreover, they have been only focused on a few botanical origins and countries. In most of these studies, the numbers of samples analyzed are insufficient to characterize honeydew honeys, and additionally, only a few carbohydrates have been identified and quantified. Obviously, a lot of studies are needed to characterize honeydew honeys of different botanical and geographical origins on the basis of their carbohydrate compositions and draw clear conclusions. It would also be interesting to know to what extent the compositions of carbohydrates and the chemical compositions in general of honeydew honeys from a certain botanical origin can be affected by different geographical locations within the

include using high-performance liquid chromatography (HPLC) with several detectors, such as a refractive-index detector (RID), diode-array detector (DAD), pulsed-amperometric detector (PAD), or evaporative light-scattering detector (ELSD). Gas chromatography (GC) coupled with a flameionization detector (GC-FID) or mass spectrometry (GC-MS) is also commonly used. The GC methods require previous derivatization in order to obtain the volatile carbohydrate compounds.11 GC-MS was used to determine the carbohydrate compositions in Spanish honeys from an Abies sp. (fir) and Quercus ilex (holm oak). In the sample of Abies sp. honey analyzed, the amounts of fructose and glucose were 33.1 and 24.2% (w/w), respectively. In the Quercus ilex honey, the amounts of fructose and glucose were 38.3 and 26.3% (w/w), respectively. The main disaccharides found in the Abies sp. samples were turanose, maltulose, isomaltose, kojibiose, and trehalose (4.56, 3.48, 3.1, 2.95, and 2.15%, w/w, respectively). In the Quercus ilex honey, the main disaccharides were maltose, turanose, maltulose, and kojibiose (2.3, 2.1, 1.9, and 2.0%, w/w, respectively). In relation to the trisaccharides, the Quercus ilex honey presented higher amounts of raffinose, kestose, and melezitose (0.1, 0.36, and 0.3%, w/w, respectively) than the Abies sp. honey. Furthermore, raffinose was not detected in the Abies sp. samples.25 Although differences were found in the carbohydrate compositions between the two botanical origins, the results should be taken with caution because of the small number of samples analyzed (holm oak, n = 2; fir, n = 1). HPLC-RID was applied to the determination of carbohydrates in Turkish honeys. In this case, the samples belonged to Quercus robur L. (oak, n = 3) and Pinus L. (pine, n = 4) honeys. The amounts of fructose and glucose found in the pine honey were 39.80 and 23.67% (w/w), respectively; in the oak honey, the amounts were 43.28 and 21.73% (w/w) for fructose and glucose, respectively. In the pine honey, the amounts of trehalose, melezitose, maltose, and melibiose found were 0.23, 0.62, 0.54, and 0.35% (w/w), respectively. In the oak honey, the amounts of trehalose, melezitose, and maltose found were 0.42, 2526


Review


require the use of large quantities of solvents, which are generally toxic and costly with consequent dangers to human health and the environment. On the other hand, it has been reported that the recovery of terpenic and norisoprenoid compounds in rosemary-blossom honey is best when SDE is used compared with those when the other methods, such as liquid−liquid extraction or solid-phase extraction, are used.38 HS-SPME is the most commonly used technique for the extraction of volatile fractions from honeys. When compared with traditional techniques, it shows important advantages; it is a solvent-free simple technique which integrates the sampling, isolation, and enrichment of analytes into one step. However, it requires the optimization of the conditions of its use in terms of the SPME fiber type, temperature, sorption time, and desorption temperature, which is time consuming.39 In some cases, HS-SPME/GC-MS and USE/GC-MS were applied simultaneously with each using different extraction solvents. The two techniques provided different, complementary chromatographic profiles for the samples analyzed, allowing better characterization of honey aromas.19,40−42 Some studies have been carried out to characterize honeydew honeys from different botanical origins and countries, mainly from Spain, Greece, Turkey, and Croatia, on the basis of their volatile-compound compositions. A microscale SDE/GC-MS method was used to study the volatile profile of Spanish holm oak, oak, and forest (a blend of holm oak and oak) honeys.17 The most abundant of the 66 volatile compounds found in the analyzed samples (n = 9) was phenylacetaldehyde. Certain norisoprenoids, such as isophorone and ketoisophorone, were also plentiful in all of the samples. The terpene fractions included two isomers of epoxylinalool, linalool oxide, α-terpineol, eugenol, car-2-en-4one, hotrienol, p-cymen-8-ol, and 2-hydroxycineol. Hydroxyketones (principally 3-hydroxy-2-butanone) were also found in the volatile fraction. Some compounds were suggested as chemical markers: 2-aminoacetophenone, which was not detected in the oak honey, and propylanisol for holm oak honey and trans-β-methyl-γ-octalactone, which was not detected in the holm oak honey, for oak honey. However, 2aminoacetophenone has also been suggested as marker for chestnut honey43 and rhododendron honey,44 leaving in question whether this compound could be a botanical marker for holm oak honey. trans-β-Methyl-γ-octalactone is also known as trans-oak-lactone because it has been found only in oak wood. This compound contributes significantly to the aroma of oak honey and can be found in two isomeric forms that have very low odor thresholds: 1 μg/kg for the cis isomer and 2 μg/ kg for the trans isomer.45 Spanish honeydew honeys from Abies sp. (n = 1) and Quercus ilex (n = 2) were analyzed using HS-SPME/GC-MS.25 Comprehensive information on the volatile compositions of the three analyzed samples were not indicated, only the main volatile compounds found were described. In any case, studies with greater numbers of samples should be carried out in order to characterize these honeydew honeys. In the Abies sp. honey sample, the main compounds found were butanoic acid, methyl butyrate, α-pinene, α-phellandrene, and 1,8-cineole. Dimethyl sulfide, 3-methyl-1-butanol, 3-methyl-3-buten-1-ol, cis-linalool oxide, and isophorone were in the Quercus ilex honey. High amounts of acetic acid were also found; all of these compounds, except dimethyl sulfide, were also identified in oak, holm oak, and forest honeys of Spanish origin. High concentrations of acetic acid seem to be characteristic of honeydew honeys.46,47

same country as well as the other factors mentioned at the beginning of this section. Quercitol (acorn sugar or 1,3,4/2,5-cyclohexane-pentol) is a minor constituent in Quercus acorns, leaves, and bark.32 Quercitol and other cyclitols possess antiradical activities. Quercitol also shows glucosidase-inhibitory activity, blocking the absorption and metabolism of carbohydrates.33 Therefore, it can also contribute to the healthy properties of oak honey.34 Quercitol along with other carbohydrates has been detected by GC-FID and proposed as a specific marker for Quercus sp. honeys. In the 17 samples of honeydew honey analyzed, its content ranged from 0.013 to 1.5% (w/w), and in the 13 blossom honeys analyzed, its content ranged between 0 (in most samples) and 0.010% (w/w).22 Other researchers also analyzed quercitol and other polyalcohols in blossom and honeydew honeys.25 Noticeable amounts of quercitol were found only in the two samples of Quercus ilex honey analyzed (0.23 and 0.49%, w/w), which would be in agreement with the proposal of considering quercitol as a marker for Quercus sp. honeys.22 Quercitol was also identified in oak-honeydew honey by nuclear-magnetic-resonance (NMR) spectroscopy.35 Using this technique, quercitol was identified in the 15 samples of oak honey analyzed, whereas the samples of blossom honeys (n = 6) and other honeydew honeys (from fir and spruce, n = 2) did not contain it. 2.2. Volatile Compounds. Aroma is a very sought-after property in honey. The honey aroma is formed by volatile substances which may come from the honeydew or nectar used by the bees to make the honey. Therefore, the aroma depends significantly on the source plant and maturity of the honey. Additionally, honeybees can produce flavor components, or these components can originate during the thermal processing and storage of the honey.23 Volatile substances in honey belong to a great variety of chemical compounds. Results regarding the characterization of honeydew honeys based on their volatile compositions are summarized in Table 5. The study of botanical chemical markers should be dedicated to find constituents derived from plants, such as benzene derivatives, norisoprenoids, terpenes, and terpene derivatives.17 However, several benzene derivatives cannot be considered as potential biomarkers because they are present at high concentrations in all types of honey. These include benzaldehyde, benzyl alcohol, 2-phenylethanol, and phenylacetaldehyde, among others.36,37 The most used technique to measure volatile compounds in honey is GCMS coupled with different extraction methods: headspace solidphase microextraction (HS-SPME/GC-MS), solid-phase microextraction (SPME/GC-MS), purge and trap (purge-and-trap/ GC-MS), ultrasonic solvent extraction (USE/GC-MS), and simultaneous distillation−extraction (SDE/GC-MS). Different volatile compositions have been reported depending on the extraction procedure employed and, if applicable, the polarity of the solvent used. This fact makes it difficult to characterize honeys according to their origins and identify chemical markers. As an example, methyl salicylate, a compound suggested as chemical marker for Salix sp. honeys, was identified by HS-SPME/GC-MS in headspace volatiles, but it was not detected when USE was used as the extraction method.19 Simultaneous distillation−extraction, ultrasonic extraction, and other traditional extraction techniques, such as supercritical fluid extraction, liquid−liquid extraction, and solid-phase extraction, are laborious and time-consuming. Moreover, they 2527


Review

Journal of Agricultural and Food Chemistry The volatile composition of Croatian Quercus f rainetto honey (n = 2) was studied using HS-SPME/GC-MS and USE/GCMS. More complete and representative information on the volatile composition of this kind of honey was obtained by using both techniques simultaneously.40 HS-SPME/GC-MS allowed the identification of the most-volatile organic headspace compounds and resulted in reliable compositions of the most-volatile organic constituents of the honey samples. Of the 30 organic compounds found in the headspace, the most abundant were terpenes (cis- and trans-linalool oxides, hotrienol, and epoxylinalool), mainly isomers of linalool oxide. These compounds (linalool oxide as the Z isomer) were also found in Spanish oak, holm oak, and forest honeys. Another important group of organic compounds found in the samples were aliphatic acids: octanoic, nonanoic, decanoic, and hexadecanoic acids. The USE methodology elucidated the volatile and less-volatile organic compositions. This extraction procedure does not require heat, and thus, any thermal generation of artifacts is avoided. Two solvents, dichloromethane and a mixture of pentane/diethyl ether (1:2, v/v), were studied separately and led to different analytical results. Phenylacetic acid was the most abundant of the shikimatepathway derivatives. This compound was not found in the samples of Spanish honeys, which might be due to the use of a different extraction method. Other abundant benzene derivatives were also not identified in the Spanish honeys: benzoic acid, 4-hydroxybenzoic acid, 4-hydroxybenzyl alcohol, 4hydroxycinnamic acid, and methyl syringate. Although the Quercus f rainetto was an oak species, trans-oak-lactone, proposed as a chemical marker for oak honey, was not detected in the two analyzed samples. Greek Pinus sp. honey (n = 39) has been characterized according to its volatile composition (HS-SPME/GC-MS) and physicochemical parameters.48 Various compound classes were identified: esters, alcohols, carboxylic acids, aldehydes, ketones, and hydrocarbons, among others. Most of the identified esters may originate from the resinous components of pine trees. Numerous volatile compounds found have been previously identified in Greek and Turkish pine honeys14 as well as in some blossom honeys. It is worth noting the presence of 2,3butanediol in the samples. This compound has been considered by several researchers as characteristic of honeydew honeys.46,47 In contrast,48 other researchers have identified 1-chloro-octane and tridecane in Greek and Turkish pine honeys using purgeand-trap/GC-MS and have proposed those as botanical chemical markers for pine honey.14 Other researchers have suggested several volatile compounds, identified by HS-SPME/GC-MS, as chemical markers to discriminate between Greek Pinus sp. (n = 39) and Abies sp. (n = 31) honeys. On the one hand, several compounds were identified only in one kind of honey: 1-nonanol and (1S,4S,5R)-4-methyl-1-propan-2-ylbicyclo[3.1.0]hexan-3-one (β-thujone) were identified in pine honey, and 6-methyl-5hepten-2-one, 2-hydroxy-3,5,5-trimethylcyclohex-2-en-one, 3,4,5-trimethylphenol, and 6,10-dimethyl-5,9-undecadien-2one (geranyl acetone) were identified in fir honey. On the other hand, higher amounts of certain compounds were found in honey samples of particular botanical origins: ethyl esters of hexanoic, heptanoic, octanoic, nonanoic, decanoic, dodecanoic, and tetradecanoic acids; nonanal; nonane; 1-(2-furanyl)ethanone; and (Z)-5-methyl-4-nonene were found in higher amounts in fir honey, and octane was found in higher amounts in pine honey.49 Other researchers did not identify β-thujone in

pine honeys of Greek or Turkish origins using purge-and-trap/ GC-MS, which might be due to the different extraction technique used.14 Polish fir (Abies alba Mill.) honeydew honey was characterized using three analytical techniques, HPLC-DAD, USE/GC-MS, and HS-SPME/GC-MS, which allowed the identification of a wide range of compounds. The honey’s typical physicochemical parameters were also determined. The chemical profiles were dominated by benzene derivatives originating from the source plants, such as 3,4-dihydroxybenzoic acid (protocatechuic acid), determined by HPLC-DAD; methyl syringate, determined by USE/GC-MS; and benzaldehyde, determined by HS-SPME/GC-MS. Other important compounds identified were terpenes, including norisoprenoids, mainly 4-hydroxy-3,5,6-trimethyl-4-(3-oxobut-1-enyl)cyclohex2-en-1-one (USE/GC-MS), and monoterpenes, mainly linalool derivatives as well as borneol (HS-SPME/GC-MS).42 The results obtained in this study differed a lot from those obtained by other researchers studying fir honeys from Greece49 and Spain. 25 4-Hydroxy-3,5,6-trimethyl-4-(3-oxobut-1-enyl)cyclohex-2-en-1-one, coniferyl alcohol isomers, borneol, and benzaldehyde were proposed for fir-honeydew-honey screening. According to the authors of this study, there was no report on the occurrence of coniferyl alcohol isomers in any honey variety, including honeydew honey. On the other hand, protocatechuic acid was suggested as a potential marker of fir-honeydew honey regardless of the honey’s geographical origin because this compound was also previously found in fir honeys by several other researchers.42 However, protocatechuic acid was also found in Turkish oak and pine honeys.26 SPME/GC-MS has been applied to the analysis of phenolic and other aromatic compounds in different types of European honeys. The honeydew honeys studied included Abies alba Miller honey (France and Italy), Quercus sp. honey (France), Pyrenees honey (France), and forest honey (Italy), the last two being mixtures of honeydew honeys. French Pyrenees honey could be differentiated from the others honeys by the absence of cinnamic acid. Only a small number of samples were analyzed (one or two of each kind). Additional studies with larger numbers of samples are necessary to confirm this finding.50 Cinnamic acid was also identified in Croatian Quercus f rainetto honey by other researchers.40 Salix sp. (willow) honey can be produced from honeydew or nectar, resulting in two completely different honeys. Croatian willow-honeydew honey was analyzed using USE/GC-MS and HS-SPME/GC-MS with two different chromatographic columns.19 Volatile compounds with different functionalities, molecular weights, and polarities were extracted and identified, including benzoic acid and its derivatives, fatty acids, alcohols, hydrocarbons, and others. Among the identified compounds, 33 were only identified in the headspace volatiles. USE was applied using four solvents, pentane, diethyl ether, diethyl ether (after pentane extraction), and a mixture of pentane/diethyl ether (1:2, v/v), in order to obtain more complete volatile profiles. In total, 101 volatile compounds were identified. It has been pointed out that high concentrations of benzoic acid, phenylacetic acid, 2-hydroxybenzoic acid (salicylic acid), and 4-hydroxyphenylacetic acid and minor amounts of 4-hydroxy-2phenylethanol, 4-methoxybenzoic acid, and 4-hydroxybenzoic acid differentiate this botanic origin. All of these compounds probably came from the Salix plant, which is a source of salicylic acid and its derivatives. 2528


Review


intensities in almost all of the spectra of the blossom honeys studied. Markers for blossom honeys of several floral origins were also proposed.55 NMR spectroscopy has also been used by other researchers to detect possible chemical markers for several kinds of Italian honeys, including acacia, linden, orange, eucalyptus, chestnut, and honeydew. The NMR spectra of chloroform extracts of the honey samples (n = 353) were analyzed, and specific markers were identified for each botanical origin. A diacylglycerilether was identified as a specific marker for honeydew honeys, which could be useful in discriminating blossom honeys from honeydew honeys.53,56 The properties and composition of a honey not only depends on its botanical origin but also on other factors, as already indicated in previous paragraphs. Great interest has also been put into the authentication of the geographical origins of honeydew honeys, because the most important characteristics of a honey also depend on the geographical area in which it was produced. Pine honey is very appreciated in Greece and Turkey, and it is produced from honeydew secreted by the insect Marchalina hellenica (Gennadius).57 Differentiation between Greek and Turkish pine honeys based on their physicochemical parameters was not possible because of the broad variation in the variable values within each type of honey. However, the pine honeys of the two countries could be differentiated by two volatile compounds: 3-carene (3,7,7trimethylbicyclo[4.1.0]hept-3-ene) and one unidentified compound (m/z: 55, 79, 91, 107, 123, and 165). These compounds were found in 100% of the Turkish honey samples and were not detected in any sample of Greek honey.14 2.3. Phenolic Compounds. In recent years, there has been increasing interest in the determination of the antioxidant activities of honeys. It has been reported that a honey’s botanical origin has the greatest influence on its antioxidant activity, whereas other factors such as the processing, handling, and storage of the honey affect its activity only to a minor degree. Moreover, antioxidant activities vary widely with the botanical sources.58,59 An official method for honey-antioxidant-activity determination does not exist. Several assays can be used, including assays determining the ferric-reducing antioxidant power (FRAP), 1,1-diphenyl-2-picrylhydrazyl (DPPH)-free-radical-scavenging activity, oxygen-radical-absorbance capacity (ORAC), and Trolox-equivalent antioxidant capacity (TEAC) and assays involving 2,20-azinobis (3ethylbenzothiazolin)-6-sulfonate (ABTS), among others. Using a combination of antioxidant tests and comparing the results has been suggested as it would provide more reliable criteria of honey antioxidant behaviors because several phenolic compounds can react differently depending on the test used.60−63 Another problem is that when different researchers use the same test, different modifications are often included, making it difficult to compare the results of the different studies. Many studies have suggested that phenolic compounds are mostly responsible for the antioxidant activities of honeys because a high correlation between the two parameters has been found. In addition, a high correlation between the color of a honey and its total phenolic content (TPC) and antioxidant activity was found. Therefore, darker honeys such as honeydew honeys and some blossom honeys (chestnut, heather, buckwheat, anzer, and manuka, among others) have higher antioxidant activities because of their higher TPCs.4,8,58,60,64−67 Several researchers have found high correlations among a

The main volatile compounds identified by HS-SPME/GCMS were nonan-1-ol, hotrienol, dimethyl sulfide, benzaldehyde, 2-phenylethyl acetate, 3-methylbutanoic acid, isophorone, hexanoic acid, benzyl alcohol, and 2-phenylethanol. Small amounts of methyl salicylate were detected in the samples, in contrast to the high concentrations of this compound found in the Spanish willow-blossom honeys.25 Other researchers did not find methyl salicylate in Croatian willow-blossom honey, either by HS-SPME/GC-MS or by USE/GC-MS, although it should be noted that its shikimate-pathway precursors (salicylic and benzoic acids) were detected.41 In addition, methyl salicylate was not detected by reverse-phase (RP)-HPLCDAD in Croatian willow honeys made from nectar or honeydew.51 Therefore, there is controversy about the possible use of methyl salicylate as a specific marker for willow honeys because it has not been detected in other honeydew honeys or blossom honeys.19 Further studies performed with more samples are necessary to confirm whether this compound is a specific marker of Salix sp. honeys. Using RP-HPLC-DAD, several compounds were identified that could serve as markers for differentiating willow-blossom honey from willow-honeydew honey. Abscisic acids (ABA), predominantly the isomer (Z,E)-ABA rather than (E,E)-ABA, were not detected in willow-honeydew honey and thus could be considered characteristic of willow-blossom honey. On the other hand, kynurenic acid and salicylic acid could be characteristic of willow-honeydew honey. Salicylic acid was only detected in willow-honeydew honey, and a greater amount of kynurenic acid was found in the samples of willow-honeydew honey than in those of willow-blossom honey.51 Other researchers had detected salicylic acid in willow-nectar and -honeydew honey by USE/GC-MS, but much higher concentrations were found in the samples of honeydew honey19 than in those of the blossom honey.41 Salicylic acid was also found in Quercus frainetto honey using this same technique.40 These findings are in agreement with those previously reported by several researchers who found higher amounts of salicylic acid in honeydew honeys (0.71−7.06 μg/g) than in blossom honeys (0−0.48 μg/g). They suggested the use of salicylic acid as a marker when discriminating between blossom honeys and honeydew honeys.50 NMR spectroscopy is also a valuable technique in the characterization of honeys. It allows research into specific chemical markers in particular kinds of honeys that provide information on the honeys’ geographical and botanical origins. Moreover, NMR spectroscopy is a powerful technique that can be used to obtain structural information on a wide range of chemical species in a single experiment.52,53 The use of this technique does not require complex pretreatments of the honey samples. However, the high spectral complexity requires the use of multivariate techniques to extract the useful information.52,54 Italian commercial honeys of 20 botanical origins, including blossom honeys and honeydew honeys, were analyzed by 1H NMR spectroscopy in order to find botanical chemical markers. Solid-phase extraction was used before the NMR analysis. Three samples of honeydew honeys were studied, two labeled as “metcalfa” and one labeled generically as “wood honeydew”. They gave almost identical NMR profiles containing the typical resonances of aliphatic components, which very likely derived from the honeydew. The authors of the study suggested that these aliphatic resonances were markers of honeydew honeys. In addition, these resonances could be used to detect honeydew in blossom honeys, because they were observed at lower 2529


Review


Anatolian honeys had similar amounts (Quercus robur L.: 94.5− 129.8 mg of GAE per 100 g, Pinus L.: 58.6−74.6 mg of GAE per 100 g).70 Other researchers analyzed the TPCs in Turkish Quercus L. (78−91 mg of GAE per 100 g) and Pinusburia L. (36.7−48.3 mg of GAE per 100 g) honeys, and they found lower values for each type of honey.4 TPC values were evaluated in Spanish honeys of different botanical origins. A TPC of 101 mg of GAE per 100 g was reported in Quercus sp. honey.29 Values between 100 and 154.4 mg of GAE per 100 g were found in Quercus pyrenaica (Pyrenean oak) honey.71 In Portuguese and Spanish Quercus rotundifolia Lam. (holm oak) honeys, a TPC of 81.03 mg of GAE per 100 g was found.72 Several studies showed TPCs of 24.14, 21.75, and 23.39 mg of GAE per 100 g in Slovenian Abies alba Mill. (fir), Picea abies (L.) Karst (spruce), and forest honeys, respectively.58 A moderately high TPC was found in Polish Abies alba Mill. honey.42 Italian forest (insect, Metcalfa pruinosa) and fir (Abies alba Mill. and Picea abies L.) honeys contained TPCs of 80.1 and 59.6 mg of GAE per 100 g, respectively.63 On the other hand, much higher TPCs and antioxidant activities have been reported in willow-honeydew-honey samples (119.79 mg of GAE per 100 g) than in those of willow-blossom honey (50.86 mg of GAE per 100 g). In relation to this, willow-honeydew honey is almost black with a very low lightness indicator (L* = 7.0), whereas willow-blossom is much clearer (L* = 64.3).51 The main sources of the phenolic compounds in honeys are the plants. Therefore, phenolic compounds could be an interesting tool in elucidating the botanical origins of honeydew honeys. Several phenolic compounds have already been suggested as botanical markers of blossom honeys.23 Few studies have been carried out that characterize honeydew honeys of different botanical origins on the basis of their phenolic compositions. Analyses of phenolic compounds in honeys are usually carried out by HPLC. Honey is a complex matrix with a high concentration of sugars and very low concentrations of phenolic compounds. Therefore, analyses of phenolic compounds usually require previous cleanup steps to remove the sugars and other interfering compounds and preconcentrate the analytes. The most used detectors are DADs and UV/vis detectors. Other analytical techniques with higher levels of sensitivity and selectivity have also been used. HPLC-DAD coupled to a mass spectrometer with electrospray-ionization interface (HPLC-DAD-ESI-MS) has been used to identify and quantify flavonoid aglycons and ABA isomers in Slovenian honeydew and blossom honeys. Solid-phase extraction using Strata-X SPE cartridges was used.73 UHPLC-ESI-MS/MS was applied to the analysis of phenolic compounds in blossom and honeydew honeys using the same solid-phase extraction procedure.65 Several researchers identified and quantified phenolic compounds in blossom and honeydew honeys by HPLC-ESI-MS/MS without previous cleaning or preconcentration procedures.74 SPME/GC-MS has also been applied to the determination of phenolic and other aromatic compounds in honeydew and blossom honeys.50 HPLC-ESI-MS/MS has also been used for the determination of 30 phenolic compounds and other honey constituents in Brazilian Mimosa scabrella Bentham (bracatinga) honeydew honeys (Table 7).75 Benzoic acid (1.2−11.05 μg/g), 3,4dihydroxybenzoic acid (1.28−1.78 μg/g), and salicylic acid (0.82−2.02 μg/g) were found to be the most abundant phenolic compounds in the nine samples analyzed. According

honey’s antioxidant capacity and TPC and other parameters such as its pH, EC, acidity, and net absorbance.68 In some studies, a correlation between TPC and antioxidant activity was not found. The Folin−Ciocalteu spectrophotometric method is usually used to determine TPCs in honeys, and it is based on the chemical reduction of the Folin− Ciocalteu reagent, which can also be easily reduced by other compounds in honeys. Therefore, this assay should be seen as a measure of total antioxidant capacity rather than TPC; many nonphenolic substances show significant reactivity to the Folin−Ciocalteu reagent, such as many vitamins, amino acids, reducing sugars, and even some inorganic ions such as Fe(II) and Mn(II).69 This could be the reason why the TPC of Anatolian heather honey was higher than those of oak and chestnut honeys, although the antioxidant capacities of the latter were higher than that of the heather honey. The heather honey samples were distinguished from the other honeys by high Fe amounts, and Fe shows considerable reactivity toward the Folin−Ciocalteu reagent. Similarly, the high Mn contents of oak honeys are probably responsible for their TPCs in addition to phenolic substances.70 Interferences from hydroxymethylfurfural were also noted in the determination of total flavonones with the reagent 2,4-dinitrophenylhiydrazine.65 The TPCs of honeydew honeys belonging to several botanical and geographical origins have been reported. The data are shown in Table 6. Turkish Quercus robur L. honey had a higher TPC and antioxidant capacity than those of Pinus brutia L. honey, and it is also darker. The TPCs found in samples of oak and pine honeys were 120.04 and 61.42 mg of gallic acid equivalent (GAE) per 100 g of honey, respectively.26 Table 6. Total Phenolic Contents (TPCs) in Honeydew Honeys of Different Botanical and Geographical Origins

botanical origin Quercus robur L. Quercus robur L. Quercus L. Quercus sp. Quercus pyrenaica Quercus ilex subsp. ballota (Quercus rotundifolia Lam.) Pinus brutia L. Pinus L. Pinusburia L. Abies alba Mill. Abies alba Mill. Abies alba Mill. and Picea abies L. Picea abies (L.) Karst forest forest Salix sp.

geographical origin Quercus spp. (Oak) Turkey Turkey (Anatolia) Turkey Spain Spain Spain and Portugal Pinus spp. (Pine) Turkey Anatolia (Turkey) Turkey Abies spp. (Fir) Slovenia Poland Italy Picea sp. (Spruce) Slovenia Forest Italy Slovenia Salix sp. (Willow) Croatia

TPC (milligrams of GAE per 100 g of honey)

ref

120.04 94.5−129.8

26 70

78−91 101 100−154.4 81.03

4 29 71 72

61.42 58.6−74.6

26 70

36.7−48.3

4

24.14 53.32 59.6

58 42 63

21.75

58

80.1 23.39

63 58

119.79

51 2530


Review


Table 7. Characterization of Honeydew Honeys of Different Botanical and Geographical Origins Based on Their Phenolic Compositions botanical origin

geographical origin

no. of samples

main phenolic compounds


ref

HPLC-ESI-MS/MS

75

3

luteolin, hesperidin, isorhamnetin, pinobanksin, coniferaldehyde, and p-aminobenzoic acid rutin, protocatechuic acid, p-OH benzoic acid, and gallic acid

26

4

protocatechuic acid, p-OH benzoic acid, catechin, and vanillic acid

RP-HPLC-UV/vis detector RP-HPLC-UV/vis detector

Mimosa scabrella Bentham (bracatinga) Quercus robur L.

Brazil

9

Turkey

Pinus L.

Turkey

26

Table 8. Analytical Methods with Multivariate Analyses for the Authentication of the Botanical Origins of Honeydew Honeys parameter type

botanical origin

physicochemical parameters physicochemical parameters microscopic characteristics flavonoids and abscisic acid isomers physicochemical parameters mineral content physicochemical parameters mineral contents physicochemical parameters amino acids physicochemical parameters volatile compositions spectral fingerprinting spectral fingerprinting spectral fingerprinting spectral fingerprinting spectral fingerprinting

and and and and

geographical origin

discrimination or classification techniquea


ref

pine and unifloral holm oak, unifloral, and polyfloral pine and fir

Turkey Spain and Portugal

 

LDA ANN

77 72

Greece

CA and MDS analysis

82

fir, spruce, forest, unifloral, and polyfloral pine, acacia, and polyfloral oak and unifloral

Slovenia

melissopalynological analysis HPLC-DAD/ESI-MS

LDA

73

India

mineral content: FAAS

PCA

79

Spain

LDA and QDA

78

holm oak, Pyrenean oak, and unifloral pine, fir, and unifloral

Spain

mineral content: AES and ICP-OES RP-HPLC-FD

LDA

80

Greece

HS-SPME/GC-MS

LDA

49

pine, fir, and unifloral fir, unifloral, and polyfloral fir, metcalfa, oak, unifloral, and polyfloral pine, cedar, unifloral, and polyfloral fir, metcalfa, oak, unifloral, and polyfloral

Greece Switzerland (fir)

HS/SPME/GC-MS FT-NIR spectroscopy

OPLS-HCA LDA

88 86

Spain (oak), Switzerland (fir), Germany (fir), and Italy (metcalfa) Anatolia

FTIR-ATR spectroscopy FTIR-ATR spectroscopy front-face fluorescence spectroscopy

LDA

84

HCA

85

LDA

87

Spain (oak), Switzerland (fir), Germany (fir), and Italy (metcalfa)

a

LDA, linear discriminant analysis; ANN, artificial neural network; CA, cluster analysis; MDS, multidimensional scaling; PCA, principal-component analysis; QDA, quadratic discriminant analysis; OPLS-HCA, orthogonal-partial-least-squares hierarchical-clustering analysis; HCA, hierarchicalclustering analysis.

other researchers.76 Other compounds, such as protocatechuic acid and rutin can also be considered markers because much higher amounts of them were found in oak honeys (protocatechuic acid: 744.60 μg/g, rutin 538.68 μg/g) than in pine honeys (protocatechuic acid: 81.19 μg/g, rutin: 11.64 μg/g).

to the authors of this study, several phenolic compounds were identified for the first time in honeydew honeys: luteolin (6.54−9.74 μg/100 g), hesperidin (0−18.06 μg/100 g), isorhamnetin (8.73−10.64 μg/100 g), pinobanksin (2.86− 6.64 μg/100 g), and coniferaldehyde (0−9.04 μg/100 g). pAminobenzoic acid was also identified for the first time in honeydew honeys, but it could not be quantified. Except for pinobanksin, which had been identified in Slovenian honeydew and blossom honeys,73 these phenolic compounds could be considered as characteristic of Brazilian bracatinga-honeydew honeys. In a study of several Turkish blossom and honeydew honeys, Quercus robur L. and Pinus brutia L. honeys differed considerably from one another in their phenolic compositions.26 Their phenolic compounds were analyzed by RPHPLC with a UV−vis detector. The major compounds found in the samples of the oak honey (n = 3) were rutin, protocatechuic acid, gallic acid, and p-OH benzoic acid. In the pine honey (n = 4), the main compounds were catechin, protocatechuic acid, p-OH benzoic acid, and vanillic acid. Gallic acid was proposed as a chemical marker to differentiate oak honey from pine honey because it was only detected in the oak honey and in a relatively high amount (82.49 μg/g). Moreover, the absence of gallic acid in pine honey was also reported by

3. ANALYTICAL METHODS AND MULTIVARIATE ANALYSES Another valuable tool in the authentication of the botanical and geographical origins of honeys, especially when no specific markers are detected, is the combination of an analytical methodology with a chemometric approach. In classification techniques, mathematical models are constructed that are capable of predicting whether a given sample belongs to a honey class, category, or type on the basis of the characteristics of the sample. In order to construct the model, it is necessary to have a set of samples, a “training set”, for which the samples’ class is known beforehand as well as the values of the prediction variables. Predictor variables must contain discriminant information; that is, they must be able to distinguish between classes. Once constructed, the model is used to predict the categories of new samples from measurements of their predictor variables. These chemometric techniques are framed 2531


Review


Pyrenean oak (Q. pyrenaica Willd.), sweet chestnut (Castanea sativa), or heather (Calluna vulgaris (L.) Hull and Erica sp.) honeys. The amino acids were derivatized with o-phthaldialdehyde and then analyzed by RP-HPLC with a fluorescence detector (FD). Before the chromatographic analysis, the sugars were removed using ionic-exchange resins. By selecting 10 variables (b*, phenylalanine contents, valine contents, and seven amino acids ratios), 85% of the cross-validated honeys were appropriately categorized. Within the same study, a classification model was developed that allowed the discrimination of holm oak from Pyrenean oak honeys. By selecting four variables (a*, phenylalanine contents, and glutamine/ arginine and arginine/lysine ratios), 95% of the cross-validated honeys were appropriately categorized.80 Ten flavonoid aglycons and two ABA isomers were identified in Slovenian honeys. The samples (five or six from each class) were of Abies alba Mill. (fir), Picea abies (L.) Karst (spruce), and forest honeys; three varieties of unifloral honeys; and a polyfloral honey. Authentication of the botanical origins using specific markers was not possible because the profiles of the compounds were similar for all of the botanic sources. In addition, a wide range of concentrations of these compounds was observed in each type of honey, and no characteristic concentration ranges could be set. In future studies, it will be necessary to increase the number of phenolic compounds analyzed, such as including flavonoid glycosides and phenolic acids, and analyze a larger number of samples to find such markers, if it is possible. Chemometric analysis proved to be more effective at finding the most significant compounds for botanical authentication: pinobanksin, galangin, and two ABA isomers. LDA was applied on the amounts of these compounds found. The overall correct classification rate was 85% (60− 100%), showing that further studies were required to improve these results.73 Other researchers analyzed phenolic and other aromatic compounds in European honeys and successfully differentiated between honeydew and blossom honeys using PCA.50 LDA was applied on physicochemical variables and volatilecompound contents in order to classify Greek honey samples into four botanical origins: pine, fir, thyme, and orange honeys. Selecting 30 volatile compounds as the variables, the overall correct classification rate (84.0%) was the worst. Selecting 10 physicochemical parameters or 40 variables increased the overall correct classification rates to 97.5% and 95.8%, respectively.49 There are fewer studies on discrimination or classification methods of honeydew honeys according to their geographical origins. The composition of a honey is more influenced by its botanical origin than its geographical area, so it is expected that there is a greater difficulty in differentiating honeys from a given botanical source according to their geographical origins. A study of pine honeys (n = 39) from four regions in Greece was carried out to authenticate the geographical areas in which honeys were produced. LDA was applied on the physicochemical-parameter values and volatile compositions. The origins of the honeys could be determined more accurately (crossvalidated) by using selected volatile compounds (correct classification of 84.6%) than by using physicochemicalparameter values (correct classification of 79.5%) or a combination of both (correct classification of 74.4%).48 An artificial neural network employing the Kohonen selforganizing map algorithm (ANN/KSOM) was successfully applied on volatile-composition data to authenticate the Greek

within what is known as supervised analysis, in which the class to which each sample belongs is known when the model is built. Various types of classifying techniques are used, such as linear and quadratic discriminant analyses (LDA and QDA), artificial neural networks (ANNs), soft independent modeling of class analogies (SIMCA), and k-nearest neighbors (KNN), among others. Conversely, an unsupervised analysis, such as a cluster analysis (CA) or a principal-component analysis (PCA), helps researchers know if the samples form groups or classes. In this case, the existence of categories is not known or deliberately ignored. The use of analytical methods with data multivariate analyses has the drawback that a large amount of reference samples is required to build a robust database or model to discriminate or classify the samples. In this review, only those chemometric and analytical methods that involve honeydew honeys have been included, and they are briefly described in Table 3 (studies pertaining to geographical origins) and Table 8 (studies pertaining to botanical origins). They were classified into three types according to the kind of parameter used: (i) analytical methods based on physicochemical parameters or chemical compositions, (ii) analytical methods based on microscopic parameters, and (iii) analytical methods based on spectral information. In all of the cases, the analytical results were chemometrically processed, which allowed the discrimination or classification of the honey samples according to their botanical or geographical origins. As can be observed in Tables 3 and 8, the most used classification technique is LDA. 3.1. Analytical Methods Based on Physicochemical Parameters and Chemical Compositions. Several analytical methods have been developed which allow the classification of honeys using only physicochemical parameters. For instance, Turkish pine honeys and several types of unifloral honeys could be successfully classified using pH values and LDA; a correct classification rate of 100% was obtained for all of the honey types studied.77 Spanish and Portuguese honeys from 11 unifloral varieties, holm oak, and a polyfloral group could be classified by ANN using EC values and chromatic characteristics (a* and b*). About 95% of the honeys were appropriately categorized.72 Blossom honeys of seven botanical origins and Quercus sp. honeys, all them of Spanish origin, have been classified with metal-content data and physicochemical parameters. By far the most abundant element was K. Other majority elements were Na, Mg, Ca, and Al. Elements present at medium levels were Mn, Fe, Zn, and Cu. Trace elements included Co, Cr, Ni, Cd, and Pb. Significant differences were found among all of the honeys in terms of the mean concentrations of all of the variables, except for that of the apparent sucrose, hydroxymethylfurfural, Fe, and Zn. A procedure using a sequence of seven discriminant analyses (linear and quadratic) was developed because a single step did not produce good results. A correct classification percentage close to 90% was achieved following cross-validation.78 Pine, acacia, and polyfloral honeys from the Kashmir Valley of India could be differentiated by the application of PCA to their physicochemical parameters and mineral contents (Cu, Mn, Fe, Zn, Pb, and Cd). The botanical origins significantly affected all of the variables except the total solids. A correct classification rate of 100% was obtained by LDA.79 Stepwise LDA was applied to chromatic characters and amino acid profiles in order to classify Spanish honey samples as holm oak (Quercus ilex L. subsp. ballota (Desf.) Samp.), 2532


Review


3.3. Analytical Methods Based on Spectral Parameters. Analytical methods based on determinations of physicochemical or microscopic parameters and chemical compositions involve a large amount of sample preparation and are time-consuming. Analytical methods using spectral information have also been developed, and they seem to be more suitable for routine quality control regarding the botanical and geographical authentication of honeys. These methods use the information contained in the spectra of the samples, which are related to the qualitative and quantitative compositions of the honeys. However, they do not require the quantification of the analytes, thus avoiding any time-consuming preparation of calibration curves. Analytical methods based on IR or fluorescence spectroscopy have been developed for the botanical authentication of blossom and honeydew honeys. They are fast, nondestructive, and easy-to-use; they only require the sample’s spectrum, which provides a great deal of information. Moreover, they do not require extensive sample preparation, the use of expensive reagents, or highly expensive equipment. Fourier-transform infrared spectroscopy with attenuated total reflectance (FTIR-ATR) in combination with LDA was used for the botanical identification of samples from several different origins. The honeydew honeys included fir (Abies sp. and Picea sp.), metcalfa (Metcalfa pruinosa), and oak (Quercus sp.) honeys. Eight varieties of blossom honeys and a group of polyfloral honeys were also included in the study. The first model developed often classified polyfloral honeys into the groups with single botanical sources. The problem related to the polyfloral honeys was successfully handled using two successive mathematical models. The obtained error probabilities were ≤3%, except for that of the alpine rose honey (8.3%). Therefore, the monovarietal honeys could be distinguished from each other and from the polyfloral honeys using FTIR-ATR with a multivariate analysis. The authentication of the botanical origins was in good agreement with determinations using classical criteria from chemical, pollen, and sensory analyses. Models were also developed to authenticate the geographical origins of the honeys. Promising results have been obtained but additional studies are required.84 FTIR-ATR spectroscopy with hierarchical-clustering analysis (HCA) provided good botanical discrimination between Anatolian honeys, including pine honey, cedar honey, several unifloral honeys, and a group of polyfloral honeys. Better discrimination was achieved over the spectral region between 1800 and 750 cm−1.85 Fourier-transform near-infrared spectroscopy (FT-NIR) in transflection mode coupled with LDA was used to classify honey samples belonging to several botanical origins, including fir (Picea sp. and Abies sp.) honeys, six varieties of unifloral honeys, and a polyfloral honey cluster. The developed model only allowed the classification of the samples into four types: acacia, fir, chestnut, and a pooled group formed by the other honey types. A two-step procedure similar to that in ref 84 was applied, which led to error probabilities less than 6.3%.86 Front-face fluorescence spectroscopy in combination with LDA was also successfully applied in the authentication of honeys from the same botanical origins as those classified in ref 84, and the chemometric-data processing was also similar. The most discriminating fluorescent spectra of honeys from a single botanical source were (A) excitation spectra at 220−400 nm with the emissions measured at 420 nm, (B) fluorescence spectra at 290−500 nm with excitations at 270 nm, and (C)

or Turkish origins of pine honeys. The same discriminant effect and the same map were obtained if only the 15 compounds found in 100% of samples or the most discriminant of these were used.14 An analytical method based on the determination of free amino acids allowed the geographical discrimination of Mimosa scabrella Bentham (bracatinga) honeys from five different areas in the state of Santa Catarina in Brazil. Free amino acids were determined by GC-MS after a derivatization step with an alkyl chloroformate reagent in the organic phase. The techniques PCA and CA were used for the chemometric treatment of the analytical results. According to the authors of this work, the free amino acid concentrations in the bracatinga honeys were higher than those reported for blossom honeys and other honeydew honeys.81 3.2. Analytical Methods Based on Microscopic Parameters. Studies have shown that the species compositions of fungal elements in honeys are significantly affected by the botanical and geographical origins of the honeys. Therefore, the identification and quantification of fungal-species compositions might serve to characterize particular kinds of honeys and identify specific microscopic indicators. Microscopic examination allowed the differentiation between Abies cephalonica (fir) and Pinus sp. (pine) honeys of Greek origin.82 Fir honey (n = 13) had a smaller honeydew-element (HDE; microalgae, fungal mycelia, and spores, among others)to-pollen-grain (P) ratio (HDE/P) and a lower abundance of honeydew elements than pine honey (n = 60). However, they did not differ in their pollen-grain values. A ratio of HDE/P > 3 is generally required to establish a honey sample as honeydew honey.18 In most of the honey samples studied, a ratio

Honeydew honeys: a review on characterization and authentication of

Recommend Documents