1. bookTom 34 (2022): Zeszyt 2 (December 2022)
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Development of dandelion (Taraxacum spp.) quality evaluation technology based on phenolic acids

Data publikacji: 18 Nov 2022
Tom & Zeszyt: Tom 34 (2022) - Zeszyt 2 (December 2022)
Zakres stron: 187 - 209
Otrzymano: 17 Jun 2022
Przyjęty: 03 Oct 2022
Informacje o czasopiśmie
License
Format
Czasopismo
eISSN
2083-5965
Pierwsze wydanie
01 Jan 1989
Częstotliwość wydawania
2 razy w roku
Języki
Angielski
INTRODUCTION

Dandelion (Taraxacum spp.) is a phytoalimurgic plant having a worldwide distribution, and it has antioxidant, anti-bacterial and anti-inflammatory effects (Grauso et al., 2019). Dandelion is a popular medicinal and edible plant in China. It has been used for tea, feed additives and pharmaceutical raw materials (González-Castejón et al., 2012). However, with the rising demand and price, producers overwhelmingly focussed on the yield; and the result was, particularly given the absence of related evaluation standards, a poor controllability over quality (Chen et al., 2021; Li et al., 2021).

At present, dandelion quality evaluation in China is reliant exclusively on China Pharmacopoeia. China Pharmacopoeia (Ed. 2015) stipulated that caffeic acid content in dandelion should be at least 0.02%; the newly released version stipulated that cichoric acid content shall be >0.45%. However, most researchers pointed out that very complicated effective compounds have been found in dandelion, including phenolic acids, flavonoids and terpenes, etc., and that accordingly, using the concentration of a single chemical component as a quality evaluation standard would be inadequate to fully reflect dandelion quality (Chen et al., 2021; Li et al., 2021).

According to the theory of traditional Chinese medicine, dandelion functions mainly include heat-clearing and detoxifying effects, and these are attributed to the rich phenolic acids in dandelion, such as caffeic acid, cichoric acid and chlorogenic acid (González-Castejón et al., 2012). These phenolic acids possess similar chemical molecular structure and chemical properties (Grauso et al., 2019; Tajner-Czopek et al., 2020). Therefore, we may infer that the most reasonable way to evaluate the quality of dandelion intended for therapeutic usage would be to determine the concentration of a few main phenolic acid compounds as key indices.

The usage of multiple indices or statistical methods to evaluate plant traits finds broad application in the literature. Li et al. (2021) evaluated dandelion (Taraxacum mongolicum Hand.-Mazz.) quality with methods of hierarchical cluster analysis, principal component analysis and chromatographic fingerprint analysis though the comparison of multiple components in dandelion. Wu et al. (2020b) evaluated the salt-tolerant ability of sunset mallow (Abelmoschus manihot (L.) Medik) with linear regression method through the analysis of multiple biochemical indices. Chen et al. (2012) evaluated the drought tolerance of wheat (Triticum aestivum L.) using a membership function value method through the analysis of 14 biological indices. These methods produced a comprehensive evaluation value by calculating the weight of each index through complex statistics, resultantly avoiding conflict with the single evaluation index. However, these methods required cumbersome weight calculation, which people not having the requisite specialised skills would find unable to master; additionally, the complex nature of the calculation tasks involved in these methods limited their actual application. Therefore, we developed a comprehensive quality evaluation method for dandelion based on multiple phenolic acid compounds considering the aspects of actual popularisation and application, so as to supplement the deficiency of the single index used in the current China Pharmacopoeia.

MATERIALS AND METHODS
Dandelion samples

Since from 2017, we have collected 96 dandelion resources from different regions of China and together these have been transplanted to the demonstration base of the Institute of Coastal Agriculture, Hebei Academy of Agriculture and Forestry Sciences (North China, 39.23°N, 118.57°E). These resources were cultured in different sites involving greenhouse, saline-alkali land and common field, and harvested in different seasons (spring and autumn). Finally, we obtained a total of 578 dandelion samples. The aboveground parts were harvested after cultivation for 1 month. For related field management, the standard, “Technical specification for cultivation of dandelion in saline-alkali soil” was referred to DB13/T 2986-2019. Dandelion samples were washed and dried at 60 °C. Dry samples were ground and passed by 100-mesh sieve. Water content in the resulting fine powders was controlled <13% according to the stipulation of China Pharmacopoeia. Parts of dandelion samples with some indices were assigned to testing companies, and related details of dandelion samples and examination results are shown in Table S1 in Supplementary Materials.

Phenolic compounds extraction

Phenolic acids were extracted based on our previously published method (Wu et al., 2020a). About 0.5 g dry powder was mixed with 15 mL cellulase solution (cellulase dosage, 0.1%; enzyme activity, 3,000 U · g−1) and placed in water bath at 60 °C for 30 min. Then, 15 mL of methanol was added, and ultrasonic treatment was continued for 30 min (ultrasonic power 400 W). The extract was cooled to room temperature, filtered with a 0.45 μm membrane and then examined using high performance liquid chromatography (HPLC).

Phenolic compounds’ examination

The extract was checked by HPLC (HPLC 1200 series, Agilent Technologies Inc., USA) equipped with chromatographic column (Mars ODS-AQ (4.6 mm × 250 mm, 5 μm), Hming Technologies Co. Ltd, China) under our optimised HPLC conditions based on the technical specifications laid down under China Pharmacopoeia (Eds 2015 and 2020). The optimal determination conditions based on our equipment were the following: injection volume, 0.5 μL; flow rate, 1 mL · min−1; methanol:0.2% phosphoric acid ratio, 40:60; detection wavelength, 327 nm; and detection time, 15 min. Meanwhile, the contents of four kinds of phenolic acids were determined by the following linear regression equations (Table 1) based on quantitative analysis with standard chemicals of caftaric acid, chlorogenic acid, caffeic acid and cichoric acid (Li et al., 2021).

Linear regression equations for four compounds in dandelion.

Compounds Equations R2 Valid scope (mg · mL−1)
Caftaric acid Y = 0.6342x + 1.0263 0.9965 10–70
Chlorogenic acid Y = 0.4946x − 0.8089 0.9669 5–30
Y = 0.6148x + 0.9279 0.9997 30–105
Caffeic acid Y = 0.4605x − 0.8895 0.9905 5–30
Y = 0.39x + 0.814 0.9994 30–105
Cichoric acid Y = 0.4564x + 3.0071 0.9995 45–220
Y = 0.569x − 60.97 0.9502 240–512

Y represents the component content (μg · mL−1), and × the HPLC peak area.

HPLC, high performance liquid chromatography.

Data analysis
Determination of main evaluation indices

Fifteen random HPLC detection spectrums from 578 dandelion samples were imported into the software of Similarity Evaluation System for Chromatographic Fingerprint of TCM published by Chinese Pharmacopoeia Commission (version 2012, Beijing, China) using median method and an adjustment retention time (RT) of 0.1 min. According to the combination analysis of similarity assessment and matching numbers for each component shown in HPLC spectrum, the common and dominant phenolic compounds were chosen as the main index for quality evaluation (Wu et al., 2020).

Compound content classification

Data pertaining to the weights of the main compounds contained in the dandelion samples, together with data from quality evaluation related references, were analysed by SPSS 19.0 software (IBM SPSS Statistics, USA) using descriptive statistics involving mean, mode, median and frequency. Then, based on statistics and general level division methods with a certain percentage used in the literature cited in the present article or in the industrial standards in force in China, each compound content was divided into five levels from low to high, of which Level 1 represented the highest content.

Dandelion quality evaluation

Using the equal weight average calculation method, the content level of each component was converted into a quality index (QI) according to the following formula: QI=Σ Gi/(n×5)×100 {\rm{QI}} = \Sigma {{{\rm{G}}_{\rm{i}}}/\left( {{\rm{n}} \times 5} \right) \times 100} where Gi represents the content level of each component and n the number of components; here n was 4 and the level numbers were 5.

According to the QI formula, totally 17 QIs were obtained and then the probability or proportion of each QI was calculated based on the completely random combination of all levels for four components. Considering that setting industry standards in China is possible only by satisfying the requirements of high standard and universality, here we stipulated that the probability of QI <1% be classified into Grade 1, indicating the super high content, while most samples were classified into Grades 2–5, and the overall hierarchical structure was spindle-shaped.

RESULTS AND DISCUSSION
Selection of evaluation indices based on HPLC determination result

We tested HPLC conditions following the method from China Pharmacopoeia and found that some peaks, except for caffeic acid or cichoric acid, were obviously shown in the HPLC spectrum, but the separation of these peaks was unclear (Figure 1A). Thus, we adjusted HPLC conditions and obtained an ideal HPLC spectrum (Figure 1B). Through HPLC fingerprint comparison analysis, totally 17 compounds were found, of which four compounds (corresponding retention times, ~4.2 min, ~4.7 min, ~6.1 min and ~10.0 min, respectively) showed 100% matching numbers with the reference fingerprint, and they were identified as caftaric acid, chlorogenic acid, caffeic acid and cichoric acid by standard chemicals (Figure 1C and Table S2 in Supplementary Materials). The four compounds possessed similar molecular structures and belonged to phenolic acids (González-Castejón et al., 2012; Tajner-Czopek et al., 2020). Thus, the four compounds were preliminarily considered as candidates for main quality evaluation indices.

Figure 1

Optimisation of HPLC determination conditions and fingerprint analysis. (A) HPLC spectrum using determination conditions from China Pharmacopoeia; (B) optimised HPLC conditions; (C) fingerprint analysis, of which S1–S15 represents randomly selected dandelion HPLC spectrums, R indicates the reference fingerprint generated by the comparison of 15 samples and the dot on the fingerprint map represents a compound found in dandelion. HPLC, high performance liquid chromatography.

Dandelion is theorised to contain complex components and the presence of all of these components has not been proved as yet, and neither have the therapeutic effectiveness or other useful functions of a majority of these components been demonstrated as yet (Fatima et al., 2018). We referred to the traditional Chinese medicine theory that attributes heat-clearing and detoxifying effects to dandelion, and additionally considered the inference that these effects derive mainly from the phenolic acids that are present in this plant. Therefore, we selected some main phenolic acids as the key evaluation indices that could reflect dandelion quality with some extent (Fatima et al., 2018; Lis and Olas, 2019). However, choosing too many or few indices was deemed unsuitable owing to redundancy or insufficiency, respectively. From Figure 1, we see that some unknown compounds (e.g. retention time at ~5.5 min, ~7.1 min and ~10.8 min) were also found in parts of the dandelion samples; however, the four phenolic acids were found in all of the 15 dandelion samples and belonged to caffeic acid derivatives (Tajner-Czopek et al., 2020).

The content (by weight) of each compound in dandelion was different, and the effectiveness of each of these compounds with regard to a particular function (e.g., with regard to a therapeutic function, studies have identified chlorogenic acid as exerting a significant hypoglycaemic action) was also different. Compounds such as caffeic acid, chlorogenic acid and chicoric acid were the most abundant phenolic compounds in dandelion, and these have been recognised to exhibit significant antioxidant, anti-inflammatory, anti-bacterial and anti-carcinogenic effects (Didier et al., 2011). Dandelion has also been reported to contain significant amounts of phytosterols and derivatives such as plant sterols, stanols and sitosterol (Ovesnaâ et al., 2004), and also to exhibit anti-inflammatory activity, anti-inflammatory effect and anti-cancer properties (Aldini et al., 2014). However, the effectiveness of each component in dandelion is difficult to compare. In order to better evaluate the overall quality, some researchers used membership function, principal component analysis and fingerprint similarity analysis to determine the weight of each compound in dandelion. However, the actual operation of these methods is complex and inconvenient, especially for the purposes of popularisation and application for people lacking a specialised knowledge in these statistical techniques. Hence, the current method of dandelion quality evaluation in China mainly follows China Pharmacopoeia, although the single evaluation index used in the Pharmacopoeia has been subject to some dispute. To ensure a comprehensive approach, we adopted the equal weight average calculation method, and referring to local standards presently applicable in China, converted the above four phenolic acids into a QI to evaluate the quality of dandelion, as follows.

Statistical analysis result
Descriptive statistics

We conducted statistical analyses on dandelion samples and collected data from some references meanwhile (shown in Table 2 and 3; and Table S1 in Supplementary Materials). The statistical data in Table 2 and 3 are the reference sources used to classify the content level of each component.

Descriptive statistics of four components (%) in dandelion.

Compounds Numbers Min–Max Mean Mode Median
Cichoric acid 470 0.0175–2.1732 0.3834 0.0714 0.0369
Caffeic acid 437 0.0010–0.0600 0.0155 0.0138 0.0025
Chlorogenic acid 437 0.0011–0.5337 0.0828 0.0294 0.0023
Caftaric acid 465 0.0234–0.6419 0.1705 0.0858 0.0576

Data of components contents (%) from relevant references.

Literature sources Numbers Statistics Cichoric acid Caffeic acid Chlorogenic acid Caftaric acid
Literature 1 (Hao, 2010) 25 Min 0.008 0.0050
Max 0.0455 0.0470
Mean 0.0189 0.0173
Literature 2 (Lang et al., 1999) 29 Min 0.0089 0.0363
Max 0.0559 3.7819
Mean 0.0248 0.5154
Literature 3 (Liu et al., 2017) 11 Min 0.104 0.013 0.015 0.103
Max 0.599 0.051 0.072 0.441
Mean 0.272 0.033 0.035 0.307
Literature 4 (Chen et al., 2018) 15 Min 0.266 0.022 0.030 0.180
Max 0.909 0.060 0.072 0.359
Mean 0.608 0.036 0.046 0.286
Literature 5 (Ning et al., 2012) 11 Min 0.0281 0.0338
Max 0.0184 0.0802
Mean 0.0281 0.0576

– indicates not checked.

Correlation analysis

The four compound contents showed different extents of positive correlation according to Pearson correlation coefficient analysis (Table 4). China Pharmacopoeia (Ed. 2020) stipulated the content of cichoric acid as the one and only quality evaluation index. However, further linear regression analysis showed that the coefficient of determination (R2) of cichoric acid and those of the other three components were perceptibly different (Figure 2). Especially, the R2 of cichoric acid and caffeic acid was 0.1978, implying that using the content of cichoric acid to represent other components to evaluate dandelion quality was still insufficient. Therefore, the detection of the content of only one component could not suffice for the comprehensive evaluation of the quality of dandelion.

Pearson correlation analysis for four components in dandelion.

Components Cichoric acid Caffeic acid Chlorogenic acid Caftaric acid
Cichoric acid 1 0.410 0.934 0.889
Caffeic acid 1 0.451 0.674
Chlorogenic acid 1 0.774
Caftaric acid 1

Figure 2

Linear regressions of four compounds’ contents (%) in dandelion.

Division of content level in dandelion
Cichoric acid content level

China Pharmacopoeia (Ed. 2020) stipulated that the content of cichoric acid in dandelion shall exceed 0.45%, and that in dandelion herbal pieces it shall not be <0.3%. The cichoric acid content in Table 2 ranges from 0.0175% to 2.1732%, with an average of 0.3834%. Based on referring the division method used in Hao's dissertation (2010), content <80% of the average was defined as low (literature 1; Table 3), and thus that value was just in line with the provisions of Pharmacopoeia. Therefore, the content <0.3% was defined as low (Level 5).

Figure 3A showed that the contents of most samples were distributed within 1.2%, which was almost consistent with studies from the literature cited in Table 3. Thus, the valid division range was considered from 0% to 1.2%, and the division of other content levels was comprehensively determined as follows: the reasonable division was reckoned at 0.3%–0.5% as Level 4 referenced from China Pharmacopoeia, 0.5%–0.65% as Level 3 referenced from Chen et al. (2018) (literature 4; Table 3), 0.65%–0.75% as Level 2 and >0.75% as Level 1 referenced from histograms (Figure 3A).

Figure 3

Distributions of four compounds contents (%) that cichoric acid (A), caffeic acid (B), chlorogenic acid (C) and caftaric acid (D).

Caffeic acid content level

China Pharmacopoeia (Ed. 2015) stipulated that the content of caffeic acid in dandelion shall be >0.02%. The caffeic acid content in Table 2 ranges from 0.001% to 0.06%, with an average of 0.0155%. Similarly, content <80% of the average, and for convenience of application, here <0.015%, was defined as low (Level 5). Histograms of caffeic acid contents showed a relatively uniform distribution (Figure 3B), and thus the percentage distance of 0.01 was reasonable for the division of the rest of content levels as follows: 0.015%–0.025% was determined as Level 4, 0.025%–0.035% as Level 3, 0.035%–0.045% as Level 2 and >0.045% as Level 1.

Chlorogenic acid content level

China Pharmacopoeia did not indicate chlorogenic acid content as QI, and therefore we had to divide its content level based on statistical analysis and related references. The chlorogenic acid content in Table 2 ranges from 0.001% to 0.5337%, with an average of 0.0828%, mode of 0.0294% and median of 0.0023%. The overall contents’ distribution was relatively uniform, except for the two obvious parts divided at 0.1% (Figure 3C). Ling et al. (1999) (literature 2; Table 3) showed the highest content with an average of 0.5154%, which may be the outcome of either actually high content in dandelion or errors of determination results. However, data from the remaining studies cited in this paper were consistent with the statistical analysis. In summary, referring to the mode in Table 2, <0.03% was defined as low (Level 5); <0.085% according to the mean was Level 4; <0.15% (around twice of mean) was Level 3; <0.25% was Level 2 and >0.25% was Level 1 based on histograms (Figure 3C).

Caftaric acid content level

Similarly, Caftaric acid was not mentioned in China Pharmacopoeia for dandelion. The caftaric acid content in Table 2 ranged from 0.0234% to 0.6419%, with an average of 0.1705%, mode of 0.0858% and median of 0.0576%. The overall contents’ distribution was relatively uniform (Figure 3D). The data distribution evident in the studies cited in Table 3 was similar to that discerned from the statistical analysis. Thus, <0.1% was defined as low (Level 5) according to the mean and mode; and then the remaining content levels were divided sequentially based on the interval distance of 0.1, as follows: 0.1%–0.2% was reckoned as Level 4, 0.2%–0.3% as Level 3, 0.3%–0.4% as Level 2 and >0.4% as Level 1. Finally, we summarise the four kinds of phenolic acids’ content levels in Table 5.

Contents (%) level division for dandelion.

Index/level 1 2 3 4 5
Cichoric acid ≥0.750 ≥0.650 ≥0.500 ≥0.300 <0.300
Caffeic acid ≥0.045 ≥0.035 ≥0.025 ≥0.015 <0.015
Chlorogenic acid ≥0.250 ≥0.150 ≥0.085 ≥0.030 <0.030
Caftaric acid ≥0.400 ≥0.300 ≥0.200 ≥0.100 <0.100
Dandelion quality evaluation

The equal weight average calculation method was used here. Actually, this method is often adopted in domestic or industrial standard setting in China, and some examples are “Rules for characterisation and evaluation of cotton salt tolerance” (DB13/T 1339-2010), “Technical code of practice for identification of salt tolerance in rice” (NY/T 3692-2020) and “Evaluation guidance for water security” (DB37/T 4499-2022). In the present study, the content levels of four components were converted into a dandelion QI. From Table 5 and using the QI formula, totally 625 complete combinations and 17 QIs were obtained. According to the design requirements of quality standards, the probability within 1% was classified into Grade 1, and the rest were divided according to spindle structure. The above results are shown in Table 6.

Dandelion QI and grade division.

QI Grade Numbers Total Result Probability (%)
20 1 1 5 Super high 0.8
25 1 4
30 2 10 117 High 18.72
35 2 20
40 2 35
45 2 52
50 3 68 233 Medium 37.28
55 3 80
60 3 85
65 4 80 200 Qualified 32
70 4 68
75 4 52
80 5 35 70 Low 11.2
85 5 20
90 5 10
95 5 4
100 5 1

QI, quality index.

Quality evaluation result for dandelion samples

A total of 578 dandelion samples were checked, of which the quality levels of 324 samples with four phenolic acids were evaluated, as shown in Table 7 and Table S1 in Supplementary Materials. Of that quantity, Grade 1 samples amounted to 0.62%, and Grade 5 to 58.95%, indicating that the overall quality of this batch of dandelion samples was low, and that the overall samples collected from the greenhouse presented a lower compounds’ content compared with samples cultured in saline land (Table S1 in Supplementary Materials).

Quality evaluation result for 578 dandelion samples.

Grade Super high (Grade 1) High (Grade 2) Medium (Grade 3) Qualified (Grade 4) Low (Grade 5)
Quantity 2 54 32 45 191
Percentage (%) 0.62 16.67 9.88 13.89 58.95

According to the 2020 report from National Institutes for Food and Drug Control (Zhang et al., 2021), the overall dandelion quality in Hebei Province, China was generally substandard, going by the method of assessment recommended by China Pharmacopoeia (Ed. 2015). It has been suggested that the low concentration of phenolic acid compounds in dandelion plants cultivated in this province is attributable to the cultivation method employed, since producers focussed on maximising dandelion yield and accordingly input a large amount of fertiliser and water, leading to the dandelions’ rapid growth, and thus insufficient accumulation of the needed components (Wu et al., 2019; Zhang et al., 2021). Considering this situation, the dandelion evaluation standard could be appropriately decreased; however, improving dandelion quality with regard to the aspects of cultivation technology or breeding technology has remained the fundamental strategy. In addition, we proposed an idea for dandelion quality evaluation; however, the determination of evaluation indices may be adjusted following the deepening understanding of functional components of dandelion in future.

CONCLUSIONS

A dandelion quality evaluation method that is relatively comprehensive and capable of widespread application was developed based on phenolic acids’ analysis from 578 samples and related references. Four phenolic acids, namely cichoric acid, caffeic acid, chlorogenic acid and caftaric acid, were chosen as the main evaluation indices. Contents of the four phenolic acids were divided into five levels and then converted into a dandelion QI using the equal weight average calculation method. Finally, five grades of dandelion quality were identified according to the QI, namely Grade 1 (super high, 0.8%), Grade 2 (high, 18.72%), Grade 3 (medium, 37.28%), Grade 4 (qualified, 32%) and Grade 5 (low, 11.2%). Advantageously, this method enabled avoiding conflict with that of the single evaluation index used in China Pharmacopoeia, possesses the characteristics of scientific nature and widespread applicability or reproducibility and can be more conveniently adopted by dandelion industries or research facilities even in the absence of specialised knowledge of statistical techniques.

Figure 1

Optimisation of HPLC determination conditions and fingerprint analysis. (A) HPLC spectrum using determination conditions from China Pharmacopoeia; (B) optimised HPLC conditions; (C) fingerprint analysis, of which S1–S15 represents randomly selected dandelion HPLC spectrums, R indicates the reference fingerprint generated by the comparison of 15 samples and the dot on the fingerprint map represents a compound found in dandelion. HPLC, high performance liquid chromatography.
Optimisation of HPLC determination conditions and fingerprint analysis. (A) HPLC spectrum using determination conditions from China Pharmacopoeia; (B) optimised HPLC conditions; (C) fingerprint analysis, of which S1–S15 represents randomly selected dandelion HPLC spectrums, R indicates the reference fingerprint generated by the comparison of 15 samples and the dot on the fingerprint map represents a compound found in dandelion. HPLC, high performance liquid chromatography.

Figure 2

Linear regressions of four compounds’ contents (%) in dandelion.
Linear regressions of four compounds’ contents (%) in dandelion.

Figure 3

Distributions of four compounds contents (%) that cichoric acid (A), caffeic acid (B), chlorogenic acid (C) and caftaric acid (D).
Distributions of four compounds contents (%) that cichoric acid (A), caffeic acid (B), chlorogenic acid (C) and caftaric acid (D).

Linear regression equations for four compounds in dandelion.

Compounds Equations R2 Valid scope (mg · mL−1)
Caftaric acid Y = 0.6342x + 1.0263 0.9965 10–70
Chlorogenic acid Y = 0.4946x − 0.8089 0.9669 5–30
Y = 0.6148x + 0.9279 0.9997 30–105
Caffeic acid Y = 0.4605x − 0.8895 0.9905 5–30
Y = 0.39x + 0.814 0.9994 30–105
Cichoric acid Y = 0.4564x + 3.0071 0.9995 45–220
Y = 0.569x − 60.97 0.9502 240–512

Quality evaluation result for 578 dandelion samples.

Grade Super high (Grade 1) High (Grade 2) Medium (Grade 3) Qualified (Grade 4) Low (Grade 5)
Quantity 2 54 32 45 191
Percentage (%) 0.62 16.67 9.88 13.89 58.95

Descriptive statistics of four components (%) in dandelion.

Compounds Numbers Min–Max Mean Mode Median
Cichoric acid 470 0.0175–2.1732 0.3834 0.0714 0.0369
Caffeic acid 437 0.0010–0.0600 0.0155 0.0138 0.0025
Chlorogenic acid 437 0.0011–0.5337 0.0828 0.0294 0.0023
Caftaric acid 465 0.0234–0.6419 0.1705 0.0858 0.0576

Dandelion QI and grade division.

QI Grade Numbers Total Result Probability (%)
20 1 1 5 Super high 0.8
25 1 4
30 2 10 117 High 18.72
35 2 20
40 2 35
45 2 52
50 3 68 233 Medium 37.28
55 3 80
60 3 85
65 4 80 200 Qualified 32
70 4 68
75 4 52
80 5 35 70 Low 11.2
85 5 20
90 5 10
95 5 4
100 5 1

Contents (%) level division for dandelion.

Index/level 1 2 3 4 5
Cichoric acid ≥0.750 ≥0.650 ≥0.500 ≥0.300 <0.300
Caffeic acid ≥0.045 ≥0.035 ≥0.025 ≥0.015 <0.015
Chlorogenic acid ≥0.250 ≥0.150 ≥0.085 ≥0.030 <0.030
Caftaric acid ≥0.400 ≥0.300 ≥0.200 ≥0.100 <0.100

Data of components contents (%) from relevant references.

Literature sources Numbers Statistics Cichoric acid Caffeic acid Chlorogenic acid Caftaric acid
Literature 1 (Hao, 2010) 25 Min 0.008 0.0050
Max 0.0455 0.0470
Mean 0.0189 0.0173
Literature 2 (Lang et al., 1999) 29 Min 0.0089 0.0363
Max 0.0559 3.7819
Mean 0.0248 0.5154
Literature 3 (Liu et al., 2017) 11 Min 0.104 0.013 0.015 0.103
Max 0.599 0.051 0.072 0.441
Mean 0.272 0.033 0.035 0.307
Literature 4 (Chen et al., 2018) 15 Min 0.266 0.022 0.030 0.180
Max 0.909 0.060 0.072 0.359
Mean 0.608 0.036 0.046 0.286
Literature 5 (Ning et al., 2012) 11 Min 0.0281 0.0338
Max 0.0184 0.0802
Mean 0.0281 0.0576

Compounds’ content (%) of 578 dandelion samples.

No. Caftaric acid Chlorogenic acid Caffeic acid Cichoric acid Original site State QI
1 0.0323 0.0037 0.0012 0.0195 Tanghai 1 G-F 100
2 0.0409 0.0011 0.0011 0.0317 Tanghai 2 G-F 100
3 0.0409 0.0021 0.001 0.0314 Tanghai 3 G-F 100
4 0.0411 0.0013 0.001 0.0345 Tanghai 4 G-F 100
5 0.0414 0.0013 0.001 0.0321 Tanghai 5 G-F 100
6 0.0419 0.0013 0.0011 0.0338 Tanghai 6 G-F 100
7 0.0424 0.0017 0.0016 0.0274 Tanghai 7 G-F 100
8 0.0449 0.0015 0.0011 0.0376 Tanghai 8 G-F 100
9 0.0452 0.0017 0.0012 0.0469 Tanghai 9 G-F 100
10 0.0452 0.0027 0.002 0.0339 Tanghai 10 G-F 100
11 0.0457 0.0017 0.0027 0.0275 Tanghai 11 G-F 100
12 0.0457 0.0019 0.0011 0.0474 Tanghai 12 G-F 100
13 0.0465 0.0021 0.001 0.048 Luannan 1 G-F 100
14 0.047 0.0013 0.001 0.0418 Luannan 2 G-F 100
15 0.047 0.0013 0.0012 0.042 Luannan 3 G-F 100
16 0.047 0.0027 0.0016 0.0338 Luannan 4 G-F 100
17 0.0475 0.0025 0.002 0.0339 Luannan 5 G-F 100
18 0.0477 0.0013 0.0011 0.0699 Kaiping 1 G-F 100
19 0.0482 0.0015 0.0012 0.0704 Kaiping 2 G-F 100
20 0.0485 0.0015 0.0011 0.0706 Kaiping 3 G-F 100
21 0.0488 0.0023 0.0011 0.0296 Yixian 1 G-F 100
22 0.0488 0.0023 0.0012 0.0301 Yixian 2 G-F 100
23 0.0498 0.0011 0.0011 0.0369 Yixian 3 G-F 100
24 0.0546 0.0021 0.0012 0.0465 Yixian 4 G-F 100
25 0.0559 0.0037 0.002 0.0814 Yixian 5 G-F 100
26 0.0559 0.0049 0.0025 0.0443 Yixian 6 G-F 100
27 0.0564 0.0179 0.0051 0.1018 Shexian 1 G-F 100
28 0.0566 0.0023 0.001 0.0617 Shexian 2 G-F 100
29 0.0566 0.0051 0.0027 0.0447 Shexian 3 G-F 100
30 0.0569 0.011 0.0065 0.0369 Shexian 4 G-F 100
31 0.0569 0.0023 0.0014 0.0613 Shexian 5 G-F 100
32 0.0574 0.0033 0.0022 0.0821 Shexian 6 G-F 100
33 0.0574 0.0039 0.0011 0.0619 Handan 1 G-F 100
34 0.0576 0.0055 0.0044 0.0316 Handan 2 G-F 100
35 0.0576 0.0055 0.0054 0.0356 Handan 3 G-F 100
36 0.0576 0.0035 0.0011 0.0787 Handan 4 G-F 100
37 0.0581 0.0051 0.0025 0.0453 Zhangjiakou 1 G-F 100
38 0.0589 0.0047 0.0044 0.0403 Zhangjiakou 2 G-F 100
39 0.0592 0.0118 0.0065 0.0369 Zhangjiakou 3 G-F 100
40 0.0594 0.0043 0.0031 0.0575 Zhangjiakou 4 G-F 100
41 0.0594 0.0082 0.0071 0.0356 Zhangjiakou 5 G-F 100
42 0.0594 0.0116 0.0068 0.0356 Zhangjiakou 6 G-F 100
43 0.0597 0.0189 0.0057 0.1092 Hengshui 1 G-F 100
44 0.0597 0.0191 0.0058 0.1099 Hengshui 2 G-F 100
45 0.0599 0.0043 0.0027 0.0568 Hengshui 3 G-F 100
46 0.0602 0.0043 0.0029 0.0551 Hengshui 4 G-F 100
47 0.0607 0.0015 0.0011 0.0454 Hengshui 5 G-F 100
48 0.0612 0.0092 0.0071 0.0336 Xingtai 1 G-F 100
49 0.0622 0.0063 0.0045 0.0407 Xingtai 2 G-F 100
50 0.0627 0.0011 0.0025 0.0471 Cangzhou 1 G-F 100
51 0.0637 0.0132 0.0071 0.0763 Cangzhou 2 G-F 100
52 0.064 0.0094 0.0056 0.0341 Cangzhou 3 G-F 100
53 0.065 0.0021 0.0014 0.0394 Chongli 1 G-F 100
54 0.065 0.0033 0.0031 0.0562 Chongli 2 G-F 100
55 0.0655 0.0134 0.0068 0.0787 Chongli 3 G-F 100
56 0.0655 0.0061 0.0053 0.048 Baoding 1 G-F 100
57 0.0657 0.0094 0.0066 0.0422 Baoding 2 G-F 100
58 0.0663 0.0071 0.0077 0.0467 Baoding 3 G-F 100
59 0.0665 0.0011 0.0012 0.0347 Baoding 4 G-F 100
60 0.067 0.0078 0.0053 0.0323 Baoding 5 G-F 100
61 0.0675 0.0098 0.006 0.1018 Chengde 1 G-F 100
62 0.0688 0.0037 0.0012 0.0695 Chengde 2 G-F 100
63 0.0688 0.0039 0.0033 0.0595 Chengde 3 G-F 100
64 0.069 0.0146 0.0066 0.084 Zunhua 1 G-F 100
65 0.0693 0.0041 0.0051 0.0487 Zunhua 2 G-F 100
66 0.0698 0.0039 0.0033 0.0589 Zunhua 3 G-F 100
67 0.0703 0.0043 0.0014 0.0717 Renqiu 1 G-F 100
68 0.0708 0.0017 0.001 0.037 Renqiu 2 G-F 100
69 0.0729 0.0047 0.0022 0.0734 Renqiu 3 G-F 100
70 0.0734 0.0021 0.0011 0.0913 Shenyang 1 G-F 100
71 0.0734 0.0104 0.0065 0.0558 Shenyang 2 G-F 100
72 0.0736 0.0013 0.0011 0.0905 Shenyang 3 G-F 100
73 0.0749 0.0023 0.0025 0.0657 Dalian 1 G-F 100
74 0.0749 0.0027 0.0025 0.0657 Dalian 2 G-F 100
75 0.0751 0.0146 0.0025 0.1117 Dalian 3 G-F 100
76 0.0751 0.0128 0.0066 0.056 Shandong 1 G-F 100
77 0.0754 0.0023 0.002 0.0542 Shandong 2 G-F 100
78 0.0754 0.0031 0.0016 0.0684 Shandong 3 G-F 100
79 0.0754 0.0276 0.0072 0.0869 Nemenggu 1 G-F 100
80 0.0764 0.0136 0.0069 0.0832 Nemenggu 2 G-F 100
81 0.0769 0.0124 0.006 0.0454 Nemenggu 3 G-F 100
82 0.0774 0.0015 0.0029 0.0449 Dandon 1 G-F 100
83 0.0774 0.0148 0.0038 0.1148 Dandon 2 G-F 100
84 0.0777 0.0031 0.001 0.0951 Dandon 3 G-F 100
85 0.0777 0.0121 0.0062 0.0712 Zhengzou 1 G-F 100
86 0.0777 0.0132 0.0025 0.115 Zhengzou 2 G-F 100
87 0.0787 0.0084 0.0059 0.0487 Zhengzou 3 G-F 100
88 0.0789 0.0013 0.0027 0.0418 Heilongjiang 1 G-F 100
89 0.0789 0.0169 0.0057 0.0876 Heilongjiang 2 G-F 100
90 0.08 0.0015 0.0018 0.0438 Heilongjiang 3 G-F 100
91 0.08 0.0027 0.0025 0.0571 Xinjiang 1 G-F 100
92 0.0807 0.0023 0.0033 0.0369 Xinjiang 2 G-F 100
93 0.0807 0.0114 0.0084 0.0495 Xinjiang 3 G-F 100
94 0.0815 0.0023 0.0033 0.0372 Xian 1 G-F 100
95 0.082 0.0116 0.006 0.073 Xian 2 G-F 100
96 0.082 0.0146 0.0081 0.0719 Xian 3 G-F 100
97 0.0822 0.014 0.0075 0.0721 Tanghai 1 G-F 100
98 0.0825 0.0122 0.0063 0.0734 Tanghai 2 G-F 100
99 0.083 0.0031 0.0025 0.0584 Tanghai 3 G-F 100
100 0.083 0.0118 0.0084 0.0502 Luannan 1 G-F 100
101 0.0838 0.0023 0.0027 0.0381 Luannan 2 G-F 100
102 0.084 0.0015 0.0014 0.0367 Kaiping 1 G-F 100
103 0.084 0.0116 0.0065 0.1059 Kaiping 2 G-F 100
104 0.0843 0.0011 0.002 0.0816 Yixian 1 G-F 100
105 0.0843 0.0144 0.0069 0.0841 Yixian 2 G-F 100
106 0.0845 0.0124 0.0065 0.0814 Shexian 1 G-F 100
107 0.0848 0.0112 0.0065 0.0867 Shexian 2 G-F 100
108 0.0858 0.0078 0.0018 0.0794 Handan 1 G-F 100
109 0.0858 0.01 0.0063 0.0849 Handan 2 G-F 100
110 0.0863 0.0013 0.0025 0.0832 Tanghai 1 G-A 100
111 0.0863 0.0094 0.0054 0.0352 Tanghai 2 G-A 100
112 0.0866 0.009 0.0053 0.0582 Tanghai 3 G-A 100
113 0.0866 0.0124 0.0065 0.1121 Luannan 1 G-A 100
114 0.0871 0.0124 0.0071 0.0595 Luannan 2 G-A 100
115 0.0873 0.0017 0.0016 0.0374 Kaiping 1 G-A 100
116 0.0876 0.0074 0.002 0.0816 Kaiping 2 G-A 100
117 0.0878 0.0122 0.0068 0.0819 Yixian 1 G-A 100
118 0.0881 0.014 0.0072 0.0359 Yixian 2 G-A 100
119 0.0883 0.0134 0.0075 0.1066 Shexian 1 G-A 100
120 0.0886 0.0019 0.002 0.0376 Shexian 2 G-A 100
121 0.0893 0.0063 0.002 0.0874 Handan 1 G-A 100
122 0.0893 0.0138 0.0069 0.0823 Handan 2 G-A 100
123 0.0896 0.0015 0.001 0.0485 Zhangjiakou 1 G-A 100
124 0.0896 0.0027 0.0016 0.1108 Zhangjiakou 2 G-A 100
125 0.0901 0.0027 0.0016 0.1097 Hengshui 1 G-A 100
126 0.0906 0.0029 0.0018 0.1112 Hengshui 2 G-A 100
127 0.0921 0.0011 0.0023 0.0453 Xingtai 1 G-A 100
128 0.0921 0.0013 0.0022 0.0458 Xingtai 2 G-A 100
129 0.0942 0.0118 0.0069 0.0456 Cangzhou 1 G-A 100
130 0.0962 0.0132 0.0063 0.0995 Cangzhou 2 G-A 100
131 0.0967 0.0136 0.0069 0.094 Chongli 1 G-A 100
132 0.0967 0.0043 0.0029 0.1 Chongli 2 G-A 100
133 0.0982 0.0047 0.0034 0.1033 Baoding 1 G-A 100
134 0.0995 0.0152 0.0068 0.0832 Baoding 2 G-A 100
135 0.0997 0.0045 0.0016 0.0903 Chengde 1 G-A 100
136 0.0997 0.0126 0.0069 0.0564 Chengde 2 G-A 100
137 0.101 0.0049 0.0033 0.1055 Zunhua 1 G-A 95
138 0.103 0.021 0.051 0.203 Zunhua 2 G-A 75
139 0.103 0.0043 0.0016 0.0902 Zunhua 3 G-A 95
140 0.1033 0.0023 0.0012 0.0549 Renqiu 1 G-A 95
141 0.1058 0.0019 0.002 0.0522 Renqiu 2 G-A 95
142 0.1066 0.0015 0.0025 0.0524 Shenyang 1 G-A 95
143 0.1068 0.0011 0.0011 0.0338 Shenyang 2 G-A 95
144 0.1068 0.0013 0.0012 0.0336 Dalian 2 G-A 95
145 0.1071 0.0011 0.0011 0.0336 Shandong 1 G-A 95
146 0.1074 0.0023 0.002 0.0529 Shandong 2 G-A 95
147 0.1086 0.0076 0.0029 0.1546 Nemenggu 1 G-A 95
148 0.1089 0.0086 0.0027 0.1559 Nemenggu 2 G-A 95
149 0.1104 0.0084 0.0027 0.1566 Dandon 1 G-A 95
150 0.1155 0.0063 0.0047 0.0794 Dandon 2 G-A 95
151 0.1162 0.0171 0.0071 0.153 Zhengzou 1 G-A 95
152 0.125 0.015 0.024 0.149 Zhengzou 2 G-A 90
153 0.1259 0.0047 0.0022 0.0715 Heilongjiang 1 G-A 95
154 0.1259 0.0154 0.0066 0.14 Heilongjiang 2 G-A 95
155 0.1271 0.0045 0.0023 0.0719 Xinjiang 1 G-A 95
156 0.1276 0.0179 0.0068 0.142 Xinjiang 2 G-A 95
157 0.1284 0.0164 0.0069 0.1575 Xian 1 G-A 95
158 0.1292 0.0047 0.0023 0.0701 Xian 2 G-A 95
159 0.1297 0.0213 0.0093 0.1517 Tanghai 1 N-F 95
160 0.1304 0.0421 0.0109 0.2638 Tanghai 2 N-F 90
161 0.1315 0.0229 0.0087 0.2645 Tanghai 3 N-F 95
162 0.1327 0.0027 0.0018 0.0774 Luannan 1 N-F 95
163 0.133 0.0021 0.0014 0.0768 Luannan 2 N-F 95
164 0.1334 0.0416 0.0047 0.44 Kaiping 1 N-F 85
165 0.1358 0.0029 0.0016 0.0785 Kaiping 2 N-F 95
166 0.1378 0.0213 0.0107 0.1475 Yixian 1 N-F 95
167 0.1393 0.0361 0.0087 0.2846 Yixian 2 N-F 90
168 0.152 0.0031 0.0057 0.0995 Shexian 1 N-F 95
169 0.1532 0.0369 0.0055 0.5023 Shexian 2 N-F 80
170 0.1533 0.0027 0.0045 0.0969 Handan 1 N-F 95
171 0.1538 0.0027 0.0045 0.098 Handan 2 N-F 95
172 0.1548 0.0162 0.0107 0.1455 Zhangjiakou 1 N-F 95
173 0.155 0.0173 0.0081 0.1502 Zhangjiakou 2 N-F 95
174 0.1573 0.0144 0.0068 0.1517 Hengshui 1 N-F 95
175 0.1649 0.0047 0.0047 0.0792 Hengshui 2 N-F 95
176 0.1672 0.0039 0.0047 0.0796 Xingtai 1 N-F 95
177 0.1691 0.0414 0.018 0.5406 Xingtai 2 N-F 75
178 0.1761 0.0088 0.0036 0.1272 Cangzhou 1 N-F 95
179 0.1779 0.0059 0.0034 0.1285 Cangzhou 2 N-F 95
180 0.18 0.039 0.022 0.496 Chongli 1 N-F 80
181 0.1807 0.0092 0.0038 0.1305 Chongli 2 N-F 95
182 0.1845 0.0059 0.004 0.1389 Baoding 1 N-F 95
183 0.1845 0.0272 0.0106 0.2417 Baoding 2 N-F 95
184 0.1852 0.0047 0.004 0.1398 Chengde 1 N-F 95
185 0.1857 0.0249 0.0119 0.2422 Chengde 2 N-F 95
186 0.187 0.0051 0.0044 0.1447 Zunhua 1 N-F 95
187 0.1898 0.0344 0.0033 0.5368 Zunhua 2 N-F 80
188 0.1969 0.0286 0.0116 0.2461 Zunhua 3 N-F 95
189 0.2012 0.0577 0.0076 0.5777 Renqiu 1 N-F 75
190 0.208 0.016 0.034 0.104 Renqiu 2 N-F 80
191 0.2109 0.0524 0.009 0.6053 Shenyang 1 N-F 75
192 0.2188 0.0366 0.0032 0.4757 Shenyang 2 N-F 80
193 0.222 0.03 0.033 0.383 Dalian 2 N-F 70
194 0.2225 0.0493 0.0058 0.6703 Shandong 1 N-F 70
195 0.23 0.036 0.042 0.497 Shandong 2 N-F 65
196 0.23 0.0335 0.0011 0.5053 Nemenggu 1 N-F 75
197 0.2314 0.034 0.0016 0.4756 Nemenggu 2 N-F 80
198 0.2316 0.0359 0.0069 0.5158 Dandon 1 N-F 75
199 0.2349 0.0552 0.0111 0.6842 Dandon 2 N-F 70
200 0.2383 0.0803 0.008 0.5941 Zhengzou 1 N-F 75
201 0.2432 0.0615 0.0095 0.6524 Zhengzou 2 N-F 70
202 0.244 0.045 0.025 0.596 Heilongjiang 1 N-F 65
203 0.2452 0.0725 0.0136 0.7869 Heilongjiang 2 N-F 65
204 0.2499 0.0397 0.0049 0.5899 Xinjiang 1 N-F 75
205 0.252 0.021 0.044 0.231 Xinjiang 2 N-F 75
206 0.2602 0.0372 0.0015 0.5937 Xian 1 N-F 75
207 0.2636 0.0686 0.0139 0.6526 Xian 2 N-F 70
208 0.264 0.037 0.044 0.449 Tanghai 1 N-A 65
209 0.2663 0.0419 0.0063 0.5641 Tanghai 2 N-A 75
210 0.2673 0.0425 0.0075 0.614 Tanghai 3 N-A 75
211 0.2674 0.0682 0.013 0.6524 Luannan 1 N-A 70
212 0.2705 0.0384 0.0018 0.6103 Luannan 2 N-A 75
213 0.2739 0.0477 0.0043 0.5881 Kaiping 1 N-A 75
214 0.2772 0.0359 0.0024 0.5438 Kaiping 2 N-A 75
215 0.2804 0.0715 0.0142 0.691 Yixian 1 N-A 70
216 0.283 0.039 0.035 0.587 Yixian 2 N-A 60
217 0.2834 0.0476 0.0052 0.5976 Shexian 1 N-A 75
218 0.2837 0.0476 0.0078 0.6254 Shexian 2 N-A 75
219 0.284 0.053 0.031 0.66 Handan 1 N-A 60
220 0.2874 0.0446 0.007 0.6179 Handan 2 N-A 75
221 0.2876 0.0465 0.008 0.6386 Zhangjiakou 1 N-A 75
222 0.2904 0.0473 0.0086 0.6414 Zhangjiakou 2 N-A 75
223 0.2924 0.0479 0.0034 0.6896 Hengshui 1 N-A 70
224 0.297 0.053 0.036 0.65 Hengshui 2 N-A 55
225 0.304 0.034 0.033 0.655 Xingtai 1 N-A 55
226 0.306 0.05 0.038 0.717 Xingtai 2 N-A 50
227 0.3062 0.0497 0.004 0.6348 Cangzhou 1 N-A 70
228 0.3092 0.0236 0.0234 0.2842 Cangzhou 2 N-A 80
229 0.31 0.0448 0.0134 0.8845 Chongli 1 N-A 60
230 0.3106 0.0395 0.0127 0.7987 Chongli 2 N-A 60
231 0.316 0.032 0.06 0.266 Baoding 1 N-A 60
232 0.321 0.06 0.032 0.768 Baoding 2 N-A 50
233 0.3215 0.0714 0.0069 1.0737 Chengde 1 N-A 60
234 0.3293 0.083 0.0101 1.0919 Chengde 2 N-A 60
235 0.3317 0.0276 0.0248 0.3212 Zunhua 1 N-A 75
236 0.334 0.072 0.013 0.599 Zunhua 2 N-A 70
237 0.3349 0.0225 0.0208 0.2808 Zunhua 3 N-A 80
238 0.339 0.072 0.037 0.899 Renqiu 1 N-A 45
239 0.344 0.067 0.025 0.909 Renqiu 2 N-A 50
240 0.3456 0.0464 0.0136 0.7979 Shenyang 1 N-A 60
241 0.347 0.051 0.02 0.348 Shenyang 2 N-A 70
242 0.3529 0.0882 0.0142 1.1522 Dalian 2 N-A 55
243 0.359 0.05 0.041 0.592 Shandong 1 N-A 55
244 0.364 0.039 0.032 0.273 Shandong 2 N-A 70
245 0.3793 0.1119 0.0163 1.2967 Nemenggu 1 N-A 50
246 0.381 0.059 0.02 0.346 Nemenggu 2 N-A 70
247 0.3831 0.2189 0.0178 1.8585 Dandon 1 N-A 45
248 0.3884 0.2614 0.0189 2.0501 Dandon 2 N-A 40
249 0.3906 0.0308 0.0327 0.3756 Zhengzou 1 N-A 65
250 0.3915 0.2214 0.0173 1.8708 Zhengzou 2 N-A 45
251 0.3975 0.0277 0.0302 0.3223 Heilongjiang 1 N-A 70
252 0.403 0.037 0.033 0.258 Heilongjiang 2 N-A 65
253 0.4168 0.1977 0.0201 2.0018 Xinjiang 1 N-A 40
254 0.4196 0.2228 0.0199 1.9534 Xinjiang 2 N-A 40
255 0.42 0.027 0.0326 0.3397 Xian 1 N-A 65
256 0.423 0.025 0.043 0.245 Xian 2 N-A 65
257 0.4239 0.1498 0.016 1.8405 Xian 1 S-A 45
258 0.4247 0.027 0.0295 0.3135 Xian 2 S-A 65
259 0.43 0.2457 0.0205 2.0467 Xinjiang 1 S-A 40
260 0.4303 0.1247 0.0186 1.4579 Xinjiang 2 S-A 45
261 0.4303 0.2373 0.0189 2.0335 Heilongjiang 1 S-A 40
262 0.4308 0.154 0.0169 1.8664 Heilongjiang 2 S-A 40
263 0.4343 0.2002 0.0205 2.0508 Zhengzou 1 S-A 40
264 0.4376 0.0324 0.037 0.3885 Zhengzou 2 S-A 55
265 0.441 0.032 0.049 0.235 Dandon 1 S-A 55
266 0.4422 0.035 0.0334 0.4394 Dandon 2 S-A 60
267 0.4425 0.0299 0.0355 0.3689 Nemenggu 1 S-A 60
268 0.4435 0.2696 0.0222 1.9106 Nemenggu 2 S-A 35
269 0.4437 0.2243 0.019 1.9031 Shandong 1 S-A 40
270 0.4445 0.2715 0.0202 1.9174 Shandong 2 S-A 35
271 0.448 0.1441 0.0219 1.6236 Dalian 2 S-A 45
272 0.4486 0.2285 0.019 2.1732 Shenyang 1 S-A 40
273 0.4496 0.1914 0.0187 1.6429 Shenyang 2 S-A 40
274 0.4498 0.1827 0.0204 1.4069 Renqiu 1 S-A 40
275 0.4506 0.1702 0.0186 1.5942 Renqiu 2 S-A 40
276 0.4506 0.1781 0.0179 1.6643 Zunhua 1 S-A 40
277 0.4513 0.1459 0.0196 1.6809 Zunhua 2 S-A 45
278 0.4513 0.1928 0.0184 1.6488 Zunhua 3 S-A 40
279 0.4526 0.2361 0.0192 2.046 Chengde 1 S-A 40
280 0.4536 0.1466 0.0201 1.6891 Chengde 2 S-A 45
281 0.4559 0.1744 0.0167 1.6247 Baoding 1 S-A 40
282 0.4574 0.1621 0.0205 1.7663 Baoding 2 S-A 40
283 0.4597 0.0293 0.0338 0.3585 Chongli 1 S-A 65
284 0.4605 0.1628 0.0193 1.757 Chongli 2 S-A 40
285 0.4607 0.1864 0.0172 1.4338 Cangzhou 1 S-A 40
286 0.464 0.242 0.0207 2.0899 Cangzhou 2 S-A 40
287 0.4645 0.2806 0.0232 1.9145 Xingtai 1 S-A 35
288 0.4681 0.1739 0.0148 1.7294 Xingtai 2 S-A 45
289 0.4704 0.0346 0.0369 0.4201 Hengshui 1 S-A 55
290 0.4721 0.0787 0.0148 1.4385 Hengshui 2 S-A 55
291 0.4734 0.0333 0.0367 0.3911 Zhangjiakou 1 S-A 55
292 0.475 0.0346 0.037 0.4142 Zhangjiakou 2 S-A 55
293 0.476 0.0343 0.0372 0.4124 Handan 1 S-A 55
294 0.4764 0.0343 0.038 0.4128 Handan 2 S-A 55
295 0.4765 0.0801 0.0155 1.442 Shexian 1 S-A 50
296 0.4927 0.1717 0.022 2.115 Shexian 2 S-A 40
297 0.4947 0.1687 0.0201 1.8958 Yixian 1 S-A 40
298 0.4955 0.082 0.0155 1.4945 Yixian 2 S-A 50
299 0.5011 0.1739 0.022 2.1518 Kaiping 1 S-A 40
300 0.5059 0.1596 0.0222 1.7722 Kaiping 2 S-A 40
301 0.5077 0.3738 0.0275 1.9905 Luannan 1 S-A 25
302 0.5099 0.1891 0.0214 2.0187 Luannan 2 S-A 40
303 0.5122 0.2081 0.0208 1.7135 Tanghai 1 S-A 40
304 0.5188 0.2533 0.0329 2.0622 Tanghai 2 S-A 25
305 0.5191 0.18 0.0213 2.1065 Tanghai 3 S-A 40
306 0.5206 0.1877 0.0204 1.9682 Tanghai 1 S-F 40
307 0.5211 0.1891 0.0195 1.9882 Tanghai 2 S-F 40
308 0.5219 0.1985 0.0202 2.0446 Luannan 1 S-F 40
309 0.5239 0.1643 0.0226 1.8355 Luannan 2 S-F 40
310 0.5257 0.195 0.0225 2.1218 Kaiping 1 S-F 40
311 0.5264 0.213 0.0186 2.0833 Yixian 1 S-F 40
312 0.5267 0.195 0.0228 2.1207 Shexian 2 S-F 40
313 0.5319 0.0295 0.0442 0.4174 Handan 1 S-F 60
314 0.5323 0.1422 0.0217 2.077 Zhangjiakou 3 S-F 45
315 0.5363 0.1434 0.0223 2.1104 Hengshui 2 S-F 45
316 0.5363 0.1808 0.0184 1.9834 Xingtai 1 S-F 40
317 0.5417 0.2504 0.0211 2.043 Cangzhou 2 S-F 35
318 0.5455 0.2523 0.0223 2.0551 Chongli 3 S-F 35
319 0.5701 0.1759 0.021 1.8323 Baoding 3 S-F 40
320 0.5784 0.1827 0.0193 1.9443 Chengde 1 S-F 40
321 0.5916 0.1889 0.0207 2.0078 Shenyang 1 S-F 40
322 0.6238 0.0087 0.0081 1.7417 Dalian 2 S-F 60
323 0.6391 0.0127 0.0121 1.7941 Shandong 3 S-F 60
324 0.6419 0.0047 0.0041 1.7727 Dandon 1 S-F 60
325 0.01 0.026 0.179 Tanghan 1 N-A
326 0.017 0.026 0.194 Luannan 1 N-A
327 0.019 0.058 0.285 Baoding 1 N-A
328 0.059 0.028 0.868 Zhangjiakou 3 N-A
329 0.062 0.043 1.068 Tanghai 3 N-A
330 0.0234 0.0182 Tanghai 1 G-F
331 0.0236 0.0184 Tanghai 2 G-F
332 0.0351 0.0328 Tanghai 3 G-F
333 0.0353 0.0217 Tanghai 4 G-F
334 0.0353 0.0328 Tanghai 5 G-F
335 0.0358 0.0255 Tanghai 6 G-F
336 0.0363 0.0175 Tanghai 7 G-F
337 0.0366 0.0259 Tanghai 8 G-F
338 0.0366 0.0348 Tanghai 9 G-F
339 0.0373 0.0186 Tanghai 10 G-F
340 0.0373 0.0268 Tanghai 11 G-F
341 0.0381 0.0212 Tanghai 12 G-F
342 0.0386 0.031 Luannan 1 G-F
343 0.0389 0.0325 Luannan 2 G-F
344 0.0394 0.0288 Luannan 3 G-F
345 0.0396 0.0243 Luannan 4 G-F
346 0.0396 0.0312 Luannan 5 G-F
347 0.0401 0.0277 Kaiping 1 G-F
348 0.0404 0.0208 Kaiping 2 G-F
349 0.0406 0.0285 Yixian 1 G-F
350 0.0406 0.0288 Yixian 2 G-F
351 0.0411 0.0215 Yixian 3 G-F
352 0.0414 0.0279 Shexian 1 G-F
353 0.0414 0.0285 Shexian 3 G-F
354 0.0439 0.0259 Shexian 4 G-F
355 0.0452 0.0367 Handan 1 G-F
356 0.0457 0.0372 Handan 2 G-F
357 0.0462 0.0378 Handan 3 G-F
358 0.0467 0.0193 Handan 4 G-F
359 0.0472 0.0193 Zhangjiakou 1 G-F
360 0.0475 0.0195 Zhangjiakou 2 G-F
361 0.0475 0.0338 Zhangjiakou 3 G-F
362 0.048 0.0219 Zhangjiakou 4 G-F
363 0.048 0.0297 Zhangjiakou 5 G-F
364 0.0485 0.0246 Zhangjiakou 6 G-F
365 0.0488 0.0343 Hengshui 1 G-F
366 0.049 0.0259 Hengshui 2 G-F
367 0.049 0.0268 Hengshui 3 G-F
368 0.049 0.0332 Hengshui 4 G-F
369 0.0493 0.0259 Hengshui 5 G-F
370 0.0498 0.0281 Baoding 1 G-F
371 0.0498 0.0369 Baoding 2 G-F
372 0.05 0.0272 Baoding 3 G-F
373 0.0503 0.0281 Baoding 4 G-F
374 0.051 0.0266 Baoding 5 G-F
375 0.051 0.0268 Xingtai 1 G-F
376 0.051 0.0272 Xingtai 2 G-F
377 0.0518 0.0301 Xingtai 3 G-F
378 0.0521 0.0279 Cangzhou 1 G-F
379 0.0526 0.0277 Cangzhou 2 G-F
380 0.0528 0.0478 Cangzhou 3 G-F
381 0.0536 0.0317 Chongli 1 G-F
382 0.0536 0.0436 Chongli 2 G-F
383 0.0538 0.0275 Chongli 3 G-F
384 0.0538 0.0316 Chengde 1 G-F
385 0.0538 0.0369 Chengde 2 G-F
386 0.0538 0.0453 Chengde 3 G-F
387 0.0541 0.0369 Zunhua 1 G-F
388 0.0548 0.027 Zunhua 2 G-F
389 0.0551 0.0257 Zunhua 3 G-F
390 0.0556 0.0244 Renqiu 1 G-F
391 0.0556 0.031 Renqiu 2 G-F
392 0.0556 0.0312 Renqiu 3 G-F
393 0.0556 0.0323 Shenyang 1 G-F
394 0.0559 0.0339 Shenyang 2 G-F
395 0.0559 0.0367 Shenyang 3 G-F
396 0.0559 0.0392 Dalian 1 G-F
397 0.0561 0.039 Dalian 3 G-F
398 0.0564 0.0332 Shandong 1 G-F
399 0.0564 0.0394 Tanghai 1 N-F
400 0.0569 0.0361 Tanghai 2 N-F
401 0.0569 0.039 Tanghai 3 N-F
402 0.0571 0.0274 Tanghai 4 N-F
403 0.0576 0.0275 Tanghai 5 N-F
404 0.0576 0.0469 Tanghai 6 N-F
405 0.0581 0.0274 Tanghai 7 N-F
406 0.0581 0.0345 Tanghai 8 N-F
407 0.0586 0.0263 Tanghai 9 N-F
408 0.0586 0.0314 Tanghai 10 N-F
409 0.0594 0.027 Tanghai 11 N-F
410 0.0599 0.0385 Tanghai 12 N-F
411 0.0602 0.0299 Luannan 1 N-F
412 0.0612 0.0338 Luannan 2 N-F
413 0.0612 0.0339 Luannan 3 N-F
414 0.0614 0.0425 Luannan 4 N-F
415 0.0622 0.0325 Luannan 5 N-F
416 0.0622 0.0327 Kaiping 1 N-F
417 0.0627 0.054 Kaiping 2 N-F
418 0.0632 0.0334 Yixian 1 N-F
419 0.0632 0.0451 Yixian 2 N-F
420 0.0632 0.0544 Yixian 3 N-F
421 0.0637 0.0348 Shexian 1 N-F
422 0.064 0.0551 Shexian 3 N-F
423 0.0645 0.0427 Shexian 4 N-F
424 0.0652 0.0301 Handan 1 N-F
425 0.0652 0.0303 Handan 2 N-F
426 0.0655 0.0467 Handan 3 N-F
427 0.0657 0.031 Handan 4 N-F
428 0.0657 0.0396 Zhangjiakou 1 N-F
429 0.066 0.0401 Zhangjiakou 2 N-F
430 0.066 0.0453 Zhangjiakou 3 N-F
431 0.067 0.031 Zhangjiakou 4 N-F
432 0.0673 0.0644 Zhangjiakou 5 N-F
433 0.0675 0.0332 Zhangjiakou 6 N-F
434 0.068 0.0325 Hengshui 1 N-F
435 0.068 0.0533 Hengshui 2 N-F
436 0.0706 0.037 Hengshui 3 N-F
437 0.0708 0.0361 Hengshui 4 N-F
438 0.0721 0.0365 Hengshui 5 N-F
439 0.0726 0.0365 Baoding 1 N-F
440 0.0729 0.0358 Baoding 2 N-F
441 0.0729 0.0491 Baoding 3 N-F
442 0.0744 0.0363 Baoding 4 N-F
443 0.0751 0.035 Baoding 5 N-F
444 0.0754 0.0498 Xingtai 1 N-F
445 0.0756 0.0516 Xingtai 2 N-F
446 0.0759 0.0646 Xingtai 3 N-F
447 0.0762 0.0639 Cangzhou 1 N-F
448 0.0764 0.0531 Cangzhou 2 N-F
449 0.0767 0.0317 Cangzhou 3 N-F
450 0.0772 0.0321 Chongli 1 N-F
451 0.0782 0.0317 Chongli 2 N-F
452 0.0805 0.0489 Chongli 3 N-F
453 0.0825 0.0456 Chengde 1 N-F
454 0.0833 0.0462 Chengde 2 N-F
455 0.0863 0.0823 Chengde 3 N-F
456 0.0893 0.0434 Zunhua 1 N-F
457 0.0904 0.0736 Zunhua 2 N-F
458 0.0924 0.0458 Zunhua 3 N-F
459 0.0926 0.0451 Renqiu 1 N-F
460 0.0926 0.0465 Renqiu 2 N-F
461 0.0931 0.0487 Renqiu 3 N-F
462 0.0934 0.0474 Shenyang 1 N-F
463 0.0937 0.0462 Shenyang 2 N-F
464 0.0939 0.0467 Shenyang 3 N-F
465 0.1226 0.0593 Dalian 1 N-F
466 0.1231 0.0595 Dalian 2 N-F
467 0.1251 0.0608 Dalian 3 N-F
468 0.1279 0.0387 Shandong 1 N-F
469 0.1297 0.0394 Shandong 2 N-F
470 0.1325 0.0398 Shandong 3 N-F
471 0.2292 0.0208 Tanghai 1 S-A
472 0.2302 0.0213 Tanghai 2 S-A
473 0.2309 0.0386 Tanghai 3 S-A
474 0.2334 0.0217 Tanghai 4 S-A
475 0.2339 0.0229 Tanghai 5 S-A
476 0.2218 0.0238 Tanghai 6 S-A
477 0.2226 0.0247 Tanghai 7 S-A
478 0.2206 0.0269 Tanghai 8 S-A
479 0.2206 0.0261 Luannan 1 S-A
480 0.212 0.0181 Luannan 2 S-A
481 0.2128 0.0214 Luannan 3 S-A
482 0.2408 0.0303 Luannan 4 S-A
483 0.2499 0.0201 Luannan 5 S-A
484 0.2499 0.0214 Kaiping 1 S-A
485 0.251 0.0559 Kaiping 2 S-A
486 0.2548 0.0216 Kaiping 3 S-A
487 0.2549 0.0224 Yixian 1 S-A
488 0.261 0.0214 Yixian 2 S-A
489 0.2646 0.0222 Yixian 4 S-A
490 0.2669 0.0214 Yixian 6 S-A
491 0.2713 0.0294 Shexian 1 S-A
492 0.3766 0.0013 Shexian 2 S-A
493 0.3785 0.0253 Shexian 3 S-A
494 0.3797 0.0252 Shexian 4 S-A
495 0.418 0.0229 Shexian 5 S-A
496 0.44 0.0197 Handan 1 S-A
497 0.4469 0.0305 Handan 3 S-A
498 0.4538 0.03 Handan 4 S-A
499 0.4953 0.029 Zhangjiakou 1 S-A
500 0.5337 0.0142 Zhangjiakou 2 S-A
501 0.2846 0.0305 Zhangjiakou 3 S-A
502 0.2858 0.0219 Hengshui 1 S-A
503 0.2892 0.0273 Hengshui 5 S-A
504 0.2911 0.0392 Xingtai 1 S-A
505 0.2912 0.0225 Xingtai 2 S-A
506 0.2927 0.0309 Cangzhou 1 S-A
507 0.2937 0.0465 Cangzhou 3 S-A
508 0.2956 0.0229 Chongli 1 S-A
509 0.2973 0.0243 Chongli 3 S-A
510 0.2983 0.0232 Baoding 1 S-A
511 0.3018 0.0241 Baoding 3 S-A
512 0.3165 0.0235 Chengde 1 S-A
513 0.3197 0.0247 Chengde 2 S-A
514 0.332 0.0228 Zunhua 1 S-A
515 0.3357 0.0232 Zunhua 2 S-A
516 0.3527 0.0285 Zunhua 3 S-A
517 0.3534 0.0284 Renqiu 1 S-A
518 0.273 0.0219 Renqiu 3 S-A
519 0.2745 0.0125 Shenyang 1 S-A
520 0.2784 0.0208 Shenyang 3 S-A
521 0.2787 0.0249 Dalian 1 S-A
522 0.047 0.0256 Dalian 3 S-A
523 0.0679 0.0095 Shandong 1 S-A
524 0.0524 0.0216 Shandong 3 S-A
525 0.0755 0.0286 Tanghai 1 G-A
526 0.0779 0.0367 Tanghai 2 G-A
527 0.0694 0.0256 Tanghai 3 G-A
528 0.0802 0.0454 Tanghai 4 G-A
529 0.1441 0.015 Tanghai 5 G-A
530 0.1459 0.0237 Tanghai 6 G-A
531 0.1724 0.0253 Tanghai 7 G-A
532 0.1829 0.0155 Tanghai 8 G-A
533 0.18 0.0253 Luannan 1 G-A
534 0.1692 0.0244 Luannan 2 G-A
535 0.1697 0.0246 Luannan 3 G-A
536 0.17 0.0234 Luannan 4 G-A
537 0.1655 0.0089 Luannan 5 G-A
538 0.1658 0.0226 Kaiping 1 G-A
539 0.0294 0.018 Kaiping 2 G-A
540 0.0294 0.023 Kaiping 3 G-A
541 0.0336 0.0106 Yixian 1 G-A
542 0.0336 0.0134 Yixian 2 G-A
543 0.0338 0.0184 Yixian 4 G-A
544 0.0363 0.0012 Yixian 6 G-A
545 0.0394 0.0205 Shexian 1 G-A
546 0.0438 0.0244 Shexian 2 G-A
547 0.0417 0.0258 Shexian 3 G-A
548 0.0138 0.0142 Shexian 4 G-A
549 0.0151 0.0264 Shexian 5 G-A
550 0.0152 0.0455 Handan 1 G-A
551 0.0268 0.011 Handan 3 G-A
552 0.0244 0.0186 Handan 4 G-A
553 0.0231 0.0276 Zhangjiakou 1 G-A
554 0.0192 0.0178 Zhangjiakou 2 G-A
555 0.0182 0.0243 Zhangjiakou 3 G-A
556 0.0088 0.0115 Hengshui 1 G-A
557 0.0091 0.0146 Hengshui 5 G-A
558 0.0107 0.0213 Xingtai 1 G-A
559 0.0109 0.0128 Xingtai 2 G-A
560 0.0115 0.0109 Cangzhou 1 G-A
561 0.0121 0.0172 Cangzhou 3 G-A
562 0.0129 0.0158 Chongli 1 G-A
563 0.005 0.008 Chongli 3 G-A
564 0.0062 0.0209 Baoding 1 G-A
565 0.0072 0.0112 Baoding 3 G-A
566 0.0077 0.0296 Chengde 1 G-A
567 0.2019 0.0238 Chengde 2 G-A
568 0.2032 0.0208 Zunhua 1 G-A
569 0.2049 0.0204 Zunhua 2 G-A
570 0.2056 0.0223 Zunhua 3 G-A
571 0.1987 0.001 Renqiu 1 G-A
572 0.1965 0.0229 Renqiu 3 G-A
573 0.197 0.0226 Shenyang 1 G-A
574 0.0839 0.01 Shenyang 3 G-A
575 0.0791 0.0394 Dalian 1 G-A
576 0.1739 0.019 Dalian 3 G-A
577 0.0406 0.0225 Shandong 1 G-A
578 0.019 0.0389 Shandong 3 G-A

Pearson correlation analysis for four components in dandelion.

Components Cichoric acid Caffeic acid Chlorogenic acid Caftaric acid
Cichoric acid 1 0.410 0.934 0.889
Caffeic acid 1 0.451 0.674
Chlorogenic acid 1 0.774
Caftaric acid 1

Matching numbers of various compounds with reference fingerprint.

No. RT S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 S12 S13 S14 S15 Reference fingerprint RSD (%) of RT RSD (%) of peak area Matching numbers of peak
1 2.318 0 0 0 0 0 0 0 0 8.63 0 0 0 0 0 0 0.575 0 0 1
2 2.541 0 0 0 0 0 0 0 0 6.331 0 21.9 14.973 0 0 0 2.88 1.3 54.16 3
3 2.688 0 0 0 0 0 0 0 0 9.236 0 0 0 0 0 0 0.616 0 0 1
4 3.056 0 0 0 0 0 0 0 0 0 22.975 8.39 0 0 0 22.975 3.623 0.35 46.49 3
5 3.237 8.724 0 0 0 0 6.603 0 0 7.313 0 5.175 0 0 0 0 1.854 1.37 21.25 4
6 3.369 11.109 0 0 0 0 0 0 0 0 0 8.688 0 0 0 0 1.32 1.31 17.3 2
7 3.546 0 0 0 0 0 0 0 0 0 0 5.155 0 0 0 0 0.344 0 0 1
8 3.711 6.551 0 8.155 7.964 0 7.324 0 0 13.008 0 8.024 0 0 0 0 3.402 0.39 26.89 6
9 4.261 58.823 44.069 40.544 59.498 39.897 55.235 79.784 29.548 42.652 47.433 78.453 81.856 30.968 44.163 47.433 52.024 0 32.3 15
10 4.737 8.152 9.173 7.001 7.464 6.891 7.127 8.565 8.324 9.102 7.778 16.782 9.995 6.451 7.222 7.778 5.988 0 32.21 15
11 5.521 0 0 6.632 7.234 0 0 0 7.214 0 0 0 0 0 0 0 1.933 0.05 13.22 3
12 6.082 16.932 8.53 17.211 14.888 15.773 11.236 14.381 11.564 13.326 10.901 14.922 15.469 8.918 15.604 10.901 13.37 0 21.12 15
13 6.264 0 0 0 5.678 0 0 0 0 0 0 6.214 0 0 7.721 0 0 1.23 0 3
14 6.913 0 9.345 10.343 12.234 0 0 23.563 0 0 0 12.342 18.232 0 0 0 3.237 1.512 15.1 6
15 7.198 0 9.234 0 0 0 0 5.61 0 0 0 0 0 0 0 7.507 1.818 0.25 14.41 3
16 10.012 15.601 50.93 14.225 36.09 19.228 28.025 70.559 10.246 18.551 44.01 68.768 74.05 10.69 25.134 44.01 35.341 0.07 63.37 15
17 10.256 0 7.213 0 0 0 0 6.324 0 0 0 0 8.233 0 0 0 1.257 0.45 13.32 3

Aldini, R., Micucci, M., Cevenini, M., Fato, R., Bergamini, C., Nanni, C., Cont, M., Camborata, C., Spinozzi, S., and Montagnani, M. (2014). Antiinflammatory effect of phytosterols in experimental murine colitis model: Prevention, induction, remission study. PLoS ONE, 9(9), e108112, doi: 10.1371/journal.pone.0108112. AldiniR. MicucciM. CeveniniM. FatoR. BergaminiC. NanniC. ContM. CamborataC. SpinozziS. MontagnaniM. 2014 Antiinflammatory effect of phytosterols in experimental murine colitis model: Prevention, induction, remission study PLoS ONE 9 9 e108112 10.1371/journal.pone.0108112 418232725268769 Otwórz DOISearch in Google Scholar

Chen, J., Gong, D., Liu, X., Sun, G., and Sun, W. (2021). Quality and antioxidant activity evaluation of dandelion by HPLC with five-wavelength fusion fingerprint. New Journal of Chemistry, 45(22), 9856–9863. ChenJ. GongD. LiuX. SunG. SunW. 2021 Quality and antioxidant activity evaluation of dandelion by HPLC with five-wavelength fusion fingerprint New Journal of Chemistry 45 22 9856 9863 10.1039/D1NJ01422F Search in Google Scholar

Chen, M., Kong, J., Zhang, Y., He, J., Sun, R., Huang, G., Lu, D., Wu, Q., Wang, M., Li, W., Li, S., Fan, Y., Feng, X., Huang, Y., Jiang, Y., and Shi, R. (2018). Quantitative determination of phenolic characteristic components in Taraxaci herba and its correlation analysis of quality characterization of specific chromatogram. Chinese Journal of Experimental Traditional Medical Formulae, 24(16), 12–20. ChenM. KongJ. ZhangY. HeJ. SunR. HuangG. LuD. WuQ. WangM. LiW. LiS. FanY. FengX. HuangY. JiangY. ShiR. 2018 Quantitative determination of phenolic characteristic components in Taraxaci herba and its correlation analysis of quality characterization of specific chromatogram Chinese Journal of Experimental Traditional Medical Formulae 24 16 12 20 Search in Google Scholar

Chen, X., Min, D., Yasir, T. A., and Hu, Y. G. (2012). Evaluation of 14 morphological, yield-related and physiological traits as indicators of drought tolerance in Chinese winter bread wheat revealed by analysis of the membership function value of drought tolerance (MFVD). Field Crops Research, 137, 195–201. ChenX. MinD. YasirT. A. HuY. G. 2012 Evaluation of 14 morphological, yield-related and physiological traits as indicators of drought tolerance in Chinese winter bread wheat revealed by analysis of the membership function value of drought tolerance (MFVD) Field Crops Research 137 195 201 10.1016/j.fcr.2012.09.008 Search in Google Scholar

Didier, F., Catherine, F., Odile, T., and Jean-Louis, L. (2011). Caffeoyl derivatives: Major antioxidant compounds of some wild herbs of the Asteraceae family. Food and Nutrition Sciences, 2, 181–192. DidierF. CatherineF. OdileT. Jean-LouisL. 2011 Caffeoyl derivatives: Major antioxidant compounds of some wild herbs of the Asteraceae family Food and Nutrition Sciences 2 181 192 10.4236/fns.2011.230025 Search in Google Scholar

Fatima, T., Bashir, O., Naseer, B., and Hussain, S. Z. (2018). Dandelion: Phytochemistry and clinical potential. Journal of Medicinal Plants Studies, 6, 198–202. FatimaT. BashirO. NaseerB. HussainS. Z. 2018 Dandelion: Phytochemistry and clinical potential Journal of Medicinal Plants Studies 6 198 202 Search in Google Scholar

González-Castejón, M., Visioli, F., and Rodriguez-Casado, A. (2012). Diverse biological activities of dandelion. Nutrition Reviews, 70(9), 534–547. González-CastejónM. VisioliF. Rodriguez-CasadoA. 2012 Diverse biological activities of dandelion Nutrition Reviews 70 9 534 547 10.1111/j.1753-4887.2012.00509.x22946853 Search in Google Scholar

Grauso, L., Emrick, S., De Falco, B., Lanzotti, V., and Bonanomi, G. (2019). Common dandelion: A review of its botanical, phytochemical and pharmacological profiles. Phytochemistry Reviews, 18(4), 1115–1132. GrausoL. EmrickS. De FalcoB. LanzottiV. BonanomiG. 2019 Common dandelion: A review of its botanical, phytochemical and pharmacological profiles Phytochemistry Reviews 18 4 1115 1132 10.1007/s11101-019-09622-2 Search in Google Scholar

Hao, Z. (2010). Studies on the quality standard of dandelion. M.Sc. dissertation, Henan University of Chinese Medicine, China, doi: 10.7666/d.d196724. HaoZ. 2010 Studies on the quality standard of dandelion M.Sc. dissertation, Henan University of Chinese Medicine China 10.7666/d.d196724 Otwórz DOISearch in Google Scholar

Li, C., Tian, Y., Zhao, C., Li, S., Wang, T., Qiao, B., and Fu, Y. (2021). Application of fingerprint combined with quantitative analysis and multivariate chemometric methods in quality evaluation of dandelion (Taraxacum mongolicum). Royal Society Open Science, 8(10), 210614, doi: 10.1098/rsos.210614. LiC. TianY. ZhaoC. LiS. WangT. QiaoB. FuY. 2021 Application of fingerprint combined with quantitative analysis and multivariate chemometric methods in quality evaluation of dandelion (Taraxacum mongolicum) Royal Society Open Science 8 10 210614, 10.1098/rsos.210614 854878834729206 Otwórz DOISearch in Google Scholar

Ling, Y., Fang, G., Xiao, Y., and Zheng, J. (1999). Studies on quality standard of dandelions (Taraxacum Weber). Chinese Traditional and Herbal Drugs, 12, 897–899. LingY. FangG. XiaoY. ZhengJ. 1999 Studies on quality standard of dandelions (Taraxacum Weber) Chinese Traditional and Herbal Drugs 12 897 899 Search in Google Scholar

Lis, B., and Olas, B. (2019). Pro-health activity of dandelion (Taraxacum officinale L.) and its food products – history and present. Journal of Functional Foods, 59, 40–48. LisB. OlasB. 2019 Pro-health activity of dandelion (Taraxacum officinale L.) and its food products – history and present Journal of Functional Foods 59 40 48 10.1016/j.jff.2019.05.012 Search in Google Scholar

Liu, Y., Lan, R., Dui, J., and Su, Y. (2017). Simultaneous determination of monocaffeyltartaric acid, chlorogenic acid, caffeic acid and chicoric acid in herba taraxaci by HPLC. China Pharmacist, 20(9), 1677–1679. LiuY. LanR. DuiJ. SuY. 2017 Simultaneous determination of monocaffeyltartaric acid, chlorogenic acid, caffeic acid and chicoric acid in herba taraxaci by HPLC China Pharmacist 20 9 1677 1679 Search in Google Scholar

Ning, W., Jia, Q., Zhu, D., and Tianlai, L. (2012). Determination of chlorogenic acid and caffeic acid in 11 species of Taraxacum distributed in northeast China. Journal of Shenyang Agricultural University, 43(5), 595–598. NingW. JiaQ. ZhuD. TianlaiL. 2012 Determination of chlorogenic acid and caffeic acid in 11 species of Taraxacum distributed in northeast China Journal of Shenyang Agricultural University 43 5 595 598 Search in Google Scholar

Ovesná, Z., Vachálková, A., and Horváthová, K. (2004). Taraxasterol and b-sitosterol: New naturally compounds with chemoprotective/chemopreventive effects mini review. Neoplasma, 51(6), 407–414. OvesnáZ. VachálkováA. HorváthováK. 2004 Taraxasterol and b-sitosterol: New naturally compounds with chemoprotective/chemopreventive effects mini review Neoplasma 51 6 407 414 Search in Google Scholar

Tajner-Czopek, A., Gertchen, M., Rytel, E., Kita, A., Kucharska, A. Z., and Sokółętowska, A. (2020). Study of antioxidant activity of some medicinal plants having high content of caffeic acid derivatives. Antioxidants, 9(5), 412, doi: 10.3390/antiox9050412. Tajner-CzopekA. GertchenM. RytelE. KitaA. KucharskaA. Z. Sokół-ŁętowskaA. 2020 Study of antioxidant activity of some medicinal plants having high content of caffeic acid derivatives Antioxidants 9 5 412 10.3390/antiox9050412 727875132408518 Otwórz DOISearch in Google Scholar

Wu, Z., Li, Z., Xue, Z., Lu, X., and Wang, X. (2020a). Optimization of extraction technology for determination of caffeic and chlorogenic acid in dandelion. Banat's Journal of Biotechnology, 11(21), 26–37. WuZ. LiZ. XueZ. LuX. WangX. 2020a Optimization of extraction technology for determination of caffeic and chlorogenic acid in dandelion Banat's Journal of Biotechnology 11 21 26 37 10.7904/2068-4738-XI(21)-26 Search in Google Scholar

Wu, Z., Xue, Z., Lu, X., Jia, Y., Wang, X., and Zhang, X. (2020b). Salt-tolerance identification and quality evaluation of Abelmoschus manihot (L.) Medik. Canadian Journal of Plant Science, 100(5), 568–574. WuZ. XueZ. LuX. JiaY. WangX. ZhangX. 2020b Salt-tolerance identification and quality evaluation of Abelmoschus manihot (L.) Medik Canadian Journal of Plant Science 100 5 568 574 10.1139/cjps-2019-0231 Search in Google Scholar

Wu, Z., Xue, Z., Li, H., Zhang, X., Wang, X., and Lu, X. (2019). Cultivation of dandelion (Taraxacum erythropodium) on coastal saline land based on the control of salinity and fertilizer. Folia Horticulturae, 31(2), 277–284. WuZ. XueZ. LiH. ZhangX. WangX. LuX. 2019 Cultivation of dandelion (Taraxacum erythropodium) on coastal saline land based on the control of salinity and fertilizer Folia Horticulturae 31 2 277 284 10.2478/fhort-2019-0022 Search in Google Scholar

Zhang, P., Guo, X.-H., Jing, W.-G., Li, M.-H., Cheng, X.-L., Wei, F., and Ma, S.-C. (2021). Quality of Chinese medicinal materials and decoction pieces in 2020. Modern Chinese Medicine, 23(10), 1671–1678. ZhangP. GuoX.-H. JingW.-G. LiM.-H. ChengX.-L. WeiF. MaS.-C. 2021 Quality of Chinese medicinal materials and decoction pieces in 2020 Modern Chinese Medicine 23 10 1671 1678 Search in Google Scholar

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