Heliyon 7 (2021) e06651
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Heliyon
journal homepage: www.cell.com/heliyon
Research article
The sources and quality of Iranian honey
Elmira Khansaritoreh a, Yasaman Salmaki b, Tayebeh Akbari Azirani c, Farnood Henareh d,
Kamaleddin Alizadeh a, e, *, Elias Ramezani d, Shahin Zarre b, Gudrun Beckh e, Hermann Behling a
a
University of Goettingen, Department of Palynology and Climate Dynamics, Untere Karspüle 2, 37073, Goettingen, Germany
Department of Plant Science, Center of Excellence in Phylogeny of Living Organisms, School of Biology, College of Science, University of Tehran, P.O. Box 14155-6455,
Tehran, Iran
c
Department of Physical Geography, School of Earth Sciences, Shahid Beheshti University (S.B.U), Tehran, Iran
d
Department of Forestry, Faculty of Natural Resources, Urmia University, Urmia, Iran
e
Quality Service International GmbH, Flughafendamm 9, 28199, Bremen, Germany
b
A R T I C L E I N F O
A B S T R A C T
Keywords:
Honey
Adulteration
NMR
Melissopalynology
Sensory
Physicochemical analyses
Iran is one of the largest honey-producing countries worldwide and is considered as an important source of honey
for international markets. However, since Iran is not registered for honey export to Europe, the quality of Iranian
honey remains unknown to European traders. As the first step in filling this gap, we analyzed 225 honey samples
using palynology, sensory, nuclear magnetic resonance (NMR) and conventional physicochemical analyses as
outlined by the European Union coordinated control plan. The results show that while various types of genuine
unifloral honey can be harvested in Iran, 85% of collected samples were adulterated. Performing principal
component analysis on physicochemical parameters reveals that feeding tablet sugar and syrup of C4 origin to
bees during the foraging season is a common mode of fraud. Replacement of natural nectar with sugar syrup
together with presence of intensive aftertaste from Taraxacum and Eryngium affect the taste of unifloral honeys
produced in Iran.
1. Introduction
According to statistics from the Food and Agriculture Organization of
the United Nations (FAOSTAT), Iran is ranked 9th worldwide in average
annual production of honey between 1993 and 2018 (FAOSTAT, 2018).
This fact implies that Iran can be a considerable supplier of honey for the
international market. However, among the 10 largest honey-producing
countries in the FAOSTAT report, Iran is the only one that cannot
export honey to Europe. The reason is the lack of a monitoring program
that ensures the rules and principles applied by Iranian certifying agents
to provide guarantees equivalent to those laid down in Directives
96/93/EC and 2001/110/EC (Council of the European Union, 1996;
2001). Therefore, to the best of our knowledge, the widespread monitoring of Iranian honey has never been performed through random
sampling and analysis by a European certified food quality control laboratory. Consequently, the source and quality of Iranian honey is unknown to the European market.
In former studies on the characterization of honey from different
regions of Iran, sensory and detailed palynological analyses, as the core
tools to identify botanical origin of honey, were not addressed
sufficiently (Moloudian et al., 2018; Parviz et al., 2015; Zahedi Namini
et al., 2018) or the methodology was poorly explained (Moloudian et al.,
2018). However, before the botanical origin of honey samples is determined according to international conventions, any comparison of their
physicochemical properties can be misleading. Another common issue in
these studies is focusing on honey types that are not well defined. For
instance, the concept of milkvetch or Gavan (common names for Astragalus spp.) honey exists only in Iran and China. However, in European
melissopalynology laboratories the pollen of Astragalus is excluded from
counting if the aim is verification of a unifloral honey. The reason, is the
absence of any trace of Astragalus nectar in the taste of honey even if the
sample contains a high percentage of Astragalus pollen. It is shown that
Astragalus spp. is not a highly prolific source of nectar (Knuth et al.,
1906). In addition, if the Astragalus honey exists, the standards for its
organoleptic and palynological characteristics must be set up first so that
its botanical origin can be approved prior to description of physicochemical properties. Another example of unusual honey types reported in
the literature is pear honeydew (Moloudian et al., 2018). Honeydew is a
liquid secreted by aphids and collected and processed by bees. The result
is a dark honey with an electrical conductivity greater than 0.8 mS/cm
* Corresponding author.
E-mail address: kamal.alizadeh@gmail.com (K. Alizadeh).
https://doi.org/10.1016/j.heliyon.2021.e06651
Received 14 November 2020; Received in revised form 24 January 2021; Accepted 26 March 2021
2405-8440/© 2021 Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
E. Khansaritoreh et al.
Heliyon 7 (2021) e06651
Goettingen were used for identification. The slides also were checked for
the amount of starch, spores and yeast. The number of starch particles is
reported as <10%, 10%–30% and >30% of counted pollen that are
scored as low, medium and high levels, respectively. Spores were counted in the same way as starch and yeast with a hemocytometer only if it
was very abundant in the background.
Although some of blossom honey types such as Castanea, Calluna, Arbutus, Erica, and Tilia can also have electrical conductivity near or higher
than 0.8 mS/cm (Oddo and Piro, 2004)., honey from pear and other fruit
trees of Rosaceae has light color and electrical conductivity of less than
0.4 mS/cm (D.I.B., 2014). Therefore, due to the lack of compliance with
international conventions, the questions about the quality of Iranian
honey cannot be answered based on the former studies.
This study aims at utilizing the standard and state of the art methods
used by commercial food control labs to introduce the source and quality
of honey from one of the world's largest honey producers. In a collaborative project between the University of Goettingen, Bayer Bee Care
center and Quality Service International (QSI GmbH), we tested Iranian
honey samples using palynology, sensory, and physicochemical analyses
as outlined by the European Union coordinated control plan (Council of
the European Union, 2015).
2.3. Organoleptic (sensory) analysis
The taste and smell of the samples were described according to the
IHC odor and aroma wheel (Piana et al., 2004) by the sensory team of QSI
composed of 3 men and 4 women led by 3 sensory experts. The team
leaders have between 10 and 25 years of experience in daily analysis of
honey from different botanical and geographical origins. Informed consent was obtained from all participants in sensory experiments. The
sensory room and questionnaire were in accordance with the method
described by sensory group of international honey commission (Marcazzan et al., 2018). The questionnaire is provided as Table 1. The color
of samples at the viscose state was compared with the Pfund color chart
(USDA, 1985). The consistency of samples was recorded 3, 6 and 12
months after sampling to explore the rate of crystallization. Fluid,
viscose, partly crystallized and crystallized are the four categories of
consistency used in the QSI honey laboratory (Standard For Honey Codex
Stan 12-1981, 2001). If the sensory (in particular taste and smell)
matches any of the unifloral honey types, the sensory of the sample was
judged as source specific.
2. Materials and methods
2.1. Sampling
For the present study, the Iranian provinces West Azerbaijan, East
Azerbaijan and Ardabil were chosen because they are respectively ranked
as the 1st to the 3rd for honey production in Iran (Agricultural Bank of
Iran, 2011). Isfahan province, ranked nationally as the 6th, was also
included because the honey from Khansar region has a good reputation
nationwide. These four provinces account for approximately 58% of
honey production in Iran, and their flora is representative of
Irano-Turanian and Euxine-Hyrcanian floristic regions and the Zagros
zone as the main floristic regions of Iran (Sagheb-Talebi et al., 2014).
Moreover, during the sampling, we realized that many beekeepers spent
spring and early summer in southern (Saharo-Sindian phytochorion) and
northern (Hyrcanian phytochorion) areas of Iran. Therefore, the samples
examined in this study could represent the main floral sources of honey
from different regions of Iran. The beekeepers we met during the fieldworks believe that the main floral source of their honeys are Astragalus
spp. and Eryngium spp.
In total, 225 honey samples were collected during two fieldworks in
2015 (29 samples) and 2017 (196 samples). The number of collected
samples for each province ranges from 53 to 61. In both fieldworks,
plants with flowers (bud and blossom) were sampled for the reference
slide preparation. All honey samples were examined by palynology and
sensory. However, since the samples taken from neighboring apiaries
showed closely similar pollen spectra and thus had more likely similar
physicochemical properties, 85 samples were excluded from physicochemical analyses.
2.4. Physicochemical analyses
Besides assisting the palynology and sensory to approve the botanical
origin of honey, physicochemical analyses were performed to detect
adulteration. In the framework of the NMR project, QSI together with
Bruker are developing a database for chemical profiles of honey samples
collected worldwide to combat fraud in the honey business. To create the
NMR database, conventional physicochemical parameters, including
electrical conductivity, moisture content, hydroxymethylfurfural (HMF),
diastase activity, sugars, pH and acidity, were also measured as described
below. All measurements were carried out in duplicate and all methods
were validated by Deutsche Akkreditierungsstelle GmbH.
2.4.1. Electrical conductivity
Electrical conductivity is routinely used together with palynology and
sensory as a reliable method to determine the botanical origin of the
honey. In general, blossom honey and honeydew have electrical conductivity of <0.5 and >0.8 mS/cm, respectively. There are some exceptions among blossom honey types which have electrical conductivity
near or higher than 0.8 mS/cm (Oddo and Piro, 2004) for example
Castanea, Calluna, Arbutus, Erica, and Tilia Between these two ranges, the
honey is classified as blossom-honeydew. In addition, each unifloral
honey type has a specific standard range of electrical conductivity (Beckh
and Camps, 2009).
Electrical conductivity was measured as described by the harmonized
methods of the European honey commission (Bogdanov et al., 1997) in
10 g of honey dissolved in 75 ml of demineralized water using the EC
Electrode model LF413T3MIDS installed on the Schott instrument
Titroline 7800 from SI analytics operating via software Titrisoft 3.1.5. .
2.2. Melissopalynology
Slide preparation was performed according to the method suggested
by the International Honey Commission (IHC); 10 g of honey were mixed
with 20 ml of water in a 50-ml conical tube. Then the solution was
centrifuged for 10 min at 1000 g, the supernatant was decanted and a
second wash and centrifugation for 5 min at 1000 g was carried out (Von
Der Ohe et al., 2004). The concentrate was mixed with one droplet of
glycerol-gelatin and mounted on a glass slide. After covering with a cover
slip, the slides were left for 10 min to let the gelatin harden. To retain
important particles, such as yeast and starch, on the background of slides,
we avoided acetolysis.
To make reference slides, using the parental plants, which were
taxonomically identified at the Tehran and Urmia Universities, the stamen anthers were dissected, washed with water and sieved to remove the
large particles. After centrifuging for 5 min at 1000 g, the sediment was
mounted on the slide as described above.
In each slide, at least 300 pollen grains were counted and identified
under light microscopy with 400x magnification. The reference slides
made in this study, the reference collections at QSI and the University of
2.4.2. Moisture content
The water content is an important factor to determine the shelf life of
the honey. The higher the moisture, the faster the fermentation due to the
yeast activity (Bogdanov et al., 1997). According to honey directive
2001/110/EC (Council of the European Union, 2001), the moisture
content should not exceed 20 g/100 g.
As suggested by the harmonized methods of the European honey
commission (Bogdanov et al., 1997), approximately 5 g of honey was
melted at 60 C, and any foam and large impurities were removed prior
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Standardization (DIN - Deutsches Institut für Normung, 2010). The
measurement was performed on a Thermo Fisher ARENA auto-analyzer
using 5 g of honey dissolved in demineralized water and reagents HMF
R1 Amin (containing aminoacetophenone and glycerol 85%) and HMF
R2 Barbi (containing barbituric acid).
Table 1. The sensory questionnaire used in the study as described by Marcazzan
et al. (2018).
Sample code
Assessor
Date
Intensity of sensory descriptors:
Odour/Aroma (Global olfactory intensity)
2.4.4. pH and acidity
In general, honey is acidic with a pH ranging between 3.5 and 4.5
(Beckh and Camps, 2009). The duration of storage, adulteration with
sugar (Yadata, 2014) and botanical origin (Sousa et al., 2016) can affect
these values. The free acidity of honey may not be greater than 50 milliequivalents of acid per 1000 g (Council of the European Union, 2001).
Acidity and pH were measured as suggested by the harmonized
methods of the European honey commission (Bogdanov et al., 1997). In a
specimen cup, 10 g of honey was dissolved in 75 ml of demineralized
water, and pH and acidity were then measured using the pH-Electrode
model ScienceLine A 162 2 M-DIN-ID installed on the Schott instrument Titroline 7800 from SI analytics operating via the software Titrisoft
3.1.5.
Floral
Soft
Heady
Fruity
Fresh fruit
Tropical fruit
Sugary
Processed food
Like wine (winish)
Warm
Slight
Lactic
Caramelized
Toasty
2.4.5. Diastase activity
Diastase activity reflects the freshness of the honey and can also be
used as an indicator for adulteration (Pasias et al., 2017). Diastase activity, which is measured after processing and/or blending, in general
should not be less than 8 Schade units and in the case of honeys with low
natural enzyme content not less than 3 Schade units (Council of the
European Union, 2001).
The method used here was adopted based on the harmonized
methods of the European Honey Commission (Bogdanov et al., 1997) and
DIN method number 10750. First, 1 g of honey was dissolved in 4.5 ml of
acetate buffer, and then the diastase was measured on a Thermo Fisher
ARENA auto analyzer by applying the following reagents: i) reagent 1
corresponding to the DIN starch solution, ii) reagent 2 corresponding to
the DIN dilute iodine solution, and iii) buffer containing sodium acetate
and common salt dissolved in demineralized water.
Malty (Molasses)
Burned
Aromatic
Spicy
Resinous
Woody
Camphorated (Mentholated)
Esperidato (Citrus fruit)
Bitter almond
Chemical
Phenolic
Soap
Smocked
Vinegar (Pungent)
Ammoniacal
2.4.6. Sugars
A large variety of sugars are measured by means of both NMR and
HPLC (as a control for NMR). In the present study, however, we used only
the values obtained from NMR except for erlose, which is not measured
by NMR. This sugar can act as an indicator for botanical origin, particularly to distinguish between honeydew and blossom honey. The values
of erlose oscillate between 0.1 and 0.9 g/100 g in blossom honey, while
this range is between 0 and 3.4 g/100 g in honeydew. Detectable
amounts of erlose do not exist in many types of unifloral honey (Horn &
Lüllmann, 2017).
Two standards used for HPLC were 958do internal standard (31.25 g
of xylose þ1 ml of 1% methylene blue B 524 and 100 ml of 25% methanol) and standard measurement solution for the sugar spectrum (Spectrum chemical corp) containing Xylose (100.0), Fructose (40.1), Glucose
(27.4), Saccharose (5.3), Turanose (3.1), Maltose (2.9), Trehalose (1.8),
Isomaltose (2.0), Erlose (4.1), Melizitose (3.9), Maltotriose (2.9). The
numbers in parenthesis shows concentration in g/100g.
For evaluation, a mixture of 1.25 g of honey, 250 μl of internal
standard 958do and 23.8 ml of 25% methanol is passed through a
membrane filter and measured using a refractive index (RI) detector on a
Shimadzu HPLC system at 40 C, with a dilution factor of 1, flow rate of
1.2 ml/min and injection volume of 4.0 μl for 12 min.
Vegetal
Green
Mouldy
Dry
Animal
Sulphuric
Proteic
Perspiration
Cat's urine
Taste Intensity
Sweetness
Sourness
Bitterness
Saltiness
to measurement. The remaining sample was homogenized once again
without severe stirring to avoid air bubble formation in the mixture. After
cooling, the sample was measured on a Schmidt and Haensch automatic
table refractometermodel ATR BR, operating via the software 3.2.
2.4.3. Hydroxymethylfurfural
The value of HMF is used to assess the freshness of the sample, the
amount of heat the honey received and the potential adulteration (Pasias
et al., 2017). The HMF content should not exceed 40 mg/kg after processing and/or blending. However, this value may reach 80 mg/kg if the
honey comes from a tropical origin (Council of the European Union, 2001).
The base of the technique used for hydroxymethylfurfural evaluation
was method number 10751 proposed by the German Institute for
2.4.7. Isotopes
The C4-sugar content of honey is an indicator for adulteration by
cheap sugar from corn and sugar cane. This value can be calculated from
the difference in δ13C between the entire honey and its protein fraction
(White and Winters, 1989).
All steps of measurement, including the preparation of honey and
protein fraction, protein isolation and purification and determination of
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Figure 1. Pie charts demonstrating the relative abundance of most important plant families (a) and genera (b), honey smells and tastes (c) and honey colors (d). N
¼ 225.
All chemicals used in NMR were of analytical grade (>99% purity).
The sample preparation method was adopted from BrukerBiospin (BrukerBiospin, Rheinstetten, Germany). The homogenized honey samples (5
g) were diluted in 17.5 ml of NMR-buffer (15.7 g of KH2PO4, 0.05 g of
NaN3 in 1 L of deionized water) and adjusted to pH 3.1 with 1 M HCl and
1 M NaOH. A volume of 100 μl of standard solution (deuterium oxide
containing 0.1% of 2,2,3,3-d(4)-3-(trimethylsilyl)propionic acid sodium
salt (TSP)) was added to 900 μl of homogenized honey solution. The final
solution was centrifuged at 14000 rpm, and 600 μl was transferred into
an NMR-tube for direct measurement.
All measurements were performed on a Bruker AscendTM 400 MHz
FoodScreener equipped with a 5-mm PA BBI 400SI H-BB-D-05 Z probe
and Bruker SampleXpress (BrukerBiospin, Rheinstetten, Germany) for
automatic sample change. The samples were measured without rotation.
1
H-NMR-spectra were acquired at 300.1 K using the pulse programs
noesygppr1d (1D spectra with water presaturation at 4.8 ppm) and
jresgpprqf (2D J-resolved spectra, displaying chemical shift and spin-spin
coupling information). For 1D spectra, 32 scans and 4 dummy scans of 64
k points were acquired with a spectral width of 20.6 ppm, a receiver gain
of 16 and an acquisition time of 4.0 s. The 2D spectra were performed
using 4 scans and 16 dummy scans of 8 k (F2-axis) and 40 k (F1-axis)
points. The spectral widths were 16.7 ppm (F2) and 0.19 ppm (F1),
receiver gain was 16 and acquisition times were 0.6 s (F2) and 0.3 s (F1).
NOESY spectra were used for quantification, and JRES spectra were used
for verification of compound identification. All spectra were automatically phased, baseline-corrected, and calibrated using TSP as a reference
at 0.0 ppm. The compounds were quantified using the Honey-Profiling
routine (release 1.0, BrukerBiospin, Rheinstetten, Germany) by automatic integration of the peak area calculated with an external standard
(Spraul et al., 2009).
carbon isotopes, were performed based on the AOAC official method
number 988.12 (Association of Official Analytical Chemists (AOAC),
2013). Both honey and protein fractions were measured on Picarro
G2121-i Isotope and Gas Concentration Analyzer (operating via the
software WinPro10 64 Bit Version 1903) together with a Thermo Fisher
Delta V Advantage Isotope Ratio Mass Spectrometer (operating with the
software Isolat 3.0).
2.4.8. NMR
NMR profiles were obtained of compounds belonging to different
functional groups, such as saccharides, organic acids, amino acids,
alkaloid, and alcohols, within honey. The final purpose of the NMR
project is to establish a reference database of these profiles that can be
used to determine the botanical and geographical origin as well as potential adulteration of an unknown sample. Such a database currently
exists in QSI for many botanical origin and adulteration sources from
various countries. The following compounds were detected in Iranian
honey samples using NMR:
- Saccharides (fructose, glucose, sucrose, turanose, maltose, melezitose, maltotriose, gentiobiose, and raffinose);
- Organic acids (citric acid, malic acid, lactic acid, formic acid, fumaric
acid, pyruvic acid, succinic acid, and acetic acid);
- Amino acids and their derivatives (alanine, glutamine, proline,
valine, tyrosine, phenylalanine, pyroglutamic acid)
- Other organic chemicals, such as: shikimic acid; trigonelline; 2,3butanediol; and ethanol.
Table 2. Changes in crystallization of samples in one year. Values are calculated
as the percentage of the total number of samples.
Consistency
month 3
month 6
month 12
Viscose
73%
33%
28%
Partly crystalized
16%
20%
5%
Crystalized
11%
47%
67%
2.5. Statistics
Graphs for descriptive statistics were created in Excel. Principal
component analysis (PCA) was performed in R by applying functions
prcomp from package stats. Raw data were auto-scaled prior to PCA that
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Figure 2. PCA displaying the position of adulterated and authentic samples relative to different parameters. The numbers inside the round brackets on each axis show
the contribution from that axis to total variation in dataset. Hollow, crossed and solid circles show adulterated samples determined by NMR, conventional and both
NMR and conventional methods, respectively. Bottom, left, top and right axes show PC1 score, PC2 score, loadings on PC1, and loadings on PC2.
frequently seen pollen types at the genus level (Figure 1.b). The slash sign
is used between genera names with very similar pollen grains that cannot
be separated under a light microscope.
Among the taxa that are internationally accepted as a source of unifloral honey, pollen of Brassica napus (rapeseed honey), Centaurea cyanus
(cornflower honey), Citrus spp. (orange honey), Helianthus annuus (sunflower honey), Pyrus/Prunus spp. (fruit blossom honey), Taraxacum spp.
(dandelion honey), Tilia spp. (lime honey), Trifolium spp. (clover honey),
and Ziziphus jujuba (jujube honey) were detected. The pollen of Prosopis
was also found in many samples but in Iran this plant grows as a small
shrub that is locally called Jeqjeqeh (which means rattle) and differs from
the tropical Prosopis that is the source of mesquite honey. Samples containing sufficient percentages of pollen from Centaurea cyanus, Citrus,
Helianthus annuus, Taraxacum, Thymus and Tilia to be considered as
unifloral honey are discussed in section 3.4.
The relative abundance of starch grains did not exceed 10% in any
sample. The spores and yeast were too scattered in the background to be
considered for counting.
means variables are shifted to be zero centered and then scaling is conducted by means of standard deviation.
3. Results and discussion
3.1. Melissopalynology
In the current study, palynological results are used to explore the
main botanical origin of Iranian honey and examine whether any sample
can be labeled as unifloral. Therefore, only the plant families, most
frequent genera and plants that can produce unifloral honey are presented here.
In total, pollen types from 101 taxa were identified. From a palynological point of view, the 10 most frequently visited plant families by bees
in landscapes of Iran are Fabaceae, Asteraceae, Apiaceae, Rosaceae,
Brassicaceae, Plantaginaceae, Amaranthaceae, Poaceae, Scrophulariaceae and Papaveraceae (family concept follows APG IV (Chase et al.,
2016)). The relative abundance of these families is shown in Figure 1.a
where “others” includes Lamiaceae, Malvaceae, Rutaceae, Salicaceae,
Thymelaeaceae, Boraginaceae, Polygonaceae, Caryophyllaceae, Cannabaceae, Cyperaceae, Rhamnaceae, Myrtaceae, Solanaceae, Lythraceae,
Rubiaceae, Convolvulaceae, Euphorbiaceae, Acanthaceae, Campanulaceae, Hypericaceae, Juglandaceae, Urticaceae, Caprifoliaceae, Ranunculaceae, Aquifoliaceae, Betulaceae, Oleaceae, Cucurbitaceae,
Elaeagnaceae, Smilacaceae, and Xanthorrhoeaceae, in descending order
of abundance.
The pollen types belonging to the genera Astragalus, Xeranthemum/
Achillea, Eryngium, Prosopis, Pyrus/Prunus, Onobrychis/Alhagi, Centaurea,
Cousinia/Centaurea (C. cyanus type), Plantago and Solanum were the most
3.2. Organoleptic (sensory) analysis
Using the honey wheel, the taste and smell of samples were classified
into families and when possible into subfamilies. The taste and smell of
all samples fell into the same classes. The pie chart in Figure 1.c shows
the relative abundance of these classes. In this paper, a slash symbol is
used to separate different tastes when more than one taste is detected
within a sample (e.g., woody/spoiled), a comma symbol is used if the
name of the taste family has two parts (e.g., floral, fresh fruit) and a dash
symbol is used between family and subfamily names (e.g., woody-spicy).
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Figure 3. Boxplots showing the range of values for sugars in adulterated (grey boxes) and authentic (white boxes) samples.
results with the honey directive (Council of the European Union, 2001)
and the NMR reference database comprising the data from over 20,000
samples collected worldwide. The outcome shows that only 15% of
samples were authentic. The remaining samples were assessed as
adulterated: 57% by both NMR and conventional methods, 18% only by
NMR and 10% exclusively by conventional methods. In many cases,
there were several parameters indicating adulteration of one sample;
thus, it was not possible to quantify the contribution from each
parameter to overall assessment. However, PCA was applied to identify
parameters that play essential roles in authentication. Before performing statistical tests, the notion that the unequal numbers of adulterated
and authentic samples may affect the reliability of the tests must be
considered. The PCA in Figure 2 shows that the adulterated and
authentic samples can be mainly separated through axis PC1. Disaccharides (maltose and sucrose) and C4 sugars are placed to the far
right of PC1 that is dominantly populated by adulterated samples.
Conversely, monosaccharides (glucose and fructose), Amino acids (e.g.
proline, valine, alanine, and glutamine) and diastase activity are located
to the left of PC1, close to authentic samples. Samples that are labeled as
adulterated only based on one method (either NMR or conventional)
appear mainly on transition between adulterated and authentic samples
implying their borderline quality. The boxplots in Figures 3, 4, and 5
show the range of values for different parameters in authentic and
The woody-spicy class, individually or together with the spoiled and
floral, fresh fruit classes, was the most frequently perceived flavor (51%),
followed by floral, fresh fruit (20% alone and 23% together with woodyspicy), spoiled (4% spoiled, 4% spoiled-animal and 13% spoiled/woodyspicy), warm (warm-cooked fruit 10% and warm-burned 2%), vegetaldry (6%), chemical-medicine (2%) and woody-dry (1%). The few samples with organoleptic properties of unifloral honey are discussed in
section 3.4.
The color of samples covers all seven Pfund color categories (USDA,
1985) from water white to dark amber. Figure 1.d illustrates the percentage of samples falling into each category. The number of samples in
white tones is slightly higher than the number of those in amber tones.
All samples, including those collected during the fieldwork and those
collected by the partners, were viscose when they arrived in Germany.
However, after one year, the majority of samples were crystalized.
Table 2 displays the change in consistency of samples in one year.
3.3. Authenticity
Authentication is the key result of physicochemical analyses that
must be addressed prior to other honey properties; otherwise, exploring
the botanical origin of an adulterated honey is pointless. The authenticity of Iranian samples was tested by comparing the physicochemical
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Figure 4. Boxplots showing the range of values for amino acids, organic acids and alkaloids in adulterated (grey boxes) and authentic (white boxes) samples.
During the fieldwork, we frequently saw storage of white sugar close
to apiaries. Beekeepers told us that they receive sugar subsidy from the
government. They solve the white sugar in a bowl of water and locates it
next to beehives.
To check whether higher values of saccharides, especially sucrose and
maltose, are associated with a specific botanical origin, such as Astragalus, the NMR quantile plots were checked. Figure 6 displays plots for
one authentic sample (top) and one adulterated sample (bottom) with
81% and 70% Astragalus spp. pollen, respectively. The peaks inside the
rectangles show maltose and sucrose. The black line that displays values
for the current sample is much higher inside the rectangles for the
adulterated samples. The number written in round brackets next to the
parameter's name shows the loading on PC1.
The positive scores and the higher contents of sucrose and maltose for
adulterated samples compared to authentic samples suggests that the
adulteration might be related to the feeding of tablet sugars to bee colonies even when they have access to natural nectar. The source of tablet
sugar could be partly sugarcane that is also used to produce white sugar
in Iran. That can explain the higher content of C4 sugars in adulterated
samples. Replacing natural nectar with sugar might be the reason for the
lower values of the compounds and parameters of natural honey such as
monosaccharides, amino acids and enzyme in adulterated samples.
7
E. Khansaritoreh et al.
Heliyon 7 (2021) e06651
Figure 5. Boxplots showing the range of values for other parameters in adulterated (grey boxes) and authentic (white boxes) samples.
Among the locally acknowledged floral sources, Astragalus spp. and
Eryngium spp. were found with reasonable pollen percentages. However,
no standard range is available for the properties of these honey types.
For Eryngium spp., the minimum accepted pollen percentage is considered to be 45% in this study only because this is the suggested lower
limit for two other genera in the family Apiaceae: Foeniculum vulgare
(Parvanov et al., 2011) and Coriandrum sativum (Atanassova et al.,
2012) that can produce unifloral honey. In the family Fabaceae, the
acceptable lower limits for pollen percentage differ from 20% for Robinia spp. to 70% for Trifolium spp. and 80% for Lotus spp. (bmbl, 2011).
As the predominance of Astragalus pollen in Iranian samples is more
similar to ranges of Trifolium spp. and Lotus spp. than underrepresented
Robinia spp., samples with greater than 60% Astragalus spp. pollen were
selected for Table 3. The standard range of electrical conductivity for
Astragalus honey is quoted from one study (Moloudian et al., 2018) with
unclear palynology and sensory analyses. These uncertainties prevented
approval of samples with Astragalus and Eryngium origins. Moreover,
potential Astragalus and Eryngium honey types constitute only nine and
one percent of the samples tested in this study, respectively. This finding
is in contrast to the common belief that these two plants are the main
source of honey in Iran.
Since the electrical conductivity of all samples is less than 0.50 mS/
cm, each sample that is neither unifloral nor adulterated can be categorized as polyfloral blossom honey according to the honey directive. The
spicy taste in almost half of the samples is due to the presence of Eryngium. Plants from the Apiaceae family typically have a persistent strong
anise-like flavor (Dinkov & Ivanov, 2009; Parvanov et al., 2011). The
spoiled odor perceived in approximately 20% of samples can be emitted
from Taraxacum, which is found in trace amounts in many samples. The
intensive odor of the nectar of Taraxacum can be easily realized particularly when another fragrant nectar is not present in the honey (Oddo
and Piro, 2004).
Pollen of Tilia spp. is usually underrepresented in honey (Oddo and
Piro, 2004); thus, a sample with 70% of Tilia pollen as reported in this
study must have a strong flavor of lime honey. However, such pure
sample and some of the others listed in Table 3 with accepted pollen
contents (e.g. Citrus, Helianthus, and Thymus) did not have respective
adulterated sample, although it has a lower content of Astragalus pollen.
Therefore, the high values of sugars are not related to floral source.
Since there is a common misconception in Iran that crystallization of
honey is due to adulteration, we calculated the percentage of adulterated
samples for viscose and crystallized (plus partly crystallized) honeys at
their consistency state after one year. This value is higher for crystalized
(90%) compared to viscose (74%) samples; however, this small difference
can be due to the larger number of individuals in the crystalized group
(72% of samples). In addition, two-thirds of the viscose samples were fake,
suggesting that consistency is not a reliable measure for authentication.
3.4. Botanical origin
According to Codex Alimentarius, “honey may be designated according to floral source if it comes wholly or mainly from that particular source
and has the organoleptic, microscopic and physicochemical properties
corresponding with that origin” (Standard For Honey Codex Stan 12-1981,
2001). By this definition, identification of floral source can be obtained by
putting together all the results previously presented in this study. Among
the parameters used for identification, palynology is given priority in this
study. Thus, if the percentage of a pollen type belonging to a source plant
met the standard ranges found in the literature (bmbl, 2011; D.I.B., 2014;
Oddo and Piro, 2004), the respective sample was included in Table 3 as
potential unifloral honey. Further assessment is performed based on
adulteration (adult.), sensory (sens.), electrical conductivity and fructose/glucose (F/G) ratio, as these are the routinely used parameters in honey
evaluation. Unifloral source of a sample is approved if all parameters are in
accordance with the standards (stand.).
The results approved only one unifloral honey to be assigned to
C. cyanus with certainty. The 4 authentic dandelion (Taraxacum spp.)
samples had the typical sensory features, but their electrical conductivity
values were too low. However, as electrical conductivity is not a characterizing parameter for dandelion honey (Oddo and Piro, 2004), a
unifloral source of these samples can be accepted. The other 10 dandelion
samples also showed typical sensory features, but they were assessed as
adulterated.
8
E. Khansaritoreh et al.
Heliyon 7 (2021) e06651
Figure 6. Quantile plots for one authentic (a) and one adulterated (b) sample. The thick black line shows the values for current sample and the background shades
display values for samples in reference database.
Table 3. The possible unifloral honeys found in this study. Approved unifloral honeys are marked with an asterisk. The names of some plants are repeated twice when
both authentic and adulterated (adult.) samples are present with accepted pollen contents. NA is used when the standard (stand.) is not available. Yes/No in the sensory
(sens.) column indicates whether or not the sample(s) has typical sensory features. The lower 4 rows display properties of potential samples with locally acknowledged
unifloral origin. The column “NO.” indicates the number of samples found with the respective properties.
Plant
No.
Pollen%
Adult.
Stand.
study
Sens.
EC
F/G
Stand.
Study
Stand.
Study
C. cyanus*
1
>10
28
No
Yes
>30
0.39
>1.10
1.25
Citrus spp.
1
>20
20
No
No
0.10–0.30
0.23
>1.10
1.20–1.23
Citrus spp.
1
>20
23
Yes
No
0.10–0.30
0.15
>1.10
1.23
Helianthus spp.
3
>50
50–53
Yes
No
0.20–0.40
0.43–0.50
>1.10
1.12–1.14
Taraxacum spp.*
4
>05
6–17
No
Yes
0.37–0.65
0.23–0.30
>0.85
1.20–1.35
Taraxacum spp.
10
>05
5–10
Yes
Yes
0.37–0.65
0.13–0.33
>0.85
1.12–1.29
Thymus spp.
1
>13
17
No
No
0.35–0.75
0.34
>1.17
1.25
Tilia spp.
1
>20
73
Yes
No
0.37–0.97
0.16
>0.94
1.31
Astragalus spp.
8
NA
62–81
No
-
0.24–0.47
0.23–0.42
NA
1.20–1.36
Astragalus spp.
12
NA
60–86
Yes
-
0.24–0.47
0.17–0.27
NA
1.21–1.28
Eryngium spp.
1
>45
50
No
-
NA
0.34
NA
1.25
Eryngium spp.
2
>45
50–53
Yes
-
NA
0.17–0.26
NA
1.22–1.28
honey types. They establish apiaries in rangelands where Astragalus and
Eryngium are the dominant plants. Since the nectar yield of these plants is
not enough beekeepers have to feed sugar to bees during the foraging
season. Moreover, the Iranian beekeepers are not trained to avoid lands
covered by flowers that secret nectar with intensive aftertaste. As a result,
the main source of authentic Iranian honey is nectar of various wild flowers
(multifloral), sometimes with unpleasant aftertaste. Also the quality of
Iranian honey does not comply with international standards, and therefore,
Iran cannot act as producer of some unifloral honey types for global market
unless the beekeeping practices undergo fundamental changes.
sensory features. According to the results of this study, the most
probable reasons are replacement of natural nectar with sugar and
dominance of nectar with intensive flavor from Taraxacum spp. and
Eryngium spp.
4. Conclusion
This study indicates that the flora of Iran has the potential for production of genuine unifloral honeys with international marketability.
However, apparently Iranian beekeepers are not informed about these
9
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Heliyon 7 (2021) e06651
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Author contribution statement
Elmira Khansaritoreh, Kamaleddin Alizadeh: Conceived and designed
the experiments; Performed the experiments; Analyzed and interpreted
the data; Contributed reagents, materials, analysis tools or data; Wrote
the paper.
Yasaman Salmaki, Elias Ramezani, Shahin Zarre: Analyzed and
interpreted the data; Contributed reagents, materials, analysis tools or
data; Wrote the paper.
Tayebeh Akbari Azirani, Farnood Henareh: Performed the experiments; Analyzed and interpreted the data; Contributed reagents, materials, analysis tools or data; Wrote the paper.
Gudrun Beckh, Hermann Behling: Conceived and designed the experiments; Analyzed and interpreted the data; Contributed reagents,
materials, analysis tools or data; Wrote the paper.
Funding statement
This work was supported by Bayer CropScience and Quality Service
International GmbH.
Data availability statement
Data included in article/supplementary material/referenced in
article.
Declaration of interests statement
The authors declare no conflict of interest.
Additional information
No additional information is available for this paper.
Acknowledgements
Special thanks goes to all colleagues in QSI, in particular the experts
in pollen department who thoroughly helped this project with their
several years of experience in palynology and sensory. We would also like
to show our gratitude to Dr. Sebastian Bachmann and Dr. Jane van der
Meulen from NMR department in QSI for assisting us in physicochemical
aspects of the project. We thanks Mr. Arne Duebecke for his revision of
adulteration section. We thank also the state organizations of Iran for
their great help in data acquisition.
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