Genotype-by-management interactions for grain yield and grain protein concentration of wheat

The magnitude of genotype-by-management (G x M) interactions for grain yield and grain protein concentration was examined in a multi-environment trial (MET) involving a diverse set of 272 advanced breeding lines from the Queensland wheat breeding program. The MET was structured as a series of management-regimes imposed at 3 sites for 2 years. The management-regimes were generated at each site-year as separate trials in which planting time, N fertiliser application rate, cropping history, and irrigation were manipulated. irrigation was used to simulate different rainfall regimes. From the combined analysis of variance, the G x M interaction variance components were found to be the largest source of G x E interaction variation for both grain yield (0.117 +/- 0.005 t(2) ha(-2); 49% of total G x E 0.238 +/- 0.028 t(2) ha(-2)) and grain protein concentration (0.445 +/- 0.020%(2); 82% of total G x E 0.546 +/- 0.057%(2)), and in both cases this source of variation was larger than the genotypic variance component (grain yield 0.068 +/- 0.014 t(2) ha(-2) and grain protein 0.203 +/- 0.026%(2)). The genotypic correlation between the traits varied considerably with management-regime, ranging from -0.98 to -0.31, with an estimate of 0.0 for one trial. Pattern analysis identified advanced breeding lines with improved grain yield and grain protein concentration relative to the cultivars Hartog, Sunco and Meteor. It is likely that a large component of the previously documented G x E interactions for grain yield of wheat in the northern grains region are in part a result of G x M interactions. The implications of the strong influence of G x M interactions for the conduct of wheat breeding METs in the northern region are discussed. (C) 2001 Elsevier Science B.V. All rights reserved.

Managing the Brisbane River and Moreton Bay: an integrated research/management program to reduce impacts on an Australian estuary

The Brisbane River and Moreton Bay Study, an interdisciplinary study of Moreton Bay and its major tributaries, was initiated to address water quality issues which link sewage and diffuse loading with environmental degradation. Runoff and deposition of fine-grained sediments into Moreton Bay, followed by resuspension, have been linked with increased turbidity and significant loss of seagrass habitat. Sewage-derived nutrient enrichment, particularly nitrogen (N), has been linked to algal blooms by sewage plume maps. Blooms of a marine cyanobacterium, Lyngbya majuscula, in Moreton Bay have resulted in significant impacts on human health (e.g., contact dermatitis) and ecological health (e.g., seagrass loss), and the availability of dissolved iron from acid sulfate soil runoff has been hypothesised. The impacts of catchment activities resulting in runoff of sediments, nutrients and dissolved iron on the health of the Moreton Bay waterways are addressed. The Study, established by 6 local councils in association with two state departments in 1994, forms a regional component of a national and state program to achieve ecologically sustainable use of the waterways by protecting and enhancing their health, while maintaining economic and social development. The Study framework illustrates a unique integrated approach to water quality management whereby scientific research, community participation and the strategy development were done in parallel with each other. This collaborative effort resulted in a water quality management strategy which focuses on the integration of socioeconomic and ecological values of the waterways. This work has led to significant cost savings in infrastructure by providing a clear focus on initiatives towards achieving healthy waterways. The Study's Stage 2 initiatives form the basis for this paper.

Strategic maintenance management

The approach to maintenance management has changed over the last one hundred years. Over the last few years, the Reliability Engineering and Risk Management Group (RERMG) at the University of Queensland has developed an approach called the strategic maintenance management (SMM) approach. The paper outlines the approach and contrasts it with the current approaches. It then discusses the industry-university partnership in the implementation of this approach and the current activities at the University of Queensland to assist industry in the implementation of the SMM approach.

Linguistic evaluation method for the environmental assessment of infrastructure projects

A soft linguistic evaluation method is proposed for the environmental assessment of physical infrastructure projects based on fuzzy relations. Infrastructure projects are characterized in terms of linguistic expressions of 'performance' with respect to factors or impacts and the 'importance' of those factors/impacts. A simple example is developed to illustrate the method in the context of three road infrastructure projects assessed against five factors/impacts. In addition, a means to include hard or crisp factors is presented and illustrated with respect to a sixth factor.