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Method validation for bifenthrin emulsifiable concentrate and uncertainty calculation using gas chromatographic approach



Bifenthrin is the third-generation synthetic pyrethroid insecticide having an effective control on the pest of cotton, vegetable, and fruits. This study is focused on the validation of the test procedure for the quantitative determination of bifenthrin contents in the emulsifiable concentrate and measurement of uncertainty. The purpose of this validation procedure is to demonstrate that it is suitable for the intended use. This was determined by gas chromatography with a flame ionization detector (FID). The estimation was carried out on Shimadzu GC equipped with TRB-5 (95% dimethyl, 5% diphenyl polysiloxane) column using a nitrogen carrier gas.


Different parameters of validation (precision, accuracy, linearity, specificity, selectivity, and robustness) were executed. All steps of method validation were performed, and its uncertainty is determined. The method is simple, selective, accurate, precise, cost-effective, and suitable. The validation parameters are based on harmonized guidelines on the validation of the analytical test method.


Pesticide formulation bodies can use this method for the qualitative and quantitative determination of bifenthrin different formulations. These data verify that the method is validated, and all results are in an acceptable limit. The method is developed on GC. Moreover, the analysis time is also short as compared to that of HPLC. The developed method is simple reliable and has a realistic approach.


Pesticides are being employed at a large scale throughout the world for the control of pests and for the good yield of crops in the agriculture sector [1,2,3,4,5,6,7]. There are so many pesticide groups including organophosphates, organochlorides, carbamates, and pyrethroids. Among all the pesticides, pyrethroids are in good fame for application to control the pests. Pyrethroids have efficient control over pests like jassid, thrips, and whitefly [8,9,10]. The major sucking insect pests whitefly (Bemisia tabaci Genn), thrips (Thrips tabaci Lind), and jassid (Amrasca biguttula Ishida) are harmful to the cotton and are responsible for 40% damage of cotton [5, 11, 12]. It is studied that pyrethroid sticks and activates the voltage-sensitive sodium channels of the heart, nerve, and skeletal muscle cell membranes in the nervous system of insects which ultimately proceed to death. Paralysis is the startling effect of pyrethroid which leads to death. Pyrethrins have a low level of toxicity in mammals and birds [13,14,15].

Bifenthrin, cypermethrin, deltamethrin, and permethrin are the examples of pesticides from group pyrethroids. Bifenthrin is the third-generation synthetic pyrethroid insecticide having an effective control on the pest of cotton, vegetable, and fruits.

Chemically, bifenthrin is 2-methylbiphenyl-3-ylmethyl (Z)-(1 RS)-cis-3-[2-chloro-3,3,3-trifluoroprop-1enyl)-2,2-dimethyl cyclopropane carboxylate. Bifenthrin has shown assurance in the pest control of vegetables [7, 16]. Figure 1 shows the structural formula for bifenthrin. Environmental Protection Agency (EPA) has registered the bifenthrin for ornamental and cotton pest control usage. It is one of the moderately stable active ingredients under sunlight conditions. Its toxicity level is oral rat LD 50 = 54 to70 mg/kg. The mode of action of bifenthrin is through the central nervous system. Skin irritation effects of bifenthrin can last for 12 h.

Fig. 1
figure 1

Structure of bifenthrin

Bifenthrin is a pyrethroid insecticide that is widely used to kill the insects [8]. There is effectual control of aphids, jasid, and whiteflies through bifenthrin 10 EC with 97.9%, 85.9%, and 86% mortality rate, respectively [17]. Bifenthrin is very effective against the malarial attack and inhabits the mosquitoes for blood-sucking activity [18,19,20,21]. Literature review showed that bifenthrin was analyzed and quantified through different techniques like GC-AED [22], hall electrolytic conductivity detector [23], GCMS [24], GC with ECD [25], HPLC [26], GCMS using 100% polydimethylsiloxane) fused silica capillary column [1], GC with ECD, and dimethylpolysiloxane column [9, 10, 12, 15, 27,28,29,30].

Ermer and Miller [31] reported that validation includes the process and steps that ensure the suitability of the intended method for a particular test. ISO 8402:1994 defines the validation as “Confirmation by examination and provision of objective evidence that the particular requirements for a specified intended use are fulfilled.”

Validation of the test method will make it reliable for testing. The confidence level for the results extracted through a validated method is more than a non-validated method. Validation ensures the fitness for purpose. Method validation is a reliable process having different analytical steps for the trueness of any analytical test method for implementation onwards for testing. Internationally, it is recommended that the laboratory must take some evaluations that convince the dependability of the test method. Method validation and uncertainty calculation will help to determine the capacity of any test methods. Both of these are also recommended by ISO 17025 for any laboratory. So, both of these have solid references to make it applicable and practicable in any laboratory. Method validation includes suitability, specificity and selectivity, precision, accuracy, linearity, robustness, limit of detection, and limit of quantification [32,33,34].

Uncertainty is mandatory for any measurement which will ensure the reliability of that measured results. Uncertainty includes the involvement of all factors which may affect the test results up to defined value [35]. The main objective of this study was to perform method validation and to calculate uncertainty measurements.


All the chemicals and reagents employed in this study were of analytical grade and were purchased from Sigma Aldrich. The stock solution of bifenthrin is prepared by taking 0.11 g in 25 mLflask. Add 10 mLand 1% internal standard solution (ISS) followed by mixing and then filtration for injection into GC injector. 1% ISS is prepared by taking 1 g di-butyl phthalate (DBP) into a 100 mLvolumetric flask and made up the volume with acetone solvent.

Sample preparation

0.97 g of emulsifiable concentrate pesticide formulation sample was taken into 25 mLvolumetric flask. Ten milligrams of internal standard solution is added through a pipette. Mixed it well and sonicate for 1 min. The sample was then filtered through a 0.45-μ syringe filter, and after filtration, the sample was injected into GC.

A GC equipped with a flame ionization detector (FID) was used for the present research work. The separation was achieved using TRB-5 (95% dimethyl, 5% diphenyl polysiloxane bonded and cross-linked phase) (0.25-mm ID, 30-m length, and 0.1-μm-film thickness. The carrier gas was nitrogen with a flow rate of 20 mL/min for 4.5 min and then increased to 25 mL/min for 9 min at the rate of 20 mL/min. The column temperature was 220 °C for 5 min and then increased to 260 °C for 9 min at the rate of 50 °C per min. Injector temperature and detector temperature were 260 °C.

Method validation

Suitability of the system is checked by injecting the same solution of active ingredient repeatedly more than one time; each and every time the peak area of the active ingredient was consistent with reasonable relative standard deviation. The linearity of the method is confirmed by injecting the solutions having increased concentrations in specific regular proportions. The specificity and selectivity of the method are tested. This was done by making the solutions having ingredients of test method and formulation separately in a unique way. Accuracy is the ability of the test method to conclude the results near the true value. Accuracy is verified after getting the analysis results of known increased concentrations (80%, 100%, and 120% of claimed active ingredient) [36,37,38,39]. The precision is the recovery of the results over and over again when each time tested. The robustness of the test method is evaluated by changing different parameters of the test method. The limit of detection and limit of quantitation are calculated by signal to noise ratio [27, 40,41,42]. The uncertainty of the test method estimates using the Eurachem guide [43].


Suitability and linearity

Five samples having a concentration of 0.11 g of the standard bifenthrin were injected repeatedly to check the response of the system. The response of the system is shown in Table 1.

Table 1 Conclusive data with peak areas and standard deviation for system suitability

The calibration curve was made of concentrations ranges from 0.06 g bifenthrin/10 ml ISS solution to 0.16 g bifenthrin/10 ml ISS solution (Figs. 2 and 3; Table 2).

Fig. 2
figure 2

Linearity graph showing the relation of bifenthrin concentration and peak area ratio

Fig. 3
figure 3

Linearity graph showing the relation of bifenthrin concentration and peak area

Table 2 Bifenthrin responses summarized according to the increased concentration (linearity)

Specificity and selectivity

During the testing, the acetone is used while during the formulation of bifenthrin, 10 EC emulsifier and xylene are used. Injecting solutions of each of these is prepared and injected into GC to check the response of all ingredients, and it was found that no interfering peaks were observed in the chromatograms during the testing with active ingredient peak area (Fig. 4).

Fig. 4
figure 4

Representative gas chromatogram showing the specificity and selectivity of the method

Accuracy and precision

Accuracy is assessed by analyzing a sample with known concentrations and comparing the measured value with the true value as supplied with the material (Table 3). The precision of the method is checked by analyzing the samples in repetition. The standard weight taken was 0.11 g and then diluted up to 10 mLof internal standard solution, and a sample taken was 0.97 g (+ 0.005 g) which is diluted up to 10 mL through the same internal standard.

Table 3 Data for accuracy and precision studies


Limit of detection (LOD) is the lowest amount of the active ingredient that can be detected, and the limit of quantitation (LOQ) is the lowest amount of analyte that can be detected and can be quantified. The LOD is not necessarily that which can be determined and accepted with accuracy and precision. Through the signal to noise ratio, the LOQ and LOD are determined. The samples are injected to such extent that the signal to noise ratio was 3:1, and the amount of active sample responded to ratio 3:1 is LOD. On the other hand, the sample amount responded to a signal to noise ratio 10:1 is LOQ.

For robustness, the ability of the method is checked by doing small variations in the method parameters. The conclusive data acquired from different variations is summarized (Table 4) while uncertainty measurements are given in Table 5. Uncertainty can be expressed in both ways, i.e., positive and negative.

Table 4 Summarized data for robustness
Table 5 Uncertainty calculation


Analytical method development and validation are an important process for pesticides. This is to ensure quality and safety. The analytical methods provide data for analytical problem sensitivity, accuracy, precision, and range of analysis. These requirements essentially are the specifications to analyze the desired analyte with certainty. Five samples having a concentration of 0.11 g of the standard bifenthrin were injected repeatedly to check the response of the system. The response of the system in terms of peak area, retention time, and theoretical plates were evaluated. The importance of equipment suitability cannot be neglected as it shows the availability of equal response on getting the analyte. The relative standard deviation (RSD) of the observed retention factor (RF) values is 0.27% which confirms that the system is suitable for analysis. These results were consistent. Linearity is the step of the validation that verifies the response of the detector against the subjected sample. The absence of linear response may be attributed to equipment, extraction solvent, dilution, injection volume, or complex formation issues.

Measuring the samples with reference to accuracy, it is the closeness of the results that is accepted.

The response must be linear if the concentration is increased in the same pattern. During testing, acetone is used while during the formulation of bifenthrin, 10 EC emulsifier and xylene are used. Injecting solutions are prepared and injected into GC to check the response of all ingredients. It was found that no interfering peaks were observed in the chromatogram during testing with an active ingredient peak area. Varying amounts of active ingredient (80%, 100%, and 120% of claimed active ingredient) are spiked. The precision of the method is checked by analyzing the samples in repetition. On day 1, standard and samples against these standards were injected to get results. Similarly, on day 2, freshly prepared standard solutions and sample solutions were injected to get the detector response.

The robustness defines the flexibility of the intended test method for validation. Different types of changes done in the test method as we changed the column temperature, detector temperature, injector temperature, sample temperature, etc. After changing the method parameters, there should be no prominent/effective change in the test result.

Uncertainty is the range in which the concluded value may resonate. Error expresses as a problem and can only be expressed (in statistical terms) as either positive or negative value, while uncertainty is expressed in both forms positive and negative [37, 44, 45]. Uncertainty from two types of sources is calculated and then merged into the final uncertainty budget. Type A was calculated through reproducibility and repeatability standard deviation which onwards used to measure standard uncertainty. Type B is calculated through different distribution laws like normal distribution, rectangular distribution, and triangular distribution law. Through the uncertainty budget, relative uncertainty is calculated. Combined uncertainty results through relative uncertainty which multiplied with coverage factor resulted in expanded uncertainty with a certain confidence level. The uncertainty value of the test method was calculated is 0.18%w/w with a 99% confidence level. The proposed method was found to be simple, swift, linear, accurate, precise, and robust for the determination and quantification of bifenthrin. Hence, the method could be easily and conveniently adapted for routine analysis.


The following conclusions are drawn:

Method validation was performed as per ICH guidelines. The method was validated for precision, linearity, robustness, accuracy, specificity, and precision. The data verifies that the method is validated, and all results are in an acceptable limit. The method is developed on GC. Analysis of the bifenthrin 10 EC can be possible on HPLC also, but it requires considerable amounts of solvents for sample dilution as compared to GC. Moreover, the analysis time is also short as compared to that of HPLC. The developed method is simple and reliable and has a realistic approach and could certainly and appropriately implemented for routine analysis.

Availability of data and materials

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



Di-butyl phthalate


Emulsifiable concentrate


Electron capture detector


Environmental Protection Agency


Food and Agriculture Organization


Flame ionization detector


Gas chromatography


Gas chromatography-electroantennogram detector


Gas chromatography-mass spectrometry


High-performance liquid chromatography


Internal diameter


International Organization for Standardization


Internal standard solution


Limit of detection


Limit of quantification


Retention factor


Relative standard deviation


United States of America


  1. Menezes Filho A, dos Santos FN, Pereira PAP (2010) Development, validation and application of a method based on DI-SPME and GC–MS for determination of pesticides of different chemical groups in surface and groundwater samples. Microchem J 96(1):139–145

    Article  CAS  Google Scholar 

  2. Suleman M, Nouren S, Hassan SM, Faiz AH, Sahr GA, Soomro GA, Tahir MA, Iqbal M, Nazir A (2018) Vitality and implication of natural products from Viburnum grandiflorum: an eco-friendly approach. Pol J Environ Stud 27(3):1407–1411

    Article  Google Scholar 

  3. Akhtar M, Hasany SM, Bhanger M, Iqbal S (2007) Low cost sorbents for the removal of methyl parathion pesticide from aqueous solutions. Chemosphere 66(10):1829–1838

    Article  CAS  PubMed  Google Scholar 

  4. Darko G, Akoto O (2008) Dietary intake of organophosphorus pesticide residues through vegetables from Kumasi, Ghana. Food Chem Toxicol 46(12):3703–3706

    Article  CAS  PubMed  Google Scholar 

  5. Fu Y, Dou X, Zhang L, Qin J, Yang M, Luo J (2019) A comprehensive analysis of 201 pesticides for different herbal species-ready application using gas chromatography–tandem mass spectrometry coupled with QuEChERs. J Chrom B 1125:121730

    Article  CAS  Google Scholar 

  6. Hidaka H, Nohara K, Zhao J, Serpone N, Pelizzetti E (1992) Photo-oxidative degradation of the pesticide permethrin catalysed by irradiated TiO2 semiconductor slurries in aqueous media. J Photochem Photobiol A Chem 64(2):247–254

    Article  CAS  Google Scholar 

  7. Qamar A, Asi R, Iqbal M, Nazir A, Arif K (2017) Survey of residual pesticides in various fresh fruit crops: a case study. Pol J Environ Stud 26(6):2703–2709

    Article  CAS  Google Scholar 

  8. Vázquez PP, Mughari AR, Galera MM (2008) Solid-phase microextraction (SPME) for the determination of pyrethroids in cucumber and watermelon using liquid chromatography combined with post-column photochemically induced fluorimetry derivatization and fluorescence detection. Anal chim Acta 607(1):74–82

    Article  CAS  PubMed  Google Scholar 

  9. Xiang D, Chu T, Li M, Wang Q, Zhu G (2018) Effects of pyrethroid pesticide cis-bifenthrin on lipogenesis in hepatic cell line. Chemosphere 201:840–849

    Article  CAS  PubMed  Google Scholar 

  10. Schwanz TG, Carpilovsky CK, Weis GCC, Costabeber IH (2019) Validation of a multi-residue method and estimation of measurement uncertainty of pesticides in drinking water using gas chromatography–mass spectrometry and liquid chromatography–tandem mass spectrometry. J Chrom A 1585:10–18

    Article  CAS  Google Scholar 

  11. Asi MR, Afzal M, Anwar SA, Bashir MH (2008) Comparative efficacy of insecticides against sucking insect pests of cotton. Pak J Life Soc Sci 6(2):140–142

    Google Scholar 

  12. Zhang H, Watts S, Philix MC, Snyder SA, Ong CN (2018) Occurrence and distribution of pesticides in precipitation as revealed by targeted screening through GC-MS/MS. Chemosphere 211:210–217

    Article  CAS  PubMed  Google Scholar 

  13. Gonzalez-Coloma A, Reina M, Diaz CE, Fraga BM, Santana-Meridas O (2013) Natural product-based biopesticides for insect control. In: Reedijk J (ed) Reference Module in Chemistry, Molecular Sciences and Chemical Engineering. Elsevier, Amsterdam

    Google Scholar 

  14. Bertotto LB, Bruce R, Li S, Richards J, Sikder R, Baljkas L, Giroux M, Gan J, Schlenk D (2019) Effects of bifenthrin on sex differentiation in Japanese Medaka (Oryzias latipes). Environ Res 177:108564

    Article  CAS  PubMed  Google Scholar 

  15. Wang X, Zhou L, Zhang X, Luo F, Chen Z (2019) Transfer of pesticide residue during tea brewing: Understanding the effects of pesticide’s physico-chemical parameters on its transfer behavior. Food Res Int 121:776–784

    Article  CAS  PubMed  Google Scholar 

  16. Sachin K, Reena C, Beena K (2013) Persistence and decontamination of bifenthrin residues in okra fruits. Afr J Agric Res 8(38):4833–4838

    Google Scholar 

  17. Shah RA (2010) The efficacy of some new insecticides against the vectors of viruse of potato. Mycopath 8(1):15–18

    Google Scholar 

  18. Hougard J-M, Duchon S, Zaim M, Guillet P (2002) Bifenthrin: a useful pyrethroid insecticide for treatment of mosquito nets. J Med Entomol 39(3):526–533

    Article  CAS  PubMed  Google Scholar 

  19. Awwad AM, Salem NM, Aqarbeh MM, Abdulaziz FM (2020) Green synthesis, characterization of silver sulfide nanoparticles and antibacterial activity evaluation. Chem Int 6(1):42–48

    Google Scholar 

  20. Nazir A, Kalim I, Sajjad M, Usman M, Iqbal M (2019) Prevalence of aflatoxin contamination in pulses and spices in different regions of Punjab. Chem Int 5(4):274–280

    Google Scholar 

  21. Fazal-ur-Rehman M (2018) Methodological trends in preparation of activated carbon from local sources and their impacts on production: a review. Chem Int 4(2):109–119

    CAS  Google Scholar 

  22. Chen Z-M, Wang Y-H (1996) Chromatographic methods for the determination of pyrethrin and pyrethroid pesticide residues in crops, foods and environmental samples. J Chrom A 754(1-2):367–395

    Article  CAS  Google Scholar 

  23. Ishii Y, Taniuchi J, Sakamoto T (1990) Residue analysis of organochlorine pesticides by gas chromatography equipped with a Hall electrolytic conductivity detector (Halogen mode). J Pest Sci 15(2):231–256

    Article  CAS  Google Scholar 

  24. Đorđević T, Đurović R, Gajić-Umiljendić J (2012) Comparison of methods for bifenthrin residues determination in fermented wheat samples. Pest fitomed 27(2):167–174

    Article  CAS  Google Scholar 

  25. Le X, Hui D, Dzantor EK (2011) Characterizing rhizodegradation of the insecticide bifenthrin in two soil types. J Environ Protect 2:940–946

    Article  CAS  Google Scholar 

  26. LIA N, Gui-ping L (2005) Fine Chemical Intermediates 5. Zhi-juan Hunan Research Institute of Chemical Industry, Changsha

    Google Scholar 

  27. Jiang W, Kon R, Othoudt R, Leavitt R, Kumar S, Geissel L, Gomaa E (2004) Method development, validation, and analysis of bifenthrin residues in fresh and dry cilantro foliages and cilantro seeds using GC-ECD. Bull Environ Contam Toxicol 73(1):9–16

    Article  CAS  PubMed  Google Scholar 

  28. Xu Z, Huan Z, Luo J, Xie D (2016) Simultaneous determination of eight pesticide residues in Cowpeas by GC–ECD. J Chrom Sci 55(1):1–6

    Article  CAS  Google Scholar 

  29. Rajesh S, Raja DP, Rathi J, Sahayaraj K (2012) Biosynthesis of silver nanoparticles using Ulva fasciata(Delile) ethyl acetate extract and its activity against Xanthomonas campestris pv. malvacearum. J Biopest 5(119):2012

    Google Scholar 

  30. Walorczyk S, Drożdżyński D, Kierzek R (2015) Determination of pesticide residues in samples of green minor crops by gas chromatography and ultra performance liquid chromatography coupled to tandem quadrupole mass spectrometry. Talanta 132:197–204

    Article  CAS  PubMed  Google Scholar 

  31. Ermer J, Miller JHM (2006) Method validation in pharmaceutical analysis: a guide to best practice: KGaA. Wiley-Vch Verlag GmbH and Co., Weinheim

    Google Scholar 

  32. Thompson M, Ellison SL, Wood R (2002) Harmonized guidelines for single-laboratory validation of methods of analysis (IUPAC Technical Report). Pure Appl Chem 74(5):835–855

    Article  CAS  Google Scholar 

  33. Nikodimos Y, Hagos B, Dereje D, Hussen M (2018) Voltammetric study of secnidazole and its determination in pharmaceutical tablet using 1, 4-benzoquinone modified carbon paste electrode. Chem Int 4(1):43–51

    CAS  Google Scholar 

  34. Gul S, Khanum K, Mujtaba N (2015) New validated method for analysis of salymarin in polyherbal formulation (aqueous extract, oral liquid and solid dosage form). Chem Int 1(3):103–106

    Google Scholar 

  35. Ramsey MH, Ellison SL (2007) Eurachem/EUROLAB/CITAC/Nordtest/AMC Guide: Measurement uncertainty arising from sampling: a guide to methods and approaches.

  36. Kalra K (2011) Method development and validation of analytical procedures: in quality control of herbal medicines and related areas, Janeza Trdine 9 51000, Rejika, Croatia.

  37. Padmasubashini V, Sunilkumar B, Krishnakumar M, Singh SB (2020) Method validation and uncertainty for the determination of rare earth elements, yttrium, thorium and phosphorus in monazite samples by ICP-OES. Chem Int 6(3):98–109

    Google Scholar 

  38. Ayofe NA, Oladoye PO, Jegede DO (2018) Extraction and quantification of phthalates in plastic coca-cola soft drinks using high performance liquid chromatography (HPLC). Chem Int 4(2):85–90

    CAS  Google Scholar 

  39. Desta K, Amare M (2017) Validated UV-visible spectrometry using water as a solvent for determination of chloroquine in tablet samples. Chem Int 3(3):288–295

    CAS  Google Scholar 

  40. Knoll JE (1985) Estimation of the limit of detection in chromatography. J Chrom Sci 23(9):422–425

    Article  CAS  Google Scholar 

  41. Standard B (2006) General requirements for the competence of testing and calibration laboratories. EN ISO/IEC 17025

  42. Wood R (1999) How to validate analytical methods. TrAC Trend Anal Chem 18(9-10):624–632

    Article  CAS  Google Scholar 

  43. ISO I, OIML B (1995) Guide to the expression of uncertainty in measurement, Geneva

  44. Gul S, Hameed A (2018) UV spectroscopic method for determination of phenytoin in bulk and injection forms. Chem Int 4(3):177–182

    CAS  Google Scholar 

  45. Thakur R, Tarafder PK, Jha RR (2015) Micelle-mediated extraction of cobalt and its spectrophotometric determination in rocks, soils, sediments and sea-bed polymetallic nodules. Chem Int 5(1):109–116

    Google Scholar 

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AN contributed to the conception, design, interpretation of data, and preparation of the first draft. JI has performed all the experiments and was responsible for data acquisition. MI has proofread the draft of the work for the project and also helped in the interpretation of data. MA has helped in the revision of the manuscript. NN has proofread the revised manuscript. All authors have read and approved the manuscript.

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Correspondence to Arif Nazir.

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Nazir, A., Iqbal, J., Iqbal, M. et al. Method validation for bifenthrin emulsifiable concentrate and uncertainty calculation using gas chromatographic approach. Futur J Pharm Sci 6, 5 (2020).

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