Accelerated solvent extraction (ASE) was evaluated as a possible rapid, low solvent replacement for Soxhlet and bath sonication/shaking extraction in established soil screening methods. A spiked uncontaminated clay loam and soils contaminated with organochlorine pesticides (OCPs) and polycyclic aromatic hydrocarbons (PAHs) were extracted with 1:1 dichloromethane/acetone. Extracts were analyzed by gas chromatography with mass spectrometric detection in selective ion monitoring mode. For the spiked soil, ASE recoveries were higher than those from Soxhlet extraction for most analytes and generally close to 100% at the 4 and 20 mg/kg levels. At the 0.4 mg/kg level, background peaks caused significant interference for both techniques. This was a greater problem for ASE as the method blank gave a more crowded, complex chromatogram. For the OCP soil, ASE gave higher results than Soxhlet but lower results than bath sonication/shaking, for which a more effective solvent for OCPs was used. For the PAH soils, ASE recoveries were equivalent or superior to bath sonication/shaking, with ASE giving approximately double the total PAH content for matrices containing small stones and/or coal. ASE would be a suitable replacement for existing extraction methods; however, more work is required to reduce background interference.

The efficiency of various trialling systems for wheat variety evaluation in New South Wales (NSW) is considered. This involved the estimation of the variance components due to genotype, genotype-by-year, genotype-by-location and genotype-by-year-by-location. It is shown that there is a significant reduction in the magnitude of these variance components by the inclusion of the interaction of genotype maturity, winter habit and aluminium tolerance with environment.

The retrospective analysis of a large database on wheat variety testing in New South Wales (NSW) is considered. This analysis involved three key steps. Initially error variance heterogeneity is modelled, indicating significant differences in error variance due to trial location, year of trialling, sowing date and trial mean yield. The implication of this modelling for the estimaion of variance components is discussed.

A method for the analysis of early generation variety trials is described. The method is an extension of the analysis proposed by Gleeson and Cull is for replicated trials and uses the residual maximum likelihood estimation method of Patterson and Thompson. Best linear unbiased predictors of test line effects are derived. A small simulation experiment is conducted to assessthe reliability of the method. A wheat trial with a weed density covariate and missing values is analysed to illustrate the method.

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