RAPID PESTICIDE EXTRACTION AND ANALYSIS METHODS FOR BETTER

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					    RAPID PESTICIDE EXTRACTION AND ANALYSIS METHODS FOR
                    BETTER ENVIRONMENTAL MANAGEMENT


OLIVER, G; DOYLE, R; JORDAN, T; BROWN P
Tasmanian Institute of Agricultural Research, Private Bag 54, University of Tasmania,
Hobart, TAS 7001, Australia.
Garth.Oliver@utas.edu.au

ABSTRACT
Public concerns expressed by the Tasmanian shell fish industry and medical
practitioners regarding pesticide use required validation of a best practise pesticide
model for local conditions. The collection of data to validate the model PIRI
(Pesticide Impact Rating Index; Kookana and Correll, 2008) involved the processing
of large numbers of soil samples over a very short project timeframe. Samples from
field and laboratory trials needed to be collected, stored, processed, extracted and then
analysed. The logistics of dealing with several thousand samples through all these
stages requires careful planing and automation. Of particular importance is the
preparation, extraction and clean-up of soil extracts prior to analysis.

The pesticides cypermethrin, clopyralid, glyphosate, MCPA, simazine and
sulfometuron methyl were applied to five different Tasmanian soil types to determine
their field half-lives and leaching potential. Sorption coefficients for the five soils
were also required for PIRI. Four different extraction protocols were required to deal
with this broad suite of pesticides highlighted by the community consultative
committee.

An accelerated solvent extraction system (Dionex ASE 200) interfaced with an
automatic liquid handling system (Gilson ASPEC XL) was chosen for five of the
pesticides. ASE allows for the automated extraction of twenty four 1-10 g soil
samples by common laboratory solvents at elevated temperature and pressure. The
extracts can subsequentially be concentrated or cleaned via Solid Phase Extraction
(SPE) methods performed automatically by the ASPEC XL system. Extraction of
MCPA, simazine and sulfometuron methyl were combined in a single extraction cell
then filtered using a 0.45 micron filter and then analysed by LCMS-MS. However
clopyralid required separate extraction, clean-up and analysis due low detector
sensitivity and poor chromatography. The ASPEC system was used to automatically
pre-condition a 3 g GCB cartridge which was dried and then eluted before analysis by
LCMS-MS. Aqueous insolubility with cypermethrin meant it was also extracted
separately in ASE cells, cleaned-up and run on a GCMS-MS.

Glyphosate extraction was trialled with both 0.1M and 0.01M KOH, adjusted to pH 2
by orthophosphoric acid, and then analysed by HPLC using fluorescence detection.
The weaker extraction solvent (0.01 M KOH) was trialled due to reduced matrix
interference. However on certain soils the extraction efficiency was compromised and
the stronger extraction solvent was needed (see Figure 1). Figure 1 shows the
differences in extraction efficiency of the two different KOH concentrations on the
five soil types seven days after glyphosate application. No glyphosate was detected in
the northern Red Ferrosol extract. This is a soil with high levels of iron oxides and is
strongly P sorbing. Both these factors are linked to glyphosate sorption (Vencill,
2002) and suggest KOH extraction(s) maybe inappropriate in some soils. Conversely
the sandy textured Kurosol showed little variation in extraction efficiency.


                                   Glyphosate extration efficency
                  3.00
                                0.01M KOH
                  2.50
  mg/kg in Soil




                                0.1M KOH
                  2.00
                  1.50
                  1.00
                  0.50
                  0.00
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                  Fe



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                                                     Soil Type
Figure 1 Extraction of glyphosate using either 0.1 M or 0.01 M KOH seven days
following application to a range of Tasmanian soils.

The ASE/ASPEC system allowed for constant unsupervised extractions that
maximised sample throughput. These developments mean large and accurate data
sets can be generated rapidly for better modelling of pesticide behaviour which are
locally relevant and utilised by various community and industry groups.

References
Kookana, R. and Correll, R. 2008, Pesticide Impact Rating Index (PIRI) risk indicator
for minimizing off-site migration of pesticides. Tasmanian Water Quality Initiative,
CSIRO Land and Water, Adelaide, Australia.

Vencill, W.K. 2002, Herbicide Handbook, 8th Edition, Weed Science Society of
America, 493p.

				
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