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.
There is a commonly held view that limestone particles <0.25 mm are fully effective in amending acidic soils. However, this is not consistent with some available data. We assessed the importance of particle size in a field experiment using six particle size segregations covering a range of mean diameters from 3 mm to 0.005 mm. These products were applied at rates of 2.5, 5 and 10 t ha-1. Lime was incorporated in April 1986 and soil samples were collected 6, 12, 24 and 36 months later. The experiment was cropped to wheat in 1986, 1987 and 1989. Effectiveness was evaluated as the capacity of the particle size segregation to increase soil pH, exchangeable calcium (Caex,) or grain yield of wheat. No minimum particle size for maximum effectiveness was identified. Throughout the range of particle sizes evaluated, progressively finer particles produced larger increases in pH and Caex. Wheat yield was related to soil pH. Changes in soil pH and Caex between 6 months and 3 years after lime application were small compared to the changes in the first 6 months. Fine lime products should be preferred in practice, subject to cost considerations and handling difficulties.
SummaryTwo scries of simulation experiments were used to investigate the accuracy of treatment and variance estimation with a neighbour analysis of field trials proposed by Gleeson & Cullis (1987). The first series examined the accuracy of residual maximum likelihood (REML) estimation of seven theoretical error models applicable to field trials. REML estimation provided accurate estimates of the variance parameters, but the Ftest of treatments was slightly biased upward (to +2·4%) for first differences models and slightly biased downwards (to –1·4%) for second differences models. The second series of simulations, based on 19 uniformity data sets, illustrated that treatment effects were consistently estimated more accurately by the REML neighbour (RN) analysis of Gleeson & Cullis (1987) than by incomplete block (IB) analysis with recovery of interblock information. The relative gain in accuracy of RN over IB depends on the amount of systematic variation or ‘trend’ in the trial, and ranged from 6 to 18% with an average of 12% for a range of trend and error variances commonly encountered in field trials. The predicted average standard errors of pairwise treatment differences from the RN analysis were in close agreement with their empirical estimates, indicating that the predicted average S.E.D. is approximately valid.
Low productivity and decreasing profitability have caused a dramatic reduction in planted area and negligible replanting of canning peach trees in the Murrumbidgee Irrigation Areas (M.I.A.) of New South Wales over the past 14 years. The production of canning peaches is now falling below processor requirements. Peach production must be maintained at present levels for continued viability of the canning fruit industry in this region. Furthermore, the average productivity of the remaining plantings is very low by world standards. Faced with rising production costs, growers must raise average efficiency of production to improve profitability.
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