Environ. Sci. Technol. 1996, 30, 1846-1851
Reflectometric Interference Spectroscopy for the Determination of Atrazine in Natural Water Samples C . M O U V E T , * ,† L . A M A L R I C , † S. BROUSSARD,‡ G. LANG,§ A. BRECHT,§ AND G. GAUGLITZ§ BRGM, Research Division, Geochemistry and Physical Chemistry Department and Mineral Processing and Analysis Department, Avenue de Concyr, BP 6009, 45060 Orle´ans Ce´dex 2, France, and Universita¨t Tu ¨ bingen, Institut fu ¨ r Physikalische und Theoretische Chemie, Auf der Morgenstelle 8, 72076 Tu ¨ bingen, Germany
We assessed the performance of a new sensing device based on reflectometric interference spectroscopy (RIFS) for the determination of atrazine in water samples. The correlation coefficients between concentrations of natural water samples measured by RIFS and by HPLC/GC were highly significant (0.903; p < 0.001) for the 31 surface water and groundwater samples tested, but very poor (0.190; p < 0.5) for the 9 lysimetric plate water samples. Marked interferences were observed with humic acid solutions, probably due to strong nonselective polyanion-polycation binding to the transducer surface, which involves a basic aminodextran. The detection limit was 0.35 µg/L. Since there was a significant cross-reactivity of simazine and terbutylazine, the present system might be used for screening groups of pesticides rather than for the determination of a single molecule. The total duration of one determination, 15 min, enables semicontinuous measurements without any sample pretreatment. No significant alteration of the sensor was observed after 160 determinations. These results demonstrate the potential of RIFS as a new technology for monitoring pesticides in natural water samples.
Introduction The utilization of xenobiotics to control various pests likely to decrease the quantity and quality of agricultural products is undoubtedly beneficial from an economical point of view, but the environmental risk caused by the residues transported to the groundwaters and surface waters after * To whom correspondence should be addressed; fax: 33-38-6447-30. † BRGM, Geochemistry and Physical Chemistry Department. ‡ BRGM, Mineral Processing and Analysis Department. § Universita ¨ t Tu ¨ bingen.
1846
9
ENVIRONMENTAL SCIENCE & TECHNOLOGY / VOL. 30, NO. 6, 1996
application needs to be assessed (1). Herbicides such as s-triazines are commonly used to control weeds in corn, sorghum, wheat fields, and vineyards (2, 3). Studies monitoring surface, groundwaters, and soil waters have shown that atrazine is one of the most ubiquitous herbicides (4, 5). Immunoassay techniques are being used more and more widely for the quantification of herbicides in aquatic environments (6-9) to complement gas and liquid chromatography, which are often too time-consuming and costly (10, 11). Conventional immunoassays use a labeled component of the antigen-antibody system to amplify the signal. This marker can either be radioactive, a fluorophore, or an enzyme (12). Although these systems (e.g., ELISA tests) can detect concentrations as low as 0.05 µg/L and process up to 96 analyses in 1-2 h, they require several incubation, washing, and separation steps with complex reagents such as labeled substances or chromogens. In many situations, it is advantageous to replace the discontinuous assay with a sensor system that can be operated continuously (13). To our knowledge, such detection systems with simple test protocols giving an almost continuous reading of the analyte concentration have not yet been validated for herbicides in natural water samples. An atrazine competitive assay with immobilized ligand and free antibodies, a test format similar to the approach presented here, has been reported to reach a 0.06 µg/L detection limit in near real time (14). The performance of this sensor based on surface transverse wave devices was demonstrated, however, with phosphate-buffered saline standard solutions only. The direct monitoring of bio-affinity interactions in real time was introduced recently to bioresearch with considerable success (15). Such methodsscalled “direct” because antibody binding is monitored without further labeling or development stepssoffer the advantage of the simplicity and speed of the analytical process. The two main means of detection used in this direct monitoring of antibody binding are the measurement of the change of either mass (16) or optical properties (15, 17). Results of direct measurements of pesticides in standard solutions and tap water using optical transducers have been recently reported (18, 19). We present here the first results of RIFS, based on the principle of optical detection, used for the detection of triazine herbicides. Atrazine was chosen as the major test molecule because analytical techniques to which the performance of the new RIFS methodology could be compared are available [GC (10, 20, 21), HPLC (8)] or are under development [immunoassays (22), biosensors (13)]. Furthermore, the presence of atrazine in surface waters and groundwaters (2, 9, 20, 23) makes the monitoring of this molecule an increasing priority. RIFS determines with very high resolution the thickness of transparent layers by evaluating their reflectance properties (24). Binding of antibodies at a surface leads to an increase in layer thickness, which can be monitored by RIFS in real time (25). The objectives of this study were to validate the RIFS technique on natural groundwaters, surface, and soil water samples by comparison with established chromatographic methods, GC and HPLC. The sensitivity, precision, and
S0013-936X(95)00389-0 CCC: $12.00
1996 American Chemical Society
specificity of RIFS were also assessed using atrazine, terbutylazine, and simazine standard solutions.
Materials and Methods Materials. Herbicides, humic acid, and methanol were bought from Promochem, Fluka, and Carlo Erba, respectively, and were used without further purification. Standard working solutions of atrazine, simazine, and terbutylazine from 0.1 to 5 µg/L with a final methanol content lower than 2.4 × 10-3 % (v/v) were prepared by diluting 200 mg/L stock solutions in methanol with Milli-Q water. The precision of the method was assessed by (i) measuring daily, for 5 days, one or two replicates of each of the atrazine standard solutions and (ii) triplicate determinations of one natural groundwater and one surface water sample for 1 or 2 days. Atrazine monoclonal antibodies K4E7 (7.5 mg/L) were provided by Professor Hock, University of Munich/ Weihenstephan. Pepsin (Sigma P-6887, 2 g/L) at pH 2 was used to regenerate the sensor surface. Phosphate-buffered isotonic saline (PBS) 0.01 mol/L at pH 7.4 was used both to rinse the flow cell and as the blank for producing the base line. The same buffer, with a concentration of 0.05 mol/L (PBS5), was used to prepare the sample before injection. Interference layers for RIFS (500 nm of SiO2 on top of 10 nm of Ta2O5 on BK7-glass) were supplied by Schott/ Mainz and cut into 15 × 15 mm pieces prior to use. Chips were cleaned by immersion in a freshly prepared hot mixture of concentrated H2SO4/30% H2O2 2:1 for 30 min and afterwards thoroughly rinsed with water. Care must be taken in preparing and handling this solution, as the strongly oxidizing mixture heats to above 150 °C. Activation of the surface was achieved by treatment with 4-aminobutyl dimethylethoxysilane to introduce amino groups and subsequent reaction with succinic anhydride (200 mg/cm2 of surface area and 1 mL/cm2 of phosphate buffer 10 mM KH2PO4, pH 7.4, for 1 h) to convert these to carboxylic groups. Aminodextran was coupled with an excess of ethyl(dimethylaminopropyl)carbodiimide in aqueous solution (30 µL of aminodextran 30% (w/w)/cm2, pH 3-4, 12 h). Finally, atrazine-caproic acid (100 mg/mL in dimethylformamide) was coupled to the chips with diisopropylcarbodiimide (200 µL/mL). Details will be given in a forthcoming paper (26). The specificity of the atrazine RIFS determinations was assessed by comparing calibration curves of two other triazines over the 0.1-5 µg/L range. Simazine and terbutylazine were chosen because they are widely used triazines (3, 4) known to cross-react with atrazine in various existing or emerging analytical methodologies (19, 22, 27, 28). Interference by dissolved organic matter was tested by analyzing various pesticide-free humic acid solutions. A 1 g/L humic acid stock solution (HA, Fluka 53680) in Milli-Q water was prepared by first adding NaOH to obtain a pH >10 and then lowering the pH to 6.5 by addition of HNO3 before filtering the solution with a 0.45-µm cellulose filter (Sartorius SM 16555Q). This stock solution was then diluted with Milli-Q water to provide 5, 20, and 100 mg/L working solutions, equivalent to a range of dissolved organic carbon concentrations likely to be found in groundwaters or surface waters as well as in gravitational waters from agricultural soils sampled by lysimetric plates. The 48 natural samples tested were 20 surface water, 17 groundwater, and 11 lysimetric plate water samples. The
FIGURE 1. System for reflectometric interference spectroscopy (RIFS) measurement. The white light emitted by a halogen lamp is guided onto the interfaces of the receptor layer in perpendicular incidence by bifurcated fiber optics. The reflected partial beams are collected in the same light guide and detected by a diode array spectrometer. A computer controls the flow injection analyzer (FIA) and the diode array and enables on-line data evaluation.
concentrations of atrazine, simazine, terbutylazine, deethylatrazine, and deisopropylatrazine were determined in the surface water samples by the analytical laboratory of the CRITT (Poitiers) and the Laboratoire Municipal et Re´gional de Rouen using GC/NPD after liquid/liquid extraction according to French Standard Procedure AFNOR 90-121, similar to ISO/TC 147 (29). Seventeen groundwater and 11 lysimetric plate water samples from various field sites in the Centre Region of France were analyzed by BRGM using HPLC with a diode array detector after liquid/liquid extraction, a procedure equivalent to EPA Method 4 used in the U.S. National Pesticide Survey (30). The detection limit of both GC and HPLC was 0.05 µg/L. In all samples, atrazine represented more than 80% of the total triazines, with terbutylazine and deisopropylatrazine hardly ever detected (31). The major cations, anions, and dissolved organic carbon were determined in one sample of each of the three water types using ICP/MS, ion chromatography, and infrared absorbance, respectively. Preliminary results showed the upper limit of the working range of the present RIFS configuration to be 1.5 µg/L. Therefore, natural samples whose previous GC or HPLC analysis showed the triazine concentrations to be >1.5 µg/L were diluted with Milli-Q water. Two of the 17 groundwater samples had to be diluted by a factor of 2 and 5, respectively. Of the nine samples of the lysimetric plates, four were diluted by a factor of 2 and five were diluted by a factor of 5. Of the 20 surface water samples, two were diluted by a factor of 2, four were diluted by a factor of 5, and one was diluted by a factor of 10. The measurement system (Figure 1) consisted of a halogen lamp, a flow cell, and a diode array detector connected by a light guide. The sample was delivered to the flow cell by a flow injection analyzer (FIA) system from Ismatec. A personal computer was used for controlling both the diode array and the FIA and for data evaluation.
VOL. 30, NO. 6, 1996 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
9
1847
FIGURE 2. (a) Preparation of the sample. From left to right: 800 µL of the sample is added to 200 µL of concentrated phosphate-buffered saline (PBS5). 900 µL of this solution is mixed with 100 µL of K4E7 antibody (7.5 mg/L) and incubated at room temperature for 5 min. The solution is then injected into the FIA system, and the measurement cycle starts. (b) Changes in the optical thickness of the interference layer during an FIA run. From 2.5 to 5.5 min, the pre-incubated solution is injected. From 7.5 to 11.5 min, the surface of the sensor chip is regenerated by rinsing with pepsin (2 g/L) at pH 2. During the rest of the cycle, the cell is rinsed with isotonic PBS at pH 7.4.
Methodology. RIFS is based on the reflection of white light at both interfaces of a thin transparent film. The reflected beams interfere and lead to a spectral modulation of reflectance, the pattern of which enables the calculation of the optical thickness of the interference layer. The detection of atrazine is based on a competitive scheme where analytes present in the sample bind to the antibodies and block their binding sites. When this solution is delivered to the transducer, only unoccupied antibodies with free binding sites will bind at the atrazine-modified transducer surface (Figure 2a). The lower the concentration of atrazine in the sample, the higher the concentration of unoccupied antibodies and the higher the binding effect at the transducer surface. During antibody binding, the optical thickness increases linearly (Figure 2b). The slope of this binding curve is calculated by linear regression and is taken as the key parameter for calibration and measurement. Hereafter, this key parameter will be referred to as the reading of the RIFS assay, expressed in picometer per second (pm/s). The operational protocol is described in Figure 2a. PBS5 (200 µL) was first added to the raw sample (800 µL) and briefly hand-mixed. An aliquot (900 µL) of this solution was then added to 100 µL of the antibody solution (7.5 mg/L), hand mixed, and incubated at room temperature for 5 min before injection in the FIA system. The complete assay procedure, including the regeneration by pepsin, took 15 min.
Results and Discussion Precision, Detection Limit, and Specificity with Standard Solutions. The mean calibration curve for atrazine obtained from measurements on 5 consecutive days is
1848
9
ENVIRONMENTAL SCIENCE & TECHNOLOGY / VOL. 30, NO. 6, 1996
FIGURE 3. Calibration curve for atrazine obtained from RIFS (mean and standard deviation of daily measurements taken on 5 consecutive days).
presented in Figure 3. Most relative standard deviations (RSD) were in the 15% range (Table 2), which indicates good day-to-day precision. The detection limit can be determined as (i) the amount of atrazine necessary to achieve S/S0 ) 90%, where S and S0 are the readings of an unknown sample and of the blank, respectively (32), and (ii) the mass equivalent of three times the standard deviation of the blank from its mean value in the linear part of the calibration curve (33). The values obtained with these two methods were 0.19 ( 0.12 and 0.35 µg/L, respectively. This sensitivity is better than the U.S. EPA HPLC Method 4 detection limit of 0.94 µg/L for the determination of triazines in water samples (30), although significantly lower detection limits have been reported for GC/MS and HPLC/UV [ca. 0.05 µg/L (20, 21, 8)] and for various commercially available ELISA microtiter plates [0.01-0.07 µg/L (31)]. Detection limits of 0.2-0.4 µg/L are considered a generally acceptable performance level (34) in light of the 3 µg/L maximum contaminant goal set by the U.S. EPA for atrazine in primary drinking water sources (35). The detection limit of RIFS is significantly better than that of the fibre optic immunosensor for an herbicide of the imidazolinone class reported by Anis et al., 3 µg/L (36), and than that of the flow-injection immunosensor for triazines developed by Wortberg et al., 1 µg/L (13). It is in the same range as the 0.1 µg/L detection limit of the fiber optic immunosensor based on fluorescence for herbicides of the triazine class tested by Bier et al. (37). Cross-reactivity in immunoassays is commonly evaluated by comparing the concentration of various analogues which yield a 50% decrease of the signal (7, 28, 38). For the atrazine determination by RIFS, simazine and terbutylazine exhibited 72 and 56% cross-reactivity, respectively. This is significantly higher than the cross-reactivity observed with the same antibody in a competitive immunoassay, 4% for simazine and 26% for terbutylazine (28). This can be explained by the different test schemes applied. In a competitive immunoassay, the labeled analyte (tracer) and the unlabeled analyte from the sample compete for the binding sites of the antibodies. The cross-reactivity there-
TABLE 1
TABLE 2
Values of pH, Cation, and Anion Concentrations (mg/L), Dissolved Organic Carbon (DOC, mg/L), and Suspended Matter (SM, mg/L) for One Sample of Each Water Type
Relative Standard Deviations (RSD, %) for the RIFS Determination of Concentrations of Atrazine Standard Solutions Measured at Least Once a Day for 5 Consecutive Days
parameter pH Ca Mg Na K HCO3 Cl SO4 NO3 DOC SM
surface water 7.7 25.7 4.9 7.4 2.9 93.0 9.0 14.6 6.6 4.6 17.2
groundwater 8.1 90.6 9.9 7.3 1.1 241.0 14.8 6.0 38.1 0.5 25.4
lysimetric plate water 5.9 150.0 5.8 12.4 2.7 43.0 77.2 73.0 287.0 4.4 44.9
fore reflects the ratio of the equilibrium binding constants for the tracer and the unlabeled analyte (39). In the RIFS approach, the unlabeled analyte and the antibody react during the pre-incubation period and the unoccupied antibodies that bind to the surface of the transducer are detected. Various analytes will affect the reading of the RIFS test if the differences in binding constants with the antibody are limited, resulting in roughly equivalent fractions of the analyte being bound during pre-incubation. As a general rule, this will happen when the inverse of the binding constant for this analyte exceeds the concentration of the analyte. Humic Acid (HA) Solutions. The 5, 20, and 100 mg/L HA solutions in distilled water yielded readings 1.6, 5.9, and 23.3 times higher than the mean blank value, respectively. Several 15-min washing cycles with either pepsin, methanol, or an acetonitrile/propionic acid/water (50/1/ 49) mixture were necessary to return to the initial optical thickness value, suggesting that HA sticks in or on the dextran sensor surface, inducing a large increase in optical thickness. This effect may be due to the surface chemistry used in this investigation. Amino groups in the aminodextran are protonated at the pH values used for the tests, creating a polycationic surface. In the presence of acidic humic substances, which are effectively polyanions, strong polyanion-polycation interactions occur at the surface, possibly causing the nonspecific effects observed. Natural Samples. The physical and chemical characteristics of one sample of each water type are presented in Table 1. The lysimetric plate water was somewhat more acidic than the two other waters and had higher concentrations of Ca, Cl, SO4, and NO3. The dissolved organic carbon was much higher in the surface and lysimetric plate water samples than in the groundwater. The possible matrix effect on the precision was tested by measuring triplicates of one groundwater sample on one day (0.70 ( 0.19 µg/L) and by measuring triplicates of another groundwater sample (0.49 ( 0.13 µg/L) and one surface water sample (0.56 ( 0.03 µg/L) on two separate days. The RSD (28, 25, and 5%) were similar to those obtained for the calibration with atrazine standard solutions (Table 2). The atrazine concentration of seven of the 48 samples could not be precisely quantified by RIFS. The reading of one of the groundwater samples was lower than the minimum reading obtained from standard solutions, sug-
concn (µg/L)
RSD (%) a
0.1
0.25
0.5
1
1.5
2
13 n)5
15 n)7
14 n ) 11
7 n ) 15
31 n)7
64 n)6
n ) number of measurements.
TABLE 3
Statistical Parameters of Linear Correlation Equations between Atrazine RIFS and Triazine Chromatography Concentrations for the Various Water Types Testeda statistical parameter
surface + groundwater samples (n ) 31)
lysimetric plate water samples (n ) 9)
correlation coeff (r) level of significance slope intercept
0.903 +++ 0.85 0.24
0.190 0.30 3.03
a
+++, p < 0.001. -, not significant at 0.5.
gesting a concentration of more than 1.58 ( 0.10 µg/L, whereas its concentration measured by HPLC (0.70 µg/L) was in fact in the working range of RIFS. The readings of three other groundwaters and one of the surface water samples were above the reading of the blank, indicating a concentration below the RIFS detection limit, 0.35 µg/L, in good agreement with their concentrations measured by HPLC and GC (0.05, 0.10, 0.16, and 0.21 µg/L). Two lysimeter plate water samples could not be measured because of interference during the RIFS determination. These seven samples were not taken into consideration in the correlation between RIFS and GC/HPLC values, nor was one other surface water sample whose concentration was below the HPLC detection limit (0.05 µg/L). The correlation between the concentrations measured by RIFS and chromatography was therefore based on 40 samples (Table 3). In order to take into account the crossreactivity evidenced for the RIFS, the chromatography values are the sum of the five triazines quantifiedsatrazine, simazine, terbutylazine, deethylatrazine, and deisopropylatrazine. The correlation coefficient obtained with the 31 surface water and groundwater samples was significant at the 0.001 level. The correlation coefficient for the nine lysimetric plate water samples was not significant even though five of these nine samples were diluted 5-fold because their atrazine concentrations were known from chromatography measurements to be out of the RIFS working range. This suggests a very strong matrix effect in the lysimeter plate samples, even though they did not appear to be more colored or less limpid than the groundwater or surface water samples. Drift. No significant change in the base line or the slope of the blanks and the standards was observed during a 9-day trial of the sensor involving determinations of about 160 samples. The limited drift suggests that the analyte
VOL. 30, NO. 6, 1996 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
9
1849
concentration difference from the beginning to the end of a 20-sample run would be lower than 10 %.
Conclusion The highly significant correlation coefficients between the concentrations of natural surface water and groundwater samples measured by both RIFS and HPLC/GC, together with the absence of false negatives, show that RIFS has a significant potential for the determination of small molecular weight analytes, such as atrazine, in water samples. While the technical approach is highly attractive, reproducibility, dynamic range, and, to a lesser extent, sensitivity need to be improved by further work. Studies are now being carried out with a nonionic surface and a surface based on a carboxy-modified hydrogel in order to determine whether this will reduce the nonselective binding observed for water samples from lysimetric plates. Compared to established techniques such as GC/HPLC, the RIFS technology offers several advantages: low operating costs, real time measurements, limited sample handling, low reagent consumption, and small sample volume required. The present total cycle time of 15 min, already very close to the time required for continuous real time measurements, could be reduced to 10 min. The operational characteristics of the system were recently improved by adding an autosampler, enabling unattended operation for 50 samples. The lack of any significant alteration of the sensor over at least 160 determinations and the low cost of the sensor chip itself enable RIFS to be used for extensive sampling surveys. The operating costs of RIFS are estimated at about 10 U.S. dollars per sample. Some characteristics of the present RIFS system might be seen as drawbacks. These are the detection limit, which is not yet low enough for drinking water quality analysis with regard to present European guidelines, and the limited specificity, as shown by the significant cross-reactivity of simazine and terbutylazine. Preliminary results of attempts to optimize the system, i.e., lowering the variability of the blanks and increasing the slope of the calibration curve in the low range, indicate that a level of 0.1 µg/L will be reached. Concerning specificity, it may in fact not need to be improved if RIFS is to be used as a screening tool. The potential for such screening could in fact be further enhanced by preparing sensor chips with herbicides of different classes attached to the surface. By sequentially incubating the sample with one antibody of each class of herbicide, the present RIFS setup could be turned into an automated sequential multianalyte sensor. Environmental studies with extensive sampling are needed in order to identify the processes which affect the fate and transport of herbicides in soils and groundwater and during the exchanges between groundwater and surface water (40, 41). RIFS may prove useful in such studies, notably by removing most of the burden of costly and cumbersome sample handling.
Acknowledgments This work was achieved as part of BRGM contribution to the Research Project “Optical Biosensing Techniques for Monitoring Organic Pollutants in the Aquatic Environment” (BIOPTICAS; Project Number EV5V-CT92-0067), financed by the European Union with matching funds from BRGM. This is BRGM Contribution no. 95028. We thank Professor Hock, University of Munich/Weihenstephan, for providing
1850
9
ENVIRONMENTAL SCIENCE & TECHNOLOGY / VOL. 30, NO. 6, 1996
the atrazine monoclonal antibodies K4E7. Thanks to the Agence de l’Eau Loire-Bretagne and the DIREN Centre for allowing the CRITT Poitiers and the Laboratoire Municipal et Re´gional de Rouen to provide results on the GC analysis of the surface water samples.
Literature Cited (1) Manclus, J. J.; Primo J.; Montoya, A. J. Agric. Food Chem. 1994, 42, 1257-1260. (2) Schottler, S.; Eisenreich, S. J. Environ. Sci. Technol. 1994, 28, 2228-2232. (3) Pereira, W. E.; Hostettler, F. D. Environ. Sci. Technol. 1993, 27, 1542-1552. (4) Mills, M. S.; Thurman, E. M. Environ. Sci. Technol. 1994, 28, 600-605. (5) Adams, C. D.; Thurman, E. M. J. Environ. Qual. 1991, 20, 540547. (6) Baker, D. B.; Bushway, R. J.; Adams, S. A.; Macomber, C. Environ. Sci. Technol. 1993, 27, 562-564. (7) Ferguson, B. S.; Kelsey, D. E.; Fan, T. S.; Bushway, R. J. Sci. Total Environ. 1993, 132, 415-428. (8) Bushway, R. J.; Hurst, H. L.; Perkins, L. B.; Tian, L.; Guiberteau Cabnillas, C.; Young, B. E. S.; Ferguson, B. S.; Jennings, H. S. Bull. Environ. Contam. Toxicol. 1992, 49, 1-9. (9) Thurman, E. M.; Goolsby, D. A.; Meyer, M. T.; Kolpin, D. W. Environ. Sci. Technol. 1991, 25, 1794-1796. (10) Gruessner, B.; Shambaugh N. C.; Watzin, M. C. Environ. Sci. Technol. 1995, 29, 251-254. (11) Vanderlaan, M.; Watkins, B. E.; Stanker, L. Environ. Sci. Technol. 1988, 22, 247-254. (12) Lang, G.; Brecht, A.; Gauglitz, G. Fresenius J. Anal. Chem. 1994, 348, 602-605. (13) Wortberg, M.; Middendorf C.; Katerkamp A.; Rump, T.; Krause J.; Cammann, K. Anal. Chim. Acta 1994, 289, 177-186. (14) Tom-Moy, M.; Baer, R. L.; Spira-Solomon, D.; Doherty, T. P. Anal. Chem. 1995, 67, 1510-1516. (15) Lo¨fas, S.; Malmqvist, M.; Ro¨nnberg, I.; Stenberg, E.; Liedberg, B.; Lundstro¨m, I. Sens. Actuators B 1991, B5, 79-84. (16) Ebato, H.; Gentry, C. A.; Herron, J. N.; Mueller, W.; Okahata, Y.; Ringsdorf, H.; Suci, P. A. Anal. Chem. 1994, 66, 1683-1689. (17) Lukosz, W. Biosens. Bioelectron. 1991, 6, 215-225. (18) Bier, F. F.; Schmid, R. D. Biosens. Bioelectron. 1994, 9, 125-130. (19) Minnuni, M.; Macsini, M. Anal. Lett. 1993, 26, 1441-1460. (20) Clark, L.; Gomme, J.; Hennings, S. Pestic. Sci. 1991, 32, 15-33. (21) Kolpin, D. W.; Kalkhoff, S. J. Environ. Sci. Technol. 1993, 27, 134-139. (22) Giersch, T. J. Agric. Food Chem. 1993, 41, 1006-1011. (23) Legrand, M. F.; Costentin, E.; Bruchet, A. Environ. Technol. 1991, 12, 985-996. (24) Brecht, A.; Gauglitz, G.; Nahm, W. Analusis 1992, 20, 135-140. (25) Brecht, A.; Gauglitz, G.; Polster, J. Biosens. Bioelectron. 1993, 8, 387-392. (26) Piehler, J.; Brecht, A.; Geckeler, K.; Gauglitz, G. Biosens. Bioelectron., in press. (27) Dunbar, B.; Riggle B.; Niswender, G. J. Agric. Food. Chem. 1990, 38, 433-437. (28) Giersch, T.; Kramer, F. K.; Hock, B. Sci. Total Environ. 1993, 132, 435-448. (29) Association Franc¸ aise de NORmalisation. Standard Procedure T90-121, 15 p. (30) Munch, D. J.; Graves, R. L.; Maxey, R. A.; Engel, T. M. Environ. Sci. Technol. 1990, 23, 1446-1451. (31) Mouvet C.; Broussard, S.; Jeannot, R.; Maciag, C.; Abuknesha, R.; Ismail, G. Anal. Chim. Acta 1995, 311, 331-339. (32) Midgley, A. R.; Niswender, G. D.; Rebar, R. W. Acta Endricol. 1969, 63, 163-180. (33) Anal. Chem. 1980, 52, 2242-2249. (34) Potter, T. L.; Carpenter, T.; Putman, R.; Reddy, K.; Clark, J. M. J. Agric. Food Chem. 1991, 39, 2184-2187. (35) U.S. EPA Health Advisory Summary, Atrazine. Office of Drinking Water, U.S. EPA: Washington, DC, 1989; pp 1-25; EPA Report 106. (36) Anis, N. A.; Eldefrawi, E.; Wong, R. B. J. Agric. Food Chem. 1993, 41, 843-848. (37) Bier, F. F.; Sto¨cklein, W.; Bo¨cher, M.; Bilitewski, U.; Schmid, R. D. Sens. Actuators B 1992, 7, 509-512. (38) Lawruck, T. S.; Lachman, C. E.; Jourdan, S. W.; Fleeker, J. R.; Herzog, D. P.; Rubio, F. M. J. Agric. Fod Chem. 1993, 41, 747752.
(39) Ekins, R. Immunoassay design and optimisation. In Principle and practice of immunoassay ; Price, C. P., Newman, D. J., Eds.; Stockton Press, New York, 1991; pp 96-153. (40) McMahon, P. B.; Chapelle, F. H.; Jagucki, M. L. Environ. Sci. Technol. 1995, 26, 1556-1559. (41) Squillace P. J.; Thurman, E. M. Environ. Sci. Technol. 1992, 26, 538-545.
Received for review June 7, 1995. Revised manuscript received December 20, 1995. Accepted February 11, 1996.X ES9503894 X
Abstract published in Advance ACS Abstracts, April 15, 1996.
VOL. 30, NO. 6, 1996 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
9
1851
