Introduction
Chinese medicinal materials are the material basis
for the application of traditional Chinese medicine (TCM) in disease prevention
and treatment. Their quality directly affects the clinical efficacy of TCM, the
experimental research of Chinese herbal medicines, and the quality control of
Chinese patent medicines. There are many kinds of Chinese Herbal Medicine (CHM)
in China with a wide range of sources, and the treatment by using these
medicines vary from place to place. In the market, fake products are often
claimed to be genuine, and so-called “superior” products are of a low quality.
Such products include not only certified products but also substitutes, fake
products, and adulterants with a great discrepancy in quality.
The active ingredients in CHM are mainly
secondary metabolites from plants (or animals). These ingredients are
influenced by factors, such as the place of production, climate, ecological
environment, cultivation or culturing techniques and conditions, harvest
seasons, storage conditions, etc., significant differences also occur in the
secondary metabolites from the same plant or animal species (Liu et al. 2016). In addition, most Chinese
medicinal materials need to be processed and treated before being used as
medicine. Different processing and treatment methods also influence the composition
of CHM, leading to unstable chemical compositions and quality, which in turn
affects their clinical efficacy (Gao et
al. 2011). Therefore, it is
particularly important to find a method that can comprehensively and truly
evaluate the quality of CHM.
With an in-depth study on the chemical
composition of TCM and the technical improvement of modern instrumental
analysis, methods of identification and quality evaluation of TCM are no longer
limited to traditional and classic identification measures, such as
morphological and microscopic identification. Various modern instruments have
been used to perform physical and chemical identifications to reveal the
inherent quality of TCM (Qu et al. 2014). However, owing to the long-term influence of the quality control mode
for chemicals, quality of Chinese medicinal materials is also monitored by measuring the content of an effective or an
active ingredient to determine the quality of specific medicinal materials.
This mode does not fulfill the requirements of the overall efficacy that TCM
advocates and cannot provide a comprehensive or reasonable evaluation of
Chinese medicinal materials. Compound recipes are a significant feature of CHM.
The chemical composition of a single herbal
medicine is already quite complex with more than one active ingredient.
Sometimes, synergistic effect between the components has a therapeutic role, and often, the antagonistic
effect is curative. Therefore, a comprehensive quality evaluation of Chinese
medicinal materials should not solely rely on a quantitative determination or
qualitative identification of single or several chemical components (Sun et al.
2013). The chromatographic fingerprints of Chinese herbal medicines can provide
comprehensive information about their quality and reveal most or even all of
the effective components in herbal medicines or all of the active ingredients.
This approach is more comprehensive and typical than the detection of the
contents of a single component. Combined with other measures, it can be used to
determine the quality and authenticity of Chinese medicinal materials.
The Bulbus F. thunbergii in the group of
"eight herbal medicines of Zhejiang" is a famous Chinese medicinal
material in Zhejiang Province (Yuan et al. 2010). It is of high quality
and stable texture, and the associated products are sold in many places within
and outside the province and further to countries and regions in Southeast
Asia. This material is large with a shape of Yuanbao (gold or silver ingots
with a Chinese style); thus, it is also called Yuanbao fritillary. Wild F. thunbergii is distributed in southern
Jiangsu, northern Zhejiang, Hunan, etc. Large-scale cultivations occur in
Ningbo, Pan'an of Zhejiang Province, and Nantong in Jiangsu Province, and it is
also cultivated in other provinces, such as Hunan, Hubei, Sichuan, Anhui, and
Henan. However, besides the cultivation bases, majority of medicinal materials
are purchased from individual farmers. Problems, such as unclear sources and
mixed varieties, often occur. To ascertain the authenticity of medicinal
materials, to establish quality standards for the varieties, and to guide Good
Agricultural Practices (GAP) production, we conducted a chemical fingerprint
study of F. thunbergii.
Thus far,
more than 130 compounds have been isolated and identified from Fritillaria plants. These compounds are
mainly alkaloids, most of which are isosteroidal alkaloids, and only a few are
steroidal alkaloids or other types of alkaloids (Temel et al. 2015;
Smolskait et al. 2015; Wang et al. 2018). Based on the
heterocyclic structures of these compounds, isosteroid alkaloids from Fritillaria can be divided into the
cevanine, jervine, and veratramine groups (Lyu et al. 2015; Ruan et al.
2016; Wang et al. 2018). There are also 15 steroidal alkaloids and one other
alkaloid (Arshadi et al. 2012; Temel et al.
2015).
Currently,
methods for the identification of Fritillaria
include high-performance liquid fingerprint chromatography (HLPC), thin-layer
chromatography, infrared, and ultraviolet spectroscopies, etc. Recently, there
have been many research studies on HPLC fingerprinting. Zhang et al. (2015) established a fingerprint
analytical method for F. hupehensis
using HPLC-ELSD using the experimental details as follows: the column was a
Hypersil ODS (250 × 4.6 mm), mobile phase was methanol (containing 0.05%
triethylamine)–water for gradient elution, flow rate was 1.0 mL/min, and
detector was an ELSD. Li et al.
(2006) examined 11 Fritillaria samples using HLPC according to the following
details: XDP-C18 (4.6 × 250 mm) as the chromatographic column, the mobile phase
was methanol–water in the ratio of 70:30 (v/v) containing 7.5 mmol/L sodium
dodecyl sulfate (SDS) with the pH at 4.5 ± 0.1, and the detection wavelength
was 215 nm. Based on the retention time and relative peak area of different
chemical components in the sample, chemometric methods were applied to
calculate and cluster the important parameters used to describe the degree of
separation and quality of two adjacent chromatographic peaks. The results
revealed the consistency between the cluster analysis and the botanical
classification. This method can be used for the identification of Fritillaria, and it aided the
establishment of the characteristic fingerprints of Fritillaria. Chen et al. (2013) used HPLC–differential
thermal analysis (DTA) to determine the quality of F. thunbergii, F. thunbergii var.
chekiangensis, F. hupehensis, and F. anhuiensis
obtained under the same ecological environments with Fritillaria origins and different processing methods. These
studies showed that Fritillaria
samples processed by traditional methods contained the same ingredients and can
be mixed, whereas samples fumigated with sulfur were different owing to the
presence of sulfur dioxide; additionally, the Fritillaria dried with lime was stable (Mitra et al. 2009). Wang et al.
(2017) reported that the alkaloids of Fritillaria
from Jilin indicated significant difference in the HPLC spectra of extracts
using different solvents and different methods. Lim et al. (2018) established an HPLC-ELSD method for the detection of Fritillaria alkaloids and gluco-alkaloid
to provide an accurate and concise approach for quality control of Fritillaria medicinal materials.
In addition
to HPLC fingerprinting, many researchers also use thin-layer chromatography to
identify Fritillaria medicinal
materials. Wu et al. (2010) applied
thin-layer chromatography to compare F.
ussuriensis of different origins and harvesting periods with different
varieties of Fritillaria and
counterfeits, and this method provided a reliable basis for the identification
of the medicinal materials of F.
ussuriensis. Li et al. (2006)
used microscopic examination and TLC to identify F. pallidiflora with F.
walujewii as reference substances. Rashid et al. (2015) identified and differentiated fresh tubers of F. thunbergii and its adulterant with
TLC and ultraviolet spectral identification to provide a basis for further
identification. Huang et al. (2005)
analyzed the total saponins from various Fritillaria
medicinal materials using thin-layer chromatography to distinguish F. chuanxiensis from other fritillary
materials.
There have
been also many studies on the identification of Fritillaria using spectroscopic techniques. Lee et al. (2015) combined near-infrared
diffuse reflectance spectroscopy and principal component analysis (PCA) to show
that this approach can identify Fritillaria
and its related species, being capable of clustering and identification.
Mitra et al. (2009) established a
method using near-infrared diffuse reflectance spectroscopy for the
identification of Fritillaria and its
counterfeits, providing a new method for the identification and analysis of Fritillaria and other TCM. Smolskait et al. (2015) used FTIR spectroscopy and
cluster analysis to identify and analyze Fritillaria
medicinal materials and their counterfeits. Li et al. (2014) applied FTIR spectroscopy to directly determine the
FTIR spectra of TCM, which provided a direct, quick, and accurate measurement
of F. chuanxiensis, F. thunbergii, and F. thunbergii var. chekiangensis.
Majo et al. (2011) used UV
spectrophotometry to measure and compare the UV spectra of anhydrous ethanol
extracts of F. walujewii and four
other types of Fritillaria samples.
The results revealed that F. walujewii showed
consistent differences from the other four types of Fritillaria.
Although
there are many studies on the chemistry and fingerprints of F. thunbergii, the fingerprints of
medicinal materials produced in Pan'an County, which is the main production
site of medicinal materials in Zhejiang Province, have not been studied
previously. This study focused on the chemical fingerprinting of medicinal
materials of F. thunbergii produced
in Pan’an to establish quality control standards for the medicinal materials
produced in Pan’an County and to guide GAP production.
Materials and Methods
Test materials
The test materials were F. thunbergii samples
collected from Pan’an, Ningbo of Zhejiang Province and Nantong of Jiangsu
Province, F. chuanxiensis from
Maoxian, Sichuan Province, and F.
ussuriensis from Jilin Province during the spring and summer time of
2018~2019 (Table 1). Among them, there are two varieties of F. chuanxiensis: one has a shorter
growth period and a smaller bulb, and the other has a longer growth period and
a larger bulb.
Preparation of test solutions
According to the Chinese Pharmacopoeia (2020
edition), the extraction method of F.
thunbergii was slightly modified to prepare the test solution. A 2 g of the
test powder were accurately weighed, placed in an Erlenmeyer flask, and
immersed in 4 mL of concentrated ammonia solution for 1 h. Forty mL of a
chloroform–methanol (4:1) solvent was added, weighed, mixed well, and the flask
was placed in a 40 °C water bath for 30 min and filtered. The filtrate was
evaporated to dryness, and the residue was dissolved in methanol
(chromatography grade) and transferred to a 10 mL volumetric flask. Methanol
was added to make up the final volume, and the solution was filtered through a
0.45 μm filter membrane.
Preparation of the reference solution
Peimine and peiminine standards were accurately
weighed and dissolved in methanol during ultrasonication to make a 0.1 mg/mL
reference solution.
Setup of chromatographic conditions
As described by Wei et al. (2017),
methanol–water (0.03% triethylamine) was used as the mobile phase for gradient
elution. The experimental results were promising. The following gradient
elution procedure was set up through repeated experiments: flow rate of 1
mL/min, injection volume of 5 μL. The ELSD detection parameters were as
follows: drift tube temperature of 35°C and carrier gas flow rate of 2.2 L/min.
Data analysis
Similarity analysis of fingerprints: Fingerprints were exported
in AIA format from the Agilent chromatographic workstation, and imported into
the ‘Chinese Herbal Medicine Chromatographic Fingerprint Similarity Evaluation
System’
Table
1: Sample of regular table design Details of plant materials
collected from different regions
|
No. |
Name |
Origin |
Time |
|
S1 |
Fritillaria cirrhosa (small) |
Songpinggou, Maoxian County,
Sichu |
Jun. 2018 |
|
S2 |
F.
cirrhosa (large) |
Songpinggou, Maoxian County,
Sichu |
Jun. 2018 |
|
S3 |
F.
thunbergii var. chekiangensis |
Yanshang village, Pan'an,
Zhejiang |
Jun. 2018 |
|
S4 |
F.
ussuriensis |
Huinan County, Tonghua City,
Jilin Province |
Aug. 2018 |
|
55 |
F.anhuiensis |
Cixia village, Pan'an,
Zhejiang |
Jun. 2018 |
|
S6 |
F.anhuiensis |
Yanshang village, Pan'an,
Zhejiang |
Jun. 2018 |
|
S7 |
F.
thunbergii |
Zhangzhishan, Nantong,
Jiangsu |
Jun. 2018 |
|
S8 |
F.
thunbergii (many-seeded) |
Houtang village, Pan'an,
Zhejiang |
Jun. 2018 |
|
S9 |
F.
thunbergii |
Zhangshui, Ningbo, Zhejiang |
Jun. 2018 |
|
S10 |
F.
thunbergii |
Cixia village, Pan'an,
Zhejiang |
Jun. 2018 |
|
S11 |
F.
thunbergii |
Houtang village, Pan'an,
Zhejiang |
Jun. 2018 |
|
S12 |
F.
thunbergii |
Pantanlengshui, Pan'an,
Zhejiang |
Jun. 2018 |
|
S13 |
F.
thunbergii |
Yangzhai village, Pan'an,
Zhejiang |
Jun. 2018 |
%20131-138_files/image002.png)
Fig. 1: HPLC-ELSD fingerprints of 13 Fritillaria
samples
(promulgated by the National
Pharmacopoeia Commission, Version A) software. Multiple
operation steps were performed to obtain the analytical results, including
trimming of the first 5 min of the chromatograms, baseline adjustment,
multi-point correction, automatic matching, and similarity analysis after
generating the control spectra.
Cluster
analysis: Peaks in the fingerprint spectra were automatically integrated using
the Agilent chromatographic workstation to obtain the area of each peak and to
calculate the relative peak area by dividing each peak by the area of the
corresponding peaks of peimine and peiminine. An absent peak was assigned a
peak area of 0. The relative peak area was used as the basis for clustering
analysis. The cluster analysis function in the
multivariate analysis menu in the DPS system was used to standardize the
original data, based on Euclidean distance measurement (Saurabh et al. 2017) and shortest-distance clustering, DPS
V8.01.
Principal
component analysis (PCA): The relative peak area of each peak in the
fingerprints was obtained in the same way as the cluster analysis. Based on the
relative peak area, the PCA analysis function, which is an unsupervised
multivariate data analysis approach, in the multivariate analysis
menu in the DPS V8.01 was used to analyze the original
data to obtain the PCA chart.
Calibration
of chromatographic peaks in the HPLC-ELSD fingerprints: A 5 μL of the standard
solutions of peimine and peiminine were injected into a HPLC and measured
according to the determined chromatographic conditions to produce the
chromatograms (Fig. 1).
Investigation of fingerprinting methodology
After determination of the extraction and
chromatographic separation conditions for the samples, we conducted a
methodological investigation on the effectiveness of the entire method.
Investigation indicators were selected from the following three aspects: the
precision of the instruments, stability of the samples, and reproducibility of
the method. Details are described as follows.
Precision test: A test solution of Fritillaria sample 6 was precisely injected at a volume of 5 μL five
consecutive times. The chromatogram was recorded, and the relative retention
time, relative peak area, and RSD of each peak were calculated. The results
showed that the RSD% values of the relative retention time of the common peaks
were between 0.18% and 3.01%, and the RSD% values of the relative peak area
were between 2.1% and 3.46%. ELSD detection has lower precision than UV
detection, but it basically meets the technical requirements of fingerprints,
controlled within 5%.
Stability test: A test solution of Fritillaria sample 5 was precisely injected at a volume of 5 μL and at
intervals of every 2, 4, 6, 12, and 24 h. The results revealed that the RSD%
values of the relative retention time of the common peaks were from 1.6 to
2.84, which were all less than 3%. The RSD% values of the relative peak area
were between 1.9% and 4.23%, which
%20131-138_files/image004.jpg)
Fig. 2:
Compare of different Fritillaria
species (after calibration)
indicated that the tested
product was stable within 24 h.
Repeatability test: Five replicates of
Fritillaria sample 6 were prepared as the test solution according to the
determined method. The solutions were injected separately, and the
chromatograms were recorded. The results showed that the RSD% values of the
relative retention time of the common peaks were between 0.97% and 1.35%, which
were all less than 3%. RSD% values of the relative peak area were between 2.74%
and 4.26%. Fig. 1 shows that the retention times of
peimine and peiminine standards were 8.102 and 8.252 min, respectively, and the
time difference between the two was only 0.15 min. The retention times of
peimine and peiminine in the test solutions were almost the same, showing a
large peak at approximately 8 min in the fingerprints.
Results
Analysis and comparison of HPLC fingerprints of
different species of Fritillaria
In this study, the HPLC spectra of F. thunbergii, F. thunbergii var. chekiangensis,
F. anhuiensis, F. chuanxiensis, and F.
ussuriensis were compared. Fig. 2 shows that the spectra of different
species of Fritillaria are quite
different. The chromatograms were imported into the "Chinese Herbal
Medicine Chromatographic Fingerprint Similarity Evaluation System" in AIA
format with multi-point correction. F.
anhuiensis had the highest number of peaks. Although F. thunbergii var. chekiangensis
is a variant of F. thunbergii, its
chemical composition was significantly different from F. thunbergii with an extra peak (No. 7) compared to other Fritillaria, and the retention time of
each peak was quite different from that of other samples. The HPLC spectrum of
multi-seed F. thunbergii was similar
to that of F. thunbergii, but its
content is not as high as that of F.
thunbergii. Number 10 peak was present in the spectra of F. ussuriensis, F. chuanxiensis, and F. anhuiensis but not in the spectra of F. thunbergii and F. thunbergii var. chekiangensis.
HPLC-ELSD fingerprint similarity of 13 batches of
Fritillaria
Similarity analysis was carried out using the
method specified previously. The results showed that the similarities among the
F. thunbergii samples were all above
0.90. The similarities among F.
chuanxiensis (large), F. anhuiensis
and F. thunbergii were between 0.80
and 0.90, indicating that they can be distinguished. However, the similarity
between F. ussuriensis and F. thunbergii was also above 0.90,
implying the difficulty in distinguishing these two species.
Cluster analysis of 13 batches of Fritillaria
Different Fritillaria
samples were considered as one entity. By comparing the properties and
characteristics of the relative peak area change among the different samples,
i.e., the areas of all peaks were divided by the peak area of the No. 4 peak,
the relative peak areas of the 13 Fritillaria
samples were systematically clustered by the DPS system (Table 2). The
Euclidean
Table 2:
Similarity of HPLC
fingerprints from 13 Fritillaria sample
|
|
S1 |
S2 |
S3 |
S4 |
S5 |
S6 |
S7 |
S8 |
S9 |
S10 |
S11 |
S12 |
S13 |
|
S1 |
|
0.856 |
0.95 |
0.965 |
0.872 |
0.963 |
0.902 |
0.979 |
0.942 |
0.974 |
0.927 |
0.977 |
0.979 |
|
S2 |
0.856 |
|
0.862 |
0.928 |
0.816 |
0.891 |
0.914 |
0.878 |
0.931 |
0.892 |
0.893 |
0.891 |
0.893 |
|
S3 |
0.95 |
0.862 |
|
0.97 |
0.908 |
0.972 |
0.903 |
0.975 |
0.944 |
0.956 |
0.933 |
0.954 |
0.967 |
|
S4 |
0.965 |
0.928 |
0.970 |
|
0.902 |
0.992 |
0.945 |
0.99 |
0.984 |
0.983 |
0.966 |
0.981 |
0.99 |
|
S5 |
0.872 |
0.816 |
0.908 |
0.902 |
|
0.921 |
0.857 |
0.894 |
0.893 |
0.900 |
0.886 |
0.9 |
0.903 |
|
S6 |
0.963 |
0.891 |
0.972 |
0.992 |
0.921 |
|
0.936 |
0.988 |
0.978 |
0.985 |
0.966 |
0.984 |
0.991 |
|
S7 |
0.902 |
0.914 |
0.903 |
0.945 |
0.857 |
0.936 |
|
0.931 |
0.959 |
0.958 |
0.976 |
0.936 |
0.95 |
|
S8 |
0.979 |
0.878 |
0.975 |
0.99 |
0.894 |
0.988 |
0.931 |
|
0.965 |
0.982 |
0.957 |
0.975 |
0.992 |
|
S9 |
0.942 |
0.931 |
0.944 |
0.984 |
0.893 |
0.978 |
0.959 |
0.965 |
|
0.981 |
0.97 |
0.978 |
0.98 |
|
S10 |
0.974 |
0.892 |
0.956 |
0.983 |
0.900 |
0.985 |
0.958 |
0.982 |
0.981 |
|
0.984 |
0.994 |
0.998 |
|
S11 |
0.927 |
0.893 |
0.933 |
0.966 |
0.886 |
0.966 |
0.976 |
0.957 |
0.97 |
0.984 |
|
0.967 |
0.978 |
|
S12 |
0.977 |
0.891 |
0.954 |
0.981 |
0.900 |
0.984 |
0.936 |
0.975 |
0.978 |
0.994 |
0.967 |
|
0.992 |
|
S13 |
0.979 |
0.893 |
0.967 |
0.99 |
0.903 |
0.991 |
0.95 |
0.992 |
0.98 |
0.998 |
0.978 |
0.992 |
|
%20131-138_files/image006.jpg)
Fig. 3:
Result of cluster analysis for Fritillaria
species
distance was used for the measurement, and
clustering was done using the minimum distance method (Fig. 3).
Results showed that the F. anhuiensis product grown in Cixia village of Pan’an showed the
most significant difference from other Fritillaria
species, followed by F. chuanxiensis
with a longer growth period (Fig. 4). F.
thunbergii samples grown in Nantong of Jiangsu were not clustered together
with the samples of the same species grown in Zhejiang, indicating a difference
between the chemical compositions of the F.
thunbergii samples from these two sources, which may be influenced by the
growing environment. Although F.
thunbergii var. chekiangensis is
a variety of F. thunbergii, its
chemical composition was significantly different from that of F. thunbergii. The difference was
evident in the fingerprints as follows: peaks 2 and 7 are absent from the
spectrum of F. thunbergii, and they
cluster with F. chuanxiensis, which
has a short growth period. F. ussuriensis
and the F. thunbergii produced in
Cixia and Yangzhai clustered together. However, according to the HPLC spectra, F. anhuiensis and F. thunbergii can be easily distinguished. It is likely that the
source of F. anhuiensis was
different. The fingerprints of F.
ussuriensis and F. thunbergii were
very similar, and F. ussuriensis
showed an extra peak (No. 9) compared with the spectrum of F. thunbergii.
PCA of 13 batches of Fritillaria
In addition to the cluster analysis of the HPLC
fingerprints of Fritillaria, we also
applied PCA to analyze the data of all Fritillaria
samples (Fig. 5). It was concluded that samples S7 and S5 were quite different
from other samples; F. thunbergii samples
produced in Nantong of Jiangsu and F.
anhuiensis samples produced in Cixia of Pan’an, showed different HPLC
fingerprints from other Fritillaria samples.
This indicated that there was a difference in the composition or content
between the F. thunbergii samples
produced in Jiangsu and Zhejiang Province, which further confirmed the
authenticity of these medicinal materials. Almost all other samples clustered
together, and they could not be compared. However, the PCA results can be
combined with the cluster analysis results to reveal information as follows.
Three samples with the greatest differences were F. anhuiensis from Cixia Village of Pan’an, F. thunbergii from Nantong of Jiangsu, and F. chuanxiensis with a longer growth period. S2, S3, S4 and S6 were
distributed in the sample region with all other F. thunbergii samples, but were not distinguished in this analysis.
Discussion
The HPLC fingerprints of different species of Fritillaria were analyzed by HPLC-ELSD
and further compared. The results showed that the greatest difference was
between F. anhuiensis from Cixia
Village of Pan’an and other Fritillaria
samples. Under the same extraction and detection conditions, F. anhuiensis have more fingerprint
peaks than those of F. thunbergii, F. chuanxiensis and F. ussuriensis. F. anhuiensis
samples are clustered together with F.
thunbergii in the clustering charts, but their HPLC spectra indicate that
some peaks of the two types of F.
anhuiensis samples are consistent, such as peak No. 6, 12, 13, and 15, all
of which are unique to F. anhuiensis (Fig. 3). Further investigation
is needed to determine the causes of this difference. One possible reason is
that local farmers introduced seeds from different sources. The other is that
these two F. anhuiensis samples may
belong to different species. In addition, F.
anhuiensis is just a vague collective term for Fritillaria species in Anhui. There are many specific varieties,
such as Anhui Fritillaria, Wanjiang Fritillaria, Wannan Fritillaria, and Wanxi Fritillaria
(Paz et al. 2015). Second, F.
chuanxiensis with a longer growth period is isolated, whereas F. chuanxiensis with a shorter growth
period was gathered first with F.
thunbergii var. chekiangensis and
then with F. thunbergii, indicating
that the chemical composition of
Fritillaria is a dynamic accumulation process. The chemical composition of Fritillaria with different growth years
may not be identical, which provides a basis for the harvest time limits of
medicinal materials. F. thunbergii
var. chekiangensis is a variety of F. thunbergii. It is mainly produced in
Pan'an, Zhejiang. It has a smaller size, similar to F. chuanxiensis. It has been used to replace F. chuanxiensis by the public. However, its chemical composition is
closer to that of F. thunbergii with
some differences. Zhao et al. (2014)
analyzed it chemical composition and confirmed that it is a variety of F. thunbergii. It is quite different
from F. chuanxiensis and cannot
replace it. Of the F. thunbergii
samples, there was no obvious difference between the F. thunbergii collected in Zhejiang Province (Pan'an and Ningbo),
but the F. thunbergii from Nantong,
Jiangsu was isolated separately, indicating that there were differences in F. thunbergii from different regions.
This may have been caused by the growing environment, and it further confirmed
the authenticity of the medicinal materials.
In this study, F. ussuriensis and F.
thunbergii were clustered together. A review of relevant studies showed
that the main alkaloid components in F.
ussuriensis are pingpeimine A and pingpeimine B (Sun et al. 2013), which
have similar chemical structures as peimine and peiminin.
Thus, they may have retention times
that are very close to those of F.
thunbergii in the HPLC fingerprints. F.
ussuriensis also contains peimine at a level of 0.002–0.003% (Chen et al.
2011), which may coelute with pingpeimine A and pingpeimine B to form a huge
peak at approximately 8 min. The above reasons caused their fingerprints to be
very similar in this study and not distinguishable.
Based on the HPLC-ELSD fingerprints of 13 batches
of Fritillaria, five types, i.e., F. thunbergii, F. thunbergii var. chekiangensis,
F. chuanxiensis, F. anhuiensis and F.
ussuriensis, were compared to obtain preliminary results. However, there
exist some problems and issues. 1) there were only 13 batches of samples with
only eight batches of F. thunbergii samples
(seven taken within the province and one taken outside the province). To
establish the HPLC fingerprints of F.
thunbergii from Zhejiang Province, at least 10 batches of samples from
places within the province were required. Thus, the number of samples needs to
be increased; 2) information on the samples was partially missing, for example,
the purchased F. anhuiensis sample
did not have a specific species name and 3) the HPLC detection conditions need
to be further optimized.
Conclusion
HPLC-ELSD fingerprints could well distinguish F. thunbergii grown in Pan’an, and F. thunbergii var. chekiangensis, F. anhuiensis,
F. thunbergii, F. chuanxiensis, and F. ussuriensis
samples from places outside Zhejiang Province, indicating that the environment
has an important influence on the composition of medicinal materials, which
confirmed the authenticity of the medicinal materials. In this study, only the
fingerprints of the alkaloids of Fritillaria
were studied. The non-alkaloids were excluded because many of the components in
Fritillaria are similar in structure,
only differing in some of the substituent groups. This makes it difficult to
distinguish these components in the HPLC spectra, and more investigation is
needed to optimize the HPLC separation conditions.
Acknowledgement
This research was supported by National Natural
Science Foundation of China (31600257 and 31800187) and Natural Science
Foundation of Zhejiang Province (LY18C030003).
Author Contributions
ZJ conceived the idea of work; QM conducted
formal analysis; RH investigated the materials; RH and QM wrote the original
draft; YL and JZ reviewed and edit the draft. All authors have read and agreed
to the published version of the manuscript.
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