Assessment of Quercetin Content in Selected Vegetables and Fruits by Conventional Extraction and High Performance Liquid Chromatography

Introduction

Quercetin (QRN) is a flavonol (plant polyphenol) found in fruits, vegetables, seeds and edible parts. It is also present in medicinal botanicals, plays a key role in developing antioxidants. Phenolic compound play a crucial role in maintaining nutritious substances which help to improve human health from chronic diseases. Figure.1 shows the chemical structure of QRN .Whose name is derived from the Latin word “quercetum,” which signifies “oak forest,” it  is   a category in the class of flavonoids, and a sub class of flavonol¹ . Flavonoids are phenolic compounds with a three-ring system, composed of 15 carbon atoms in the form of C₆,C₃, C₆.This compound cannot be synthesised by the human body². QRN a yellow crystalline substance which is soluble in alcohol is anticipated that persons with balanced nutrition consume 25–50 mg per day³. The optimal effective dose of QRN for decreasing blood pressure and inflammation has been determined⁴.QRN is not a carcinogen, and may protect against Genotoxicants⁵. In the food sector, antioxidant supplementation may help to avoid mycotoxin toxicity⁶. The bioctivity and solubility of QRN in the body increase when combined with metal ions to build a complex⁷ . Green tea infusions and bitterness are due to poly phenols were investigated⁸. Deep Eutectic Solvents (DESs) gives high yield for extraction of QRN and its glycosylated form from onion peels⁹. Phenolic compounds have antioxidant, antimutagenic, anticarcinogenic, anti-inflammatory, and antimicrobial activities¹⁰.QRN play a vital role in the treatment of rheumatoid arthritis¹³ and   it has been demonstrated to lessen the risk of death in COVID-19 patients due to presence of anti-inflammatory and antioxidant activities¹¹

Figure 1: Structure of  QRN. Click here to View figure

The carrot and grape contains the most important phenolic compound which act as anti-oxidant activities and non–carcenogenic along with other nutritional compounds. The author reported QRN content present in vegetable (carrot) and fruit (grape) extraction and characteristics  by using HPLC-UV method

Materials and Methods

Solvents and chemicals

Reference standard of QRN was purchased from Sigma-Aldrich. Methanol, acetonitrile,  and HPLC-grade water, orthophosphoric acid,  acquired from Merck,  India

Plant materials

Thefresh and healthy vegetable carrot( Daucus carota sp . sativus)  and fruit grape(genus Vitis) were procured by cultivators from local market, Visakhapatnam, Andhra Pradesh ,India. The selected  vegetable and fruit samples were stored in glass containers and kept at room temperature.

Sample and standard solution preparation

The fruit and vegetable material procured from cultivators were dried and washed with plenty of water after washing /cleaning ,the materials were properly cut into small slices or pieces and placed on a clean filter paper for further work .Then the plant material is finely grounded by using a potable grinding machine, Maceration technique was adopted for the extraction procedure in which 100g of each sample was soaked in  small portions with (1:20) methanol and 1:1 aqueous Hydrochloric acid solution  in a conical flask with occasional shaking for two hours and using orbital shaking incubator for 60 minutes. The contents are occasionally  heated for 1 hour at 60 ^o C on water bath and  the contents were  cooled and  subjected to filtration. The process was repeated for 3 times and filtrate was mixed. The filtrate obtained was dried by using a rotary vaccum evaporator at 40^oC to get viscous concentrate sample and stored for analysis.

Mobile phase preparation

Prepare a mixture of Methanol and Water in a ratio of 700:300 v/v with 1.0ml formic acid.

Preparation of Standard Solution

10 mg of QRN standard was taken  into a clean and dry 50.0 mL volumetric flask. 5 mL of diluent was added, then dilute to the desired volume with diluent. Transfered1.0 mL  into 10.0 mL volumetric flask and dilute to the volume with diluent. Further 1.0 mL of this solution  take into 20.0 mL volumetric flask and dilute to the volume with diluent..

Preparation of test solution

Weighed accurately and transfer about 1000 mg of test sample into a clean and dry 10.0 mL volumetric flask. Add about 5 mL of diluent, sonicate to dissolve the content and dilute to the volume with diluent.

Sample preparation optimization

Various methods have been reported for the extraction and quantification of QRN^12-16.The procedure was optimized with regard to mobile phase Acetonitrile-Water, Methanol and Water in a ratio of 700:300 v/v with 1.0ml formic acid.

Chromatographic conditions

Agilent Technologies, 1260 was used for method development, quantification and method validation. The various chromatographic conditions were given in table 1

Table 1: Chromatographic conditions.

Instrument	High Performance Liquid Chromatograph, Agilent 1260
Detector	UV
Diluent	Mobile phase
Column	Zodiac C18, 250mmx 4.6mm, 5µm
Wavelength of detection	280nm
Injection volume	10µl
Chromatogram run time	30min
Column temperature	35 ºC
Sampler cooler temperature	10ºC
Flow rate	1.0 mL/min
Pump mode	Isocratic

 

Results and Discussion

The most abundant dietary flavonoid is QRN and is used to reduce the blood pressure, inflammation, blood sugar etc. The QRN content in fruits and vegetables is very imperative. QRN maximum wavelength was obtained at 285nm in Methanol. The optimum mobile phase was a mixture of acetonitrile-water and 700:300 v/v with 1.0ml formic acid. The chromatograms show a very good baseline resolution of analytes. Chromatograms of QRN were presented in figures 2-5.The QRN content in selected carrot and grape samples were presented in table 2.

Table 2: QRN content in grape and carrot

Fruit/vegetable	Sample-1	Sample-2	Sample-3	Sample-4	Sample-5
Grape(mg/100g) white	1.43	1.57	1.29	1.59	1.31
Carrot(mg/100g)	0.84	0.37	0.65	0.49	0.92

 

Figure 2: Blank chromatogram. Click here to View figure

Figure 3: QRN-HPLC Standard chromatogram. Click here to View figure

Figure 4: QRN HPLC chromatogram-Carrot sample. Click here to View figure

Figure 5: QRN HPLC chromatogram-Grape sample. Click here to View figure

Method validation:

Method validation was performed as per  AOAC(Association of Official Analytical Chemists) and ICH guidelines.Limit of Detection (LOD), Limit of Quantitation  (LOQ), Precision at LOQ level, System suitability, Specificity, Linearity,  Accuracy etc were studied.

Limit of detection and Limit of Quantification

LOQ

Transfer 2.5mL of standard solution in to 10mL volumetric flask and make up to mark with diluent.

LOD

Transfer 3.3mL of LOQ Solution into 10 mL volumetric flask and dilute to the volume with diluent. Limit of Quantification is considered for this validation is 25% of the specification and Limit of Detection is considered for this validation is 33% of the LOQ Solution. Injected blank followed by six injections of LOQ solution and inject LOD solution in triplicate. The areas of standard, LOQ and LOD were presented in table 3.

Table 3: Area of Standard LOQ and LOD

S. No	Name	Area of Standard solution
		I-1	I-2		1-3			I-4		1-5			I-6			Average			SD			RSD%
1	Quercetin	88.29	89.06		88.86			90.19		90.38			94.81			90.27			2.37			2.62
		Area of LOQ solution
		I-1		I-2		1-3			I-4			1-5		I-6			Average			SD			RSD%
2	Quercetin	19.52		19.3		19.35			19.21			19.4		19.35			19.355			0.10			0.53
		Area of LOD solutions													Average			SD			RSD%
		I-1					I-2				Injection-3
3	Quercetin	5.94					6.14				6.15				6.08			0.12			1.95

I:Injection   SD: Standard deviation RSD: relative standard deviation

System suitability

Injected  system suitability solution in  six replicates. The % RSD values (given in table 4) of the peak area and Retention time of all analytes  were less than 2.0% which satisfy the acceptance criteria.

Table 4: Percentage of RSD

S.No	Name	Area of Standard solutions
		I-1	I-2	1-3	I-4	1-5	I-6	Average	SD	RSD%
1	Quercetin	91.95	90.89	91.16	90.67	92.34	91.12	91.36	0.65	0.71

 

Specificity

Specificity reveals that the method is proficient of resolving the analyte(s). Accurately weighed and transfer about 10 mg of QRN standard into a clean and dry 50.0 mL volumetric flask.Further dilutions were done and  dilute to the volume with diluent.

Preparation of test solution

Weigh accurately and transfer about 1000 mg of test sample into a clean and dry 10.0 mL volumetric flask. Add about 5 mL of diluent, sonicate to dissolve the content and dilute to the volume with diluent.

Preparation of Spiked solution

Weighed accurately and transfer about 1000 mg of test sample into a clean and dry 10.0 mL volumetric flask. Add about 5 mL of diluent, sonicate to dissolve the content and added 0.5ml of Stock Standard solution and dilute to the volume with diluent.

No significant interference of blank and Impurity peak with analyte peak was observed.

Linearity

The linearity test reveals that the method of detection has a linear retort to concentration over the range of concentrations of the fastidious product.  Linearity to be performed separately by preparing in the range 25%-200% of Impurities concentration. Correlation coefficient of each impurity should be more than 0.99. Areas of standard and linearity were given table 5 and 6, the linearity graph was shown in figure 6.Based on final result the Correlation Coefficient was found with in acceptance criteria.

Table 5: Area of standard solution

Name	Area of standard solution
	I-1	I-2	I-3	I-4	I-5	I-6	Average	SD	RSD%
Quercetin	91.95	90.89	91.16	90.67	92.34	91.12	91.36	0.65	0.71

I-Injection

Table 6: Linearity

Sr.No	Injection Id	Areas of linearity
		Percentage	Quercetin
1	Solution-1	25	19.91
2	Solution-2	50	44.35
3	Solution-3	100	93.02
4	Solution-4	150	138.3
5	Solution-5	200	193.36
Correlation Coefficient		0.9985

 

Figure 6: Linearity graph of QRN. Click here to View figure

Accuracy

Generally accuracy reveals the potential of the method to recuperate a identified quantity of active or degradant  etc. from the placebo matrix. To demonstrate accuracy for Quercetin impurities, revival test was performed using solutions containing 50%, 100% and 200% of the theoretical active concentration in the end product. Every level was performed in triplicate and the mean value for QRN level was calculated and reported. Percentage of RSD , LOQ level  not more than 15.0% . The acceptance criteria for impurities in this parameter are that recovery for each of the concentration levels is within the limits 80.0% – 120.0%. The accuracy results were given in table 7 and recovery in table 8

Table 7: Accuracy

Accuracy at LOQ
I- 1	I-2	I-3	Average	SD	%RSD
9.04	9.10	9.19	9.11	0.08	0.83
Accuracy at 50%
22.39	21.84	22.11	22.11	0.28	1.24
Accuracy at 100%
61.99	62.3	62.04	62.11	0.17	0.27
Accuracy at 200%
163.17	164.00	162.95	163.37	0.55	0.34

I- Injection

Table 8: Percentage recovery.

Name	Accuracy at LOQ	Accuracy at 50%	Accuracy at 100%	Accuracy at 200%
	Result	Result	Result	Result
Quercetin	101.15	104.04	102.14	100.51

 

Conclusion

The QRN content varies between geographical areas, cultivators and plant parts. Methanol was used for the extraction of grape and carrot and the high total phenolic content  shows  strong antioxidant activities. Determination of quercetin is studied by using High performance liquid chromatography. The chromatographic separation was performed on Zodiac C18, 250mmx 4.6mm, 5µm column, detection at 255nm and flow rate 1mL/min. The limits of detection(LOD) and quantification(LOQ) parameters were in the ranges of 0.1–0.3 and 0.3–1.0 μ g/ mL. The detection of the active substance in carrot and grapes using the HPLC method has the advantage of being simple, fast, accurate and the reported method was validated.

Acknowledgement

We are thankful to the management, Department of chemistry, School of science, GITAM (Deemed to be University) Visakhapatnam, Andhra Pradesh, India for their support and encouragement given to us.

Conflict of Interest

The corresponding author declare that there is no conflict of interest.

References

1. Tsanova,S.; Ribarova,F.; Petkov,V., Bulg Chem Commun, 2018,50(1), 69-73.
2. David, A.V.; Arulmoli, R.;  Parasuraman, S., Pharmacognosy reviews,2016, 10(20), 84-89.  
   CrossRef
3. Septembre-Malaterre, A.; Boumendjel, A.; Seteyen, A. L. S.; Boina, C.; Gasque, P.; Guiraud, P.;  Sélambarom, J., ,Phytomedicine Plus, 2022, 2(1),100220.
   CrossRef
4. Dabeek, W. M.;Marra, M. V., Nutrients,2019,11(10): 2288.  
   CrossRef
5. Batiha, G.E.S.; Beshbishy, A.M.; Ikram, M.; Mulla, Z.S.; El-Hack, M.E.A.; Taha, A.E.; Algammal, A.M.; Elewa, Y.H.A.,. Foods, 2020,9, 374.
   CrossRef
6. Yang, D.; Wang, T.; Long, M.; Li, P.,. Oxidative Medicine and Cellular Longevity, 2020, 8825387.
   CrossRef
7. Moodi, Z.; Bagherzade, G.; Peters, J., Bioinorganic chemistry and applications, 2021, 8818452
8. Chen,Y.H.; Zhang,Y.H.; Chen,G.S.;Yin, J.F.;Chen, J. X.; Wang, F.;Xu,Y.Q., NPJ science of food, 2022,6(1),1-8.
   CrossRef
9. Ciardi, M.; Ianni, F.; Sardella, R;, Di Bona, S.; Cossignani, L.; Germani, R.;Clementi, C., Materials,2021,14(21),6465.
   CrossRef
10. Sharifi, N.; Mahernia, S.; Amanlou, M.,Pharmaceutical Sciences, 2016,23(1),59-65.
    CrossRef
11. Khursheed, R.; Singh, S. K.; Kapoor, B.; Gulati, M.; Wadhwa, S.; Gupta, S.;Kumar, V., GEN Open,2021, 1(1), 43-52.
12. Bhagat, S.; Rathore, M.; Kachhwaha, S.; Sharma, H. K., Ind. J. Pure app. Biosci, 2021,9, 254-261.
13. Berwal, M.,Indian Journal of Arid Horticulture,2018, 13(1-2), 107-108.
14. Gull, T.; Sultana, B.; Anwar, F.; Nouman, W.; Mehmood, T.; Sher, M., 2018,12(3), 1539-1547.
15. Olajire, A.;Azeez, L.,African Journal of Food Science Technology,2011,2(2), 22-29.
16. Proestos, C.; Boziaris, I. S.; Nychas, G. J.; Komaitis, M.,Food chemistry, 2006, 95(4), 664- 671..

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