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A high performance liquid chromatography (HPLC)–UV method was developed for the analysis of phenylurea herbicides and applied successfully to the analysis of herbicides spiked in three soft drink brands and tap water.
A simple and sensitive high performance liquid chromatography (HPLC)–UV method has been developed for the analysis of phenylurea herbicides, namely, monuron, diuron, linuron, metazachlor, and metoxuron, that involves a preconcentration step using solid-phase extraction. The mobile phase used was acetonitrile–water at a flow rate of 1 mL/min with direct UV absorbance detection at 210 nm. Separation of analytes was studied on a C18 column. The method was applied successfully to the analysis of the herbicides in three soft drink brands and tap water. Good linearity and repeatability were observed for all the pesticides studied.
Phenylurea herbicides are used widely in a broad range of herbicide formulations as well as for nonagricultural use; consequently, their residues frequently are detected as major water contaminants in areas where these are used extensively (1). Diuron and linuron are substituted urea compounds that are soluble in water and can migrate in soil and enter the food chain (2). These herbicides are of significant toxicological risk to humans and wildlife. Diuron, which is used in cotton growing areas and with fruit crops, is rated as the third most hazardous pesticide for groundwater resources. These herbicides also are applied on railway tracks to maintain quality and provide a safer working environment (3), but this may lead to groundwater contamination as their leaching potential is significant. Phenylureas enter the environment through pathways such as spray drift, runoff from treated fields, and leaching into groundwater. Most of the excess material penetrates into the soil where it is subjected to the action of microorganisms (4) and degradation as studied by Canonica and colleagues (5). Phenylureas are unstable photochemically, as discussed by Khodja and colleagues (6), but these can persist in water for several days or weeks depending on the temperature and pH. Cases of incidental pesticide pollution of water reservoirs (2–4,7–13) have become more numerous in recent years.
Phenylurea residues can be found in water sources, processed products, and on the crops where these are applied. In India, most of the soft drink bottling plants use surface water from canals and rivers, which have a high risk of pesticide contamination. The water treatment measures used are insufficient for complete removal of these pesticide residues, which have been found to be above permissible limits. The evidence for the abovestated facts was provided in a 2003 Centre for Science and Environment (CSE, New Delhi, India) report that found several pesticide residues in many soft drink samples of leading international brands procured from all over India. The CSE findings were affirmed further by a Joint Parliamentary Committee (JPC) created to verify the facts. In 2006, CSE conducted another round of tests and found pesticides yet again in soft drink samples. Keeping this in mind, the present work has great importance, as it involves the determination of phenyl urea herbicides in soft drink samples and tap water.
Therefore, it is imperative that sensitive, selective, and efficient methods for herbicide analysis be designed. The common analytical methods used are high performance liquid chromatography (HPLC)–UV (2–4,7–9), solid-phase microextraction (SPME)–HPLC (10), diode array (11), immunosorbent trace enrichment and HPLC (12,14), LC–mass spectrometry (MS) (15,16), gas chromatography (GC)–MS (13), capillary electrophoresis (17,18, 19), photochemically induced fluorescence (20,21), and derivative spectrophotometry (22). A useful review is presented by Sherma (23) on the use of thin-layer chromatography (TLC) and its modified versions for the analysis of these herbicides. Solid-phase extraction (SPE) of phenylurea herbicides has been reported in literature by several workers (24–29). The SPE of soft drinks has been reported extensively (30–36). As the use of polar and degradable pesticides becomes widespread, it is urgent that more sensitive analytical methods be developed for their residual analysis in various matrices. HPLC has several advantages over GC, as it can be used for simultaneous analysis of thermally unstable, nonvolatile, polar, and neutral species without a derivative step. Because of the thermally unstable nature of phenylurea herbicides, the direct application of GC to these compounds is not possible and derivatization prior to the detection is needed. For this reason, HPLC with UV absorption or fluorescence detection (7–10) is preferred over GC. As a result, HPLC is gaining popularity and preference as a pesticide analyzing technique.
The present work describes a simple and sensitive HPLC–UV method for the analysis of phenyl urea herbicides (namely, monuron, diuron, linuron, metazachlor, and metoxuron) and it involves a single-step preconcentration by SPE.
Materials and Methods
The HPLC system used included a P680 HPLC pump (Dionex, Sunnyvale, California), a 250 mm × 4.6 mm, 5-µm Acclaim C18 RP analytical column (Dionex), and a UVD 170U detector operated at a wavelength of 210 nm coupled to a Chromeleon computer program for the acquisition of data (Dionex).
Monuron, diuron, linuron, metoxuron, and metazachlor (Figure 1) pesticide standards were obtained from Riedel-de-Haen (Seelze, Germany). HPLC-grade acetonitrile and methanol were obtained from J.T. Baker (Phillipsburg, New Jersey). All the solvents were filtered through nylon 6.6 membrane filters (Rankem, New Delhi, India) using a filtration assembly (Perfit, India) and sonicated before use. Triple-distilled water was used for all purposes.
Figure 1: Structures of phenylurea herbicides
Standard Preparation
Stock solutions were prepared in a mixture of 50:50 methanol–water. All the solutions were stored under refrigeration below 4 °C.
Sample Preparation
The SPE of the tap water and soft drink samples was performed using a Visiprep SPE vacuum manifold (Supelco, Bellefonte, Pennsylvania) and C18 cartridges from J.T. Baker. The SPE cartridges were attached to the solvent-recovery assembly and connected to a vacuum pump. The conditioning was done with 1 mL each of acetonitrile, methanol, and triple-distilled water.
Soft drink samples: The presence of phenylurea herbicides was studied in three different types of locally purchased soft drinks (Coke, Mirinda, and Limca). These were filtered with nylon 6.6 membrane filters and degassed by sonicating for 30 min. The samples were spiked with the metoxuron, monuron, diuron, metazachlor, and linuron at a concentration of 5 ng/mL. A 20-mL volume of these samples was passed through the C18 SPE cartridges under vacuum, and the analytes were eluted with 1.5 mL of acetonitrile. The eluants were further used for the HPLC–UV analysis. The sample blanks also were prepared similarly.
Tap water sample: The tap water sample was taken from the laboratory. It was filtered and then degassed with an ultrasonic bath. The sample was spiked with metoxuron, monuron, diuron, metazachlor, and linuron at a concentration of 5 ng/mL each. A 50-mL sample of the tap water containing the mixture of herbicides was preconcentrated using C18 SPE cartridges. A 1.5-mL volume of acetonitrile was used for the elution, and the eluant was subjected to HPLC–UV analysis. The sample blanks were prepared by the same method.
Procedure
Aliquots of the mixture of five herbicides were taken, having concentrations of 5–500 ppb. These mixtures were analyzed at an optimum wavelength of 210 nm. The mobile phase is an important factor in HPLC analysis, as it interacts with solute species of the sample. Hence, the composition of the mobile phase was selected carefully as 60:40 acetonitrile–water, and the flow rate was set at 1 mL/min. All measurements were taken at ambient temperature. The calibration curves for all five herbicides were prepared and the curves were linear in the range studied.
Results and Discussion
HPLC–UV studies: The separation of these herbicides was studied using direct injection of samples, and parameters such as the effect of flow rate, selection of suitable wavelength, and composition of mobile phase were optimized. The composition of the mobile phase was 60:40 acetonitrile–water. At higher flow rates than 1.0 mL/min, the separations were not up to the baseline, and with lower flow rates, peak tailing was observed, so the flow rate was optimized to 1.0 mL/min. The wavelength for detection was selected from the UV absorption spectra of the five herbicides as 210 nm.
Figure 2: HPLCâUV chromatogram of mixture containing 5 ppb each of the phenylurea herbicides: 1 = metoxuron, 2 = monuron, 3 = diuron, 4 = metazachlor, and 5 = linuron
Preparation of calibration curves: The calibration curves were constructed for the detection of monuron, linuron, diuron, metoxuron, and metazachlor in the range of 5–500 ppb under the optimized conditions using the HPLC with UV detection. The calibration curves were linear over this range. Various characteristics of HPLC–UV, including regression equation, working range, and RSD, are summarized in Table I. The LODs of the phenylurea herbicides were calculated using 3.3 × S/m (S = standard deviation, m = slope of calibration curve), and they were found to be in the range 0.82–1.29 ng/mL. Characteristic chromatograms with HPLC–UV detection at 210 nm are shown in Figures 2 and 3 for the separation of these herbicides.
Table I: Analytical figures of merit obtained under optimum conditions
Recoveries, repeatability, and LODs: The method detection limits were calculated for these herbicides per the ICH Harmonized Tripartite Guidelines (www.ich.org/LOB/media/MEDIA417.pdf). The method LOQs can be calculated by using 10 × S/m. The accuracy (% recovery) and precision (%RSD) of the HPLC–UV method were evaluated for each analyte by analyzing a standard of known concentration (5 ng/mL) five times and quantifying it using the calibration curves. Method optimization and validation parameters are presented in Tables I and II. Good linearity and repeatability were observed for all the compounds studied (with correlation coefficient >0.99). The method gives satisfactory results when used to quantify these herbicides in soft drink and tap water samples (Table II) with percentage recoveries ranging from 75% to 90.1%.
Table II: Analytical figures of merit obtained using various samples
Applications
The phenylurea herbicides were studied in various soft drink and tap water samples and no interfering peaks appeared at the retention times of these herbicides in the spiked samples. The tap water, Coke, Mirinda, and Limca (Figure 3) samples were spiked with metoxuron, monuron, diuron, metazachlor, and linuron at a concentration of 5 ng/mL. The analytical validation for the simultaneous quantification of metoxuron, monuron, diuron, metazachlor, and linuron has been performed with good recovery. The recoveries obtained are very good in all cases. Thus, this method can be used to detect the presence of these harmful herbicides in the soft drink and water samples.
Figure 3: HPLCâUV chromatograms of (a) tap water, (b) Coke, (c) Limca, and (d) Mirinda spiked with a mixture of phenylurea herbicides containing 5 ppb ofeach, obtained after preconcentration by SPE
Conclusions
The objective of the current study is to develop a simple, isocratic, reproducible, specific, and highly sensitive method for quantitative and qualitative determination of phenylurea herbicides. In the present method the analysis time is 13 min (linuron tR 12.4 min), which is rapid in comparison to some of the other reported methods, like Patsias and colleagues (37) (linuron tR 18.88 min.), Gerecke and colleagues (38) (linuron tR 17.58 min), and Mughari and colleagues (39) (linuron tR 15 min). The proposed method can determine phenylurea herbicides at very low concentrations. The present paper describes the application of HPLC to the separation and quantitative determination of five phenylurea herbicides, and the feasibility of the method developed was tested by simultaneous determination of these herbicides in different brands of soft drinks and in tap water samples. Good linearity and repeatability were observed for all the compounds studied (with correlation coefficient >0.99). It is hoped that the results of the present study contribute to increased scientific knowledge in the field of pesticide residue analysis in various food and environmental samples.
References
(1) S.R. Sorensen, C.N. Albers, and J. Aamand, Appl. Environ. Microbiol. 74, 2332–2340 (2008).
(2) G.M.F Pinto and I.C.S.F. Jardim, J. Liq. Chrom. and Rel. Technol. 23, 1353–1363 (2000).
(3) H. Cederlund, E. Börjesson, K. önneby, and J. Stenström, Soil Biology and Biochemistry 39, 473–484 (2007).
(4) E. Van-der-Heeft, E. Dijkman, R.A. Baumann, and E.A. Hogendorn, J. Chromatogr. A 879, 39–50 (2000).
(5) S. Canonica and H.U. Laubscher, Photochem. Photobiol. Sci. 7, 547–551 (2008).
(6) A.A. Khodja, B. Laverdine, C. Richard, and T. Sehili, Int. J. Photoenergy, 4, 147–151 (2002).
(7) L.E. Sojo, D.S. Gamble, and D.W. Gutzman, J. Agric. Food Chem. 45, 3634–3641 (1997).
(8) J. F. Lawerence, C. Menard, M.C. Hennion, V. Pichon, F. LeGoffic, and N Durand, J. Chromatogr. A 732, 147–154 (1996).
(9) Organonitrogen pesticides Method: 5601, NIOSH manual of analytical methods, 1–21 (1998).
(10) H. Berrada, G. Font and J.C. Molto, J.Chromatogr. A 1042, 9–14 (2004).
(11) R. Jeannot, H. Sabik, and E. Genin, J. Chromatogr. A 879, 55–71 (2000).
(12) S. Herrera, A. Martin Esteban, P. Fernandez, D. Stevenson, and C. Camara Fresinius J. Anal. Chem. 362, 547–551 (1998).
(13) Fast multi-residue pesticide analysis in soil and vegetable samples, application note, mass spectrometry, www.appliedbiosystems.com.
(14) A. Martin-Esteban, P. Fernandez, D. Stevenson, and C. Camara, Analyst 122, 1113–1117 (1997).
(15) I. Ferrer and D. Barcelo, Analusis Magazine 26, 118–122 (1998).
(16) T. Yarita, K. Sugino, T. Ihara, and A. Nomura, Analytical communications 35, 91–92 (1998).
(17) M.S. Barroso, L.N. Konda, and G. Morovjan, J. High Resol. Chromatogr. 22, 171–176 (1999).
(18) S. Batista, E. Silva, S. Galhardo, P. Viana, and M.J. Cerejeira, Int. J. Env. Anal. Chem. 82, 601–609 (2002).
(19) M. Chicharro, E. Bermejo, A. Sanchez, A. Zapardiel, A. Fernandez-Gutierrez, and D. Arraez, Anal. Bioanal. Chem. 382, 519–526 (2005).
(20) A. Bautista, J.J. Aaron, M.C. Mahedero, and A. Munoz de La Pena, Analusis 27, 857–863 (1999).
(21) M.D. Gil-García, M. Martinez-Galera, P. Parrilla-Vázquez, A.R. Mughari, and I.M. Ortiz-Rodríguez, Journal of Fluorescence 18, 365–373 (2008).
(22) I. Baranowiska and C. Pieszko, Anal. Letters 35, 413–486 (2002).
(23) J. Sherma, Acta. Chromatographia 15, 5–30 (2005).
(24) M.M.C. de la Peña and A. Bautista-Sánchez, Talanta 13, 279–285 (2003).
(25) I. Ferrer, V. Pichon, M.C. Hennion, and D. Barcelá, Journal of Chromatography A1, 91–98 (1997).
(26) F. Li, D. Martens, and A. Kettrup, Se Pu 19, 534–537 (2001).
(27) T. Cserhati, E. Forgács, Z. Deyl, I. Miksik , and A. Eckhardt, Biomedical Chromatography 18, 350–359 (2004).
(28) M.J.I. Mattina, Journal of Chromatography A 549, 237–245 (1991).
(29) M. Hamada and R. Wintersteiger, Journal of Planar Chromatography-Modern TLC 15, 11–18 (2002).
(30) J.F. García-Reyes, B. Gilbert-López, and A. Molina-Díaz, Anal. Chem. 30, 8966–8974 (2002).
(31) M.A. Mumin, K.F. Akhter, and M.Z. Abedin, Malaysian Journal of Chemistry 8, 45–51 (2008).
(32) X. L. Cao, J. Corriveau, and S. Popovic, J. Agric. Food Chem. 57, 1307–1311 (2009).
(33) Z. Pan, L. Wang, W. Mo, C. Wang, W. Hu, and J. Zhang, Anal. Chim. Acta. 545, 218–223 (2005).
(34) R. Lucena, S. Cardenas, M. Gallego, and M. Valcarcel, Anal. Chim. Acta. 530, 283–289 (2005).
(35) E. Papadopoulou-Mourkidou, J. Patsias, E. Papadakis, and A. Koukourikou, Fresenius J. Anal. Chem. 371, 491–496 (2001).
(36) N. Yoshioka and K. Ichihashi, Talanta 74, 1408–1413 (2008).
(37) J. Patsias and E. Papadopoulou-Mourkidou, JAOAC International 82, 968–981 (1999).
(38) A. C. Gerecke, C. Tixier, T. Bartels, R.P. Schwarzenbach, and S.R. Müller, J. chromatography A. 930, 9–19 (2001).
(39) A.R. Mughari, P. Parrilla Vázquez, and M. M. Galera, Anal. Chimica Acta. 593, 157–163 (2007).
Manpreet Kaur, Ashok Kumar Malik, and Baldev Singh Department of Chemistry, Punjabi University, Punjab, India
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