Research Article
New HPLC-chemometric approaches to theanalysis of isoflavones in Trifoliumlucanicum Gasp.
New HPLC-chemometric approaches were proposed for the simultaneous chromato-
graphic quantification of daidzein, genistein, formononetin, and biochanin A in the
samples consisting of the aerial parts of Trifolium lucanicum Gasp. (Leguminosae). Partial
least squares and principal component regression algorithms were applied to the multiple
chromatographic data set obtained by measuring at 240, 248, 256, and 264 nm to
construct HPLC-partial least squares and HPLC-principal component regression calibra-
tions. Chromatographic separation was carried out by using a mobile phase containing
methanol, acetate buffer (pH 5 4.75) and acetonitrile (21:58:21, v/v/v) on the reversed
phase column, SupelcosilTM LC-18 (15 cm� 4.6 mm id). In addition, conventional HPLC
based on the detection at a single wavelength was used for the determination of each
compound in the extracts of T. lucanicum. The validity and applicability of the proposed
HPLC-chemometric and conventional HPLC methods were performed by analyzing
various synthetic plant samples. A good agreement was observed in the application of the
proposed HPLC-chemometric tools to the synthetic and extracted samples of T. lucanicum.
Keywords: HPLC-chemometric methods / Isoflavones / Leguminosae / Quanti-tative analysis / Trifolium lucanicumDOI 10.1002/jssc.201000273
1 Introduction
Trifolium lucanicum Gasp. (Leguminosae) is an annual plant
with flowering calyx with subulate, hirsute teeth, and corolla
somewhat longer than the calyx, leaflets thickened, with
prominent lateral nerves arcuate-recurved at the margin.
The natural habitat of T. lucanicum is dry places and rocky
ground and its distribution is Northwest, West and South
Anatolia. Besides, it is also widely distributed in France,
Italy, and Balkans. The mentioned plant is a Mediterranean
element [1].
Nowadays, red clover (T. pratense L.) has a very interest
importance for many human health benefits, particularly in
the area of women’s health. However, red clover is the main
source of phytoestrogen isoflavones. Phytoestrogens, poly-
phenolic non-steroidal plant compounds, may have protec-
tive effects on estrogen-related conditions such as
menopausal symptoms and estrogen-related diseases, such
as prostate, breast cancers, osteoporosis, and cardiovascular
diseases. In red clover, the fundamental isoflavones are
formononetin (FNT) and biochanin A (BC), with low
concentration levels of daidzein (DZ) and genistein (GT) [2].
Genus Trifolium L. is represented by 128 taxons, in
which 11 are endemic in flora of Turkey [1, 3–6]. Up to date,
not any analytical study has been performed on Trifoliumspecies growing in Turkey. A series of isoflavones consisting
of DZ, GT, FNT and BC were subjected to our investigation.
According to the substituents in the main isoflavone struc-
ture, the molecular structures of DZ, GT, FNT and BC are
shown in Fig. 1. In the previous studies, some potential
investigations on the analysis of isoflavones in plant mate-
rials and biological samples were reported by chromato-
graphic methods [7–9].
Nowadays, chemometric methods, particularly partial
least squares (PLS) and principal component regression
(PCR), have been used as chemometric powerful tools to
quantify two or more active substances in their mixtures
using spectrophotometric data. However, some application
of the chemometric calibration techniques in the chroma-
tographic analysis of complex samples were reported
[10–12].
The first main aim of this study is to develop and apply
new HPLC-chemometric methods for the simultaneous
quantification of DZ, GT, FNT, and BC compounds in the
extracted samples of T. lucanicum. The second aim is to
Nurgun Kuc- ukboyacı1
Ays-egul Guvenc-2
Erdal Dinc-3
Nezaket Adıguzel4
Barıs- Bani4
1Department of Pharmacognosy,Faculty of Pharmacy, GaziUniversity, Ankara, Turkey
2Department of PharmaceuticalBotany, Faculty of Pharmacy,Ankara University, Ankara,Turkey
3Department of AnalyticalChemistry, Faculty of Pharmacy,Ankara University, Ankara,Turkey
4Department of Biology, Facultyof Arts and Science, GaziUniversity, Ankara, Turkey
Received April 21, 2010Revised June 30, 2010Accepted July 1, 2010
Abbreviations: BC, biochanin A; DAD, diode array detector;DZ, daidzein; FNT, formononetin; GT, genistein; IS, internalstandard; PCR, principal component regression; PLS, partialleast squares
Correspondence: Professor Nurgun Kuc- ukboyacı, Department ofPharmacognosy, Faculty of Pharmacy, Gazi University, 06330Etiler, Ankara, TurkeyE-mail: [email protected]: 190-312-2235018
& 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim www.jss-journal.com
J. Sep. Sci. 2010, 33, 2558–25672558
compare the results obtained by applying HPLC-chemo-
metric approaches with those obtained by conventional
single-wavelength HPLC. After the optimization of the
chromatographic settings and conditions, a mobile phase
consisting of methanol, acetate buffer (pH 5 4.75) and
acetonitrile (21:58:21, v/v/v) and the flow rate 1.4 mL/min
were found to be suitable for an adequate chromatographic
separation of four compounds, DZ, GT, FNT, and BC, in the
presence of the internal standard (IS), spironolactone, in the
above-mentioned plant samples. It was observed that a good
agreement was reported for the chromatographic results
obtained by all of the proposed conventional and chemo-
metric HPLC approaches.
2 Theoretical aspect
This study contains the application of the PCR and PLS
algorithms to the multiple chromatographic data based on
the ratio of analyte/IS. For example, which wavelength point
or points are suitable for the multicomponent analysis of
four analytes having different maximum absorbance values
at the different wavelength points? As it is known, the
selection of the optimal wavelength is one of the chromato-
graphic analysis problems. However, chromatographic
multiple calibration (PLS and PCR) is appropriate for the
elimination of the above problem due to the use of
multiwavelength chromatographic measurements. Taking
into account maximum absorbances of analytes, single-
wavelength detection give main sensitivity problem for
the simultaneous quantification of four compounds in the
same quaternary mixture. The HPLC-chemometric
calibrations (HPLC-PCR and HPLC-PLS) based on the
multiple wavelength set instead of the single wavelength
detection provide desirable precise and accurate results for
the simultaneous chromatographic analysis. The brief
information of the HPLC-PCR and HPLC-PLS is explained
below.
2.1 HPLC-PCR method
The multiple chromatographic data (R 5 response)
consisting of the ratio of the analyte’s peak area and
analyte’s concentration set (C) were processed by mean-
centering as Ro and Co, respectively, and the covariance
dispersion matrix of the centered matrix Ro was computed.
The normalized eigenvalues and their eigenvectors were
obtained from the square covariance matrix of Ro. The
number of the optimal principal components (eigenvectors
(P)) corresponding to the highest values of the eigenvalues
was selected.
In the application of PCR algorithm, the coefficient
b defined as b 5 P� q is calculated, where P is the vectors of
eigenvectors and q is the C-loadings given by q 5
D�TT�Ro. TT indicates the transpose of the score matrix Tand D is a diagonal matrix corresponding to the inverse of
the selected eigenvalues. The analytes in samples were
predicted by using the formula, C 5 b�Rsamp. In this
equation, C is unknown concentration, b denotes the vectors
of the coefficients and Rsamp is chromatographic response of
multiple wavelength set.
HPLC-PCR calibration and data treatments were
performed by using PLS toolbox 3.0 in Matlab 7.0 software
and Microsoft Excel, respectively.
2.2 HPLC-PLS method
The PLS calibration based on the orthogonalized PLS
algorithm initiated by Wold [13] and extensively discussed
by Martens and Naes [14] consists of the simultaneous
decompositions or operations of both independent and
dependent variables. In the application of the PLS algorithm
to the multiple chromatograms, the HPLC-PLS calibration
is constructed by the decomposition of both concentration
data and ratio peak area data into latent variables, R 5
T�PT1E and C 5 U�QT1F. Here R is chromatographic
response (matrix), C is concentration set (vector). T and Uare scores, P and Q are loadings. The vector, b is calculated
by the expression b 5 W� (PT�W)�1�Q, where Wdenotes a weight matrix.
As in HPLC-PCR method, HPLC-PLS calibration and
data treatments were performed by using PLS toolbox 3.0 in
Matlab 7.0 software and Microsoft Excel, respectively.
3 Materials and methods
3.1 Chemicals and reagents
In our study, reagents (acetonitrile and methanol) used in
the HPLC analysis were of chromatographic grade (Merck,
Darmstadt, Germany). In the extraction procedure, metha-
nol and TFA were of analytical grade (Merck). Isoflavone
standards; DZ, GT, FNT, and BC were purchased from
Fluka (Buchs, Switzerland). DMSO (Merck) was used by
No Isoflavones Substituents
R1 R2
1 Daidzein H H 2 Formononetin H CH3
3 Genistein OH H 4 Biochanin A OH CH3
OHO
R1OR2
O
Figure 1. Molecular structures of isoflavones in the extract ofT. lucanicum.
J. Sep. Sci. 2010, 33, 2558–2567 Liquid Chromatography 2559
& 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim www.jss-journal.com
dissolving the isoflavone standards. Glacial acetic acid and
NaOH (Merck) were used to prepare the acetate buffer
solution (pH 5 4.75).
3.2 Plant material and sample preparation
The aerial parts of T. lucanicum Gasp. (Leguminosae) were
collected at the flowering stage from Van, C- atak, Dalbastı
village, surroundings of Seytanderesi in May 2003 in
Turkey. Plant material was provided from open oak forest
at the altitude of 1400 meters. Plant material was identified
by one of the authors (Barıs- Bani). Authenticated voucher
specimen (coded as B.B. 1603) was deposited in the
Herbarium of GAZI, Ankara, Turkey.
Two-hundred milligrams powdered materials were
extracted by using 20 mL of 80% MeOH (acidified to pH 3
with TFA) for 15 min under reflux at 851C. This procedure
was repeated two times as a sequence treatment. After
filtering the collected extract samples, 1 mL of filtrate was
diluted with 9 mL water and loaded on to a Sep-Pak C18
cartridge (Waters). Isoflavones were retained on the Sep-Pak
C18 cartridge which was then washed with 10 mL of water
twice and eluted with 80% methanol. This procedure was
repeated five times. Four isoflavones, DZ, GT, FNT, and BC
in the final extract samples were determined by using the
proposed HPLC-chemometric and conventional HPLC
methods.
3.3 Chromatographic instrumentation and software
Chromatographic analysis was performed by using an
Agilent 1100 series HPLC system (Agilent Technologies,
California, USA), a thermostatted autosampler, a thermo-
statted column compartment, and a multi wavelength diode
array detector (DAD). HP Chem Station for LC (Rev. A0.01
[403]) software (Hewlett–Packard) was used for the HPLC
data processing. Chromatographic separation was carried
out by using the HPLC column, a SupelcosilTM LC-18
(4.6� 150 mm, 5 mm).
Multiple HPLC data consisting of the ratio of analyte/IS
were processed by PLS toolbox in Madlab 7.0 software to
obtain HPLC-PCR and HPLC-PLS calibration. For the
conventional single HPLC, linear regression analysis and
statistical calculations were achieved by Microsoft Excel
software.
3.4 Chromatographic conditions and settings
Column temperature was 301C. Flow rate was maintained at
1.7 mL/min and the injection volume was 10 mL. The mobile
phase consisting of methanol, acetate buffer (pH 5 4.75),
and acetonitrile (21:58:21, v/v/v) was prepared daily, filtered
through a 0.45 mm membrane filter and degassed before
use. Tab
le1.
Cali
bra
tio
nse
tan
dco
rresp
on
din
gra
tio
peak
are
as
for
the
HP
LC
-ch
em
om
etr
icca
lib
rati
on
mo
dels
mg/m
LR
atio
ofpe
akar
eas
(DZ/
IS)
Rat
ioof
peak
area
s(G
T/IS
)R
atio
ofpe
akar
eas
(FN
T/IS
)R
atio
ofpe
akar
eas
(BC
/IS
)
Set
no.
DZ
GT
FNT
BC
IS24
024
825
626
424
024
825
626
424
024
825
626
424
024
825
626
4
12.
52.
54.
04.
025
.00.
2093
0.25
040.
3529
0.72
500.
1074
0.18
130.
3933
0.94
670.
3153
0.38
030.
5432
1.11
660.
1384
0.24
420.
5506
1.35
91
25.
05.
08.
08.
025
.00.
3773
0.46
510.
6593
1.37
050.
2105
0.35
080.
7671
1.87
370.
6220
0.76
731.
1018
2.29
370.
3041
0.50
981.
1277
2.80
62
37.
57.
512
.012
.025
.00.
5800
0.71
601.
0234
2.14
340.
3254
0.53
891.
1861
2.91
210.
8998
1.11
571.
6177
3.38
970.
4652
0.76
671.
6966
4.24
59
410
.010
.016
.016
.025
.00.
7616
0.97
911.
4005
2.95
930.
4160
0.72
871.
6030
3.97
491.
1595
1.51
582.
2024
4.65
670.
6715
1.06
022.
3442
5.91
37
512
.512
.520
.020
.025
.01.
0299
1.23
701.
7689
3.76
310.
5662
0.92
182.
0302
5.06
251.
6791
2.03
392.
9503
6.27
880.
8407
1.36
693.
0193
7.66
10
615
.015
.024
.024
.025
.01.
2187
1.47
712.
1158
4.54
140.
6552
1.07
132.
3598
5.93
701.
9193
2.34
173.
4020
7.30
400.
9902
1.59
383.
5317
9.04
46
J. Sep. Sci. 2010, 33, 2558–25672560 N. Kuc- ukboyacı et al.
& 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim www.jss-journal.com
3.5 Standard solutions
Stock solutions of 5 mg/20 mL of DZ, GT, FNT, BC,
and IS (spironolactone) were prepared in a mixture of
DMSO and methanol (1:19, v/v). A standard concentration
set of the mixture solutions containing four compounds in
the range between 2.5–15 mg/mL of DZ and GT,
and 4.0–24 mg/mL of FNT and BC using 25 mg/mL
of IS were prepared from the above stock solutions. As a
validation set, nine solution samples consisting of the
quaternary synthetic herbal mixtures were prepared by
using the same stock solutions. Methanol was used, as a
solvent, for the preparation of both concentration set and
validation set.
mAU
0
10
40
-10
20
30
-20
-30
-40
Calibration set no.1
DAD1 A, Sig=240 nmDAD1 B, Sig=248 nm DAD1 C, Sig=256 nmDAD1 D, Sig=264 nm
DZ
Time (min)0-50
AB
CD
mAU
0
10
40
-10
20
30
50
-20
-30
-40
Calibration set no.2
DAD1 A, Sig=240 nmDAD1 B, Sig=248 nm DAD1 C, Sig=256 nmDAD1 D, Sig=264 nmDZ
Time (min)0
AB
CD
Time (min)0
mAU
0
10
40
60
-10
20
30
50
70
-20
-30-40
Calibration set no.3
DAD1 A, Sig=240 nmDAD1 B, Sig=248 nm DAD1 C, Sig=256 nmDAD1 D, Sig=264 nmGTDZ
AB
CD
Calibration set no.4
DAD1 A, Sig=240 nmDAD1 B, Sig=248 nm DAD1 C, Sig=256 nmDAD1 D, Sig=264 nm
mAU
0
20
40
60
80
-40
-20
Time (min)5 10 15 20 2505 10 15 20 25
5 10 15 20 250 5 10 15 20 25
DZ
AB
CD
mAU
0
20
40
60
80
100
-40
-20
Calibration set no.5
Time (min)5 10 15 20 25
DAD1 A, Sig=240 nmDAD1 B, Sig=248 nm DAD1 C, Sig=256 nmDAD1 D, Sig=264 nm
DZ GT
A
B
CD
0 Time (min)5 10 15 20 25
mAU
0
20
40
60
80
100
-20 DAD1 A, Sig=240 nmDAD1 B, Sig=248 nm DAD1 C, Sig=256 nmDAD1 D, Sig=264 nmA
B
CD
Calibration set no.6
SICBTNFTGZD
120
0
Time (min)5 10 15 20 25
mAU
0
20
40
60
80
100
-20 DAD1 A, Sig=240 nmDAD1 B, Sig=248 nm DAD1 C, Sig=256 nmDAD1 D, Sig=264 nm
A
B
C
D
Calibration set no.6
2.89
6
4.60
5
7.69
3
15.6
20
17.1
74
SICBTNFTGZD
120
0
BC IS
BC IS
BC IS
FNT
FNT
GT FNT
BC ISGT FNT
BC ISGT FNT
Figure 2. Multiple chromato-grams of DZ (2.5, 5.0, 7.5,10.0, 12.5, and 15 mg/mL) andGT (2.5, 5.0, 7.5, 10.0, 12.5, and15 mg/mL), FNT (4.0, 8.0, 12.0,16.0, 20.0, and 24 mg/mL), BC(4.0, 8.0, 12.0, 16.0, 20.0, and24 mg/mL) in the presence ofthe constant amount of IS(25 mg/mL) in the calibrationset 1–6. The calibration set 6shows the multiple chromato-grams of DZ (15 mg/mL), GT(15 mg/mL), FNT (24 mg/mL), BC(24 mg/mL), and IS (25 mg/mL) atthe multiple wavelength set,240 nm (A), 248 nm (B),256 nm (C), and 264 nm (D).
J. Sep. Sci. 2010, 33, 2558–2567 Liquid Chromatography 2561
& 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim www.jss-journal.com
4 Results and discussion
4.1 HPLC-chemometric method development
The main problem of the chromatographic analysis of
complex mixtures is the optimization of the chromato-
graphic settings and conditions to obtain separation or to
reach the best recovery results. For this aim, in our case,
several mobile-phase systems were tested to find appropriate
chromatographic separation of DZ, GT, FNT, and BC
together with IS. The mobile phase consisting of methanol,
acetate buffer (pH 5 4.75) and acetonitrile (21:58:21, v/v/v)
at the flow rate 1.4 mL/min on the reversed phase column,
SupelcosilTM LC-18 (15 cm� 4.6 mm id) were found to be
suitable for the chromatographic separation of the target
isoflavones, DZ, GT, FNT, and BC with IS in the extract of
the aerial parts of T. lucanicum. In the chromatographic
studies, another chromatographic problem is the finding of
an optimal detection wavelength because multiple
compounds in a given sample have the different maximum
absorbances at different wavelength points. In shortly, the
use of the single wavelength detection may not give better
determination results due to bad selection of the working
wavelength in some cases. This drawback can be eliminated
by HPLC-chemometric calibrations using the multiple
wavelengths set corresponding to the maximum absorbance
values of the analytes in a large region of wavelength.
In our study, HPLC-PCR and HPLC-PLS based on the
multiple chromatograms at the wavelength set, 240, 248,
256, and 264 nm were applied to the simultaneous quanti-
fication of DZ, GT, FNT, and BC in our plant samples. For a
comparison of the results obtained by HPLC-PCR and
HPLC-PLS methods, conventional HPLC method based on
single wavelength detection was used for the same problem.
4.2 HPLC-PCR application
The brief information related to PCR algorithm was given in
Section 2.1. In our application, PCR algorithm was applied
to the multiple chromatograms of the calibration set
containing isoflavones between 2.5–15 mg/mL for DZ and
GT and 4.0–24 mg/mL for FNT and BC in the presence of
the constant amount of IS (25 mg/mL) prepared by
dissolving 5 mg of each compound in 20 mL in the
solvent system consisting of DMSO and methanol (1:19,
v/v). A calibration set consisting of six mixture samples
including the related compounds and IS is summarized in
Table 1.
The multiple chromatograms of the calibration set
corresponding to Table 1 were recorded at four-wavelength
set (240, 248, 256, and 264 nm) by using DAD system under
the above-optimized chromatographic conditions. The
multiple chromatograms of the calibration set containing
four compounds with IS are shown in Fig. 2. As shown in
Fig. 2, the retention times of DZ, GT, FNT, BC, and IS were
observed as 2.896, 4.605, 7.693, 15.620, and 17.174 min,
respectively. We concluded that this chromatographic
Table 2. Linear regression analysis and its statistical results for the conventional HPLC analysis
l ma) Nb) Rc) SE(m)d) SE(n)e) SE(r)f) LODg) LOQh)
DZ 240 0.0809 �0.0198 0.9990 1.35� 10�3 1.27� 10�3 1.43� 10�2 0.14 0.47
248 0.0966 �0.0032 0.9992 1.46� 10�3 1.37� 10�3 1.54� 10�2 0.13 0.43
256 0.1359 0.0089 0.9982 3.06� 10�3 2.88� 10�3 3.24� 10�2 0.19 0.64
264 0.2789 0.0870 0.9946 1.10� 10�2 1.03� 10�2 5.56� 10�2 0.33 1.11
GT 240 0.0447 �0.0084 0.9992 9.20� 10�4 8.96� 10�4 9.63� 10�3 0.18 0.60
248 0.0726 �0.0031 0.9994 1.21� 10�3 1.18� 10�3 1.27� 10�2 0.15 0.49
256 0.1604 �0.0140 0.9994 2.72� 10�3 2.64� 10�3 2.84� 10�2 0.15 0.49
264 0.4066 �0.1070 0.9996 6.03� 10�3 6.99� 10�3 6.30� 10�2 0.15 0.52
FNT 240 0.0818 �0.0460 0.994VN4 4.35� 10�3 6.78� 10�3 7.29� 10�2 0.75 2.49
248 0.1000 �0.0416 0.9982 3.01� 10�3 4.70� 10�3 5.04� 10�2 0.42 1.41
256 0.1459 �0.0729 0.9983 4.23� 10�3 6.58� 10�3 7.07� 10�2 0.41 1.35
264 0.3154 �0.2427 0.9982 9.48� 10�3 1.48� 10�2 1.59� 10�1 0.42 1.40
BC 240 0.0434 �0.0392 0.9992 8.74� 10�4 1.36� 10�3 1.46� 10�2 0.28 0.94
248 0.0687 �0.0377 0.9994 1.23� 10�3 1.91� 10�3 2.06� 10�2 0.25 0.84
256 0.1516 �0.0777 0.9994 2.61� 10�3 4.06� 10�3 4.37� 10�2 0.24 0.80
264 0.3904 �0.2942 0.9994 6.94� 10�3 1.08� 10�2 1.16� 10�1 0.25 0.83
a) m, slope of regression equation.
b) n, intercept of regression equation.
c) r, correlation coefficient.
d) SE(m), standard error of slope.
e) SE(n), standard error of intercept.
f) SE(r), standard error of correlation coefficient.
g) LOD (mg/mL)
h) LOQ (mg/mL).
J. Sep. Sci. 2010, 33, 2558–25672562 N. Kuc- ukboyacı et al.
& 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim www.jss-journal.com
Tab
le3.
Reco
very
resu
lts
of
the
syn
theti
cp
lan
tsa
mp
les
by
the
pro
po
sed
con
ven
tio
nal
HP
LC
meth
od
Qua
tern
ary
mix
ture
(mg/
mL)
Foun
d(m
g/m
L)
DZ
GT
FNT
BC
No.
DZ
GT
FNT
BC
240
248
256
264
240
248
256
264
240
248
256
264
240
248
256
264
12.
5012
.50
4.00
20.0
02.
502.
442.
402.
2812
.74
12.7
412
.70
12.9
34.
314.
184.
254.
5321
.12
21.5
421
.58
21.9
4
27.
507.
5012
.00
12.0
07.
457.
307.
287.
287.
427.
347.
897.
2811
.87
11.6
711
.60
11.5
611
.35
11.6
211
.57
11.5
3
312
.50
2.50
20.0
04.
0012
.20
12.2
312
.10
11.9
72.
592.
312.
482.
3519
.72
19.3
336
.85
14.7
04.
023.
783.
773.
89
410
.00
2.50
8.00
12.0
09.
819.
9610
.00
10.0
42.
332.
442.
652.
608.
007.
867.
897.
9811
.29
11.5
011
.56
11.6
0
510
.00
12.5
08.
0024
.00
10.1
910
.29
10.5
110
.39
12.8
412
.88
13.3
013
.17
8.23
7.94
8.03
8.33
23.6
324
.37
24.6
125
.08
68.
008.
004.
0016
.00
8.02
7.83
8.21
8.08
7.81
7.76
9.19
7.84
4.13
4.03
4.10
4.32
15.6
215
.67
15.6
415
.74
78.
0010
.00
24.0
016
.00
8.29
8.30
8.18
8.30
10.1
010
.26
10.5
010
.42
23.9
423
.80
23.8
423
.92
15.5
915
.71
15.7
915
.93
815
.00
6.00
16.0
08.
0015
.64
15.8
815
.05
14.9
46.
276.
026.
125.
8915
.85
15.5
915
.44
15.0
97.
627.
547.
557.
57
95.
0015
.00
20.0
012
.00
4.71
5.11
5.09
4.91
14.2
315
.17
15.4
414
.87
18.4
919
.67
19.5
119
.36
11.7
211
.52
11.6
011
.68
Rec
over
y(%
)
DZ
GT
FNT
BC
No.
240
248
256
264
240
248
256
264
240
248
256
264
240
248
256
264
110
0.18
97.5
495
.83
91.3
910
1.92
101.
9010
1.63
103.
4310
7.78
104.
5210
6.35
113.
3110
5.58
107.
7010
7.88
109.
71
299
.29
97.3
897
.05
97.0
098
.97
97.9
210
5.20
97.0
698
.92
97.2
496
.67
96.3
394
.60
96.8
196
.44
96.1
2
397
.61
97.8
696
.82
95.7
710
3.48
92.2
099
.28
93.9
498
.58
96.6
718
4.26
73.5
010
0.44
94.5
994
.34
97.3
4
498
.09
99.5
510
0.03
100.
4493
.12
97.4
910
5.94
103.
9999
.94
98.3
098
.62
99.8
194
.05
95.8
696
.31
96.6
3
510
1.95
102.
9410
5.13
103.
8610
2.73
103.
0810
6.38
105.
3410
2.86
99.2
910
0.38
104.
1798
.48
101.
5310
2.54
104.
50
610
0.28
97.8
310
2.63
101.
0497
.59
96.9
811
4.83
97.9
810
3.24
100.
6910
2.39
107.
9697
.60
97.9
497
.72
98.3
7
710
3.57
103.
7010
2.20
103.
7410
0.95
102.
6510
4.96
104.
2199
.75
99.1
599
.34
99.6
697
.44
98.1
998
.67
99.5
8
810
4.26
105.
8810
0.32
99.6
310
4.54
100.
3410
2.04
98.2
399
.05
97.4
796
.50
94.3
295
.23
94.2
694
.38
94.6
0
994
.11
102.
1910
1.84
98.2
594
.87
101.
1210
2.93
99.1
592
.47
98.3
397
.57
96.7
997
.70
96.0
096
.67
97.3
5
Mea
n99
.93
100.
5410
0.20
99.0
199
.80
99.3
010
4.80
100.
3710
0.29
99.0
710
9.12
98.4
397
.90
98.1
098
.33
99.3
6
SD
3.15
3.19
3.11
3.96
3.95
3.49
4.42
3.97
4.17
2.38
28.3
511
.15
3.52
4.21
4.35
4.79
RS
D3.
153.
173.
104.
003.
963.
524.
223.
954.
162.
4025
.98
11.3
23.
594.
304.
424.
82
J. Sep. Sci. 2010, 33, 2558–2567 Liquid Chromatography 2563
& 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim www.jss-journal.com
separation was sufficient to perform to quantify four
compounds in their samples.
PCR algorithm explained in the theoretical aspect was
applied to the multivariate HPLC data which correspond to
the ratio of DZ/IS, GT/IS, FNT/IS, and BC/IS areas at the
four-wavelength set (Table 1). The chemometric calibration
obtained by applying PCR was denoted as HPLC-PCR
method.
The multiple chromatographic areas for the extracts of
T. lucanicum containing IS were obtained at the above-
mentioned multiple wavelength set for DZ, GT, FNT, and
BC with IS. The ratio of the peak areas, DZ/IS, GT/IS, FNT/
Table 4. Recovery results of the synthetic plant samples by the proposed HPLC-chemometric methods
Quaternary mixture (mg/mL) Found (mg/mL)
DZ GT FNT BC
No. DZ GT FNT BC PLS PCR PLS PCR PLS PCR PLS PCR
1 2.50 12.50 4.00 20.00 2.55 2.57 12.79 12.79 4.06 4.07 20.53 20.63
2 7.50 7.50 12.00 12.00 7.30 7.29 7.36 7.40 11.69 11.79 11.52 11.55
3 12.50 2.50 20.00 4.00 11.80 11.79 2.40 2.41 20.62 20.66 3.88 3.88
4 10.00 2.50 8.00 12.00 9.77 9.75 2.48 2.50 7.96 7.95 11.48 11.49
5 10.00 12.50 8.00 24.00 10.18 10.18 12.97 12.99 8.16 8.20 24.30 24.40
6 8.00 8.00 4.00 16.00 7.92 7.90 7.81 7.81 4.11 4.10 15.66 15.76
7 8.00 10.00 24.00 16.00 8.08 8.09 10.20 10.28 23.81 23.87 15.75 15.74
8 15.00 6.00 16.00 8.00 14.60 14.55 6.06 6.09 15.49 15.59 7.88 7.86
9 5.00 15.00 20.00 12.00 5.01 5.02 14.84 14.84 19.23 19.29 11.63 11.63
Recovery (%)
DZ GT FNT BC
No. PLS PCR PLS PCR PLS PCR PLS PCR
1 102.18 102.90 102.34 102.34 101.42 101.66 102.67 103.17
2 97.33 97.19 98.07 98.60 97.38 98.22 96.02 96.27
3 94.41 94.33 95.88 96.28 103.09 103.30 96.97 96.97
4 97.72 97.52 99.06 99.86 99.53 99.41 95.65 95.74
5 101.84 101.84 103.77 103.93 102.03 102.53 101.25 101.67
6 99.03 98.78 97.59 97.59 102.73 102.62 97.90 98.52
7 101.03 101.15 101.96 102.80 99.19 99.44 98.46 98.40
8 97.36 97.00 100.94 101.44 96.78 97.41 98.46 98.22
9 100.16 100.37 98.96 98.96 96.17 96.47 96.95 96.95
Mean 99.00 99.01 99.84 100.20 99.81 100.12 98.26 98.43
SD 2.54 2.76 2.57 2.58 2.63 2.50 2.34 2.48
RSD 2.57 2.79 2.57 2.57 2.64 2.49 2.38 2.52
Table 5. Statistical parameters in the application of the HPLC-chemometrics method
Steps Parameter DZ GT FNT BC
PLS PCR PLS PCR PLS PCR PLS PCR
Calibration m 1.0486 1.0431 1.0000 0.9778 1.0390 1.0316 0.9338 0.9324
n �0.2802 �0.2592 0.0000 0.1223 �0.3325 �0.3023 0.9675 0.9579
r 0.9983 0.9986 0.9994 0.9990 0.9995 0.9995 0.9965 0.9966
SECa) 0.2952 0.2583 0.2126 0.2002 0.3638 0.2995 0.3591 0.3502
Prediction m 1.0486 1.0505 0.9778 0.9781 1.0123 1.0092 0.9665 0.9936
n �0.2802 �0.2997 0.1460 0.1207 �0.0598 �0.0651 0.6075 0.0514
r 0.9983 0.9983 0.9989 0.9988 0.9986 0.9987 0.9989 1.0000
SEPb) 0.2952 0.3095 0.1993 0.2130 0.3956 0.3689 0.3212 0.3186
a) SEC, standard error of calibration.
b) SEP, standard error of prediction.
J. Sep. Sci. 2010, 33, 2558–25672564 N. Kuc- ukboyacı et al.
& 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim www.jss-journal.com
IS, and BC/IS, were calculated. In the following step, the
amounts of four compounds in the extract and synthetic
samples were computed by inserting multiple peak area
ratio data to the PCR calibration equation for each
compound.
4.3 HPLC-PLS application
As in HPLC-PCR calibration, the PLS algorithm as
described above was subjected to the construction of the
HPLC-PLS calibration. A calibration set of the mixture
sample solutions of compounds between 2.5–15 mg/mL for
DZ and GT and 4.0–24 mg/mL for FNT and BC was used to
obtain the concentration data set. This concentration data
matrix was named as calibration set numbered from 1 to 6.
Table 1 summarizes the outline of the calibration set. In this
chromatographic study, the volume corresponding to 25 mg/
mL of IS was added to each sample.
For the calibration set summarized in Table 1, the
multiple HPLC chromatograms were recorded by using
DAD system. The multiple HPLC chromatograms for the
sequence of the calibration set are shown in Fig. 2. As can
be seen, a good chromatographic separation was observed
between DZ, GT, FNT, BC with IS.
HPLC-PLS calibration in the application of the PLS
algorithm to the peak area ratio data set was provided to
quantify the content of DZ, GT, FNT, and BC compounds in
samples.
4.4 Conventional single HPLC method
In the study, conventional single HPLC method is based on
the relationships between concentration and the ratio of
area (compound)/area (IS) at single-wavelength detection
for each compound in samples. In the our application,
standard series of the analyzed compounds were prepared
between 2.5–15 mg/mL for DZ and GT and 4.0–24 mg/mL
for FNT and BC using methanol. A 25 mg/mL IS was used
during the analysis of samples. The registration of DZ, GT,
FNT, BC, and IS chromatograms was performed by an
Agilent 1100 series HPLC system and DAD detections at
four different wavelengths. As in HPLC-chemometric
approaches, single-wavelength HPLC separation was accom-
plished by an isocratic mobile phase system as described in
Section 3.3. Different flow rates were tried to reach desirable
separation of the related compounds with IS. It was
observed that the flow rate at 1.4 mL/min provides a good
chromatographic separation. In case of this chromato-
graphic analysis, retention times of 2.896 min for DZ,
4.605 min for GT, 7.693 min for FNT, 15.620 min for BC,
and 17.174 min for IS are shown in Fig. 2.
Calibration equations for each compound in the
subjected samples were calculated by using the linear
regression analysis based on the relationship between
concentration and peak area ratio values at four different
wavelengths as explained above. Linear regression analysis
and its statistical results are summarized in Table 2. The
calculated linear regression functions for each compound
were used for the quantitative evaluation of DZ, GT, FNT,
and BC in synthetic and plant samples.
4.5 Analytical method validation
The method optimization and method validation are the
main problems of the chromatographic analyses and
applications. In this context, after the chromatographic
method optimization as explained above, analytical method
2.5 5.0 7.5 10.0 12.5 15.0 17.5 20.0
mAU
0
25
50
75
100
125
150
175
200
225
250
22.5 25.0 27.5 Time (min)
Extracted sample of Trifolium lucanicum
DAD1 A, Sig=240 nmDAD1 B, Sig=248 nm DAD1 C, Sig=256 nmDAD1 D, Sig=264 nm
GT SICBTNFDZ
-25
A
BC
D
0.0
Figure 3. Multiple chromato-grams of DZ, GT, FNT, BC,and IS in the extracted sampleof T. lucanicum at the multiplewavelength set, 240 nm (A),248 nm (B), 256 nm (C), and264 nm (D).
J. Sep. Sci. 2010, 33, 2558–2567 Liquid Chromatography 2565
& 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim www.jss-journal.com
validation was carried out by the observation of the linearity,
precision, accuracy, LOD, and LOQ parameters, etc.
As summarized in Table 2, good linearities for calibra-
tions with their high correlation coefficients were reported
in our concentration ranges by applying the conventional
HPLC method.
Recovery studies on the synthetic plant samples of DZ,
GT, FNT, and BC containing IS were done to observe the
precision and accuracy of the results provided by the
proposed HPLC-chemometric and conventional HPLC
methods. Mean percent recoveries, SDs, and RSDs were
calculated and listed in Tables 3 and 4. From Tables 3 and 4,
the results indicated that adequate accuracy and precision,
defined by percent mean recovery and RSD, respectively,
were sufficient for applicability and validity of HPLC-PCR,
HPLC-PLS, and conventional HPLC methods for the
analysis of the plant samples.
In addition, the LOD (S/N is 3:1) and the LOQ (S/N is
10:1) values were calculated by using the slope (m) of linear
regression equation and the SD of linear regression equa-
tion’s intercept. The LOD and LOQ values are listed in
Table 2.
The ability of the proposed HPLC-multivariate calibra-
tions was performed on the parameters defined by the
standard error of calibration and standard error of predic-
tion based on the relationship between the actual and the
predicted concentrations in the calibration and prediction
steps, respectively. The statistical results obtained by
applying least squares linear regression analysis to the
actual and predicted concentrations are summarized in
Table 5. As summarized in Table 5, in the application of
HPLC-PCR and HPLC-PLS calibrations, good correlation
coefficients between the actual and the predicted concen-
trations were observed.
Cross-validation procedure in the application of PCR
and PLS algorithms to the multiple chromatographic areas
was used to identify the optimal factor number for the
construction of HPLC-PCR and HPLC-PLS. From cross-
validation procedure, first one factor was found to be
suitable for both HPLC-PCR and HPLC-PLS [14, 15]. The
root mean square error of cross-validation for the HPLC-
PCR and HPLC-PLS calibrations were obtained as 0.5447
and 0.5446 for DZ, 0.2218 and 0.2222 for GT, 1.3201 and
1.3187 for FNT, and 0.7825 and 0.7827 for BC indicating
good accuracy and precision. In our calculation, units of the
results are mg/mL.
4.6 Analysis of plant samples
As described in the context of this study, HPLC-PCR and
HPLC-PLS approaches were applied to the multicomponent
determination of the amount of DZ, GT, FNT, and BC in
the extracts of T. lucanicum. For a comparison of the above
Table 6. Assay results obtained by applying the HPLC-chemometric and conventional HPLC to the extracts of Trifolium lucanicum
Conventional-HPLC Chemometric method Conventional-HPLC Chemometric method
No. 240 248 256 264 HPLC-PCR HPLC-PLS No. 240 248 256 264 HPLC-PCR HPLC-PLS
DZ (mg/mg) FNT (mg/mg)
1 2.524 2.314 2.391 2.396 2.3817 2.4137 1 0.0908 0.0803 0.0801 0.0903 0.0898 0.0900
2 2.471 2.389 2.378 2.510 2.4125 2.3819 2 0.0883 0.0797 0.0818 0.0916 0.0882 0.0891
3 2.387 2.393 2.391 2.450 2.4269 2.4271 3 0.0832 0.0820 0.0842 0.0932 0.0892 0.0882
4 2.404 2.388 2.568 2.396 2.3599 2.3601 4 0.0870 0.0787 0.0826 0.0922 0.0881 0.0892
5 2.367 2.258 2.373 2.485 2.4692 2.4499 5 0.0857 0.0795 0.0784 0.0882 0.0886 0.0889
Average 2.4307 2.3485 2.4203 2.4476 2.4100 2.4066 Average 0.0870 0.0800 0.0814 0.0911 0.0888 0.0891
SD 0.0653 0.0606 0.0831 0.0515 0.0421 0.0358 SD 0.0028 0.0012 0.0022 0.0019 0.0007 0.0007
RSD 2.69 2.58 3.43 2.11 1.75 1.49 RSD 3.27 1.54 2.73 2.11 0.81 0.76
SE 0.0292 0.0271 0.0371 0.0230 0.0188 0.0160 SE 0.0013 0.0006 0.0010 0.0009 0.0003 0.0003
CL 0.0572 0.0531 0.0728 0.0452 0.0369 0.0314 CL 0.0025 0.0011 0.0019 0.0017 0.0006 0.0006
GT (mg/mg) BC (mg/mg)
1 0.1316 0.1333 0.1324 0.1387 0.1314 0.1324 1 0.2697 0.2406 0.2401 0.2564 0.2509 0.2507
2 0.1388 0.1300 0.1282 0.1354 0.1316 0.1318 2 0.2619 0.2407 0.2439 0.2522 0.2507 0.2525
3 0.1361 0.1232 0.1267 0.1411 0.1326 0.1326 3 0.2549 0.2457 0.2467 0.2643 0.2535 0.2532
4 0.1380 0.1322 0.1369 0.1392 0.1332 0.1332 4 0.2557 0.2489 0.2482 0.2628 0.2532 0.2519
5 0.1360 0.1351 0.1324 0.1421 0.1360 0.1342 5 0.2552 0.2533 0.2519 0.2643 0.2519 0.2515
Average 0.1361 0.1307 0.1313 0.1393 0.1330 0.1328 Average 0.2595 0.2458 0.2462 0.2600 0.2521 0.2520
SD 0.0028 0.0046 0.0040 0.0026 0.0019 0.0009 SD 0.0064 0.0055 0.0045 0.0055 0.0013 0.0010
RSD 2.05 3.52 3.06 1.86 1.40 0.69 RSD 2.46 2.22 1.81 2.10 0.51 0.38
SEa) 0.0012 0.0021 0.0018 0.0012 0.0008 0.0004 SE 0.00285 0.00244 0.00199 0.00244 0.00058 0.00043
CLb) 0.0024 0.0040 0.0035 0.0023 0.0016 0.0008 CL 0.0056 0.0048 0.0039 0.0048 0.0011 0.0008
a) SE, standard error of slope.
b) CL, confidence limits.
J. Sep. Sci. 2010, 33, 2558–25672566 N. Kuc- ukboyacı et al.
& 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim www.jss-journal.com
HPLC-multivariate calibrations, the conventional HPLC
methods based on the single detection for each wavelength
point, 240, 248, 256, and 264 nm, respectively, were
subjected to the quantitative analysis of DZ, GT, FNT, and
BC amount in the same plant samples (Fig. 3). The assay
results provided by HPLC-chemometrics and conventional
HPLC are summarized in Table 6. In this table, the
experimental results provided by all methods are the average
of five replicates. As summarized in Table 6, the RSD values
obtained by HPLC-chemometric approaches were a little
lower than those obtained by conventional HPLC methods.
These small RSD values indicate that the precision of
HPLC-chemometric approaches is better than that of the
conventional HPLC method.
5 Concluding remarks
In this study, new HPLC multivariate calibration models
named HPLC-PLS and HPLC-PCR were improved for the
chromatographic multicomponent determination of DZ,
GT, FNT, and BC in the extract of T. lucanicum. In addition
to this, a conventional HPLC based on the single detection
was developed to compare the results obtained from the
HPLC-chemometric approaches. In comparison of the
proposed methods in our study, the HPLC-chemometric
methods give better recovery results with small RSD values
than those of conventional HPLC (Tables 3 and 4). This
investigation shows that the application of the HPLC
multivariate calibrations and conventional HPLC
approaches can be used safely for the quantitative analysis
of T. lucanicum containing phytoestrogen isoflavones.
This study was supported by Gazi University ResearchFoundation (No:02/2006-02).
The authors have declared no conflict of interest.
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