Simultaneous quantification of bioactive components in Chinese herbal spirits by ultra-high performance liquid chromatography coupled to triple-quadrupole mass spectrometry (UHPLC–QQQ–MS/MS)

Abstract

Background
The Chinese medicinal wine made from herbal medicines became prevalent among Chinese people. The Chinese herbal spirit is composed of several herbal extracts, and has the certain health functions, such as anti-fatigue and immune regulation. The quality evaluation of Chinese herbal spirit is greatly challenged by the enormous and complex components with great structural diversity and wide range of concentration distribution.

Methods
An ultra-high performance liquid chromatography coupled to triple quadrupole mass spectrometry (UHPLC-QQQ-MS/MS) with multiple reaction monitoring (MRM) method was developed to simultaneously determine forty-three bioactive components in the Chinese herbal spirits produced by year 2014 and 2018.

Results
Quantitative results showed that 11 components, i.e.., puerarin ( 5 ), purpureaside C ( 7 ), daidzin ( 8 ), echinacoside ( 9 ), acteoside ( 15 ), epimedin B ( 22 ), epimedin C ( 23 ), icariin ( 24 ), eugenol ( 27 ), chikusetsusaponin iva ( 30 ) and Z-ligustilide ( 40 ), significantly decreased along with the increasing years of storage, while 5 compounds, i.e.., geniposidic acid ( 1 ), protocatechuic acid ( 2 ), crustecdysone ( 14 ), daidzein ( 18 ) and icariside I ( 35 ), were basically stable in all samples across the years.

Concusion
The established method allowing to simultaneously determined 43 components with wide structural diversity and trace amounts will facilitate the quality control research of Chinese herbal spirits.

Full text

Huetal. Chin Med (2021) 16:26
https://doi.org/10.1186/s13020-021-00435-0
RESEARCH
Simultaneous quantication
ofbioactive components inChinese herbal
spirits byultra-high performance liquid
chromatography coupled totriple-quadrupole
mass spectrometry (UHPLC–QQQ–MS/MS)
Yan Hu1,2†, Zhe Wang3†, Fangbo Xia2, Wen Yang3, Yuan‑Cai Liu3 and Jian‑Bo Wan2*
Abstract
Background: The Chinese medicinal wine made from herbal medicines became prevalent among Chinese people.
The Chinese herbal spirit is composed of several herbal extracts, and has the certain health functions, such as anti‑
fatigue and immune regulation. The quality evaluation of Chinese herbal spirit is greatly challenged by the enormous
and complex components with great structural diversity and wide range of concentration distribution.
Methods: An ultra‑high performance liquid chromatography coupled to triple quadrupole mass spectrometry
(UHPLC‑QQQ‑MS/MS) with multiple reaction monitoring (MRM) method was developed to simultaneously determine
forty‑three bioactive components in the Chinese herbal spirits produced by year 2014 and 2018.
Results: Quantitative results showed that 11 components, i.e.., puerarin (5), purpureaside C (7), daidzin (8), echina‑
coside (9), acteoside (15), epimedin B (22), epimedin C (23), icariin (24), eugenol (27), chikusetsusaponin iva (30) and
Z‑ligustilide (40), significantly decreased along with the increasing years of storage, while 5 compounds, i.e.., genipo‑
sidic acid (1), protocatechuic acid (2), crustecdysone (14), daidzein (18) and icariside I (35), were basically stable in all
samples across the years.
Concusion: The established method allowing to simultaneously determined 43 components with wide structural
diversity and trace amounts will facilitate the quality control research of Chinese herbal spirits.
Keywords: Chinese herbal spirit, Bioactive components, UHPLC‑QQQ‑MS/MS, MRM
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Introduction
Chinese medicinal wine, an alcoholic beverage, is com-
monly produced by soaking precious Chinese medicinal
materials. It became prevalent among Chinese people
due to its nourishing and tonic functions. A Chinese
herbal spirit from Jing Brand Co., Ltd is one of the most
popular medicinal wine in China, which is brewed with
the faint-scented Xiaoqu liqueur and several author-
ized herbal extracts under the guidance of traditional
Chinese medicine theory, including Dioscoreae rhi-
zoma, Curculiginis rhizoma, Angelicae sinensis radix,
Cistanches herba, Lycii fructus, Astragali radix, Epi-
medii folium, Cinnamomi cortex, and Caryophylli
flos, etc. [1]. is Chinese herbal spirit has health-care
Open Access
Chinese Medicine
*Correspondence: jbwan@um.edu.mo
† Yan Hu, Zhe Wang authors contributed equally to this work
2 State Key Laboratory of Quality Research in Chinese Medicine, Institute
of Chinese Medical Sciences, University of Macau, Taipa, Macao SAR,
China
Full list of author information is available at the end of the article

Page 2 of 12
Huetal. Chin Med (2021) 16:26
functions of anti-fatigue and immune enhancement [1].
It was shown to strengthen the immune system in the
Shen-yang deficient rats, which was associated with the
activation of hypothalamic-pituitary-adrenal axis [2].
Furthermore, a clinic study indicated that the Chinese
herbal spirit could relieve both physical fatigue and
mental fatigue of the patients with the fatigued sub-
health status [3].
According to enterprise criterion, total saponins, total
flavonoids and icariin are current chemical markers for
quality control of this herbal spirit. However, its qual-
ity evaluation is greatly challenged by the enormous and
complex components with great structural diversity and
wide range of concentration distribution. More than 150
ingredients were identified from the herbal spirit, includ-
ing flavonoids, saponins, alkaloids, phenylethanoids,
coumarins, anthraquinones and volatile oil, etc. To date,
gas chromatography-mass spectrometry (GC-MS) [1, 4,
5] and liquid chromatography-mass spectrometry (LC-
MS) [6], have been established to quantify the volatile
flavoring substances and active ingredients in thespirit.
However, the very limited quantity of ingredients were
quantified. Ultra-high performance liquid chromatog-
raphy coupled to triple quadrupole mass spectrometry
(UHPLC-QQQ-MS) operated in multiple reaction moni-
toring (MRM) mode is an effective quantification method
owing to its well-known high sensitivity and specific-
ity, which could avoid the interference from the back-
ground matrix [7–9]. It has been successfully utilized to
quantify bioactive components in the complex systems
[10–15]. In the current study, therefore, an UHPLC-
QQQ-MS method was developed to simultaneously
quantify 43 bioactive components in the Chinese herbal
spirit samples produced by year 2014 and 2018, and their
concentrations in different peoduction years were also
compared.
Materials andmethods
Materials andchemicals
e Chinese herbal spirit samples produced by year
2014 (n = 20) and 2018 (n = 20) were kindly provided by
Jing brand Co. Ltd (Hubei, China). e voucher speci-
mens were deposited at room temperature and shielded
from light at Institute of Chinese Medical Sciences,
University of Macau, Macao. Forty-three reference
compounds listed in Table1 were purchased from Baoji
herbest Bio-Tech Co. Ltd (Baoji, China). eir chemical
structures were shown in Additional file1: Figure S1,
and the purities of reference standards were over 98 %
as confirmed by HPLC-UV. HPLC-grade acetonitrile
and methanol were purchased from Merck (Darmstadt,
Germany). Formic acid was obtained from Aladdin
Industrial Inc. (Shanghai, China). Deionized water was
purified using a Millipore Milli-Q purification system
(Bedford, MA, USA).
Sample preparation andstandard solution preparation
An aliquot of 1mL of the spirit was diluted with the
equivalent volume of acetonitrile, and vortexed for
1min. e mixture was centrifuged at 14,800rpm for
20min. After the centrifugation, the supernatant was
filtered through a 0.22μm filter (PVDF Millex-GV, 13
mm, Millipore) prior to the quantitative analysis. All
of 43 reference standards were accurately weighed
and dissolved in methanol to prepare individual stock
solutions at the concentrations ranging from 0.58 to
2.29mg mL− 1. e mixed standard solution was pre-
pared by mixing appropriate volumes of the individual
stock solutions and further diluted to a series of proper
concentrations with methanol.
LC‑MS/MS analysis
Forty bathes of the spirit samples were analyzed by
an ACQUITY™ UPLC system (Waters, Milford, MA,
US) coupled with a Xevo TQD triple-quadrupole tan-
dem mass spectrometry (QQQ-MS/MS, Waters Co.,
Manchester, UK). Chromatographic separation was
implemented on an ACQUITY UPLC BEH C18 col-
umn (150 × 2.1 mm, 1.7μm). e mobile phases were
consisted of 0.1 % (v/v) aqueous formic acid solution
(phase A) and acetonitrile containing 0.1 % formic acid
(phase B) at the flow-rate of 0.3 mL min−1 using a gra-
dient elution program as follows: 5–40 % B at 0–12min,
40–100 % B at 12–16min, isocratic 100 % B for 2min,
and the re-equilibrated by 5 % B for 3 min. e sam-
ple injection volume was set at 2 µL. e tempera-
tures of column and injector were set at 35 ℃ and 8 ℃,
respectively.
Data acquisition was performed by a Xevo TQD QQQ-
MS equipped with an electrospray ionization (ESI)
using MRM mode. MS was operated in either the posi-
tive (ESI+) or negative mode (ESI-) to obtain satisfac-
tory MS response for 43 investigated compounds due to
their different properties. e MS and MS/MS spectra of
each compound were acquired using the mixed standard

Page 3 of 12
Huetal. Chin Med (2021) 16:26
Table 1 Mass parameters, calibration curves, LOD, LOQ, precision and recovery of 43 investigated analytes by LC‑MS/MS with MRM mode
No Analyte RT (min) Transition Cone
voltage
(V)
Collision
energy
(V)
Calibration curve LOD (ng/mL) LOQ (ng/mL) Precision (RSD, %) Recovery
(%, n = 6)
Equation R2Range (μg/mL) Intra‑day Inter‑day
1 Geniposidic acid 2.05 375.40 → 195.24 15 + 15 y = 260.2x − 43.8 0.9985 0.064–16.46 8.04 32.1 4.44 5.74 94.2
2 Protocatechuic acid 2.26 155.20 → 65.13 30 + 20 y = 1781.6x + 43.5 0.9995 0.009–9.340 0.65 2.28 2.59 5.15 97.8
3 Chlorogenic acid 3.35 355.30 → 163.08 20 + 15 y = 19714x − 689 0.9973 0.007–3.575 0.10 0.33 4.89 5.80 90.8
4 Scopolin 3.47 355.11 → 193.05 25 + 15 y = 20562x − 1022 0.9987 0.005–5.550 0.18 0.60 2.91 3.04 104.2
5 Puerarin 4.03 417.30 → 297.20 46 + 25 y = 10069x + 1933 0.9954 0.007–13.89 0.03 0.11 2.60 3.13 101.2
6 Magnoflorine 4.45 342.30 → 297.30 42 + 19 y = 27481x + 1247 0.9992 0.001–5.542 0.25 0.74 1.87 3.99 104.8
7 Purpureaside C 4.64 787.46 → 163.03 20 + 30 y = 444.3x + 34.7 0.9992 0.022–11.15 5.44 21.7 1.06 3.70 103.1
8 Daidzin 4.76 417.36 → 255.22 30 + 20 y = 17278x + 4508 0.9991 0.009–36.47 0.04 0.14 1.18 3.38 98.0
9 Echinacoside 4.91 787.55 → 325.10 20 + 20 y = 317.6x + 5.9 0.9995 0.046–11.78 2.16 7.66 3.38 3.51 90.9
10 Rutinum 5.63 611.20 → 303.10 35 + 15 y = 12785x + 160 0.9991 0.003–2.600 0.05 0.15 3.17 5.20 95.6
11 Calycosin‑7‑glucoside 5.70 447.28 → 285.19 36 + 17 y = 47510x + 2889 0.9962 0.001–5.725 0.02 0.05 2.08 2.41 107.6
12 Ferulic acid 5.74 195.10 → 117.00 20 + 23 y = 10691x + 201 0.9992 0.004–4.250 0.06 0.24 4.42 5.16 100.6
13 Hyperoside 5.79 465.27 → 303.16 26 + 15 y = 14954x − 199 0.9994 0.007–3.650 0.09 0.34 2.82 2.85 97.1
14 Crustecdysone 6.04 481.41 → 371.34 30 + 15 y = 881.7x + 54.6 0.9999 0.017–16.91 4.13 16.5 2.44 3.07 99.7
15 Acteoside 6.07 625.39 → 163.12 20 + 30 y = 693.3x + 52.6 0.9989 0.015–7.721 3.77 11.3 4.50 5.72 99.4
16 Coumarin 7.41 147.25 → 91.16 30 + 30 y = 20078x + 89 0.9999 0.001–4.853 0.04 0.19 3.16 3.65 103.4
17 Ononin 8.10 431.26 → 269.26 30 + 25 y = 31798x + 1102 0.9997 0.002–7.794 0.03 0.10 1.47 3.36 103.9
18 Daidzein 8.19 255.23 → 199.41 30 + 25 y = 12439x + 90 0.9998 0.001–1.131 0.07 0.28 0.68 3.05 96.3
19 Salvianolic acid A 8.51 495.17 → 223.19 20 + 40 y = 984.7x − 53.3 0.9980 0.017–8.906 4.35 11.6 0.72 1.79 106.9
20 Quercetin 8.92 303.60 → 229.05 50 + 30 y = 3438x + 205 0.9990 0.013–13.00 0.71 2.39 3.02 3.45 91.9
21 Epimedin A1 8.98 839.58 → 369.27 36 + 34 y = 9091x + 223 0.9996 0.007–6.700 0.68 2.18 4.40 4.73 104.5
22 Epimedin B 9.31 809.57 → 369.22 30 + 34 y = 7352x + 1340 0.9924 0.007–13.80 0.19 0.75 1.08 3.85 99.4
23 Epimedin C 9.48 823.58 → 369.27 34 + 35 y = 8289x + 32 0.9998 0.005–10.25 0.71 2.11 1.48 1.90 94.8
24 Icariin 9.66 677.48 → 369.22 38 + 27 y = 12010x + 1110 0.9987 0.002–12.44 0.01 0.03 3.23 4.01 92.2
25 Formononetin 11.88 269.19 → 253.11 40 + 30 y = 10680x + 39 0.9997 0.001–1.011 0.02 0.06 1.82 2.44 111.7
26 Baohuoside II 12.03 501.29 → 355.24 30 + 15 y = 20952x − 126 0.9997 0.002–3.456 0.03 0.11 1.47 5.18 106.5
27 Eugenol 12.13 164.07 → 103.13 44 + 21 y = 185.8x + 134.1 0.9986 0.035–35.52 8.54 27.7 3.63 3.72 90.3
28 Astragaloside A 12.37 785.50 → 455.40 25 + 15 y = 947.3x + 6.2 0.9996 0.012–3.028 0.80 2.00 3.15 4.29 99.3
29 Rhamnocitrin 12.39 301.10 → 258.10 50 + 30 y = 17437x − 344 0.9989 0.003–2.900 0.06 0.22 4.54 5.38 106.4
30 Chikusetsusaponin iva 12.74 793.57 → 793.57 30 ‑20 y = 1110x + 21 1.0000 0.010–9.779 0.30 1.19 3.60 4.10 92.3
31 Geniposide 13.01 389.43 → 255.29 30 + 25 y = 72.6x + 4.7 0.9998 0.092–11.84 23.1 46.2 3.64 5.15 102.0
32 Sagittatoside A 13.16 677.33 → 369.24 30 + 15 y = 6603x + 21 0.9999 0.003–2.978 0.73 2.91 2.53 4.49 95.8
33 Astragaloside II 13.31 827.75 → 175.09 20 + 30 y = 579.6x + 9.0 0.9992 0.004–2.243 0.73 2.19 3.49 5.81 106.2
34 Sagittatoside B 13.45 647.45 → 369.22 24 + 24 y = 9750x + 95 0.9998 0.004–3.600 0.59 2.34 4.79 4.88 109.1

Page 4 of 12
Huetal. Chin Med (2021) 16:26
Table 1 (continued)
No Analyte RT (min) Transition Cone
voltage
(V)
Collision
energy
(V)
Calibration curve LOD (ng/mL) LOQ (ng/mL) Precision (RSD, %) Recovery
(%, n = 6)
Equation R2Range (μg/mL) Intra‑day Inter‑day
35 Icariside I 13.48 531.19 → 369.14 35 + 30 y = 26745x + 119 0.9991 0.000–0.563 0.03 0.07 2.70 3.96 97.5
36 2′’‑O‑rhamnosyl Icariside II 13.51 661.47 → 369.28 28 + 21 y = 14713x + 522 0.9979 0.003–5.150 0.11 0.38 3.47 4.15 90.6
37 Baohuoside I 13.83 515.30 → 369.20 26 + 20 y = 48629x + 525 0.9988 0.000–3.375 0.03 0.10 0.99 2.69 96.8
38 Desmethyl Icaritin 13.87 355.10 → 299.10 50 + 20 y = 129383x + 2666 0.9991 0.001–3.950 0.03 0.08 2.37 3.43 95.4
39 Astragaloside I 14.11 869.74 → 217.27 15 + 15 y = 854.4x + 32.2 0.9994 0.009–8.750 1.07 4.27 1.02 1.99 101.4
40 Z‑ligustilide 14.73 191.11 → 117.01 38 + 22 y = 8945x − 92 0.9998 0.005–11.00 0.86 2.94 4.27 4.68 98.8
41 Icaritin 15.38 369.14 → 313.07 50 + 26 y = 220062x + 3559 0.9959 0.000–0.322 0.00 0.01 3.13 4.85 106.9
42 Tanshinone IIA 16.04 295.29 → 277.24 50 + 19 y = 64914x + 4212 0.9911 0.001–3.200 0.05 0.17 2.06 2.68 104.9
43 Oleanolic acid 16.69 439.36 → 203.18 35 + 25 y = 19247x + 370 0.9981 0.002–1.611 0.21 0.53 3.08 3.60 92.3

Page 5 of 12
Huetal. Chin Med (2021) 16:26
solution. e optimized MS parameters were as follows:
capillary voltage, 3.5kV (positive ion mode) and − 3.0kV
(negative ion mode); source temperature, 140 ℃; desol-
vation gas flow and temperature, 650L h−1 and 350 ℃;
cone flow, 50L h−1. e ion transitions, cone voltage, and
collision energy for each compound were optimized and
shown in Table 1. All instrumentations were synchro-
nized and controlled by Waters Masslynx software (ver-
sion, 4.1).
Method validation
To evaluate sensitivity and precision of the established
UHPLC-QQQ-MS/MS method, the linearity, limit of
detection (LOD), limit of quantitation (LOQ), precision
and recovery of 43 analytes were tested. e calibration
curve of each compound was constructed by plotting the
peak areas against the concentrations using the mixed
standard solution at a series of concentrations. e pre-
cision was examined by calculating intra- and inter-day
variations of each analyte using the mixed standards for
five replicates within a day and three consecutive days.
e LOD and LOQ for each analyte were estimated at
signal-to-noise ratio (S/N) of about 3 and 10, respectively.
e accuracy of the established method was assessed by
spike recovery experiments. A known amount (equal to
the content for each analyte in the sample) of the mixed
standards was spiked into the random spirit sample
(S-2018-08). e sample was prepared with six repli-
cates and analyzed by the method mentioned above. e
recovery (%) was calculated as the following equation:
Statistical analysis
e concentrations of 43 analytes in the spirit samples
were presented as mean ± standard deviation (SD). e
difference between groups was assessed by student t-test
using a GraphPad Prism package (version 6.0, San Diego,
CA, USA), and a p-value of less than 0.05 was considered
statistically significant. Orthogonal partial least squares-
discriminant analysis (OPLS-DA), a supervised multi-
ple regression, was conducted to discriminate thespirit
samples manufactured in different years according to the
levels of investigated analytes by SIMCA-P software (ver-
sion 14.1, Umetrics, Umeå, Sweden).
Recovery
(%)=100 ×

detected amount −original amount

/
spiked amount
Results anddiscussion
LC‑MS/MS method development
e quality control research related to this Chinese
herbal spirit mainly focused on the determination of
volatile components by GC-MS [1, 4, 5], and very lim-
ited number of nonvolatile bioactive components were
quantified by LC-MS [6]. Due to consisting of multiple
herbal extracts and the faint-scented Xiaoqu liqueur,
the herbal spirit is a very complex matrix containing the
numerous organic and inorganic compounds with wide
range of concentrations. us, the simultaneous quanti-
tation of forty-three compounds with various chemical
types encounters the great challenge in short running
time using UHPLC. MRM is a highly specific technique
for quantifying the targeted analyte, regardless of base-
line chromatographic separation. e targeted analyte in
chromatographic co-elution could be accurately quanti-
fied if they have different MS or MS/MS characteristics.
However, the co-eluted analytes may cause the potential
mutual ionization suppression in ESI, leading to the low
MS response. erefore, it is also necessary to optimize
the chromatographic conditions, including column and
mobile phase, to achieve the high sensitivity and fast sep-
aration in LC-MS/MS analysis. ree UHPLC columns,
such as BEH C18 column, BEH HILIC column and HSS
T3 C18 column, were examined. As results, an ACQUITY
BEH C18 column was most suitable for the separation of
the targeted compounds in the sample owing to the best
resolution and the most peak capacity. Furthermore, sev-
eral types of mobile phases, including methanol/water
and acetonitrile/water system supplemented with vari-
ous modifiers, were tested. e results shown that 0.1 %
aqueous formic acid solution / acetonitrile with 0.1 % for-
mic acid was the optimum mobile phases to obtain the
chromatogram with the best resolution.
It is critical to design ion transition of each analyte,
including precursor ions and their corresponding prod-
uct ions, in MRM analysis. e full scan was used to
select the precursor ions using their reference standards,
and the dominated fragment ion in daughter scan was
chosen as the corresponding product ion (Fig. 1). Tak-
ing sagittatoside A (32, MW = 676.24), a main compo-
nent derived from Epimedii folium, as an example, the

Page 6 of 12
Huetal. Chin Med (2021) 16:26
Fig. 1 Full scan spectra (left), the corresponding daughter scan spectra and the proposed fragmentation pattern (right) of sagittatoside A (32, a)
and daidzin (18, b)
Fig. 2 The MRM chromatograms of daidzein (18, a), puerarin (5, b) and Chikusetsu saponin iva (30, c) in both positive and negative ion modes; The
MRM chromatograms of Chikusetsu saponin iva (d) with different transitions (m/z 793.57→793.57 and m/z 793.57→631.67) in the negative ion
mode

Page 7 of 12
Huetal. Chin Med (2021) 16:26
protonated ion [M + H]+ m/z 677.33 was presented with
the highest abundance in full scan spectrum, the adduct
ion [M + Na]+ (m/z 699.34), was also observed with less
intensity. While, the product ion m/z 369.24 was domi-
nated in the corresponding daughter scan of [M + H]+
(Fig. 1 a, b). e mass difference between parent and
product ions was 308.09, which corresponded to the loss
of one glucose and one rhamnose units [15]. Herein, the
ion transition (m/z 677.33 → 369.24) was selected to
quantify sagittatoside A in the liqueur by MRM. Like-
wise, the ion transition (m/z 417.36 → 255.22) was opti-
mized to determine daidzin (8, Fig. 1c, d). To achieve
maximum signal, both positive and negative ion modes
were tested and compared. e results indicated that all
compounds, except Chikusetsusaponin iva (30), shown
the higher sensitivities in the positive ion mode than in
the negative mode. For example, MRM chromatograms
of daidzein (18) and puerarin (5) in positive ion mode
were remarkably higher than that in negative mode
(Fig.2a, b). However, the higher MS intensity of chikuset-
susaponin iva was observed in negative mode (Fig.2c).
Furthermore, the transition of chikusetsusaponin iva in
the negative mode were further optimized. We found
that multiple ion monitoring (MIM), i.e. m/z 793.57 →
793.57, was more suitable for the detection of chikuset-
susaponin iva, compared to other transitions, such as m/z
793.57 → 631.67 (Fig.2d).
Additionally, cone voltage (CV) and collision energy
(CE), the important factors that affect the sensitivity of
UHPLC-QQQ-MS/MS analysis, were also optimized
for each analyte using reference standard. CV and
CE were optimized from 10V to 50V with a step of
10V and from 5V to 50V with a step of 5V, respec-
tively. Taking sagittatoside A as an example, the signal
intensity of product ion m/z 369.24 increased along
with CV from 10V to 30V or CE from 5V to 15V,
then decreased with the increasing voltages (Fig.3a).
Therefore, 30V of CV and 15V of CE were chosen for
the quantification of sagittatoside A. Likewise, 30V of
CV and 20V of CE were used to determine the daidzin
(Fig.3b). In a similar manner, the mass spectrometry
conditions of all analytes were optimized and listed
in Table 1. Under the optimized LC-MS/MS condi-
tions, 43 analytes were well separated and detected in
18 min. The representative MRM chromatograms of
Fig. 3 The intensity distributions of the fragment ions derived from sagittatoside A (m/z 677.33→369.24, a) and daidzin (m/z 417.36→255.22, b)
with the cone voltage ranging from 10 V to 50 V (left), and collision energy ranging from 5 to 50 V (right) in positive ion mode

Page 8 of 12
Huetal. Chin Med (2021) 16:26
the mixed standards and the Chinese herbal spirit are
shown in Fig.4.
Method validation
e established LC-MS/MS method was validated by
a series of experiments, including linearity, sensitiv-
ity, precision, and accuracy. As shown in Table1, the
calibration curves of all analytes exhibited good lin-
ear regression (R2 ≥ 0.9911) within the wide dynamic
range. e LODs and LOQs of analytes were less than
8.54 and 27.7 ng mL− 1, respectively. Other than that
of geniposide was 23.1 and 46.2 ng mL− 1, respectively,
which was higher than other compounds. e over-
all intra-day and inter-day variations were lower than
4.89 % and 5.81 %, respectively. Additionally, the devel-
oped method had the acceptable accuracy with recov-
eries ranging from 90.3 to 111.7 %. Taken together, the
proposed LC-MS/MS method is sensitive, precise and
accurate for the simultaneous determination of these 43
compounds in the Chinese herbal spirit produced in dif-
ferent years.
Fig. 4 The MRM chromatograms of glycosides (left) and the remaining analytes (right) in the mixed standards (a) and the Chinese herbal spirit
sample (S‑2018‑08, b)

Page 9 of 12
Huetal. Chin Med (2021) 16:26
Quantication of43 compounds intheChinese herbal
spirit
e validated method was successfully applied to
quantify 43 compounds in the liqueur samples. As
shown in Table2 and 35 of 43 analytes were detected
and quantified in the liqueur samples produced in both
2014 and 2018. Eight analytes, including scopolin (4),
salvianolic acid A (19), quercetin (20), rhamnocitrin
(29), geniposide (31), desmethyl icaritin (38), icari-
tin (41), tanshinone IIA (42), were not detected in all
samples. Eight compounds, including eugenol (27),
puerarin (5), icariin (24), epimedin C (23), epimedin B
(22), chikusetsusaponin iva (30), daidzin (8) and crust-
ecdysone (14) were identified as major components in
the liqueur with contents more than 1µg mL− 1. Among
them, eugenol (27) is a major components with the
highest abundance in the liqueur samples. While, daid-
zein (18), formononetin (25), baohuoside II (26) and
icariside I (35) were trace components with the con-
tent of less than 0.1µg mL− 1. Additionally, 26 analytes
were observed to be significantly different between the
Chinese herbal spirits produced in year 2014 and 2018
(p < 0.05).
In order to further visualize the difference between
samples, OPLS-DA, a supervised multivariate data
analysis, was further constructed to characterize the
differences between groups on the basis of the levels
of 35 analytes determined. As illustrated in Fig. 5a,
the spirit samples produced at 2014 and 2018 were
unambiguously segregated into two tight clusters (R2X
= 0.826, R2Y = 0.96, Q2 = 0.887), suggesting that the
great alteration in the investigated compounds were
presented. The cumulative values of R2X, R2Y, and
Q2 were close to optimal value of 1.0, indicating the
established models with excellent predictive capabil-
ity and fitness [16]. To identify the differentiated com-
ponents that contribute most to the group separation,
the differentiated compounds were selected by S-plot
derived from the constructed OPLS-DA. Eleven com-
pounds with variable importance in the projection
(VIP) of more than 1 (VIP > 1) and p value of less
than 0.05 were highlighted in the S-plot (Fig. 5b).
The group separation of the samples with the differ-
ent production years could also be clearly classified
in OPLS-DA score plot according to the contents of
these 11 highlighted components (Fig.5c). Compared
Table 2 The contents of 43 investigated components in the
Chinese herbal spirits (ND = not detected)
*p<0.05, **p<0.01 , ***p<0.001
No Analyte Content (μg/mL)
2018 2014
1 Geniposidic acid 1.15 ± 0.22 1.15 ± 0.16
2 Protocatechuic acid 0.37 ± 0.11 0.39 ± 0.09
3 Chlorogenic acid 0.48 ± 0.13 0.28 ± 0.07***
4 Scopolin ND ND
5 Puerarin 6.84 ± 2.41 5.44 ± 1.05*
6 Magnoflorine 0.31 ± 0.22 0.11 ± 0.13**
7 Purpureaside C 1.05 ± 1.26 0.08 ± 0.26**
8 Daidzin 2.56 ± 1.12 1.95 ± 0.49
9 Echinacoside 2.20 ± 2.67 0.18 ± 0.54**
10 Rutinum 0.16 ± 0.07 0.07 ± 0.04***
11 Calycosin‑7‑glucoside 0.42 ± 0.08 0.34 ± 0.06**
12 Ferulic acid 0.31 ± 0.09 0.19 ± 0.04***
13 Hyperoside 0.22 ± 0.08 0.08 ± 0.02***
14 Crustecdysone 2.18 ± 0.33 2.25 ± 0.38
15 Acteoside 0.83 ± 1.19 0.04 ± 0.13*
16 Coumarin 0.26 ± 0.13 0.22 ± 0.06
17 Ononin 0.25 ± 0.12 0.19 ± 0.03*
18 Daidzein 0.06 ± 0.04 0.06 ± 0.04
19 Salvianolic acid A ND ND
20 Quercetin ND ND
21 Epimedin A1 0.45 ± 0.15 0.27 ± 0.19**
22 Epimedin B 2.89 ± 0.61 1.65 ± 0.51***
23 Epimedin C 6.00 ± 0.92 4.55 ± 1.52***
24 Icariin 7.10 ± 0.91 4.80 ± 0.57***
25 Formononetin 0.00 ± 0.00 0.01 ± 0.00***
26 Baohuoside II 0.10 ± 0.04 0.06 ± 0.02**
27 Eugenol 18.60 ± 4.02 15.53 ± 1.55**
28 Astragaloside A 0.07 ± 0.04 0.13 ± 0.05***
29 Rhamnocitrin ND ND
30 Chikusetsusaponin iva 4.15 ± 2.81 2.76 ± 0.35
31 Geniposide ND ND
32 Sagittatoside A 0.50 ± 0.22 0.17 ± 0.1***
33 Astragaloside II 0.27 ± 0.17 0.32 ± 0.19
34 Sagittatoside B 0.30 ± 0.12 0.09 ± 0.04***
35 Icariside I 0.02 ± 0.01 0.02 ± 0.01
36 2′’‑O‑rhamnosyl icariside II 0.39 ± 0.14 0.20 ± 0.44***
37 Baohuoside I 0.35 ± 0.15 0.17 ± 0.09***
38 Desmethyl Icaritin ND ND
39 Astragaloside I 0.09 ± 0.07 0.04 ± 0.03*
40 Z‑ligustilide 1.47 ± 0.73 0.57 ± 0.16***
41 Icaritin ND ND
42 Tanshinone IIA ND ND
43 Oleanolic acid 0.14 ± 0.07 0.09 ± 0.03**

Page 10 of 12
Huetal. Chin Med (2021) 16:26
to the spirit produced in 2018, the contents of the
highlighted compounds, puerarin (5), purpureaside
C (7), daidzin (8), echinacoside (9), acteoside (15),
epimedin B (22), epimedin C (23), icariin (24), euge-
nol (27), chikusetsusaponin iva (30) and Z-ligustilide
(40), significantly decreased in the samples produced
in year 2014 (Fig.6a). Geniposidic acid (1), protocat-
echuic acid (2), crustecdysone (14), daidzein (18) and
icariside I (35) around the origin of S-plot were also
highlighted as the stable compounds, which shown
the comparable contents with less variation between
samples from two production years (Fig. 6b). Addi-
tionally, a heatmap according to the relative contents
of 35 detedcted analytes was constructed to display
the changes in the analyte levels between groups
(Fig.6c).
Conclusions
In this study, a rapid and sensitive UHPLC-QQQ-MS with
MRM mode was developed to simultaneously quantify 43
bioactive components in Chinese herbal spirits. Quantita-
tive results showed that 11 components, i.e.., puerarin (5),
purpureaside C (7), daidzin (8), echinacoside (9), acteo-
side (15), epimedin B (22), epimedin C (23), icariin (24),
eugenol (27), chikusetsusaponin iva (30) and Z-ligustilide
(40), significantly decreased along with the increasing
years of storage, while 5 compounds, i.e.., geniposidic acid
(1), protocatechuic acid (2), crustecdysone (14), daidzein
(18) and icariside I(35), were basically stable in all sam-
ples across the years. e established method allowing
to simultaneously determined 43 components with wide
structural diversity and trace amounts will facilitate the
quality control research of Chinese herbal spirits.
Fig. 5 OPLS‑DA score plots (a) and the corresponding S‑plot (b) based on the contents of 43 analytes investigated in the Chinese herbal spirit
samples produced in year 2014 and 2018. OPLS‑DA score plot (c) according to the contents of 11 highlighted differentiated ions across the samples.
The differentiated ions (VIP > 1 and p < 0.05) were marked in red. The compound number in the S‑plot represent in the same manner as in Table 1

Page 11 of 12
Huetal. Chin Med (2021) 16:26
Supplementary Information
The online version contains supplementary material available at https ://doi.
org/10.1186/s1302 0‑021‑00435 ‑0.
Additional le1: Figure S1. Chemical structures of 43 investigated
analytes.
Acknowledgements
Not applicable.
Authors’ contributions
JBW and ZW conceived and designed the study; YH, performed the experi‑
ment and prepared the manuscript; FX, analyzed the data; YW and YCL revised
the manuscript; JBW, finalized the manuscript. All authors read and approved
the final manuscript.
Funding
The work was financially supported by grants from Enterprise Cooperation
Project (CP/003/2018), and the Science and Technology Development Fund,
Macau SAR (File no. 0034/2019/A1).
Availability of data and materials
The data in this study are available from the corresponding author upon
request.
Fig. 6 The content comparisons of the highlighted analytes (a) and the compounds without difference (b). Heatmap (c) visualizing the differences
in the contents of the investigated analytes across the samples. The compound number in the S‑plot represent in the same manner as in Table 1

Page 12 of 12
Huetal. Chin Med (2021) 16:26
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Competing interests
The authors declare that there are no conflicts of interest.
Author details
1 State Key Laboratory of Southwestern Chinese Medicine Resources,
Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China.
2 State Key Laboratory of Quality Research in Chinese Medicine, Institute
of Chinese Medical Sciences, University of Macau, Taipa, Macao SAR, China.
3 Hubei Provincial Key Lab for Quality and Safety of Traditional Chinese Medi‑
cine Health Food, Jing Brand Co.,Ltd., Hubei, China.
Received: 29 December 2020 Accepted: 2 March 2021
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