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Ionic liquid-based ultrasonic-assisted extraction coupled with HPLC to analyze isoquercitrin, trifolin and afzelin in Amygdalus persica L. flowers

BMC Chemistry volume 17, Article number: 102 (2023) Cite this article

Abstract

This study aimed to establish a method for the simultaneous determination of isoquercitrin, trifolin and afzelin in A. persica flowers by high performance liquid chromatography (HPLC) with ionic liquid as extractant and ultrasonic-assisted extraction. The effects of ionic liquid concentration, solid–liquid ratio, number of crushing mesh, ultrasonic time, extraction temperature, and ultrasonic power on the extraction yield of three target compounds were investigated using the extraction yield of target analytes as the index. According to the results of single factor experiment, the Box-Behnken design-response surface methodology (BBD) was used to optimize the extraction method and compared with the traditional extraction method. The results showed that, calibration curves had excellent linearity (R2 > 0.9990) within the test ranges. In combination with other validation data, this method demonstrated good reliability and sensitivity, and can be conveniently used for the quantification of isoquercitrin, trifolin and afzelinin A. persica flowers. And the contents of isoquercitrin, trifolin and afzelin were 64.08, 20.55 and 75.63 μg/g, respectively. The optimal process obtained by BBD was as follows: ionic liquid concentration was 1.0 mol/L, solid–liquid ratio was 1:40 g/ml, mesh sieve was 50 mesh, ultrasonic time was 40 min, extraction temperature was 50 °C, and ultrasonic power was 400 W. Under the optimal conditions, the theoretical predicted total extraction yield of the three target compounds was 159.77 μg/g, which was close to the actual extraction value (160.26 μg/g, n = 3), this result indicating that the optimal process parameters obtained by response surface methodology analysis were accurate and reliable. The method was simple, accurate and rapid for determination the contents of three active ingredients in A. persica flowers.

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Introduction

Amygdalus persica L., belonging to Rosa ceae, is widely distributed in most regions of China, and with the effect of reducing diarrhea and defecation, promoting water and reducing swelling (Fig. 1) [1]. A. persica flowers contain flavonoids, polyphenols, polysaccharides, carotenoids, vitamins, amino acids and trace elements [2, 3], which has beauty and health care functions, and is widely used in the field of food and medicine. The development of A. persica flowers wine [4], essential oil [5], cake [6, 7], and other products have been reported. In addition, A. persica flowers are currently consumed as a tea for weight loss in China. The studies show that A. persica flowers exerts anti-obesity effects in obese mice and these beneficial effects might be mediated through improved hepatic lipid metabolism by reducing lipogenesis and increasing fatty acid oxidation [8, 9]. Previous studies have revealed several pharmacological effects of A. persica flowers, including protection of the skin from ultraviolet radiation [10, 11], inhibition of melanogenesis [12], stimulation of intestinal motility [13], antioxidant and antibacterial activities [14, 15].

Fig. 1
figure 1

Amygdalus persica flowers

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As an environment-friendly solvent, compared with water and conventional organic solvents, ionic liquids had the characteristics of high ionic conductivity, low volatility, strong polarity, good dissolving and extracting ability, and high chemical stability. Ionic liquids could dissolve cellulose and destroy plant cell walls, and had a broad application prospect in the field of extraction and separation of natural products [16,17,18]. Ultrasonic-assisted extraction had been proved to significantly shorten the extraction time and improve the extraction yield in the process of assisting plant extraction. In the process of ultrasonic application, cavitation and mechanical effects would be produced, which made it easier for solvents to penetrate into plant raw materials, destroy plant cell walls and promote the release of active components [19,20,21]. Ionic liquid-based ultrasonic-assisted extraction was a green extraction technology with high efficiency and energy saving, which combines the characteristics of high efficiency cavitation effect generated by ultrasound and high solubility of ionic liquid [22]. The technology had been applied to the extraction and isolation of Paris polyphylla saponins [23], flavonoids [24], acacetin [25], pectin [26] and other active components. Box-Behnken design-response surface methodology (BBD-RSM) was a widely used method to optimize experimental conditions in recent years [27]. And BBD-RSM was a two-order experimental design method based on three levels. It adopted multivariate quadratic equation to fit the functional relationship between factors and response values, and seeked the optimal process parameters by analyzing the regression equation. In the process of optimization, software was used to optimize the whole experimental conditions with respect to the fitting degree, SNR and the significance factors of the equation, so as to seek the best extraction process parameters [28, 29].

However, there is still no related report about the ionic liquid-based ultrasonic-assisted extraction of compositions in A. persica flowers. In our previous study, the chemical constituents and coagulation activity of A. persica were investigated. The results of coagulation activity showed that isoquercitrin, trifolin and afzelin could remarkably shorten activated partial thromboplastin time, prothrombin time, thrombin time and reduce the content of fibrinogen, and had procoagulant activity in vitro [30]. Thus, on this basis, this study aimed to establish a method for the simultaneous determination of isoquercitrin, trifolin and afzelin in A. persica flowers by high performance liquid chromatography (HPLC) with ionic liquid as extractant and ultrasonic-assisted extraction.

Materials and reagents

Instruments

All the analyses were performed on a Waters 2695 liquid chromatography system (Waters, Milford, USA) equipped with a vacuum degasser, a quaternary solvent deliver system, an autosampler, a column compartment, and a w2489 UV visible detector. Kq-250db CNC ultrasonic cleaner was purchased from Kunshan Ultrasonic Instrument Co., LTD (Kunshan, China). AG285 electronic analytical balance was purchased from Mettler Toledo (Switzerland). FZ102 plant sample mill (Huanghua Zhongxing Instrument Co., LTD., Hebei). KQ-500DB ultrasonic cleaner (Kunshan Ultrasonic Instrument Co., LTD., Jiangsu). Design-Expert software (Version 8.0.6, Stat-Ease. Inc., Minneapolis, MN. USA).

Chemicals and reagents

1-butyl-3-methylimi-dazolium bromide ([BMIM]Br), 1-butyl-3-methylimidazolium tetrafluorob-orate ([BMIM]BF4), 1-butyl-3-methylimidazolium hexafluorophosphate, ([BMIM]PF6), 1-hexyl-3-methylimidazolium hexafluorophosphate ([HMIM]PF6) were purchased from Tokyo Chemical industry Co., Ltd., Tokyo, Japan.

Isoquercitrin, trifolinand and afzelin were provided by Henan Engineering Research Center for Comprehensive Utilization of Edible and Medicinal Plant Resources, Huanghe Science and Technology College, and their purities were up to 98%. Deionized water was prepared using a Milli-Q ultrapure water purifier (ELGA, Labwater, Marlow, UK). Acetonitrile and methyl alcohol were purchased from Thermo Fisher Technologies LTD. All other reagents were analytical grade.

Plant material

A. persica flowers samples were obtained from the Pharmacy of Zhang Zhongjing, in June 2022, and identified by Professor Changqin Li of Henan University. The voucher specimens were deposited in the Institute of Natural Medicine of Huanghe Science and Technology College.

Methods

Preparation of solutions

Standard solutions

The Standard solutions were prepared according to the reference [31], and the concentrations of isoquercitrin, trifolin, and afzelin were 211.3, 192.7 and 236.6 μg/mL, respectively. The concentrations of isoquercitrin, trifolin, and afzelin of the mixed standard solution were 84.4, 38.5 and 94.4 μg/mL, respectively.

Sample solutions

The sample solutions of A. persica flowers were prepared according to the reference [31]. A. persica flowers were extracted by ultrasonic extraction with a certain amount of methanol after drying and crushing. And methanol was used as blank control solution.

Chromatographic conditions

Waters e2695 HPLC system (Waters, Milford, USA) was used for the chromatographic analysis. The analytical column was an XTERRA MS C18 column (4.6 mm × 250 mm, 5 µm) (Waters, Milford, USA). The mobile phase was 0.1% formic acid solution (A)—acetonitrile (B) with gradient elution (0–10 min, 10–25% B; 10–37 min, 10–25% B; 37–41 min, 35–100% B; 41–45 min, 100–10% B). The flow rate was 1.0 mL/min and column temperature was maintained at 25 °C. The detection wavelength was set at 360 nm. The injection volume was 10 μL with needle wash.

System suitability

According to the reference [31], standard solutions, sample solution and methanol blank control solution were taken for sample injection and determination to analyze system suitability according to chromatographic conditions. All results were obtained in acceptable ranges (Fig. 2).

Fig. 2
figure 2

HPLC chromatograms of A. persica flowers (A), reference substances (B) and methanol blank control (C). Note 1. isoquercitrin; 2. trifolin; 3. afzelin

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Investigation of linear relations

According to the reference [31], regression equation and each coefficient (R2) were obtained using standard solutions. The results were presented in Table 1. All the marker compounds showed good linearity within the test range (R2 > 0.9990).

Table 1 Regression equation and linear range of three active ingredients
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Optimization of ultrasonic assisted extraction technology

After selecting the extractant, ionic liquid concentration (0.2, 0.4, 0.6, 0.8 and 1.0 mol/L), solid–liquid ratio (1:20, 1:30, 1:40, 1:50 and 1:60 g/mL), mesh number (20, 30, 40, 50 and 60 mesh), ultrasonic time (20, 30, 40, 50 and 60 min), extraction temperature (30, 40, 50, 60 and 70 °C) and ultrasonic power (100, 200, 300, 400 and 500 W) were used as single factor experimental conditions to investigate the effect of single factor on the extraction efficiency of three compounds in A. persica flowers. And optimize each single factor. On this basis, combined with Box–Behnken design-response surface experiment, the extraction technology was optimized.

Results

Selection of dispersant

In this test, methanol, acetonitrile and ethanol were selected for extraction, and the results showed that methanol had the highest extraction yield of target compounds (Fig. 3). Then, on this basis, ionic liquid was added to further improve the extraction yield of the target compounds in the sample.

Fig. 3
figure 3

Influence of dispersant on the extraction yields of three target analytes

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Selection of ionic liquid

The difference of extraction solution had great influence on the extraction yield of active components. In this test, 0.6 mol/L [BMIM]BF4, [BMIM]PF6, [BMIM]Br, [HMIM]PF6 methanol solutions and pure methanol solution were selected as the extraction solution. After crushing, the A. persica flowers were screened 40 mesh, the solid–liquid ratio was 1:30 g/mL, the ultrasonic time was 40 min, the extraction temperature was 30 °C and the ultrasonic power was 200 W. The extraction effect of different ionic liquids on the target analytes were compared, and the results were shown in Fig. 4.

Fig. 4
figure 4

Effect of the type of ionic liquid on the extraction yields of three target analytes

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The results showed that the extraction yield of the four ionic liquid solutions for the target analytes were significantly higher than that of methanol solution, and the extraction yield of [HMIM]PF6 methanol solution for isoquercitrin and trifolin were the highest, and the extraction yield of [BMIM]BF4 and [HMIM]PF6 for afzelin were the similar. Therefore, [HMIM]PF6 was selected as the extraction solvent for the follow-up study.

Analysis of single factor experimental

Selection of ionic liquid concentrations

On the basis of the above optimization factors, other conditions being the same, using 0.2, 0.4, 0.6, 0.8 and 1.0 mol/L [HMIM]PF6 methanol solution as the extraction agent, the effect of ionic liquid concentration on the extraction yields of the target analytes were compared.

In Fig. 5, when the ionic liquid concentration was 0.8 mol/L, the extraction yield of the target analytes reached the maximum value. However, as the ionic liquid concentration continued to increase, the extraction yields gradually decreased. The reason may be related to the viscosity of the extraction solution. If the concentration of ionic liquid was too high, the viscosity of the extraction solution will also increase, and the diffusion ability of the extractant will become worse, which makes it difficult for the extractant to penetrate into the interior of A. persica flowers cells, thus reducing the dissolution ability of [HMIM]PF6 to the target analytes [32]. Therefore, the concentration of [HMIM]PF6 was selected as 0.8 mol/L.

Fig. 5
figure 5

Effect of ionic liquid concentrations on the extraction yields of three target analytes

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Selection of solid–liquid ratio

Based on the above optimization conditions, the effects of solid–liquid ratios of 1:60, 1:50, 1:40, 1:30 and 1:20 g/mL on the extraction yield of the target analytes were investigated.

As shown in Fig. 6, with the increase of solid–liquid ratio, the extraction yields of the three compounds gradually increased. When the solid–liquid ratio was 1:40 g/mL, the extraction yield of isoquercitrin increased slowly. However, the extraction yield of trifolin and afzelin reached the maximum, and the extraction yields tended to decrease as the solid–liquid ratio continued to increase. It may be that as the solid–liquid ratio continues to increase, the osmotic pressure of the solvent increases, resulting in the dissolution of other impurities and a decrease in the extraction yields of the target analytes. Too small solid–liquid ratio will lead to incomplete extraction of active components in the medicinal materials, while too large will lead to waste of solvents. Therefore, the solid–liquid ratio of 1:40 g/mL was selected.

Fig. 6
figure 6

Effect of solid–liquid ratio on the extraction yield of three target analytes

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Selection of mesh sieve

During the extraction of the effective components of traditional Chinese medicine, the size of the medicinal material had a great influence on the extraction yield. The smaller the particle size, the larger the effective contact area with the solvent and the higher the extraction yield. On the basis of the above optimization conditions, the influence on the extraction yield of the target analytes were investigated when the number of minced mesh were 20, 30, 40, 50 and 60 mesh, respectively. The results were shown in Fig. 7.

Fig. 7
figure 7

Effect of mesh sieve on the extraction yields of three target analytes

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In Fig. 7, the 50 mesh sampling sieve had the highest extraction yield for the target analyte, because the smaller the powder particle size, the easier it is to extract the active ingredients contained in the sample. However, when the powder particle size was too small, it was easy to be condensed into clusters by ionic liquid, thus preventing the release of the active components in the samples. Therefore, the sifted mesh number was 50.

Selection of ultrasonic time

Based on the above optimization conditions, the influence of extraction time of 20, 30, 40, 50 and 60 min on the yield of target analytes were investigated.

In Fig. 8, with the increase of ultrasonic extraction time, the extraction yield of the target extracts increased. When the ultrasonic extraction time increased to 30 min, the extraction yield reached the peak. The ultrasonic extraction time continued to increase, and the extraction rate tended to be gentle and decreased. The reason may be that the target extracts basically reached saturation and no longer dissolve obviously. In addition, too long extraction time will destroy the structure of flavones, and the extraction yield will decrease [33]. Therefore, 30 min of ultrasonic extraction was selected as the optimal condition in this experiment.

Fig. 8
figure 8

Effect of ultrasonic time on the extraction yield of three target analytes

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Selection of extraction temperature

Based on the above optimization conditions, the influence of extraction temperature at 30, 40, 50, 60 and 70 °C on the extraction yield of the target analytes were investigated. The result was shown in Fig. 9.

Fig. 9
figure 9

Effect of extraction temperature on the extraction yield of three target analytes

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With the increase of extraction temperature, the extraction yield of target analytes gradually increased. When the extraction temperature was 50 °C, the extraction yield reached the maximum, but the temperature continued to rise, and the extraction rate showed a trend of decreasing. The reason may be that with the increase of the temperature of the system, the movement rate and frequency of the ionic liquid are increasing, which makes it easier to penetrate into the peach blossom tissue cells, accelerate the dissolution of the target analytes, and thus increase the extraction rate of the target analyte [34]. However, if the temperature of the system continues to increase, the structure of the target analyte would be destroyed. It was also possible that with the increase of temperature, the dissolution of other contents in the cell increases, resulting in the increase of solution viscosity, which affects the outward dissolution of the target analyte, thus reducing the extraction yield. Therefore, the extraction temperature of 50 °C was selected.

Selection of ultrasonic power

Based on the above optimization conditions, the influence of ultrasonic power of 100, 200, 300, 400 and 500 W on the extraction yield of the target analytes were investigated.

The results were shown in Fig. 10. When the ultrasonic power was 400 W, the extraction rate of the three target compounds reached the maximum. With the increase of ultrasonic power, the breaking effect of ultrasonic on plant cells gradually increased, which could accelerate the dissolution of target components. However, when the destructive power exceeds a certain limit, the dissolved impurities also increase, and the extraction rate does not increase significantly but shows a downward trend. Therefore, ultrasonic power of 400 W was selected.

Fig. 10
figure 10

Effect of ultrasonic power on the extraction yield of three target analytes

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Box–Behnken design-response surface experiment

Synthesize the above single factor experiments, ionic liquid concentration (A), solid–liquid ratio (B), number of crushing mesh (C) and extraction time (D) were selected as independent variables of the response surface model. The fixed ultrasonic temperature and ultrasonic power were 50 °C and 400 W, respectively. The total extraction yield of three compounds from A. persica flowers was taken as the evaluation index and designed by Design-Expert 8.0.6 Trail software. Each factor involved three levels of high, low and medium, which were represented by 1, 0 and − 1, respectively. The variable levels were shown in Table 2 and the test results were shown in Table 3.

Table 2 BBD for the independent variables and corresponding response values
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Table 3 Experimental design and results of BBD
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Design-Expert 8.0.6 Trail software was used to carry out quadratic polynomial stepwise regression fitting on the test data, and the quadratic multiple regression equation was established: Y = 106.83 + 9.53A + 1.22B + 0.83C − 0.18D − 0.12AB − 0.03AC − 0.21AD − 6.70BC + 2.60BD + 2.18CD + 0.4.12A2 − 0.01B2 − 5.48C2 + 3.54D2. The variance analysis of regression model is shown in Table 4. P < 0.0001 of the regression model indicated that the regression model was extremely significant. The missing fitting item P > 0.05 was not significant, indicated that the model was valid. The coefficient of determination R2 of the model was 0.9027, and the coefficient of determination R2Adj = 0.9054. The coefficient of determination R2 of the model and the coefficient of determination R2Adj of correction were both high and close to each other, indicated that the model had high accuracy and universality, and could be used to analyze and predict the effect of ionic liquid on the extraction of three target compounds.

Table 4 ANOVA for the fitted quadratic polynomial model for optimization of extraction parameters
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The primary terms A, C, D and B2 of the model had extremely significant effects on the total extraction yield of the three target compounds (P < 0.01), and the BC had significant effects on the total extraction yield (P < 0.05). There was no significant difference between primary term B, AB, AC, AD, BD, CD, A2, C2 and D2 (P > 0.05). The F value of single factor also reflected the influence degree of each factor on the total extraction yield of target compounds. According to the results, the factor that had the greatest influence on the total extraction yield was the solid–liquid ratio (D).

The response surface diagram could significantly reflect the strength of interaction between various factors. The Design-Expert 8.0.6 Trail software was used to analyze the response surface diagram, and the influence of the interaction of various factors on the response value can be obtained. The results were showed in Fig. 11. If the response surface was steeper, it indicated that the factor had a greater influence on the total extraction yield of the target analytes, and the response value was more sensitive to the change of extraction conditions. If the response surface was relatively flat, it indicated that the fluctuation of this factor had little influence on the response value. In Fig. 11, it could be seen from the steepness of the response surface diagram that the interaction of BC factor was the strongest, while that of AD factor was the weakest. With the increase of solid–liquid ratio, the total extraction rate of the three compounds increased slowly to the maximum value and then decreased gradually. The total extraction rate increased with the increase of ionic liquid concentration. The extraction yield increased with the increase of the number of crushing mesh, and then the extraction rate changed little with the increase of the number of crushing mesh.

Fig. 11
figure 11

The interactive effect of solid-liquid ratio and ionic liquid concentration (A), number of crushing mesh and ionic liquid concentration (B), extraction time and ionic liquid concentration (C), number of crushing mesh and solid-liquid ratio (D), extraction time and solid-liquid ratio (E), number of crushing mesh and extraction time (F) on the total extraction yield of three compounds from A. persica flowers

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The regression equation was further analyzed by the Design-Expert 8.0.6 Trail software, and the optimal process parameters were obtained as follows: ionic liquid concentration was 1.0 mol/L, solid–liquid ratio was 1:40 g/ml, number of crushing mesh was 50 mesh, ultrasonic time was 40 min, extraction temperature was 50 °C, and ultrasonic power was 400 W. Under the optimal conditions, the theoretical predicted total extraction yield of the three target compounds was 159.77 μg/g, which was close to the actual extraction value (160.26 μg/g, n = 3), this result indicating that the optimal process parameters obtained by response surface methodology analysis were accurate and reliable.

Method validation

Precision test, repeatability test, stability test and recovery test indicated that the the three active ingredients (isoquercitrin, trifolin and afzelin) in A. persica flowers achieved better separation. They had good linearity in a certain mass concentration range (R2 > 0.9990), good precision (RSD < 1.79%), repeatability (RSD < 1.80%) and stability (RSD < 2.32%), and the average recoveries (n = 6) were 98.72–99.25% with RSD of 0.83–2.41%. The established HPLC method was simple to operate, high sensitivity, stable and reliable, and had good repeatability. It can be used for quality control and evaluation of A. persica flowers. The contents of isoquercitrin, trifolin and afzelin in A. persica flowers were 64.08, 20.55 and 75.63 μg/g, respectively.

Discussion

According to the reference [35, 36], the three components were scanned in the wavelength range of 200–400 nm, and the three components had a better linear relationship at 360 nm. Meanwhile, the separation effect of various mobile phase systems was investigated, and the influence of different mobile phase systems on the chromatographic peak separation degree, peak time and peak shape was analyzed. Finally, acetonitrile-0.1% formic acid solution was selected as the mobile phase.

In this study, methanol solution with ionic liquid added had a higher extraction yield for the target analytes than pure methanol solution, because ionic liquid, as a new solvent, had a higher solubility for cellulose, and the primary cell wall of Chinese medicinal plants was mainly composed of cellulose, which was the main obstacle to solvent extraction of bioactive components. The dissolution of cellulose promoted the dissolution of active ingredients and improved the extraction efficiency [37]. In addition, ionic liquid had high viscosity and low mass transfer efficiency during extraction of pure ionic liquid. Therefore, ionic liquid aqueous solution and methanol solution were commonly used as extractant. In this way, the viscosity of extractant was reduced, mass transfer was enhanced, energy consumption was reduced, and extraction rate was improved.

By comparing the effects of [BMIM]BF4, [BMIM]PF6, [BMIM]Br, [HMIM]PF6 methanol solution on extraction yields of isoquercitrin, trifolin and afzelin, it was found that [HMIM]PF6 had more advantages than the other three ionic liquids. Wu et al. compared the extraction effect of five ionic liquids with different chain lengths on tanshinone, tanshinone I and tanshinone IIA under ultrasonic assistance, and found that the short-chain ionic liquid was ineffective for tanshinone extraction, and the extraction effect was effective only when the chain length was longer than 10, and the longer the alkyl chain of ionic liquid, the stronger the extraction ability of tanshinone [38]. Wei et al. investigated the extraction rate of saponins from quinoa by a series of imidazole ionic liquids with different compositions, and found that the extraction rate was the highest when the carbon chain length of the ionic liquid was 4 [39]. Ma et al. showed that the extraction rate of alkaloids increased with the increase of cationic alkyl side chain length of ionic liquid, and ionic liquid with chain-like side chain had better extraction ability of alkaloids [40]. It could be seen that both the cation and anion of ionic liquid have influence on the extraction efficiency. However, the specificity and regularity of different types of ionic liquids for the extraction of different types of active ingredients have not been found, which needs further research.

Conclusion

In this study, the contents of isoquercitrin, trifolin and afzelin in A. persica flowers were determined by high performance liquid chromatography (HPLC) with ionic liquid as extractant and ultrasonic-assisted extraction technology for the first time and the optimal extraction conditions were determined by single factor test and response surface method. And under the optimal technological conditions, the contents of isoquercitrin, trifolin and afzelin in A. persica flowers were 64.08, 20.55 and 75.63 μg/g, respectively. Environmentally friendly reagent was used as extraction agent, which improved extraction efficiency, avoided the pollution of organic solvent to the environment, and reduced the harm to human body. And it had important reference significance for the innovation of extraction methods of active ingredients of traditional Chinese medicine. However, the research on the mechanism of extraction and separation of ionic liquid and its action law are not clear at present. Therefore, in the future research work, the interaction between A. persica flowers and the molecular structure of ionic liquid will be further studied based on the molecular model, and the action law of ionic liquid extraction of compounds will be further clarified.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

References

  1. Chinese Academy of Sciences. China Flora Editorial Board Flora of China, vol. 38. Beijing: Science Press; 1986. p. 17–8.

    Google Scholar 

  2. Komar-Tyomnaya LD, Paliy AE, Startseva OV, Paliy IN. Content of phenolic compounds in ornamental peach flowers. Acta Hortic. 2021;2021(1324):351–6.

    Article  Google Scholar 

  3. Zhao BT, Sun M, Cai ZX, Su ZW, Li JY, Shen ZJ, et al. Aroma profiling analysis of peach flowers based on electronic nose detection. Horticulturae. 2022;8(10):875.

    Article  Google Scholar 

  4. Zhou L. The medicinal food therapy of Peach blossom. Shandong Food Sci Technol. 2004;11:24.

    Google Scholar 

  5. Sun JC, Huang Y, Wang N, Gao HK, Zhang H. Biological activity analysis and skin care effect of Peach blossom essential oil. J Capital Normal Univ (Nat Sci Ed). 2020;41(6):36–40.

    Google Scholar 

  6. Wang BH, Lei S, Gu LH, Qu LL. Optimization of peach blossom cake formula based on fuzzy mathematics sensory evaluation and orthogonal experiment. Food Sci Technol. 2015;40(10):165–70.

    Google Scholar 

  7. He J, Tang LJ. Study on the development of peach blossom cookie. Cereals Oils. 2020;33(10):80–2.

    Google Scholar 

  8. Lee D, Kim JY, Qi YT, Park SS, Lee HL, Yamabe N, et al. Phytochemicals from the flowers of Prunus persica (L.) Batsch: anti-adipogenic effect of mandelamide on 3T3-L1 preadipocytes. Bioorg Med Chem Lett. 2021;2021(49):128326.

    Article  Google Scholar 

  9. Song JB, Kim YS, Kim L, Park HJ, Lee DH, Kim H. Anti-obesity effects of the flower of Prunus persica in high-fat diet-induced obese mice. Nutrients. 2019;11(9):2176.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Liu JC, Zhang QL, Jiao ZG, Zhang CL, Lv ZZ, Liu H, et al. Inhibitory effect of peach flower extract on tyrosinase and its kinetics analysis. J Fruit Sci. 2014;31(5):836–41. https://doi.org/10.13925/j.cnki.gsxb.20140189.

    Article  CAS  Google Scholar 

  11. Kwak CS, Yang J, Shin CY, Chung JH. Topical or oral treatment of peach flower extract attenuates UV-induced epidermal thickening, matrix metalloproteinase-13 expression and pro-inflammatory cytokine production in hairless mice skin. Nutr Res Pract. 2018;12(1):29–40.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Murata K, Takahashi K, Nakamura H, Itoh K, Matsuda H. Search for skin-whitening agent from Prunus plants and the molecular targets in melanogenesis pathway of active compounds. Nat Prod Commun. 2014;9(2):185–8.

    CAS  PubMed  Google Scholar 

  13. Han W, Xu JD, Wei FX, Zheng YD, Ma JZ, Xu XD, Wei ZG, Wang W, Zhang YC. Prokinetic activity of Prunus persica (L.) Batsch flowers extract and its possible mechanism of action in rats. Bio Med Res Int. 2015;2015(2015):569853.

    Google Scholar 

  14. Zeng Z, Liu HG, Hong YP, Wu GQ, Lu Q, Xu XX, et al. A study on purification of total flavonoids from Prunus persica by macroporous resin and their antioxidant activity. Acta Agriculturae Univ Jiangxiensis. 2017;39(1):182–9.

    Google Scholar 

  15. Wei Q, Peng XY. Chemical components of essential oils of the flower, leaf, stem and fruit from Amygdalus persica var. persica f. duplex and their antioxidant, antimicrobial effects. Chin J Appl Chem. 2016;33(8):945–50.

    CAS  Google Scholar 

  16. Shi MJ, He N, Li WJ, Li CQ, Kang WY. Simultaneous determination of myricetrin, quercitrin and afzelin in leaves of Cercis chinensis by a fast and effective method of ionic liquid microextraction coupled with HPLC. Chem Cent J. 2018;12(1):23.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Noorul AM, Siti HB, Atikah AA, Ambavaram VBR, Mohamed IAM, Muhammad M. Synthesis, characterization, ecotoxicity and biodegradability evaluations of novel biocompatible surface active lauroyl sarcosinate ionic liquids. Chemosphere. 2019;2019(229):349–57.

    Google Scholar 

  18. Li CQ, Cui YP, Lu J, Liu CY, Chen ST, Ma CY, et al. Ionic liquid-based ultrasonic-assisted extraction coupled with HPLC and artificial neural network analysis for Ganoderma lucidum. Molecules. 2020;25(6):1309.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Liao JQ, Xue HK, Li JL. Extraction of phenolics and anthocyanins from purple eggplant peels by multi-frequency ultrasound: Effects of different extraction factors and optimization using uniform design. Ultrason Sonochem. 2022;90:106174.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Liao JQ, Guo ZR, Yu GC. Process intensification and kinetic studies of ultrasound-assisted extraction of flavonoids from peanut shells. Ultrason Sonochem. 2021;76:105661.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Liao JQ, Peng B, Chu XH, Yu GC. Effects of process parameters on the extraction of total anthocyanins from purple sweet potatoes by ultrasound with wide frequency and its kinetics study. J Food Process Preserv. 2022;46:e16732.

    Article  CAS  Google Scholar 

  22. Xia ZY, Li DD, Li Q, Zhang Y, Kang WY. Simultaneous determination of brazilin and protosappanin B in Caesalpinia sappan by ionic-liquid dispersive liquid-phase microextraction method combined with HPLC. Chem Cent J. 2017;11(1):1–11.

    Article  Google Scholar 

  23. Liu JZ, Lin ZX, Kong WH, Zhang CC, Yuan Q, Fu YJ, et al. Ultrasonic-assisted extraction-synergistic deep eutectic solvents for green and efficient incremental extraction of Paris polyphylla saponins. J Mol Liq. 2022;368(PA):120644.

    Article  CAS  Google Scholar 

  24. Li WJ, Shi MJ, Wang PY, Guo XC, Li CQ, Kang WY. Efficient determination of three flavonoids in Malus pumila flowers by ionic liquid-HPLC. J Mol Liq. 2018;2018(263):139–46.

    Article  Google Scholar 

  25. Wei JF, Cao PR, Wang JM, Kang WY. Analysis of tilianin and acacetin in Agastache rugosa by high-performance liquid chromatography with ionic liquids-ultrasound based extraction. Chem Cent J. 2016;2016(10):76.

    Article  Google Scholar 

  26. An SH, Zhao FF, Wei J, Sun LN, Wu B. Optimization of sonication-assisted extraction of pectin from seed melon by response surface methodology. Food Ind Sci Technol. 2017;38(11):270–5.

    Google Scholar 

  27. Prajapati P, Shah H, Shah SA. Implementation of QRM and DoE-based quality by design approach to VEER chromatography method for simultaneous estimation of multiple combined dosage forms of paracetamol. J Pharm Innov. 2022;17:2–18.

    Article  Google Scholar 

  28. Prajapati PB, Bodiwala K, Shah SA. Analytical quality-by-design approach for the stability study of thiocolchicoside by eco-friendly chromatographic method. J Planar Chromatogr. 2018;31(6):477–87.

    Article  CAS  Google Scholar 

  29. Prajapati P, Patel R, Patel D, Shah S. Design of experiments (DoE) - based enhanced quality by design approach to hydrolytic degradation kinetic study of capecitabine by eco-friendly stability indicating UV-visible spectrophotometry. Am J Pharm Tech Res. 2020;10(6):115–33.

    CAS  Google Scholar 

  30. Zhang JJ, Yin ZH, Chen L, Yang BC, Kang WY. Chemical constituents and coagulation activity of Amygdalus persica L. flowers. J Food Qual. 2021;2021:1–7.

    Google Scholar 

  31. Zhang JJ, Chen XD, Yin ZH, Guo QF, Yang BC, et al. The content variation of four active components in Amygdalus persica L. during different harvesting periods. J Food Qual. 2022;2022:1–7.

    Google Scholar 

  32. Shi MJ, Zhang JJ, Liu CY, Cui YP, Li CQ, Liu ZH, et al. Ionic liquid-based ultrasonic-assisted extraction to analyze seven compounds in Psoralea fructus coupled with HPLC. Molecules. 2019;24(9):1699.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Liu XQ, Niu Y, Liu JQ, Shi MJ, Xu RA, Kang WY, et al. Efficient extraction of anti-inflammatory active ingredients from Schefflera octophylla leaves using ionic liquid-based ultrasonic-assisted extraction coupled with HPLC. Molecules. 2019;24(16):2942.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Verma R, Banerjee T. Liquid–liquid extraction of lower alcohols using menthol-based hydrophobic deep eutectic solvent: experiments and COSMO-SAC predictions. Ind Eng Chem Res. 2018;57(9):3371–81.

    Article  CAS  Google Scholar 

  35. Li CQ, Cui YP, Lu J, Meng LJ, Ma CY, Liu ZH, et al. Spectrum-effect relationship of immunologic activity of Ganoderma lucidum by UPLC-MS/MS and component knock-out method. Food Sci Hum Well. 2021;10(3):278–88.

    Article  CAS  Google Scholar 

  36. Wang TY, Guo S, Ren XM, Du JF, Bai L, Cui XQ, et al. Simultaneous quantification of 18 bioactive constituents in Ziziphus jujuba fruits by HPLC coupled with a chemometric method. Food Sci Hum Well. 2022;11(4):771–80.

    Article  CAS  Google Scholar 

  37. Passos H, Freire MG, Coutinho JAP. Ionic liquid solutions as extractive solvents for value-added compounds from biomass. Green Chem. 2014;16(12):4786–815.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Wu KK, Zhang QL, Liu Q, Tang F, Long YM, Yao SZ. Ionic liquid surfactant-mediated ultrasonic-assisted extraction coupled to HPLC: application to analysis of tanshinones in Salvia miltiorrhiza bunge. J Sep Sci. 2009;32(23–24):4220–6.

    Article  CAS  PubMed  Google Scholar 

  39. Wei R, Lin X, Zhou KX, Cheng XL, Zhao W. Extraction and antibacterial activities of saponins from quinoa wheat bran by ultrasound-assisted ionic liquids. Food Sci Technol. 2021;46(11):203–9.

    CAS  Google Scholar 

  40. Ma CH, Wang SY, Yang L, Zu YG, Yang FJ, Zhao CJ, et al. Ionic liquid-aqueous solution ultrasonic-assisted extraction of camptothecin and 10-hydroxycamptothecin from Camptotheca acuminata samara. Chem Eng Process. 2012;57–58:59–64.

    Article  Google Scholar 

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Acknowledgements

We would like to express our appreciation to Prof. Changqin Li for the authentication of plant species.

Funding

This study received financial support from the Key Research Projects of Colleges and Universities in Henan province (21B360006), Innovation and Entrepreneurship training Program for College students in Henan Province (202211834037) and Tackling-Plan Project of Henan Department of Science and Technology (232102310337).

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Authors and Affiliations

  1. Comprehensive Utilization of Edible and Medicinal Plant Resources Engineering Technology Research Center, Huanghe Science and Technology College, Zhengzhou, 450063, Henan Province, China

    Wei Zhang, Zhenhua Yin, Qingfeng Guo, Lin Chen & Juanjuan Zhang

  2. Zhengzhou Key Laboratory of Synthetic Biology of Natural Products, Huanghe Science and Technology College, Zhengzhou, 450063, China

    Zhenhua Yin, Qingfeng Guo, Lin Chen & Juanjuan Zhang

  3. Henan Joint International Research Laboratory of Drug Discovery of Small Molecules, Huanghe Science and Technology College, Zhengzhou, 450063, China

    Zhenhua Yin, Qingfeng Guo, Lin Chen & Juanjuan Zhang

Authors
  1. Wei Zhang
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  2. Zhenhua Yin
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  3. Qingfeng Guo
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  4. Lin Chen
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  5. Juanjuan Zhang
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Contributions

WZ and JJZ conceived and designed the experiments. WZ and FQG performed the experiments. LC, HZY and JJZ made substantial contributions to the interpretation of data. HZY, FQG and WZ wrote the first draft of the manuscript. LC and JJZ critically read and revised the paper. All authors read and approved the final manuscript.

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Correspondence to Juanjuan Zhang.

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Zhang, W., Yin, Z., Guo, Q. et al. Ionic liquid-based ultrasonic-assisted extraction coupled with HPLC to analyze isoquercitrin, trifolin and afzelin in Amygdalus persica L. flowers. BMC Chemistry 17, 102 (2023). https://doi.org/10.1186/s13065-023-01018-w

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  • DOI: https://doi.org/10.1186/s13065-023-01018-w

Keywords

BMC Chemistry

ISSN: 2661-801X

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