Agriculture 2012, 2, 25-37; doi:10.3390/agriculture2010025
OPEN ACCESS

agriculture
ISSN 2077-0472
www.mdpi.com/journal/agriculture
ArticleDifferentiation of Blossom Honey and Honeydew Honey from
Northwest Spain
Escuredo Olga *, Fernández-González María and Seijo María Carmen
Department of Vegetal Biology and Soil Sciences, Faculty of Sciences, University of Vigo,
As Lagoas, Ourense 32004, Spain* Author to whom correspondence should be addressed; E-Mail: oescuredo@uvigo.es.
Received: 27 December 2011; in revised form: 10 January 2012 / Accepted: 14 January 2012 /Published: 20 January 2012

Abstract: The knowledge of important parameters for honey characterization is anincreasing requirement of consumers and the honey industry. In this respect, differentiation
between blossom honeys and some honeydew honeys is still an unresolved task. This study
includes the results of physicochemical and melissopalynological analysis of 86 honeysamples from north-western Spain. The relationship between the microscopic elements inhoney, such as Metschnikowia cells and fungal spores from plant pathogens, together with
their physicochemical parameters were analysed. A cluster analysis was performed todifferentiate blossom honey samples from honeydew samples. Metschnikowia cells andcertain fungal spores were found to be good variables to enable differentiation between
blossom honeys and honeydew honeys.
Keywords: honey typification; nectar honey; honeydew honey; physicochemical analysis;
biotic elements

1. Introduction
The composition, flavour and colour of honey vary considerably depending on its botanical source.
European legislation (Council Directive 2001/110/EC of 20 December 2001 relating to honey) defines
various honey types and the requirements for labelling. Furthermore, the directive allows honeypackaging to include information about the product’s regional, territorial or topographical origin, floral
or vegetable origin, and even specific quality-related criteria. Consequently, there is an increasing

Agriculture 2012, 2

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commercial interest in determining the botanical origins of honeys, particularly to distinguish between
blossom honeys and honeydew honeys. Improved capabilities for classifying honeys could prevent
commercial frauds. The ability to be able to make these distinctions, especially for honeys with similar
physicochemical characteristics, has intrigued the scientific community [1].
The study of the microscopic elements present in honey, aims primarily to recognise the pollen
types in honey and their relationship to the botanical and geographical provenance of the honey [2].
Pollen grains are the most commonly studied element in honey; however, fungal spores, yeast, or othermicroscopic elements are less well known. Only a small number of studies has attempted to classify
these biotic elements [1,3–11]. Fungal spores and yeast can contact honeys at different points during
their harvest. These elements can come from primary sources (the honeydew or nectar), as a secondary
contamination during post-harvest, or once the honey begins to deteriorate [12].
Honeybees collect honeydew from the green parts of plants and at the same time, with honeydew,
they may collect other attached structures, such as the hyphae or fungal spores of plant pathogens andmicroalgae. Additionally, nectar itself has a microbial community associated with bees. Yeasts are themost frequent inhabitants of floral nectar and were familiar to microbiologists more than a century
ago [13], indicating the presence of yeast in floral nectaries. More recent research has examined thepresence of the microorganisms in nectar, their ecology and their classification [14–23]. The principal
group of microorganisms are Ascomycetes, particularly Metschnikowia, Candida, Zygosaccharomyces,
Debariomyces, Starmerella and Basidiomycetes, such as Cryptococcus sp. and Cystofilobasidium sp.
It has been known that physicochemical analysis could be used to differentiate between honeydew
honey and some blossom honey [24–26]. However, no studies include detailed information on fungal
structures found in the sediment of honey and its physicochemical characteristics. In this respect, themain objective of this study was to establish the relationship between these structures (mainMetschnikowia cells and fungal elements) and the source of honey.
2. Results
2.1. Microscopic Characteristics
The quantitative analysis of samples led to the identification of honeys with a high quantity ofpollen and fungal elements and others very poor in these elements. Pollen content varied between 1274
and 130,832 pollen grains per gram of honey, with a standard deviation of 25,585.
The qualitative pollen analysis identified 90 different pollen types in the samples. Table 1 lists themost commonly occurring pollens. This table includes 16 pollen types from ten botanical families,
along with their corresponding maximum values, the standard deviation, and the range and the numberof honeys in which the various pollen types reached a determined percentage level.

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Table 1. Principal pollen types, their frequency classes and their representation in
the samples.
Frequency classes a
FamilyPollen type

(%)

P

R

I

A

D

(0–1%)(1–3%)(3–15%)(15–45%)

>45%

Max.

St. Dv.

Fagaceae

Castanea

100.0

0.0

7.0

9.3

48.8

34.9

87.9

21.55

Leguminosae

Cytisus t.

100.0

18.6

25.6

52.3

2.3

1.2

48.6

6.81

Rosaceae

Rubus

100.0

3.5

3.5

29.1

34.9

29.1

83.6

21.31

Ericaceae

Erica

97.7

23.3

23.3

43.0

8.1

0.0

35.5

6.13

Leguminosae

Trifolium t.

87.2

40.7

29.1

17.4

0.0

0.0

9.6

1.87

Myrtaceae

Eucalyptus

86.0

22.1

18.6

20.9

12.8

11.6

81.0

22.81

Boraginaceae

Echium

76.7

45.3

20.9

10.5

0.0

0.0

9.8

1.82

Fagaceae

Quercus

66.3

52.3

10.5

2.3

1.2

0.0

27.8

3.03

Salicaceae

Salix

59.3

43.0

9.3

7.0

0.0

0.0

10.9

1.55

Rosaceae

Crataegus monogyna t.

40.7

33.7

5.8

1.2

0.0

0.0

3.6

0.61

Campanulaceae

Campanula t.

39.5

33.7

4.7

1.2

0.0

0.0

3.9

0.59

Umbelliferae

Conium maculatum t.

34.9

25.6

8.1

1.2

0.0

0.0

7.0

0.89

Rhamnaceae

Frangula alnus

31.4

23.3

5.8

2.3

0.0

0.0

13.7

1.72

Leguminosae

Lotus t.

20.9

17.4

2.3

1.2

0.0

0.0

3.7

0.45

Boraginaceae

Lithodora

16.3

12.8

1.2

2.3

0.0

0.0

4.3

0.60

Boraginaceae

Myosotis

11.6

10.5

0.0

1.2

0.0

0.0

5.6

0.61

Others

100.0

18.6

53.5

27.9

0.0

0.0

14.3

2.20

(%): percentage of samples in which the pollen type was identified; a Percentage of samples in which the pollen type was
identified in each marked range, according Louveaux et al. (1978); P: present pollen; R: minor pollen; I: important pollen;
A: accompanying pollen; D: dominant pollen.

Castanea sativa, Cytisus type and Rubus were present in 100% of the samples, whereas Erica waspresent in 97.7% and Eucalyptus in 86%. These pollens were the principal types found in the honeys
from north-western Spain. Echium, Quercus and Trifolium pollens were also frequently found. Pollens
from Salix, Crataegus monogyna type, Campanula type, Conium maculatum types, Frangula alnus,
Lotus type, Lithodora and Myosotis comprised more than 3% of pollen spectra and might also be
important in honeys. Fifty pollen types were present only in a few honeys (less than 10%) and were
included in other pollen type groups.
Regarding the botanical classification of honeys, 46 samples contained pollens from a variety ofsources and were classified as polyfloral. Another 25 samples contained more than 45% Rubus pollens
and were classified as blackberry monoflorals. Honeys containing more than 70% Castanea sativa
pollen were classified as chestnut honeys (9 samples). The remaining 6 samples were Eucalyptus
monofloral honeys with a percentage higher than 70%. Pollens from Erica plants were common, but
none of the samples contained enough Erica pollen to be classified as heather monofloral.
Further microscopic analysis identified additional elements in the sediments from samples. Table 2
shows a descriptive analysis of principal fungal elements sorted by frequency. Cladosporium conidia
were the best represented elements (occurring in 97.7% of samples), with a mean of 325 spores pergram of honey. Spores from Myxomycetes and Penicillium were also very abundant, with meancontent of 135 and 151 spores/g, respectively. More than 40% of the samples contained these elements.

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The second-most common element was Metschnikowia yeast, present in 79.1% of the honeys studied.
These cells have appeared in high content in some samples, with a maximum value of 46,217 cells pergram of honey.
Table 2. Descriptive analysis of microscopic elements per g of honey.
Fungal elements
Max.
Min.
Mean
St. Dv.
Rep. (%)
Cladosporium
1,934
0
325
346
97.7
a
Metschnikowia
46,217
0
2,244
5,998
79.1
Leptosphaeria
613
0
42
84
51.2
Myxomycete
3,815
0
135
443
47.7
Penicillium
1,594
0
151
324
41.9
Basidiospores
679
0
20
78
32.6
Stemphylium
251
0
19
46
32.6
Urediniospores
454
0
25
67
30.2
Alternaria
91
0
6
18
15.1
Bipolaris
92
0
3
14
5.8
Torula
241
0
4
27
4.7
Fusicladium
56
0
1
8
4.7
Curvularia
71
0
2
10
3.5
Botrytis
51
0
1
6
2.3
Pleospora
151
0
2
16
2.3
Fern spores
1,126
0
20
135
2.3
71
0
1
8
1.2
Helminthosporium
Sporidesmium
19
0
0
2
1.2
Drechslera
109
0
1
12
1.2
Unidentified
761
0
22
86
27.9
HDE/P
0.63
0
0.16
0.09
100
a
cells; Rep. (%): percentage of representation; HDE/P: honeydew index.

Fungal spores produced by plant pathogens, such as Leptosphaeria, Stemphylium, Urediniospores,
Alternaria, Pleospora and Botrytis, were also counted. Of these, Leptosphaeria was the most common(more than 50% of samples contain its spores), with a mean of 42 spores/g and a maximum of
613 spores/g. The next most common spores found were Stemphylium and Urediniospores (present inmore than 30% of samples), with means of 19 spores/g and 25 spores/g, respectively. Other elementsfrom plant pathogens were uncommon (occurring in less than 15% of the samples), with mean valuesof 6, 2 and 1 spores/g for Alternaria, Pleospora and Botrytis, respectively.
Basidiospores, which include spores from Basidiomycota other than yeasts, were present in 32.6%
of samples with a maximum of 679 spores/g. A high number of spores from ferns (Pterydophyta) were
present in two samples, probably because the bees collected them as a protein source. In relation to thehoneydew index, the highest value was 0.63 and the lowest was 0.00, with a standard deviation of 0.09.
2.2. Physicochemical Characteristics
Table 3 shows the descriptive analysis for physicochemical parameters. The honeys had a low levelof hydroxymethylfurfural (HMF), indicative of fresh honeys. The mean value was 0.3 mg/100 g; inAgriculture 2012, 2

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fact, only three samples had more than 1 mg/100 g of HMF. Diastase varied between 6.1 Shade and31.9 Shade, and invertase varied between 4.3 IN and 35.9 IN. Electrical conductivity and pH were twoparameters widely used to distinguish between nectar and honeydew honeys. The pH varied between
3.5 and 5.0, values higher than 5.0 were not detected. The electrical conductivity varied between aminimum value of 0.224 mS/cm and a maximum value of 1.168 mS/cm. The humidity content had amean value of 17.3 ± 0.8%. Colour varied between 39 and 150 mm, with a mean value of 95 ± 27 mm.
Light amber colour (34–85 mm) accounted for 38.3% of honeys; amber colour (85–114 mm) for
41.9%; and dark amber colour (more than 114 mm) for 19.8%. The studied honeys were representativeof the honeys produced in this geographical area, in which medium-high coloured honeys withmedium or high electrical conductivity predominate.
Table 3. Descriptive analysis of physicochemical parameters.
Parameters
Max.
Min.
Mean
St. Dv.
Humidity (%)
19.8
15.5
17.3
0.8
pH
5.0
3.5
4.2
0.3
EC (mS/cm)
1.168
0.224
0.615
0.218
Colour (mm pfund)
150
39
95
27
Invertase (IN)
35.9
4.3
17.5
5.7
Diastase (Shade)
31.9
6.1
16.5
5.7
HMF (mg/100 g)
1.6
0.0
0.3
0.3
Potassium (mg/100 g)
312.1
32.8
138.7
62.8
Calcium (mg/100 g)
16.6
4.4
9.0
2.8
Iron (mg/100 g)
1.1
0.0
0.3
0.2
Magnesium (mg/100 g)
30.7
1.4
7.8
7.0
Sodium (mg/100 g)
26.7
0.9
5.6
4.8
Phosphorus (mg/100 g)
31.5
3.0
8.8
5.5
Zinc (mg/100 g)
0.4
0.1
0.2
0.1
Copper (mg/100 g)
3.7
0.0
0.4
0.8
a
Total mineral (mg/100 g)
387.4
47.9
170.8
73.4
a
Contains the sum of all minerals identified; EC: electrical conductivity.

The most abundant mineral in the honeys was potassium, with a mean value of 138.7 ± 62.8 mg/100 g.
The phosphorus content varied between 31.5 mg/100 g and 3.0 mg/100 g, with a mean value of
8.8 mg/100 g. The average amount of magnesium was 7.8 ± 7.0 mg/100 g, and the calcium level was
9.0 ± 2.8 mg/100 g. Other mineral elements were present in low quantities.
2.3. Spearman’s Linear Rank Correlation between Microscopic and Physicochemical Variables
A linear rank correlation analysis was used to examine the relationships between the variables
studied. We used a non-parametric method, in which a linear correlation coefficient was calculatedusing Spearman’s linear rank correlation analysis. In this procedure, the variables with the strongest
relationship to the provenance of the honey were used.
Table 4 includes the value of the correlation coefficient and the significance (P < 0.05, P < 0.01,
P < 0.001) of its relationship with the variables obtained by microscopic analysis, that could be related

Agriculture 2012, 2

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to the source of the honey. The presence of Metschnikowia cells had a positive correlation with
Eucalyptus and Rubus pollen content (P < 0.05) and a negative correlation with Cytisus t. (P < 0.01)
and Erica pollen content (P < 0.001). The first taxon produced blossom honeys, and the other two
were numerous in dark honeys.
Table 4. Significant correlation coefficients for the microscopic analysis variables, basedon Spearman’s test.
Castanea Eucalyptus
Rubus
Cytisus t.
Erica
Metschnikowia−0.0480.240 *
0.239 *
−0.317 **−0.544 ***HD spores
0.051−0.390 ***0.264 *
0.043
−0.041* P < 0.05; ** P < 0.01; *** P < 0.001. HD: plant pathogen spores.

The group called HD spores included the levels of Alternaria, Leptosphaeria, Stemphylium,
Botrytis, Pleospora and Urediniospores. These plant pathogen fungi constitute an important subgroupof the identified fungal elements. This group had a negative correlation with the Eucalyptus pollen
content (P < 0.001) and a positive correlation with Rubus pollen (P < 0.05).
Metschnikowia cells had negative correlation coefficients with most of the physicochemicalvariables (P < 0.001) other than pH (no significance) and humidity (positive correlation P < 0.01)(Table 5).
Table 5. Significant correlation coefficients among the microscopic analysis andphysicochemical parameter variables, based on Spearman’s test.
Diastase

Invertase

pH

EC

Humidity

ColourTotal mineral

Metschnikowia−0.329 **−0.353 ***−0.179−0.663 ***0.298 **

−0.662 ***−0.592 ***HD spores

0.376 ***

0.441 ***

0.468 ***

0.476 ***

−0.240 *0.399 ***

0.436 ***

Castanea

0.141

0.038

0.105

0.247 *

0.165

0.195

0.156

Eucalyptus−0.386 ***−0.344 **−0.346 **−0.520 ***0.197−0.491 ***−0.456 ***Rubus

0.232 *

0.207

0.167

0.057

−0.179

0.053

0.043

Cytisus t.

0.251 *

0.163

0.050

0.285 **

−0.0690.347 **

0.231 *

Erica

0.161

0.122

−0.237 **0.310 **

0.111

0.437 ***

0.231 **

* P < 0.05; ** P < 0.01; *** P < 0.001; EC: electrical conductivity.

The presence of other fungal elements in honeys correlated positively with all physicochemicalvariables except humidity. HD spores in particular had a positive correlation (P < 0.001) with all thephysicochemical parameters except humidity, with which it was negatively correlated (P < 0.05).
Regarding the honeys’ pollen content, Eucalyptus pollen had similar correlations to those of nectar
yeast. Pollens from Cytisus and Erica types had positive correlations (P < 0.01) with electricalconductivity, mineral content (P < 0.05, P < 0.01, respectively) and colour (P < 0.01, P < 0.001,
respectively). Cytisus t. also had positive correlations (P < 0.05) with diastase content, and Erica had
negative correlations with pH (P < 0.01). Castanea pollen and Rubus pollen had positive correlation
with electrical conductivity (P <0.05) and diastase (P < 0.05), respectively.

Agriculture 2012, 2

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2.4. Cluster Analysis with the Main Microscopic Variables
The cluster analysis was performed with the main variables obtained by microscopy as independent
variables. These were Metschnikowia cells, HD spores, Castanea pollen, Eucalyptus pollen, Rubus
pollen, Cytisus pollen and Erica pollen. The groups (honeydew honeys or blossom honeys) were
established according to the characteristics of the samples, as previously pointed out. The cluster(Figure 1) represents the groups established in the analysis. Sixty four samples belonged to theblossom honey group (polyfloral honeys, Eucalyptus honeys, Rubus honeys and Castanea honeys) and
22 to the honeydew honey group (including blend honeys and honeydew samples).
Figure 1. Cluster analysis of the studied samples.
0,4Linkage Distance

0,3

0,2

0,1

0,0
22222222222222222222222222222222222222222222222222222222222222222111221111111111111111

1. Honeydew honeys; 2. Blossom honeys.

2.5. T Test and Levene’s Test of the Homogeneity of the Variance
The groups established by the cluster analysis were compared using a t-test for the equality of themeans. Levene’s test examined the homogeneity of the variances by performing a one-way ANOVA
on the absolute deviation scores.
Table 6 shows the descriptive statistical analysis of each group. Blossom honeys (N group) had amean electrical conductivity of 0.540 ± 0.2 mS/cm, lower than that of the HD group (mean:
0.830 ± 0.2 mS/cm). Colour was clearer for nectar honeys (85 ± 20 mm pfund) than for honeydew
honeys (124 ± 21 mm pfund). Mineral content was generally lower in blossom honeys, particularly forpotassium content (N group mean: 120.4 ± 50.7 mg/100 g vs. HD group mean: 192.1 ± 65.2 mg/100 g),
as was phosphorus content (7.4 ± 3.2 mg/100 g vs. 13.2 ± 8.2 mg/100 g). Even the enzymatic activity
was high in the nectar samples. The subindex of the variables indicates the significance levels between
the groups. Some parameters led to differentiation between the groups. These were enzymatic activity,
Metschnikowia cells and Cytisus pollen type with p < 0.05, electrical conductivity, humidity, colour,
potassium, calcium, magnesium, phosphorus, total mineral content, Eucalyptus pollen, Erica pollen
and HD spores content with p < 0.01.

Agriculture 2012, 2

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Table 6. Descriptive statistical analysis of the groups established by cluster analysis.
Parameters
Pollen grain per gram
Diastase content (Shade) b
Invertase content (IN) b
HMF (mg/100 g)
pH
EC (mS/cm) a
Humidity (%) aColour (mm pfund) a
Potassium (mg/100 g) a
Calcium (mg/100 g) a
Iron (mg/100 g)
Magnesium (mg/100 g) a
Sodium (mg/100 g)
Phosphorus (mg/100 g) a
Zinc (mg/100 g)
Copper (mg/100 g)
Total mineral (mg/100 g) a
Castanea
Rubus
Erica a
Eucalyptus a
Cytisus t. b
Mestchnikowia (cells/g) b
HD spores (spores/g) aaMax.
90,232
31.8
35.9
1.6
5.0
0.920
19.8
118
239.0
13.7
1.1
18.7
26.7
17.1
0.4
3.7
280.3
86.2
83.6
15.3
81.0
31.4
46217
406

N group (N = 64)
Min. Mean St. Dv.
1,632 24,659 23,006
7.5
15.7
5.4
4.3
16.8
5.8
0.0
0.4
0.3
3.5
4.2
0.3
0.224 0.540
0.2
16.0
17.5
0.7
39
85
20
32.8
120.4
50.7
4.7
8.4
2.3
0.03
0.3
0.2
1.6
5.8
4.4
1.2
5.7
4.9
3.3
7.4
3.2
0.1
0.2
0.1
0.02
0.4
0.8
47.9
148.6
55.9
1.0
36.2
20.9
0.3
29.7
21.6
0.0
3.7
3.9
0.0
17.9
4.6
0.1
4.0
25.2
17.1
3013
6796
0
61
84

HD group (N = 22)
Max.
Min.
Mean
130,832
1,274
26,071
30.9
6.1
18.8
26.0
10.1
19.7
0.9
0.0
0.3
4.9
3.5
4.3
1.168
0.482
0.830
17.8
15.5
16.7
150
79
124
312.0
65.5
192.1
16.6
4.4
10.6
0.7
0.1
0.3
29.2
1.4
13.5
17.8
0.9
5.3
31.5
2.9
13.2
0.4
0.1
0.2
0.7
0.1
0.3
387.4
95.2
235.4
87.9
2.5
41.5
65.8
7.1
31.5
35.5
1.3
8.9
14.2
0.0
2.7
26.8
0.3
7.7
41
0
4.7
1159
5
193

St. Dv.
32,561
5.9
4.8
0.3
0.4
0.2
0.6
20.9
65.2
3.4
0.1
9.8
4.7
8.2
0.1
0.5
80.8
23.3
20.8
9.2
4.3
10.6
286
11.5

differences among both groups (P < 0.01); b differences among both groups (P < 0.05); N group: blossom

honeys; HD group: honeydew honeys; HMF: hydroxymethylfurfural; EC: electrical conductivity.

3. Discussion
Some physicochemical parameters indicate the presence of honeydew in honey, as is the case forthe electrical conductivity. European legislation has established a minimum of 0.800 mS/cm forhoneydew honeys, chestnut honeys and their blends. Only 18.6% (16 samples) of the studied honeys
had higher electrical conductivity and all of them show a significant amount of Castanea pollen in thepollen spectra (6 samples more than 70%). In general, dark honeys had the highest mineralcontent [27,28], nevertheless Erica honeys and Castanea honeys frequently have similar mineralcontent to honeydew honeys [29]. Another physicochemical parameter used for honey typification wascolour; dark honeys or amber dark honeys were frequently associated with honeydew but as occurs
with electrical conductivity, Castanea honeys or Erica honeys, among others, have dark or amber darkcolour. Related to sensorial attributes honeydew honeys were described by González et al. [30] as dark
caramelized liquid honeys, without crystallization, of intense fruitiness with certain floral notes, spicy
with a woody fresh odor and very greasy in the mouth. Again nectar contributions of Castanea could

Agriculture 2012, 233

confuse the origin of honeys by their sensorial perceptions since this type of honey has woody
olfactory perceptions but with strong intensity [29].
The interpretation of the pollen spectra of the honeys is an important tool in its characterization.
This analysis together with some sensorial attributes and physicochemical parameters are frequently
necessary to typify honeys. Also a high ratio of HDE (spores, hyphae or algae) to P (number of pollen
grains), being the honeydew index [31], has been used to indicate the presence of honeydew. Pine
honeys from Greece had a higher HDE/P ratio, with levels higher than 1.5 [1]; this high HDE content
was reported also by Persano-Oddo et al. [29] for honeydew honeys. In the case of the honeys studied
in this work the mean HDE/P ratio of 0.16 was considered very low. As a result, the honeydew index
was not found to be a useful way to classify honeydew honeys from this region.
However considering the range of honeydew elements that can be found in honey, it has beenpossible to established a relation between some of these elements and the provenance of the honey(nectar or honeydew). The results showed the importance of the microscopic analysis for typificationof the studied honey. Yeast with an airplane-cell configuration has been found in higher quantities insome honey samples. These structures, specific to floral nectar [32–34] and identified as
Metschnikowia, could be indicative of blossom honeys. Other important fungal elements identified in
the honeys from northwest Spain belonging to the fungus kingdom were: spores, hyphae or conidia.
The most abundant conidia were Cladosporium, Myxomycete, and Penicillium. These grow frequently
in both indoor and outdoor environments [35,36] and can be passed to honey during the different
stages of production or as a secondary contamination [10]. Some fungal spores, produced by plant
pathogens, were also found, albeit of low content. The most important were Leptosphaeria, Stemphyliumand Urediniospores, present in more than 30% of the studied samples. They grow over the leaves andgreen parts of plants, causing various diseases. Fungal elements can be introduced into honeys when
the worker bees collect honeydew from the plant. As expected, the presence of fungal pathogens could
be indicative of the presence of honeydew.
Nectar honeys are produced during the spring and the early summer, normally over short periods oftime. In our region, the eucalyptus (E. globulus) honey production period starts in winter (January) andstops in April. The nectar secretion pattern is very abundant and fast; thus, honey production iscompleted quickly. These honeys have low enzyme content. Conversely, when honey production takes
longer, then enzyme content is higher. This occurs with honeys in the honeydew group, which probably
began as blossom honeys early in spring but were mixed with honeydew secretions toward the end ofsummer (August and September). This fact was supported by the values for the principal pollen taxa ineach group. In this instance, honeys with high Metschnikowia yeast had less electrical conductivity,
lighter colour, higher humidity, minor enzymatic content and lower mineral content, which are allcommon features of blossom honeys [26,29]. On the other hand, honeys with significant quantities ofHD spores were dark or dark amber honeys with high electrical conductivity, relatively high pH, highenzymatic activity, high mineral content and low humidity content. These characteristics are common
to honeydew honeys or blends [25,37,38].

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4. Material and Methods
In this study 86 honey samples were analysed from Galicia (Northwest Spain), collected during theyears 2008 and 2009 directly by the beekeepers and analysed in the Laboratory of Aerobiology and
Beekeeping of the Faculty of Sciences of Ourense (University of Vigo). Each sample (1 kg) was
separated into two parts. One of them was used for physicochemical analysis and was stored at room
temperature; the other was frozen at −30 °C for further analysis. All the determinations were
performed in duplicate.
4.1. Microscopic Analysis
Pollen and the different fungal elements were analysed, identified and counted with a modified
version of the method described by Louveaux et al. [31]. The quantitative analysis was made by a
volumetric method using two aliquots of 10 µL taken from 2 mL of sediment obtained by centrifuging
10 g of honey. The total number of pollen grains and fungal elements were counted by microscopy ineach aliquot and were expressed as an average. Pollen spectra were constructed by counting aminimum of 800 pollen grains in two 100 µL aliquots of the sediment obtained previously. The
amounts of fungal spores and yeasts were also calculated from a 100 µL aliquot, with the number ofpollen grains on the slide as a reference. The results were expressed as the quantity of the different
fungal elements per gram of honey. Also, the relation between the number of fungal spores and thenumber of pollen grains (HDE/P) named as the honeydew index (HDE) was calculated.
4.2. Physicochemical Analysis
The principal parameters of honey quality were determined using the methods adopted by theInternational Honey Commission [39].
Hydroxymethylfurfural (HMF) content was determined by UV absorbance of HMF at 284 nm. To
avoid interference from other components at this wavelength, we determined the difference between theabsorbencies of a clear aqueous honey solution and the same solution with added bisulphite, as
described by White [40].
Invertase activity was determined by spectrophotometry of 4-Nitrophenyl-alpha-D-glucopyranosidedecomposition at 400 nm. The samples were incubated at 40 °C. The invertase activity was expressedas an invertase number (IN). Diastase activity was based on the rate of starch hydrolysis by diastase,present in a honey buffer solution. The endpoint of this reaction was determined by measuring samplesof the mixture at different time intervals using a UV-VIS spectrophotometer at 660 nm. The timerequired to reach an absorbance of 0.235 was calculated using linear regression, and the results
were expressed using a Gothe scale. The UV-VIS absorbance was measured with a spectrophotometer(Jenway 6505).
The percentage of moisture was determined by refractometry, using an Abbe 325 refractometer. The
pH was measured with a pH meter (Crison micropH 2001) of honey dissolved in bidistilled water. The
electrical conductivity was determined with a conductivity meter (Knick 913 C), and the results wereexpressed as mS/cm. All measurements were performed at 20 °C. The colour was measured with aAgriculture 2012, 2

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Hanna Honey Colour C221 digital instrument, and the results were expressed in millimetres using thePfund scale.
The quantitative determination of minerals, such as potassium, calcium, iron, magnesium, sodium,
phosphorus, zinc and copper, in the honey was conducted with an atomic absorption spectrophotometer(Varian SpectrAA-220). Samples were digested in a microwave before their mineral content
was evaluated.
4.3. Statistical Analysis
Physicochemical variables, mineral content, the most frequently occurring pollen types, the yeast
content and the fungal content were statistically compared using Spearman’s rank correlation analysis.
A cluster analysis was applied to differentiate the honeys according to their botanical origin (either
blossom honeys or honeydew honeys). The variables used were principal pollen types, Metschnikowia
cells and a group of spores of plant pathogens called HD spores. Finally, the two groups established by
the cluster analysis were compared with an independent samples t-test, which determines the presenceof statistically significant differences between-groups.
All statistical analyses were performed with the SPSS Statistic 17.0 software for Windows.
5. Conclusions
Some biotic elements were identified in the sediment of the honeys. The presence of thesestructures can be used to distinguish between blossom and honeydew honeys. The statistical analysis
led to a differentiation between these two groups of honeys. The parameters showing clear differenceswere enzymatic content, electrical conductivity, humidity, colour, mineral content (especiallypotassium, calcium, magnesium and phosphorus) and microscopic elements, such as, fungal spores
from plant pathogens, yeast and some common pollen grains in the honeys.
Acknowledgments
This study was financed by the Conselleria de Medio Rural, the Ministerio de Medio Ambiente,
Medio Rural y Marino and FEADER. Research project FEADER 2008-5. To the sensory panel ofProtected Geographical Indication “Mel de Galicia”.
References
1.
2.
3.
4.
5.
6.

Dimou, M.; Katsaros, J.; Klonari, K.T.; Thrasyvoulou, A. Discriminating pine and fir honeydew
honeys by microscopic characteristics. J. Apic. Res. Bee World 2006, 45, 16–21.
Tsigouri, A.; Passaloglou-Katrali, M.; Sabatakou, O. Palynological characteristics of different
unifloral honeys from Greece. Grana 2004, 43, 122–128.
Maurizio, A. The microscopy of honeydew honey. Ann. Abeille 1959, 2, 145–157.
Barth, O.M. Microscopic constituents of Brazilian honeydew honeys. Apidologie 1971, 2, 157–167.
Borowska, A.; Demianovicz, Z. Fungi in fir honeydew. Acta Mycol. 1972, 8, 175–189.
Demianovicz, Z.; Borowska, A.; Dubik, G.; Pielka, J. Fungi in fir honeydew honey. Ann. Univ.
Mariae Curie-Sklodowska 1972, 25, 203–212.

Agriculture 2012, 2
7.

36

Ferrazzi, P. Phytophagous insects and honeybees: Incidence of honeydew in honeys from
northern Italy. Apicoltore Moderno 1984, 75, 31–38.
8. Warakomska, Z.; Jaroszynska, T. Analysis of the honeydew honeys of Roztocze. Pszczelnicze
Zeszyty Naukowe 1992, 36, 149–156.
9. Pérez-Sánchez, M.C.; Del Baño-Breis, F.; Candela-Castillo, M.E.; Egea-Gilabet, C. Microbial
flora in honey from the region of Murcia, Spain. An. de Biol. 1997, 22, 155–164.
10. Pérez-Atanes, S.; Seijo-Coello, M.C.; Méndez-Álvarez, J. Contribution to the study of fungal
spores in honeys of Galicia (NW Spain). Grana 2001, 40, 217–222.
11. Magyar, D.; Gönczöl, J.; Révay, Á.; Grillenzoni, F.; Seijo-Coello, M.C. Stauro- andscolecoconidia in floral and honeydew honeys. Fungal Divers. 2005, 20, 103–120.
12. Popa, M.; Vica, M.; Axinte, R.; Glevitzky, M.; Varvara, S. Correlations on the microbiologicaland physicochemical characteristics of different types of honey. J. Environ. Protec. Ecol. 2009,10, 1113–1121.
13. Boutroux, L. Sur la conservation des ferments alcooliques dans la nature. Ann. Sci. Natur. IV.S.
Bot. 1884, 17, 145–209.
14. Gilliam, M.; Lorenz, B.J.; Richardson, G.V. Digestive enzymes and micro-organisms in honeybees, Apis mellifera: Influence of streptomycin, age, season and pollen. Microbios 1988, 55, 95–114.
15. Inglis, G.D.; Sigler, L.; Goettel, M.S. Aerobic microorganisms associated with alfalfa leafcutter
bees (Megachile-Rotundata). Microb. Ecol. 1993, 26, 125–143.
16. Gilliam, M. Identification and roles of non-pathogenic microflora associated with honey bees.
FEMS Microbiol. Lett. 1997, 155, 1–10.
17. Rosa, C.A.; Viana, E.M.; Martins, R.P.; Antonini, Y.; Lachance, M.A. Candida batistae, a new
yeast species associated with solitary digger nesting bees in Brazil. Mycologia 1999, 91, 428–433.
18. Lachance, M.A.; Bowles, J.M.; Chavarria, M.M.; Janzen, D.H. Candida cleridarum, Candida
tilneyi and Candida powellii, three new yeast species isolated from insects associated with flowers.
Int. J. Syst. Evol. Microbiol. 2001, 51, 1201–1207.
19. Lachance, M.A.; Starmer, W.T.; Rosa, C.A.; Bowles, J.M.; Barker, J.S.F.; Janzen, D.H.
Biogeography of the yeasts of ephemeral flowers and their insects. FEMS Yeast Res. 2001, 1, 1–8.
20. Teixeira, A.C.P.; Marini, M.M.; Nicoli, J.R.; Antonini, Y.; Martins, R.P.; Lachance, M.A.;
Rosa, C.A. Starmerella meliponinorum sp. nov., a novel ascomycetous yeast species associatedwith stingless bees. Int. J. Syst. Evol. Microbiol. 2003, 53, 339–343.
21. Herrera, C.M.; García, I.M.; Pérez, R. Invisible floral larcenies: microbial communities degrade
floral nectar of bumble bee-pollinated plants. Ecology 2008, 89, 2369–2376.
22. Herrera, C.M.; de Vega, C.; Canto, A.; Pozo, M.I. Yeasts in floral nectar: A quantitative survey.
An. Bot. 2009, 103, 1415–1423.
23. De Vega, C.; Arista, M.; Ortiz, P.L.; Herrera, C.M.; Talavera, S. The antpollination system of
Cytinus hypocistis (Cytinaceae), a Mediterranean root holoparasite. An. Bot. 2009, 103, 1065–1075.
24. Terrab, A.; Díez, M.J.; Heredia, F.J. Characterisation of Moroccan unifloral honeys by their
physicochemical characteristics. Food Chem. 2002, 79, 373–379.
25. Marini, F.; Magri, A.L.; Balestrieri, F.; Fabretti, F.; Marini, D. Supervised pattern recognition
applied to the discrimination of the floral origin of six types of Italian honey samples. Anal. Chim.
Acta 2004, 515, 117–125.

Agriculture 2012, 2

37

26. Sanz, M.L.; Gonzalez, M.; de Lorenzo, C.; Sanz, J.; Martinez-Castro, I. A contribution to thedifferentiation between nectar honey and honeydew honey. Food Chem. 2005, 91, 313–317.
27. González-Paramás, A.M.; Gómez-Bárez, J.A.; García-Villanova, R.J.; Rivas-Palá, T.;
Ardanuy-Albajar, R.; Sánchez-Sánchez, J. Geographical discrimination of honeys by using
mineral composition and common chemical quality parameters. J. Sci. Food Agric. 2000, 80,
157–165.
28. Terrab, A.; Recamales, A.F.; Hernanz, D.; Heredia, F.J. Characterisation of Spanish thyme honeys
by their physicochemical characteristics and mineral contents. Food Chem. 2004, 88, 537–542.
29. Persano-Oddo, L.; Piro, R. Main European unifloral honeys: Descriptive sheets. Apidologie 2004,
35 extra issue, 38–81.
30. González, M.M.; de Lorenzo, C.; Pérez, R.A. Development of a structured sensory honey analysis:
application to artisanal Madrid honeys. Food Sci. Technol. Int. 2010, 16, 19–29.
31. Louveaux, J.; Maurizio, A.; Vorwohl, G. Methods of melissopalynology. Bee World 1978, 51,
125–131.
32. Brysch-Herzberg, M. Ecology of yeasts in plant–bumblebee mutualism in Central Europe. FEMS
Microbiol. Ecol. 2004, 50, 87–100.
33. Herrera, C.M.; Pozo, M.I. Nectar yeasts warm the flowers of a winter-blooming plant. Proc. R.
Soc. B 2010, 277, 1827–1834.
34. Pozo, M.I.; Herrera, C.M.; Bazaga, P. Species richness of yeast communities in floral nectar ofSouthern Spanish plants. Microb. Ecol. 2011, 61, 82–91.
35. Méndez, J.; Iglesias, I.; Jato, M.V.; Aira, M.J. Variación del contenido en esporas de Alternaria,
Cladosporium y Fusarium en la atmósfera de la ciudad de Ourense (años 1993–1994). Polen
1997, 8, 79–88.
36. Fernández-González, D.; Valencia, R.M.; Molnar, T.; Vega, A.; Sagüés, E. Daily and seasonalvariations of Alternaria and Cladosporium airborne spores in León (North-West, Spain).
Aerobiologia 1998, 14, 215–220.
37. Thrasyvoulou, A.; Manikis, J. Some physicochemical and microscopic characteristics of Greek
unifloral honeys. Apidologie 1995, 26, 441–452.
38. Diez, M.J.; Andres, C.; Terrab, A. Physicochemical parameters and pollen analysis of Moroccon
honeydew honeys. Int. J. Food Sci. Technol. 2004, 39, 167–176.
39. Bogdanov, S.; Martin, P.; Lullmann, C. Harmonized methods of the international honeycommission. Apidologie 1997, extra issue, 1–59.
40. White, J.W. Spectrophotometric method for hydroxymethylfurfural in honey. J. Assoc. Off. Anal.
Chem. 1979, 62, 509–514.
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