The filter system for tertiary treatment of sewage effluent by land application - its performance in a subtropical environment

FILTER is an innovative, CSIRO developed system for treating effluent using high rate land application and subsequent effluent recapture via a closely spaced, subsurface drainage network. We report on the summer performance of a FILTER system established in a subtropical environment on a relatively impermeable swelling clay soil underlain by a deep regional water table. Using secondary treated sewage effluent, the FILTER system produced effluent of tertiary nutrient standards (less than or equal to5 mg/L TN; less than or equal to1 mg/L TP), with salinity levels suitable for subsequent irrigation reuse (EC less than or equal to2.5 dS/m). Removal of faecal coliforms was considerably less effective. The hydraulic loading rate achieved was about two and a half times larger than conventional irrigation demand, but this was associated with high deep percolation losses (e 3 mm/day). Comparisons are made with the original FILTER system developed and tested by Jayawardane et al. in temperate Australia. Suggestions are made for modifications to, and further testing of FILTER in a subtropical environment.

Advances in application of climate prediction in agriculture

Agricultural ecosystems and their associated business and government systems are diverse and varied. They range from farms, to input supply businesses, to marketing and government policy systems, among others. These systems are dynamic and responsive to fluctuations in climate. Skill in climate prediction offers considerable opportunities to managers via its potential to realise system improvements (i.e. increased food production and profit and/or reduced risks). Realising these opportunities, however, is not straightforward as the forecasting skill is imperfect and approaches to applying the existing skill to management issues have not been developed and tested extensively. While there has been much written about impacts of climate variability, there has been relatively little done in relation to applying knowledge of climate predictions to modify actions ahead of likely impacts. However, a considerable body of effort in various parts of the world is now being focused on this issue of applying climate predictions to improve agricultural systems. In this paper, we outline the basis for climate prediction, with emphasis on the El Nino-Southern Oscillation phenomenon, and catalogue experiences at field, national and global scales in applying climate predictions to agriculture. These diverse experiences are synthesised to derive general lessons about approaches to applying climate prediction in agriculture. The case studies have been selected to represent a diversity of agricultural systems and scales of operation. They also represent the on-going activities of some of the key research and development groups in this field around the world. The case studies include applications at field/farm scale to dryland cropping systems in Australia, Zimbabwe, and Argentina. This spectrum covers resource-rich and resource-poor farming with motivations ranging from profit to food security. At national and global scale we consider possible applications of climate prediction in commodity forecasting (wheat in Australia) and examine implications on global wheat trade and price associated with global consequences of climate prediction. In cataloguing these experiences we note some general lessons. Foremost is the value of an interdisciplinary systems approach in connecting disciplinary Knowledge in a manner most suited to decision-makers. This approach often includes scenario analysis based oil simulation with credible models as a key aspect of the learning process. Interaction among researchers, analysts and decision-makers is vital in the development of effective applications all of the players learn. Issues associated with balance between information demand and supply as well as appreciation of awareness limitations of decision-makers, analysts, and scientists are highlighted. It is argued that understanding and communicating decision risks is one of the keys to successful applications of climate prediction. We consider that advances of the future will be made by better connecting agricultural scientists and practitioners with the science of climate prediction. Professions involved in decision making must take a proactive role in the development of climate forecasts if the design and use of climate predictions are to reach their full potential. (C) 2001 Elsevier Science Ltd. All rights reserved.

Stay-green: A consequence of the balance between supply and demand for nitrogen during grain filling?

Retention of green leaf area in grain sorghum under post-anthesis drought, known as stay-green, is associated with greater biomass production, lodging resistance and yield. The stay-green phenomenon can be examined at a cell, leaf, or whole plant level. At a cell level, the retention of chloroplast proteins such as LHCP2, OEC33 and Rubisco until late in senescence has been reported in sorghum containing the KS19 source of stay-green, indicating that photosynthesis may be maintained for longer during senescence in these genotypes. At a leaf level, longevity of photosynthetic apparatus is intimately related to nitrogen (N) status. At a whole plant level, stay-green can be viewed as a consequence of the balance between N demand by the grain and N supply during grain filling. To examine some of these concepts, nine hybrids varying in the B35 and KS19 sources of stay-green were grown under a postanthesis water deficit. Genotypic variation in delayed onset and reduced rate of leaf senescence were explained by differences in specific leaf nitrogen (SLN) and N uptake during grain filling. Matching N supply from age-related senescence and N uptake during grain tilling with grain N demand found that the shortfall in N supply for grain filling was greater in the senescent than stay-green hybrids, resulting in more accelerated leaf senescence in the former. We hypothesise that increased N uptake by stay-green hybrids is a result of greater biomass accumulation during grain filling in response to increased sink demand (higher grain numbers) which, in turn, is the result of increased radiation use efficiency and transpiration efficiency due to higher SLN. Delayed leaf senescence resulting from higher SLN should, in turn, allow snore carbon and nitrogen to be allocated to the roots of stay-green hybrids during grain filling, thereby maintaining a greater capacity to extract N from the soil compared with senescent hybrids.

Barriers to effective cancer pain management: A survey of hospitalized cancer patients in Australia

The purpose of this study was to examine attitudinal barriers to effective pain management in a consecutively recruited cohort of 114 cancer patients from four Australian hospitals. When surveyed, 48% of this sample reported experiencing pain within the previous 24 hours. Of these, 56% reported this pain to be distressing, horrible or excruciating, with large proportions indicating that this pain had affected their movement, sleep and emotional well-being. Three factors were identified as potentially impacting on patients responses to pain-poor levels of patient knowledge about pain, low perceived control over pain, and a deficit in communication about pain. A trend for older patients to experience more severe pain was also identified. These older patients reported being more willing to tolerate pain and perceive less control over their pain. Suggestions are made for developing patient education programs and farther research using concepts drawn from broader social and behavioral models. J Pain Symptom Manage 2002:23:393-405. (C) U.S. Cancer Pain Relief Committee, 2002.

Scale-up of mixer granulators for effective liquid distribution

There is considerable anecdotal evidence from industry that poor wetting and liquid distribution can lead to broad granule size distributions in mixer granulators. Current scale-up scenarios lead to poor liquid distribution and a wider product size distribution. There are two issues to consider when scaling up: the size and nature of the spray zone and the powder flow patterns as a function of granulator scale. Short, nucleation-only experiments in a 25L PMA Fielder mixer using lactose powder with water and HPC solutions demonstrated the existence of different nucleation regimes depending on the spray flux Psi(a)-from drop-controlled nucleation to caking. In the drop-controlled regime at low Psi(a) values. each drop forms a single nucleus and the nuclei distribution is controlled by the spray droplet size distribution. As Psi(a) increases, the distribution broadens rapidly as the droplets overlap and coalesce in the spray zone. The results are in excellent agreement with previous experiments and confirm that for drop-controlled nucleation. Psi(a) should be less than 0.1. Granulator flow studies showed that there are two powder flow regimes-bumping and roping. The powder flow goes through a transition from bumping to roping as impeller speed is increased. The roping regime gives good bed turn over and stable flow patterns. This regime is recommended for good liquid distribution and nucleation. Powder surface velocities as a function of impeller speed were measured using high-speed video equipment and MetaMorph image analysis software, Powder surface velocities were 0.2 to 1 ms(-1)-an order of magnitude lower than the impeller tip speed. Assuming geometrically similar granulators, impeller speed should be set to maintain constant Froude number during scale-up rather than constant tip speed to ensure operation in the roping regime. (C) 2002 Published by Elsevier Science B.V.