A high-performance liquid chromatography method was developed for simultaneous quantification of 18 polyphenolic compounds from the leaves of
Leaves of
Quality control is crucial to guarantee the safety and efficacy of the utilization of herbal medicines. Unlike the synthetic drugs, the effectiveness of herbal medicines may be attributed to the overall effect of several components rather than a single component. Moreover, the synergistic effect between components is also related to herb efficacy. Thus, the quality evaluation of herbal medicine is very difficult and requires the information of bioactive components as much as possible. Several studies have reported the determination of constituents in
High-performance liquid chromatography (HPLC) coupled with various detectors such as ultraviolet-visible (UV) detection [
In the present study, we developed a simple HPLC-PDA method to simultaneously determine 18 bioactive compounds in the leaves of
Four batches of the leaves of
A total of 18 reference compounds including 17 flavonoids and 1 phenylethanone (Figure
Effects of the extraction method, solvent type, and solvent volume on the extraction efficiency of 18 constituents in the leaves of
HPLC grade acetonitrile (Merck, Germany) was used as the mobile phase. All other reagents were at least analytical grade (Jinhuada Chemical Factory, Guangzhou, China). Water was purified using a Milli-Q water purification system (Millipore, USA).
The ground dried leaves of
The reference standards were accurately weighed and dissolved in methanol to prepare mixed standard stock solution. Consisted of each reference compounds
The HPLC system consists of a Waters 2995 controller and 2998 Photodiode Array detector. The separation was performed on an Elite Kromasil C18 column (250 mm × 4.6 mm, 5
The chromatographic peak purity analysis was performed on an Agilent 1290 UPLC system coupled with a SCIEX Triple TOF 4600 mass spectrometer equipped with an ESI interface. The optimized MS conditions were as follows: TOF mass range between 50 and 1700, curtain gas 35 psig, ion spray voltage floating −4500/5000 kV, and ion source temperature 500°C. The collision energy was set at 10 V to obtain more fragment information.
The linearity, limit of detection (LOD), limit of quantification (LOQ), precision, repeatability, stability, and recovery were checked for method validation.
Four factors (including extraction methods, extraction solvents, solvent volume, and extraction time) were evaluated to get the most efficient extraction protocol. Sonication (15, 30, and 45 min) and reflux (30 and 60 min) in factorial experiments using 80% methanol and the reflux for 30 min showed the best extraction ability. Moreover, among 60% methanol, 80% methanol, 100% methanol, 60% ethanol, and 80% ethanol, 80% methanol was the best solvent mixture and produced more chromatographic peaks. Furthermore, 25 mL of 80% methanol showed the best extraction efficiency compared to solvent volumes 50 and 100 mL. Finally, samples extracted by reflux in 25 mL of 80% methanol for 30 min were selected for the extraction method (Figure
To get an accepted resolution, separation parameters including analytical column, mobile phases, and elution gradient were assessed. The Elite Kromasil C18 column (250 mm × 4.6 mm, 5
The structures of 18 reference standards isolated from the leaves of
HPLC chromatographs. ((a) Reference standards at 289 nm; (b) reference standards at 254 nm; (c) the sample of batch no. GZ20151001 at 289 nm; (d) the sample of batch no. GZ20151001 at 254 nm;
MS spectrum (ESI− for
The established method was validated in terms of linearity, precision, stability, and accuracy. Linear regression equations (e.g.,
Linearity and sensitivity of the HPLC analysis.
No. | Compound name | Calibration curvea |
|
Linear range ( |
LODb ( |
LOQc ( |
---|---|---|---|---|---|---|
1 | Rutin |
|
0.9997 | 0.37∼139.92 | 0.18 | 0.37 |
2 | Hyperoside |
|
0.9999 | 0.34∼126.65 | 0.10 | 0.34 |
3 | Isoquercitrin |
|
0.9999 | 0.31∼117.20 | 0.10 | 0.31 |
4 | 3,3′,5,7-Tetrahydroxy-4′-methoxyflavanone |
|
0.9999 | 2.67∼1001.40 | 0.89 | 2.67 |
5 | 3′,5,5′,7-Tetrahydroxyflavanone |
|
1.0000 | 6.61∼330.47 | 1.32 | 5.29 |
6 | Quercetin |
|
0.9999 | 1.15∼57.34 | 0.23 | 0.92 |
7 | 3,3′,4′,5-Tetrahydroxy-7-methoxyflavanone |
|
0.9997 | 3.55∼443.52 | 0.88 | 3.55 |
8 | Chrysosplenol C |
|
0.9998 | 0.21∼51.55 | 0.07 | 0.21 |
9 | Diosmetin |
|
1.0000 | 0.10∼36.06 | 0.03 | 0.10 |
10 | Tamarixetin |
|
0.9997 | 0.11∼28.06 | 0.04 | 0.11 |
11 | 3,5,7-Trihydroxy-3′,4′-dimethoxyflavone |
|
0.9999 | 0.11∼95.68 | 0.04 | 0.11 |
12 | 3,3′,5-Trihydroxy-4′,7-dimethoxyflavanone |
|
1.0000 | 0.86∼747.94 | 0.29 | 0.86 |
13 | Blumeatin |
|
1.0000 | 0.72∼627.09 | 0.24 | 0.72 |
14 | Rhamnetin |
|
1.0000 | 0.20∼175.73 | 0.07 | 0.20 |
15 | 3′,4′,5-Trihydroxy-3,7-dimethoxyflavone |
|
0.9996 | 0.06∼22.04 | 0.02 | 0.06 |
16 | Xanthoxylin |
|
1.0000 | 0.99∼173.27 | 0.33 | 0.99 |
17 | Ombuin |
|
0.9999 | 0.07∼23.66 | 0.02 | 0.05 |
18 | 3,5-Dihydroxy-3′,4′,7-trimethoxyflavone |
|
0.9999 | 0.08∼20.18 | 0.03 | 0.08 |
Precision was evaluated by using intraday and interday variability. The intraday variability was assessed at three different concentration levels (low, medium, and high) with six replicates at each level within one day. The interday variability was tested in triplicate on the consecutive three days. The variations (RSD%) for intra- and interday precision are shown in Table
The results of precision, repeatability, and stability.
No. | Intraday (RSD, %, |
Interday ( |
Repeatability ( |
Stability ( | ||||
---|---|---|---|---|---|---|---|---|
Low | Medium | High | Low | Medium | High | RSD (%) | RSD (%) | |
1 | 1.08 | 1.03 | 0.77 | 1.98 | 2.17 | 1.89 | 1.46 | 2.31 |
2 | 0.31 | 0.40 | 0.39 | 1.14 | 1.07 | 0.84 | 1.03 | 1.26 |
3 | 0.52 | 0.70 | 0.58 | 1.42 | 1.17 | 0.94 | 1.01 | 1.11 |
4 | 1.86 | 1.86 | 1.60 | 2.13 | 2.30 | 1.92 | 1.97 | 2.44 |
5 | 0.50 | 0.68 | 0.61 | 0.62 | 0.62 | 0.66 | 0.56 | 0.79 |
6 | 0.57 | 0.59 | 0.60 | 1.04 | 0.88 | 0.99 | 0.69 | 0.90 |
7 | 0.86 | 0.96 | 0.73 | 1.04 | 0.76 | 0.86 | 0.70 | 0.87 |
8 | 1.08 | 1.38 | 1.28 | 1.73 | 1.74 | 2.09 | 1.38 | 1.27 |
9 | 1.05 | 1.16 | 1.11 | 1.68 | 3.33 | 2.96 | 2.84 | 3.02 |
10 | 0.98 | 1.53 | 0.98 | 1.40 | 1.21 | 1.28 | 1.04 | 1.81 |
11 | 0.57 | 0.67 | 0.56 | 0.74 | 0.74 | 0.77 | 0.54 | 0.70 |
12 | 0.65 | 0.65 | 0.50 | 0.79 | 0.79 | 0.52 | 0.60 | 0.63 |
13 | 0.59 | 0.71 | 0.56 | 0.32 | 0.52 | 0.32 | 0.52 | 0.66 |
14 | 0.70 | 0.66 | 0.62 | 0.52 | 0.87 | 1.11 | 0.82 | 0.93 |
15 | 2.39 | 2.19 | 1.90 | 0.93 | 1.12 | 1.40 | 1.25 | 1.78 |
16 | 1.21 | 1.13 | 1.02 | 0.64 | 0.58 | 0.68 | 1.31 | 1.58 |
17 | 2.35 | 3.33 | 3.06 | 1.62 | 1.70 | 1.47 | 2.98 | 1.70 |
18 | 0.99 | 0.60 | 0.45 | 0.67 | 0.70 | 0.86 | 0.65 | 0.74 |
The recovery test was used to evaluate the accuracy of the method. Three different concentration levels (80%, 100%, and 120% of the concentration of the targets in a random sample) of the standard solutions were added into an actual sample. Triplicates were done for each level (0.33 g, 0.30 g, and 0.27 g
Recovery of the targets (
No. | Original (mg) | Spiked (mg) | Found (mg) | Recovery (%)a | RSD (%)b |
---|---|---|---|---|---|
1 | 0.36 | 0.23 | 0.59 | 100.95 ± 3.95 | 3.91 |
0.30 | 0.29 | 0.61 | 104.00 ± 2.67 | 2.56 | |
0.24 | 0.35 | 0.59 | 102.15 ± 3.37 | 3.30 | |
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2 | 0.33 | 0.21 | 0.55 | 102.84 ± 4.08 | 3.97 |
0.28 | 0.26 | 0.56 | 104.51 ± 2.94 | 2.81 | |
0.22 | 0.32 | 0.54 | 102.64 ± 2.41 | 2.34 | |
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3 | 0.32 | 0.20 | 0.52 | 103.76 ± 3.67 | 3.54 |
0.27 | 0.24 | 0.53 | 105.68 ± 3.02 | 2.86 | |
0.21 | 0.29 | 0.51 | 103.49 ± 2.38 | 2.30 | |
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4 | 2.40 | 1.67 | 4.02 | 96.90 ± 4.18 | 4.31 |
2.04 | 2.09 | 4.12 | 99.95 ± 2.63 | 2.63 | |
1.60 | 2.50 | 4.09 | 99.53 ± 2.31 | 2.32 | |
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5 | 0.54 | 0.33 | 0.88 | 100.70 ± 4.80 | 4.76 |
0.46 | 0.41 | 0.89 | 103.53 ± 3.67 | 3.55 | |
0.36 | 0.50 | 0.87 | 102.48 ± 3.64 | 3.56 | |
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6 | 0.11 | 0.06 | 0.17 | 103.95 ± 4.36 | 4.19 |
0.10 | 0.07 | 0.17 | 106.42 ± 0.32 | 0.30 | |
0.08 | 0.09 | 0.17 | 109.92 ± 0.51 | 0.46 | |
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7 | 0.74 | 0.44 | 1.21 | 104.71 ± 1.64 | 1.57 |
0.63 | 0.55 | 1.17 | 96.69 ± 3.77 | 3.89 | |
0.50 | 0.67 | 1.13 | 95.37 ± 2.22 | 2.32 | |
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8 | 0.10 | 0.05 | 0.16 | 108.99 ± 3.63 | 3.33 |
0.09 | 0.06 | 0.16 | 108.76 ± 0.88 | 0.81 | |
0.07 | 0.08 | 0.15 | 107.31 ± 1.03 | 0.96 | |
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9 | 0.03 | 0.03 | 0.05 | 103.56 ± 2.84 | 2.74 |
0.02 | 0.03 | 0.06 | 109.35 ± 0.45 | 0.41 | |
0.02 | 0.04 | 0.06 | 104.19 ± 0.37 | 0.36 | |
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10 | 0.05 | 0.03 | 0.08 | 101.56 ± 3.61 | 3.56 |
0.04 | 0.04 | 0.08 | 108.86 ± 1.50 | 1.38 | |
0.03 | 0.04 | 0.08 | 107.88 ± 0.30 | 0.27 | |
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11 | 0.10 | 0.07 | 0.17 | 102.90 ± 4.55 | 4.42 |
0.09 | 0.09 | 0.18 | 104.61 ± 3.51 | 3.36 | |
0.07 | 0.10 | 0.18 | 103.53 ± 2.47 | 2.39 | |
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12 | 0.84 | 0.53 | 1.39 | 102.48 ± 4.30 | 4.20 |
0.72 | 0.67 | 1.41 | 104.43 ± 3.43 | 3.28 | |
0.56 | 0.80 | 1.39 | 103.05 ± 2.48 | 2.41 | |
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13 | 0.67 | 0.45 | 1.13 | 102.81 ± 4.19 | 4.08 |
0.57 | 0.56 | 1.16 | 104.67 ± 3.05 | 2.91 | |
0.45 | 0.67 | 1.14 | 103.34 ± 2.43 | 2.36 | |
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14 | 0.24 | 0.13 | 0.36 | 97.59 ± 3.55 | 3.64 |
0.20 | 0.16 | 0.36 | 102.75 ± 1.42 | 1.39 | |
0.16 | 0.19 | 0.36 | 106.26 ± 0.52 | 0.49 | |
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15 | 0.02 | 0.02 | 0.04 | 103.40 ± 4.19 | 4.05 |
0.02 | 0.02 | 0.04 | 104.65 ± 3.03 | 2.90 | |
0.01 | 0.02 | 0.04 | 100.95 ± 2.78 | 2.76 | |
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16 | 0.19 | 0.12 | 0.31 | 95.85 ± 2.17 | 2.26 |
0.16 | 0.16 | 0.31 | 95.64 ± 2.64 | 2.76 | |
0.13 | 0.19 | 0.31 | 95.03 ± 2.21 | 2.33 | |
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17 | 0.01 | 0.02 | 0.03 | 105.40 ± 0.99 | 0.93 |
0.01 | 0.02 | 0.03 | 107.31 ± 0.15 | 0.14 | |
0.01 | 0.03 | 0.03 | 109.30 ± 0.52 | 0.47 | |
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18 | 0.03 | 0.02 | 0.05 | 104.16 ± 4.70 | 4.52 |
0.03 | 0.03 | 0.05 | 105.74 ± 3.09 | 2.93 | |
0.02 | 0.03 | 0.05 | 105.15 ± 2.54 | 2.42 |
aRecovery% = [(found amount−original amount)/spiked amount] × 100%. bRSD% = (SD/mean) × 100%.
Above data demonstrated that the developed HPLC-PDA method was precise and accurate for quantitative determination of the 18 tested constituents in
Herbs contain multiple bioactive components. Controlling the quality of herbs using a unique constituent is not an accepted method; thus, a tailored analytical method for each herb to evaluate multiple bioactive components simultaneously is needed. In the current study, we developed a simple and accurate assay method for simultaneous determination of 18 major compounds in the leaves of
The validated HPLC-PDA method was applied to the simultaneous determination of 18 bioactive components in the leaves of
The contents of the 18 targets in the leaves of
No. | GZ20151001 | GZ20151002 | GX20151001 | YN20151001 |
---|---|---|---|---|
1 | 0.97 ± 0.001 | 1.01 ± 0.002 | 1.00 ± 0.000 | 0.47 ± 0.012 |
2 | 0.91 ± 0.003 | 0.82 ± 0.002 | 0.45 ± 0.007 | 0.47 ± 0.006 |
3 | 0.87 ± 0.003 | 0.77 ± 0.003 | 0.43 ± 0.006 | 0.45 ± 0.002 |
4 | 6.54 ± 0.050 | 12.61 ± 0.193 | 4.39 ± 0.046 | 3.81 ± 0.106 |
5 | 1.51 ± 0.007 | 0.96 ± 0.006 | 0.96 ± 0.012 | 2.38 ± 0.003 |
6 | 0.32 ± 0.003 | 0.32 ± 0.000 | 0.28 ± 0.002 | 0.33 ± 0.002 |
7 | 2.07 ± 0.027 | 2.48 ± 0.002 | 1.42 ± 0.010 | 3.29 ± 0.001 |
8 | 0.27 ± 0.004 | 0.34 ± 0.002 | 0.28 ± 0.001 | 0.17 ± 0.001 |
9 | 0.07 ± 0.001 | 0.08 ± 0.000 | 0.06 ± 0.000 | 0.01 ± 0.000 |
10 | 0.13 ± 0.001 | 0.13 ± 0.001 | 0.07 ± 0.001 | 0.11 ± 0.000 |
11 | 0.29 ± 0.003 | 0.20 ± 0.001 | 0.23 ± 0.001 | 0.28 ± 0.000 |
12 | 2.34 ± 0.020 | 2.36 ± 0.004 | 1.78 ± 0.012 | 1.80 ± 0.001 |
13 | 1.87 ± 0.012 | 2.17 ± 0.004 | 1.59 ± 0.009 | 1.31 ± 0.000 |
14 | 0.66 ± 0.005 | 0.48 ± 0.001 | 0.30 ± 0.003 | 0.31 ± 0.000 |
15 | 0.06 ± 0.001 | 0.06 ± 0.000 | 0.03 ± 0.000 | 0.06 ± 0.000 |
16 | 0.53 ± 0.001 | 1.14 ± 0.003 | 0.50 ± 0.003 | 0.35 ± 0.000 |
17 | 0.03 ± 0.001 | 0.02 ± 0.000 | 0.03 ± 0.000 | 0.01 ± 0.000 |
18 | 0.09 ± 0.001 | 0.10 ± 0.002 | 0.00 ± 0.000 | 0.06 ± 0.000 |
The content of compound
In the present study, a simple and accurate HPLC-PDA analytic method was developed to quantify 18 bioactive compounds, simultaneously, in the leaves of
High-performance liquid chromatography
Photodiode array detector
Limit of detection
Limit of quantification
Relative standard deviation.
The research data generated from this study are included within the article.
All the authors declare that there are no conflicts of interest.
This study was supported by the project of State Key Laboratory of Functions and Applications of Medicinal Plants, Guizhou Medical University (Grant no. FAMP201909K), the project of the Research on Traditional Chinese Medicine and Ethnic Medicine Science and Technology of Guizhou Provincial Administration of Traditional Chinese Medicine (Grant no. QZYY-2019-056), the National Key R&D Program “Research on Modernization of Traditional Chinese Medicine” (Grant no. 2017YFC1702005), the Science and Technology Foundation of Guizhou Province of China (QKHPTRC[2019]5657 and QKHPTRC[2018]5772-001), and the Program for Excellent Young Talents of Zunyi Medical University (15zy-004).