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HMF and diastase activity in honeys: A fully validated approach and a
chemometric analysis for identification of honey freshness and adulteration
Article in Food Chemistry · August 2017
DOI: 10.1016/j.foodchem.2017.02.084
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Food Chemistry 229 (2017) 425–431
Contents lists available at ScienceDirect
Food Chemistry
journal homepage: www.elsevier.com/locate/foodchem
Analytical Methods
HMF and diastase activity in honeys: A fully validated approach and a
chemometric analysis for identification of honey freshness and
adulteration
Ioannis N. Pasias a, Ioannis K. Kiriakou a, Charalampos Proestos b,⇑
a
b
Chemical Laboratory of Lamia, Karaiskaki 85, Lamia 35100, Greece
National and Kapodistrian University of Athens, Department of Chemistry, Food Chemistry Laboratory, Panepistimiopolis Zografou, 15771 Athens, Greece
a r t i c l e
i n f o
Article history:
Received 29 June 2016
Received in revised form 17 November 2016
Accepted 17 February 2017
Available online 22 February 2017
Keywords:
Diastase activity
HMF
Uncertainty
Honey
PCA
Cluster analysis
Chemometrics
a b s t r a c t
A fully validated approach for the determination of diastase activity and hydroxymethylfurfural content
in honeys were presented in accordance with the official methods. Methods were performed in real
honey sample analysis and due to the vast number of collected data sets reliable conclusions about
the correlation between the composition and the quality criteria were exported. The limits of detection
and quantification were calculated. Accuracy, precision and uncertainty were estimated for the first time
in the kinetic and spectrometric techniques using the certified reference material and the determined
values were in good accordance with the certified values. PCA and cluster analysis were performed in
order to examine the correlation among the artificial feeding of honeybees with carbohydrate supplements and the chemical composition and properties of the honey. Diastase activity, sucrose content
and hydroxymethylfurfural content were easily differentiated and these parameters were used for
indication of the adulteration of the honey.
Ó 2017 Elsevier Ltd. All rights reserved.
1. Introduction
During the last few years, honey consumption has increased
since it is a natural product composed of sugars, enzymes, amino
acids, organic acids, carotenoids, vitamins, minerals, and aromatic
substances. It has an important antioxidant activity and is usually
used as a food additive in many beverages and foodstuffs. The
chemical composition of honey is perfectly described by Silva
et al. in their excellent review (Silva, Gauche, Gonzaga, Costa, &
Fett, 2016).
The rapid growth in honey production has made the sector
important to the economy of many developing countries, whereas
there is an increased concern for public health since honey
undergoes many changes in its composition during storage and
processing (Barra, Ponce-Díaz, & Venegas-Gallegos, 2010; Tornuk
et al., 2013). Furthermore, the bad agricultural practice and the
small amounts of honey production have provided a heightened
interest in its adulteration (Wang, Juliani, Simon, & Ho, 2009).
The detection of the adulteration of honey is very difficult and
modern analytical techniques are required, such as liquid chromatography coupled to isotope ratio mass spectrometry, elemental
⇑ Corresponding author.
E-mail address: iharpro@chem.uoa.gr (C. Proestos).
http://dx.doi.org/10.1016/j.foodchem.2017.02.084
0308-8146/Ó 2017 Elsevier Ltd. All rights reserved.
analyzer-isotope ratio mass spectrometry and gas chromatography
coupled to mass spectrometry (Cabañero, Recio, & Rupérez, 2006;
Luo et al., 2016; Padovan, De Jong, Rodrigues, & Marchini, 2003).
Due to the availability and variety of different analytical methods and national regulation European Commission has adopted
quality assurance systems and specifically by applying methods
validated and according to common procedures and performance
criteria. In Council Directive, 2001/110/EC all quality criteria of
honey are described concerning the quality control of honey, the
rules on the conditions for the production and marketing of honey,
and the food-labelling rules (Council Directive, 2001/110/EC;
Puscas, Hosu, & Cimpoiu, 2013).
The analytical results generated by laboratories approved for
the official control of honeys must be accurate and precise with
low detection limits and costs in short analysis times. In the field
of honey chemical analysis there are some parameters that must
be determined such as, conductivity, sugar content, hydroxymethylfurfural (HMF) content, diastase activity, acidity, moisture
and pollen type. These methods are described in Codex Alimentarius, AOAC and other standards but in routine analysis are difficult
to validate (AOAC 958.09-1977, 2010; AOAC 980.23, 1983, 1990;
Codex Standard, 12-1981). Numerous studies have been carried
out on chemical composition of different pollen type honeys and
from different regions, based on these methods (Silva et al.,
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I.N. Pasias et al. / Food Chemistry 229 (2017) 425–431
2016). Among these parameters HMF, diastase activity and sugar
content are the most important for the quality control of different
honey samples. HMF is a furanic compound which is formed as an
intermediate in the Maillard reaction from the direct dehydration
of sugars under acidic conditions (caramelisation) during thermal
treatments applied to foods (Ames, 1992; Kroh, 1994). The Codex
Alimentarius of the World Health Organization and the European
Union have established a maximum quality level for the 5-HMF
content in honey (40 mg kg1) (Alinorm 01/25, 2001; Council
Directive, 2001/110/EC).
Diastase is one of the major enzymes found in honey. Diastase
activity and HMF content are well used as criteria to assess the
quality of the product (Thrasyvoulou, 1986). Furthermore, according to the European Union, when placed on the market as honey or
used in any product intended for human consumption, honey must
meet the following sugar composition criteria: (a) for blossom
honey the sum of fructose and glucose should not be less than
60%, whereas the sucrose content should not be higher that 5%
and (b) for honeydew honey the sum of fructose and glucose
should not be less than 45%, whereas the sucrose content should
not be higher that 5%.
The main difficulty in routine analysis is the full validation of a
method for the determination of diastase activity and HMF content. The fact that these methods are official does not guarantee
that the laboratories can perform the analysis correctly. The aim
of this study is to describe for the first time an approach for the
development of fully validated methods for these parameters. To
the best of our knowledge there are no similar studies concerning
the same topic. The accuracy, the precision and the uncertainty of
these methods were calculated for the first time. Different blossom
and honeydew samples were analyzed and the collected data were
statistically edited, and reliable conclusions about the correlation
between the composition and the quality criteria were exported.
Principal component analysis and cluster analysis were performed
in order to examine the correlation among the artificial feeding
with carbohydrate supplements of honeybees, the freshness of
the honey with HMF content and diastase activity.
2. Materials and methods
2.1. Honey samples
Thirty nine different honey samples (25 flower type honey and
14 honeydew honey samples) were collected from local experienced beekeepers in Lamia Greece, (from 2015 to 2016). Samples
were stored at room temperature until analysis. All honey samples
were characterized on the basis of melissopalynological characterization according to their specific botanical variety (Louveaux,
Maurizio, & Vorwohl, 1978).
2.2. HMF determination
The HMF content determination was based on the official AOAC
method (AOAC official method 980.23, 1983). Five grams of honey
were dissolved in 25 ml of water, transferred quantitatively into a
50 ml volumetric flask, added by 0.5 ml of Carrez solution I and
0.5 ml of Carrez II and make up to 50 ml with water. The solution
was filtered through paper rejecting the first 10 ml of the filtrate.
Aliquots of 5 ml were put in two test tubes; 5 ml of distilled water
were added to one tube (sample solution); 5 ml of sodium bisulphite solution 0.2% were added to the second (reference solution).
The absorbance of the solutions at 284 and 336 nm was determined using a HACH LANGE DR 5000 UV–visible spectrometer.
The HMF content was calculated by the equation (1):
HMF ðmg=kgÞ ¼ ðA284 Þ ðA336 Þ 149:7;
ð1Þ
where
A284: the absorbance at 284 nm
A336: the absorbance at 336 nm
149.7: a factor calculated by the molecular weight of HMF and
the mass of the sample.
2.3. Diastase activity
Diastase activity was determined using 10 g of honey weighted
a 50 mL beaker and 5 mL of acetate buffer were added, together
with 20 mL of water. When the sample was completely dissolved
3 mL of sodium chloride 0.5 M were added and the solution was
diluted to 50 mL with water. Moreover, a starch solution was standardized using an iodine solution. Both solutions were warmed at
40 °C. 5 mL of starch solution were added into 10 mL of honey
solution and start stop-watch. An aliquot was taken every 5 min
and was added to 10 mL of iodine solution. The absorbance was
recorded and a calibration curve was obtained. According to the
official AOAC method the number 300 was divided by the time
needed to reach the absorbance value of 0.235 and expressed as
DN or diastase number (AOAC 958.09-1977, 2010; Bodganov,
Martin, & Lüllmann, 1997).
2.4. Sugar content and conductivity measurement
The sugar content was based on the Lane Enyon method, and
the estimation of the accuracy was also calculated by the certified
reference material FAPAS T2830QC. The classical, official LaneEynon method for the determination of the total sugar content is
based on a copper reduction method before and after inversion
(AOAC, 1980). The results of the sugar content are only presented
for comparison reasons. The conductivity was measured in a 20%
(w/v) honey solution diluted with ultra-pure water.
2.5. Method validation
The difficulty in methods such as diastase activity is to perform
an accurate and precise analysis. For this reason the certified
reference material FAPAS T2830QC, Fera Science Ltd was used in
order to calculate the precision, the accuracy and the uncertainty
of the proposed methods. The instrumental limits of detection
(LOD (mg L1)) and of quantification (LOQ) were calculated. In
order to determine the composition of a honey sample correctly
the proposed LODs and LOQs should be less than one tenth and less
than one fifth, respectively, of the maximum level in Regulation
(EC) 2001/110/EC (Council Directive, 2001/110/EC).
Precision under repeatability and reproducibility conditions
were also estimated. As method’s precision performance criteria,
the HORRATr were used, meaning the observed relative standard
deviation (%RSDr) under repeatability conditions divided by the
RSDr value estimated from the Horwitz equation (Thompson,
2000) using the assumption r = 0.66R, as well as the HORRATR values, meaning the observed RSDR value under reproducibility
divided by the RSDR value calculated from the Horwitz equation.
The HORRATr and HORRATR values should be less than two to perform a precise analysis. Furthermore, the accuracy of measurements was also assessed through the recovery as calculated by
the multiple analysis of the certified reference material FAPAS
T2830QC. Recovery data are only acceptable when they are within
±20% of the certified value (European Commission, 2002).
Internal quality control charts (IQCs) were also constructed in
order to monitor whether results are reliable enough to be
released. The objective of IQCs is the elongation of method validation: continuously checking the accuracy of analytical data
obtained from day to day in the laboratory. The analytical system
is under control if no more than 5% of the measured values exceed
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I.N. Pasias et al. / Food Chemistry 229 (2017) 425–431
the warning limits and none of them the action or control limits
(Pasias, Papageorgiou, Thomaidis, & Proestos, 2012; Psoma,
Pasias, Rousis, Barkonikos, & Thomaidis, 2014; Raptopoulou,
Pasias, Thomaidis, & Proestos, 2014; Taverniers, De Loose, & Van
Bockstaele, 2004).
The uncertainty of the method was also calculated based on the
Eurachem/Citac Guidelines. For most purposes in analytical chemistry, an expanded uncertainty U should be used. The expanded
uncertainty provides an interval within which the value of the
analyte concentration is believed to lie within a higher level of confidence. U is obtained by multiplying uc (y), the combined standard
uncertainty, by a coverage factor k. The combined uncertainty uc
(y) was calculated from the summary squared of several independent parameters as (a) the mass uncertainty; (b) the stock standard
solutions; (c) the volume uncertainty; (d) the calibration
uncertainty; (e) the bias uncertainty; and (f) the random errors
uncertainty, following the rules of Eurachem/Citac Guidelines
(Eurachem, 2000).
2.6. Statistical analysis
Statistical analysis was performed with SPSS version 20.0 program. Different chemometric statistical analysis, such as principal
component analysis and cluster analysis were performed in order
to examine the correlation among the artificial feeding of honeybees with carbohydrate supplements and several chemical parameters of the honey. Whenever the content of any analyte was lower
than the LOD it was replaced by LOD/2.
3. Results and discussion
3.1. The results of method validation
For the determination of HMF content, quantification was performed using the certified reference material FAPAS T2830QC with
certified value 40.86 ± 5.04, in order to avoid the matrix interferences. Different masses of the certified reference material were
weighted and a calibration curve plotting the absorbance of the
sample against reference at 284 and 336 nm versus analyte content
in lg and typical linear correlation of R2 0.998 was obtained.
The methods LOD and LOQ were determined by the standard
deviation of the intercept of the calibration curve and were equal
to 2.4 and 7.2 mg/kg. The calculated LOD was lower than the
1/10 of the maximum permissible level of 40 mg/kg and the LOQ
was lower than the 1/5 of the maximum permissible as presented
in Regulation (EC) No 110/2001 and in Codex Alimentarius (Codex
Standard, 12-1981; Council Directive, 2001/110/EC).
Table 1
Chemical composition of different honey type samples.
Honey type
Blossom
Blossom
Honeydew
Blossom
Blossom
Blossom
Honeydew
Blossom
Blossom
Blossom
Blossom
Blossom
Blossom
Honeydew
Blossom
Blossom
Blossom
Blossom
Honeydew
Honeydew
Honeydew
Honeydew
Blossom
Blossom
Blossom
Honeydew
Honeydew
Blossom
Blossom
Honeydew
Honeydew
Blossom
Blossom
Blossom
Blossom
Honeydew
Blossom
Honeydew
Honeydew
Min-Max/Mean
Min-Max/Mean
*
Sample coded
as
Palynological
Characterization
B1*
Multifloral
B2
Multifloral
*
HD1
Abies
B3
Multifloral
B4
Citrus
B5
Strawberry
HD2
Abies
B6
Erica
B7
Multifloral
B8
Multifloral
B9
Multifloral
B10
Multifloral
B11
Multifloral
HD3*
Pine
B12*
Multifloral
B13
Multifloral
B14
Multifloral
B15
Multifloral
HD4
Abies
HD5
Abies
HD6
Abies
HD7*
Pine
B16
Cotton
B17
Cotton
*
B18
Erica
*
HD8
Pine
HD9
Pine
B19
Citrus
B20
Multifloral
HD10
Pine
HD11
Abies
B21
Multifloral
B22
Erica
B23
Multifloral
B24
Multifloral
HD12
Abies
B25
Multifloral
HD13
Abies
HD14
Abies
value for honeydew honey
value for blossom honey
Honey samples artificially fed.
HMF
(mg/kg)
Diastase activity
(DN)
Glycose + fructose content
(% w/w)
Sucrose content
(%w/w)
Conductivity
(mS/cm)
<2.4
<2.4
4.0
<2.4
26
<2.4
<2.4
7.1
22
51
18
<2.4
21
<2.4
10
6.0
6.5
<2.4
<2.4
<2.4
<2.4
<2.4
<2.4
16
<2.4
<2.4
3.9
2.5
6.3
<2.4
<2.4
<2.4
38
4.0
11
<2.4
<2.4
<2.4
<2.4
<2.4–4.0/2.4
<2.4–51/7.6
7.0
12
12
15
8.0
15
14
12
9.1
12
10
12
10
12
10
14
12
21
12
12
12
14
22
20
10
10
12
8.5
13
15
14
13
12
12
9.5
8.1
14
9.1
11
8.1–15.0/11.9
7.0–22.0/13.6
67
57
60
68
50
60
48
45
51
50
51
39
59
55
36
41
56
71
64
54
54
61
68
74
67
60
62
71
62
55
55
63
67
68
64
58
67
49
53
48–74/58
36–74/63
19
<0.5
15
1.2
1.4
<0.5
<0.5
<0.5
<0.5
<0.5
1.5
<0.5
2.0
4.1
5.2
2.2
4.1
0.7
1.2
0.7
0.5
9.0
1.0
<0.5
3.4
4.3
1.1
0.7
1.0
1.2
1.2
1.6
0.6
0.6
<0.5
<0.5
<0.5
0.6
<0.5
<0.5–15/2.9
<0.5–19/1.5
0.68
0.70
1.17
0.82
0.30
0.70
1.23
0.61
0.62
0.33
0.57
0.70
0.42
0.98
0.20
0.40
0.50
0.30
1.13
1.20
1.13
0.96
0.32
0.33
0.76
0.80
0.90
0.66
0.45
1.17
1.30
0.30
1.50
0.80
0.72
1.22
0.75
1.80
1.10
0.8–1.8/1.2
0.8–1.5/0.6
428
I.N. Pasias et al. / Food Chemistry 229 (2017) 425–431
Precision experiments were carried out and the relative standard
deviation (%RSD) values achieved from three different concentration
levels measured six times under repeatability conditions and six
times at two different days under reproducibility conditions, were
lower than 10% for all different concentration levels.
The HORRATr and HORRATR values achieved from these different concentration levels, ranged from 0.24 to 0.36. These values
were lower than the crucial value of two, and the method is ‘fitfor-purpose’.
For accuracy estimation the certified reference material FAPAS
T2830QC with certified value 40.86 ± 5.04 was analyzed 6 times
in two different days by two different analysts (n = 12) and the
recovery was found equal to 101.7 ± 4.4. The recovery data are
within ±12% of the target value, as provided by the certification
of the reference material and for this reason the method was again
considered as ‘‘fit for purpose”.
The uncertainty of the method was also calculated based on the
Eurachem/Citac Guidelines. In practice, the uncertainty of the
results in this study arose from many possible sources, including
matrix effects and interferences, environmental conditions, uncertainties of masses and volumetric equipment, reference values,
approximations and assumptions incorporated in the measurement method and procedure, and random variation. The combined
uncertainty uc (y) was calculated from the summary squared of
several independent parameters such as (a) the mass uncertainty;
(b) the volume uncertainty; (c) the calibration uncertainty; (d) the
bias uncertainty, as estimated by the recovery tests and through
the comparison of the calculated recoveries and the theoretical
ones provided by the certification of the reference material, and
(e) the precision uncertainty, as estimated by the % RSDR values
for the three different concentration levels under reproducibility
conditions. The choice of the factor k is based on the level of confidence desired. For an approximate level of confidence of 95%, k is
2. The calculated expanded uncertainties were found equal to 21.0,
11.3 and 9.78% of the content of HMF in mg/kg for the LOQ, the
centroid of the calibration curve, and the maximum permissible
value, respectively.
The validation of the diastase activity method is of vast importance, since the methods reported in the literature are not fully validated and there is a great variance among the determined values
provided by different laboratories even if they use the same official
method. In this work, the certified reference material FAPAS
T2830QC with a certified reference value of 9.76 ± 3.34 DN (diastase number) was used in order to estimate the accuracy and the
precision of the method. The calibration curve was achieved by
plotting the absorbance of the KI after the addition of a known
amount of properly prepared honey sample solution in different
periods of time versus the time of the reaction of diastase with
starch and typical linear correlation of R2 0.99 was obtained.
The LOD and the LOQ of the method was calculated by the standard
deviation of ten blank determinations and found equal to 2.6 and
7.2 DN, respectively. Precision experiments were carried out and
the relative standard deviation (%RSD) values achieved from the
multiple analysis of the certified reference material (n = 6) under
repeatability and reproducibility conditions, were lower than
12%. For accuracy estimation the certified reference material FAPAS
T2830QC with certified value 9.76 ± 3.34 DN was analyzed 6 times
in two different days by two different analysts (n = 12) and the
recovery was found equal to 90.0 ± 9.3. The recovery data are
within ±34% of the target value, as provided by the certification
of the reference material and for this reason the method was again
considered as ‘‘fit for purpose”. The combined uncertainty uc (y)
was also calculated as for the HMF method, since the same parameters contributed to the uncertainty. The uncertainty of the
method was found equal to 23.9% of the diastase activity calculated
in DN units.
3.2. Determination of HMF content and diastase activity in honey
samples
The developed and fully validated method was applied for
determination of HMF content and diastase activity in honey
samples. Thirty nine different honey samples (25 flower type
honey and 14 honeydew honey samples) were collected from local
Fig. 1. Principal component analysis plot showing the factor loadings of different honey samples (Varimax normalized).
I.N. Pasias et al. / Food Chemistry 229 (2017) 425–431
experienced beekeepers in Lamia, Greece (from 2015 to 2016).
Samples were stored at room temperature until analysis. All honey
samples were characterized on the basis of melissopalynological
characterization. The results are provided in Table 1. Other physicochemical parameters, such as electrical conductivity, and sugar
content are also given for comparison reasons. The results showed
that the HMF content is lower in honeydew honeys samples than
in blossom honey samples. The main reason of this observation
is that blossom honey is often heated in order to prevent the crystallization of honey and the inhibition of microbial growth. On the
contrary, honeydew honey has low content of sugars and the crystallization is rarely observed. However, thermal treatment has also
negative effects on the diastase activity. On the other hand, diastase activity was higher in blossom honey samples, as expected.
In general, the contents of HMF in Greek type honeys were much
429
lower than other found in the literature, such as Tualang honey,
Gelam honey, Manuka honey, Eucaliptus type honey, Rubus type
honey, Echium type honey, Leotondon type honey and other,
whereas diastase activity was similar (Gomes, Dias, Moreira,
Rodrigues, & Estevinho, 2010; Khalil, Sulaiman, & Gan, 2010;
Rizelio et al., 2012).
A full kinetic study of HMF formation and diastase activity has
been recently presented by Khan, Nanda, Bhat, and Khan (2015)
and Tosi, Martinet, Ortega, Lucero, and Re (2008). On both works
it was proved that the increase of the temperature has an effect
on the content of HMF and diastase activity, especially for temperature over 60 °C. However, there is an inconvenience about the
enhancement of diastase activity during the isothermal heating
steps. In Khan et al. work (2015) the diastase activity was further
decreased with the time of isothermal treatment, whereas in Tosi
Fig. 2. Dendrogram of the cluster analysis of the samples using Ward’s method/Euclidean distances.
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I.N. Pasias et al. / Food Chemistry 229 (2017) 425–431
Fig. 3. Dendrogram of the cluster analysis of the chemical composition of different honey type samples using Ward’s method/Euclidean distances, where diastase explains
the diastase activity, SUC the sucrose content, HMF the HMF content and GLY +FRU the sum of fructose and glucose content.
et al. work (2008) diastase activity remained constant. In general,
HMF and diastase activity were used as freshness indicators and
are considered among the most important parameters on the prediction of the quality of honey samples (Thrasyvoulou, 1986).
However, as Thrasyvoulou (1986) proved, they cannot be considered as criteria for detecting overheated honeys. In general, using
HMF and diastase as criteria to assess the quality of the product,
some honey samples could be regarded as industrial honey
although they are fresh, unheated and naturally pure. For example
citrus honey has in general low diastase activity (Table 1) and for
this reason the European Commission has set a different limit for
this type of honey (Bonvehi & Coll, 1995). In general, cotton type
honey seems to have high diastase content, whereas citrus and
thyme type honey seem to have the lower (Table 1). The differences in diastase activity in honeys may vary depending on the
age of the bees, the nectar collection period, the physiological period of the colony, the large quantity of nectar flow and its sugar
content because a high flow of concentrated nectar leads to a lower
enzyme content and pollen consumption (Khan et al., 2015; Silva
et al., 2016). Guler et al. (2014) proved that low diastase activity
occurs when honeybees are fed artificially. The honeybees were
fed with a commercial glucose and the authors found that bees
may not be fed glucose in excessive amounts, as this may have promoted an enzyme deficiency (especially diastase) which is used to
convert glucose and fructose. They also proposed that in honeys
with low diastase activity, it is essential that they contain a maximum of 15 mg/kg of HMF, in order to prove that honey has not
undergone heat treatment or prolonged storage (Guler et al.,
2014; Silva et al., 2016). The HMF content in the current study ranged from lower than the detection limit to 51 mg/kg. Capuano and
Fogliano (2011) and Yücel and Sultanoglu (2013) concluded that
high HMF content in honeys may also be an indication of falsification by adding invert syrup, because HMF can be produced by heating sugars in the presence of an acid to the inversion of sucrose
(Capuano & Fogliano, 2011; Silva et al., 2016; Yücel & Sultanoglu,
2013).
In this work, the correlation among diastase activity, HMF content, and sugar content was investigated. The multivariate technique of principal component analysis was used to identify
possible sources and grouping of different honey types. Principal
components factor analysis identified 2 principal components with
eigen values >1 when sugar content, HMF content and diastase
activity were selected as variables. These variables were the most
significant factors in the classification, according to their loading
values of the stated components. The PCA loadings extracted by
varimax normalized rotation are presented in Fig. 1. The results
showed that 95% of variance was explained in the first two principal components of the transformed data. Two main groups were
extracted with some outlier samples (Fig. 1). Samples coded as
B2, B7, B8, B9, B11, B22 were highly correlated with component
1 (>0.7), and all other samples were highly correlated with component 2. B2, B7, B8, B9, B11, B22 samples had high HMF content and
for this reason PC1 and PC2 must be highly correlated with freshness indicator. PC2 indicates fresh samples and PC2 indicated nonfresh samples. These results are in good accordance with the conclusion provided by Thrasyvoulou (1986), who proved that HMF
content and diastase activity are freshness indicators (see Fig. 2).
Furthermore, a freshness classification was attempted, tracking
back the HMF content and diastase activity of the honey samples.
Samples classification was succeeded with the help of cluster
analysis (CA). Samples codes as B4, B7, B8, B9, B17, B22 were easily
differentiated from all other samples. Thus, two main clusters were
identified. The first one corresponded to fresh samples (low HMF
content), while the second contained non-fresh samples. The
results are similar with those obtained from principal component
chemometric analysis. A classification was also attempted, tracking
back the content of sugars, HMF and diastase activity. Fig. 3 shows
the dendrogram obtained from hierarchical CA for all different
I.N. Pasias et al. / Food Chemistry 229 (2017) 425–431
cases investigated. Diastase activity, sucrose content and HMF content were easily identified as one cluster. Thus, these parameters
may be used for indication of the artificial feeding of the honeybee
with carbohydrate supplements. However, samples which were
identified to be fed artificially, such as B1, HD1, HD3, B12, HD7,
HD8, and B18, did not manage to be classified neither in a common
component not in a common cluster. Summarizing, it seems more
possible that HMF content, diastase activity and sucrose content
can be used as freshness indicators than as indicators for
adulteration.
4. Conclusion
The current work described a fully validated approach for the
determination of diastase activity and HMF content in honeys.
All crucial parameters to obtain accurate and precise results were
investigated. The uncertainty of both methods was calculated
and the results proved that the repeatability and the recovery are
the most important factors for the estimation of an accurate result.
The methods were considered as fit for purpose in terms of precision, accuracy, and ability to detect values lower than the regulation limits. Chemometric analysis was performed in order to
examine the possibility of the artificial feeding and the freshness
of the honey samples and the results proved that HMF and diastase
activity are freshness indicators, whereas HMF, sucrose and diastase activity can be used for indication of the artificial feeding of
the honeybees.
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