Soil exploration by sorghum root systems in wide row cropping systems

Wide and ‘skip row’ row configurations have been used as a means to improve yield reliability in grain sorghum production. However, there has been little effort put to design of these systems in relation to optimal combinations of root system characteristics and row configuration, largely because little is known about root system characteristics. The studies reported here aimed to determine the potential extent of root system exploration in skip row systems. Field experiments were conducted under rain-out shelters and the extent of water extraction and root system growth measured. One experiment was conducted using widely-spaced twin rows grown in the soil. The other experiment involved the use of specially constructed large root observation chambers for single plants. It was found that the potential extent of root system exploration in sorghum was beyond 2m from the planted rows using conventional hybrids and that root exploration continued during grain filling. Preliminary data suggested that the extent of water extraction throughout this region depended on root length density and the balance between demand for, and supply of, water. The results to date suggest that simultaneous genetic and management manipulation of wide row production systems might lead to more effective and reliable production in specific environments. Further study of variation in root-shoot dynamics and root system characteristics is required to exploit possible opportunities.

Optimising profitability and environmental trade-offs in managing cropping systems using differential evolution

Whilst traditional optimisation techniques based on mathematical programming techniques are in common use, they suffer from their inability to explore the complexity of decision problems addressed using agricultural system models. In these models, the full decision space is usually very large while the solution space is characterized by many local optima. Methods to search such large decision spaces rely on effective sampling of the problem domain. Nevertheless, problem reduction based on insight into agronomic relations and farming practice is necessary to safeguard computational feasibility. Here, we present a global search approach based on an Evolutionary Algorithm (EA). We introduce a multi-objective evaluation technique within this EA framework, linking the optimisation procedure to the APSIM cropping systems model. The approach addresses the issue of system management when faced with a trade-off between economic and ecological consequences.

Middleware for distributed context-aware systems

Context-aware systems represent extremely complex and heterogeneous distributed systems, composed of sensors, actuators, application components, and a variety of context processing components that manage the flow of context information between the sensors/actuators and applications. The need for middleware to seamlessly bind these components together is well recognised. Numerous attempts to build middleware or infrastructure for context-aware systems have been made, but these have provided only partial solutions; for instance, most have not adequately addressed issues such as mobility, fault tolerance or privacy. One of the goals of this paper is to provide an analysis of the requirements of a middleware for context-aware systems, drawing from both traditional distributed system goals and our experiences with developing context-aware applications. The paper also provides a critical review of several middleware solutions, followed by a comprehensive discussion of our own PACE middleware. Finally, it provides a comparison of our solution with the previous work, highlighting both the advantages of our middleware and important topics for future research.

Major issues in business process management: An Australian perspective

Business Process Management (BPM) is widely seen as the top priority in organizations wanting to survive competitive markets. However, the current academic research agenda does not seem to map with industry demands. In this paper, we address the need to identify the actual issues that organizations face in their efforts to manage business processes. To that end, we report a number of critical issues identified by industry in what we consider to be the first steps towards an industry-driven research agenda for the BPM area. The reported issues are derived from a series of focus groups conducted with Australian organizations. The findings point to, among others, a need for more consolidated efforts in the areas of business process governance, systematic change management, developing BPM methodologies, and introducing appropriate performance measures.

On aggregation issues in spatial data management

Large amounts of information can be overwhelming and costly to process, especially when transmitting data over a network. A typical modern Geographical Information System (GIS) brings all types of data together based on the geographic component of the data and provides simple point-and-click query capabilities as well as complex analysis tools. Querying a Geographical Information System, however, can be prohibitively expensive due to the large amounts of data which may need to be processed. Since the use of GIS technology has grown dramatically in the past few years, there is now a need more than ever, to provide users with the fastest and least expensive query capabilities, especially since an approximated 80 % of data stored in corporate databases has a geographical component. However, not every application requires the same, high quality data for its processing. In this paper we address the issues of reducing the cost and response time of GIS queries by preaggregating data by compromising the data accuracy and precision. We present computational issues in generation of multi-level resolutions of spatial data and show that the problem of finding the best approximation for the given region and a real value function on this region, under a predictable error, in general is "NP-complete.

Farming Systems: Beyond Production Technologies for Dairy RD&E

The challenge of Research, Development and Extension (R,D&E) is to apply agricultural science to serve the real needs of production systems. The ideal is to have community partnerships involving a variety of stakeholders with equal representation, and a sharing in the design of R, D&E actions. R,D&E policy in Australia is stressing the participation of industry in new projects. The Dairy Research and Development Corporation (DRDC) in Australia, and the Brazilian Agricultural Research Corporation for Dairy (Embrapa Dairy), have developed initiatives to identify priorities for R,D&E design with participation of the industry. However, weaknesses in the methods have been identified. The present study describes the results of a strategy to involve a broader range of stakeholders in the identification of regional dairy industry needs. The findings show that overall communication, finance and marketing as the three major priorities of three study regions, meaning that primary needs for the industry are not in production technologies. This is an apparent contradiction with what some stakeholders considered valuable for dairy farms, which are pasture, genetics and nutrition technologies. The results reflect the large amount of research activity into production technology, and the relative success of R,D&E. However, it is necessary to consider issues beyond production technologies before developing R,D&E projects or presenting technologies.

Applying a Systems Approach to the Analysis of the Benefits of Conversion to Organic Production

Although the current level of organic production in industrialised countries amounts to little more than 1-2 percent, it is recognised that one of the major issues shaping agricultural output over the next several decades will be the demand for organic produce (Dixon et al. 2001). In Australia, the issues of healthy food and environmental concern contribute to increasing demand and market volumes for organic produce. However, in Indonesia, using more economical inputs for organic production is a supply-side factor driving organic production. For individual growers and processors, conversion from conventional to organic agriculture is often a challenging step, entailing a thorough revision of established practices and heightened market insecurity. This paper examines the potential for a systems approach to the analysis of the conversion process, to yield insights for household and community decisions. A framework for applying farming systems research to investigate the benefits of organic production in both Australia and Indonesia is discussed. The framework incorporates scope for farmer participation, crucial to the understanding of farming systems; analysis of production; and relationships to resources, technologies, markets, services, policies and institutions in their local cultural context. A systems approach offers the potential to internalise the external effects that may be constraining decisions to convert to organic production, and for the design of decision-making tools to assist households and the community. Systems models can guide policy design and serve as a mechanism for predicting the impact of changes to the policy and market environments. The increasing emphasis of farming systems research on community and environment in recent years is in keeping with the proposed application to organic production, processing and marketing issues. The approach will also facilitate the analysis of critical aspects of the Australian production, marketing and policy environment, and the investigation of these same features in an Indonesian context.

Web-based expert systems:benefits and challenges

Convergence of technologies in the Internet and the field of expert systems have offered new ways of sharing and distributing knowledge. However, there has been a general lack of research in the area of web-based expert systems (ES). This paper addresses the issues associated with the design, development, and use of web-based ES from a standpoint of the benefits and challenges of developing and using them. The original theory and concepts in conventional ES were reviewed and a knowledge engineering framework for developing them was revisited. The study considered three web-based ES: WITS-advisor - for e-business strategy development, Fish-Expert - for fish disease diagnosis, and IMIS - to promote intelligent interviews. The benefits and challenges in developing and using ES are discussed by comparing them with traditional standalone systems from development and application perspectives. © 2004 Elsevier B.V. All rights reserved.