Developing high yielding wheat for water limited environments in northern Australia

A novel strategy linking physiology with plant breeding, molecular biology and computer simulation modelling is outlined here which aims to enhance selection of high yielding wheats with superior performance under conditions of water scarcity for the northern, subtropical, winter cereals region of Australia. In previous research, a source of high yield and performance under dry conditions for the target region was identified in a drought resistant parent. A large population of fixed lines for molecular genetic studies has been developed using the drought resistant line and widely grown current Australian variety. A preliminary study comparing the parent varieties was conducted in the winter of 2003. The two varieties were similar in many aspects of phenology, morphology and physiology. However, several important traits were identified that likely contribute to higher grain mass and yield of the drought resistant parent, including differences in the number and dry mass of tillers and spikes during development and the ability of drought resistant line to retain green leaves longer during grain filling.

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.

National whoppercropper - risk management discussion support software

It is a paradox that in a country with one of the most variable climates in the world, cropping decisions are sometimes made with limited consideration of production and resource management risks. There are significant opportunities for improved performance based on targeted information regarding risks resulting from decision options. WhopperCropper is a tool to help agricultural advisors and farmers capture these benefits and use it to add value to their intuition and experience. WhopperCropper allows probability analysis of the effects of a range of selectable crop inputs and existing resources on yield and economic outcomes. Inputs can include agronomic inputs (e.g crop type, N fertiliser rate), resources (e.g soil water at sowing), and seasonal climate forecast (SOI phase). WhopperCropper has been successfully developed and refined as a discussion-support process for decision makers and their advisers in the northern grains region of Australia. The next phase of the project will build on the current project by extending its application nationally and enhancing the resource management aspects. A commercial partner, with over 800 advisor clients nationally, will participate in the project.

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.

A comparison of linear forecasting models and neural networks:an application to Euro inflation and Euro Divisia

Linear models reach their limitations in applications with nonlinearities in the data. In this paper new empirical evidence is provided on the relative Euro inflation forecasting performance of linear and non-linear models. The well established and widely used univariate ARIMA and multivariate VAR models are used as linear forecasting models whereas neural networks (NN) are used as non-linear forecasting models. It is endeavoured to keep the level of subjectivity in the NN building process to a minimum in an attempt to exploit the full potentials of the NN. It is also investigated whether the historically poor performance of the theoretically superior measure of the monetary services flow, Divisia, relative to the traditional Simple Sum measure could be attributed to a certain extent to the evaluation of these indices within a linear framework. Results obtained suggest that non-linear models provide better within-sample and out-of-sample forecasts and linear models are simply a subset of them. The Divisia index also outperforms the Simple Sum index when evaluated in a non-linear framework. © 2005 Taylor & Francis Group Ltd.

A composite leading indicator of the inflation cycle for the Euro area

We evaluate the performance of composite leading indicators of turning points of inflation in the Euro area, constructed by combining the techniques of Fourier analysis and Kalman filters with the National Bureau of Economic Research methodology. In addition, the study compares the empirical performance of Euro Simple Sum and Divisia monetary aggregates and provides a tentative answer to the issue of whether or not the UK should join the Euro area. Our findings suggest that, first, the cyclical pattern of the different composite leading indicators very closely reflect that of the inflation cycle for the Euro area; second, the empirical performance of the Euro Divisia is better than its Simple Sum counterpart and third, the UK is better out of the Euro area. © 2005 Taylor & Francis Group Ltd.

Momentum profits and macroeconomic factors

This article tests whether macroeconomic variables and market sentiment influence the size of momentum profits. It finds that although returns to the winner and loser portfolios are influenced by a range of macroeconomic and market wide variables; momentum profits are influenced only by the scale of portfolio outflows. Thus, when investors are sending their capital elsewhere, reduced funds at home, dampen the profitability of the momentum trading strategy. It also finds that when the market closes, below its opening level in the previous six months, momentum profits are higher, which might be a reflection of mean reversion in the market. © 2004 Taylor and Francis Ltd.