Future contributions of crop modelling - from heuristics and supporting decision making to understanding genetic regulation and aiding crop improvement

Crop modelling has evolved over the last 30 or so years in concert with advances in crop physiology, crop ecology and computing technology. Having reached a respectable degree of acceptance, it is appropriate to review briefly the course of developments in crop modelling and to project what might be major contributions of crop modelling in the future. Two major opportunities are envisioned for increased modelling activity in the future. One opportunity is in a continuing central, heuristic role to support scientific investigation, to facilitate decision making by crop managers, and to aid in education. Heuristic activities will also extend to the broader system-level issues of environmental and ecological aspects of crop production. The second opportunity is projected as a prime contributor in understanding and advancing the genetic regulation of plant performance and plant improvement. Physiological dissection and modelling of traits provides an avenue by which crop modelling could contribute to enhancing integration of molecular genetic technologies in crop improvement. Crown Copyright (C) 2002 Published by Elsevier Science B.V. All rights reserved.

Identification of research to improve the efficiency of breeding strategies for white clover in Australia - a review

A major challenge faced by today's white clover breeder is how to manage resources within a breeding program. It is essential to utilise these resources with sufficient flexibility to build on past progress from conventional breeding strategies, but also take advantage of emerging opportunities from molecular breeding tools such as molecular markers and transformation. It is timely to review white clover breeding strategies. This background can then be used as a foundation for considering how to continue conventional plant improvement activities and complement them with molecular breeding opportunities. In this review, conventional white clover breeding strategies relevant to the Australian dryland target population environments are considered. Attention is given to: (i) availability of genetic variation, (ii) characterisation of germplasm collections, (iii) quantitative models for estimation of heritability, (iv) the role of multi-environment trials to accommodate genotype-by-environment interactions, (v) interdisciplinary research to understand adaptation to dryland environments, (vi) breeding and selection strategies, and (vii) cultivar structure. Current achievements in biotechnology with specific reference to white clover breeding in Australia are considered, and computer modelling of breeding programs is discussed as a useful integrative tool for the joint evaluation of conventional and molecular breeding strategies and optimisation of resource use in breeding programs. Four areas are identified as future research priorities: (i) capturing the potential genetic diversity among introduced accessions and ecotypes that are adapted to key constraints such as summer moisture stress and the use of molecular markers to assess the genetic diversity, (ii) understanding the underlying physiological/morphological root and shoot mechanisms involved in water use efficiency of white clover, with the objective of identifying appropriate selection criteria, (iii) estimation of quantitative genetic parameters of important morphological/physiological attributes to enable prediction of response to selection in target environments, and (iv) modelling white clover breeding strategies to evaluate the opportunities for integration of molecular breeding strategies with conventional breeding programs.

Explicit/implicit partitioning and a new explicit form of the generalized alpha method

Most finite element packages use the Newmark algorithm for time integration of structural dynamics. Various algorithms have been proposed to better optimize the high frequency dissipation of this algorithm. Hulbert and Chung proposed both implicit and explicit forms of the generalized alpha method. The algorithms optimize high frequency dissipation effectively, and despite recent work on algorithms that possess momentum conserving/energy dissipative properties in a non-linear context, the generalized alpha method remains an efficient way to solve many problems, especially with adaptive timestep control. However, the implicit and explicit algorithms use incompatible parameter sets and cannot be used together in a spatial partition, whereas this can be done for the Newmark algorithm, as Hughes and Liu demonstrated, and for the HHT-alpha algorithm developed from it. The present paper shows that the explicit generalized alpha method can be rewritten so that it becomes compatible with the implicit form. All four algorithmic parameters can be matched between the explicit and implicit forms. An element interface between implicit and explicit partitions can then be used, analogous to that devised by Hughes and Liu to extend the Newmark method. The stability of the explicit/implicit algorithm is examined in a linear context and found to exceed that of the explicit partition. The element partition is significantly less dissipative of intermediate frequencies than one using the HHT-alpha method. The explicit algorithm can also be rewritten so that the discrete equation of motion evaluates forces from displacements and velocities found at the predicted mid-point of a cycle. Copyright (C) 2003 John Wiley Sons, Ltd.

The effectiveness of personalized smoking cessation strategies for callers to a Quitline service

Aim To assess the effectiveness of a program of computer-generated tailored advice for callers to a telephone helpline, and to assess whether it enhanced a series of callback telephone counselling sessions in aiding smoking cessation. Design Randomized controlled trial comparing: (1) untailored self-help materials; (2) computer-generated tailored advice only, and (3) computer-generated tailored advice plus callback telephone counselling. Assessment surveys were conducted at baseline, 3, 6 and 12 months. Setting Victoria, Australia. Participants A total of 1578 smokers who called the Quitline service and agreed to participate. Measurements Smoking status at follow-up; duration of cessation, if quit; use of nicotine replacement therapy; and extent of participation in the callback service. Findings At the 3-month follow-up, significantly more (chi(2)(2) = 16.9; P < 0.001) participants in the computer-generated tailored advice plus telephone counselling condition were not smoking (21%) than in either the computer-generated advice only (12%) or the control condition (12%). Proportions reporting not smoking at the 12-month follow-up were 26%, 23% and 22%, respectively (NS) for point prevalence, and for 9 months sustained abstinence; 8.2, 6.0, and 5.0 (NS). In the telephone counselling group, those receiving callbacks were more likely than those who did not to have sustained abstinence at 12 months (10.2 compared with 4.0, P < 0.05). Logistic regression on 3-month data showed significant independent effects on cessation of telephone counselling and use of NRT, but not of computer-generated tailored advice. Conclusion Computer-generated tailored advice did not enhance telephone counselling, nor have any independent effect on cessation. This may be due to poor timing of the computer-generated tailored advice and poor integration of the two modes of advice.

Evidence and information for health policy: a decade of change

Over the past decade or so, there has been increasing demand for greater clarity about the major causes of disease and injury, how these differentially affect populations, and how they are changing. In part, this demand has been motivated by resource constraints and a realisation that better health is possible with more informed allocation of resources. At the same time, there has been a change in the way population health and its determinants are quantified, with a much closer integration of the quantitative population sciences (such as epidemiology, demography and health economics) to strengthen and broaden the evidence base for healthcare policy.