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Plant Physiology 134:909-911 (2004)
© 2004 American Society of Plant Biologists

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SCIENTIFIC CORRESPONDENCE

On Systems Thinking, Systems Biology, and the in Silico Plant

Graeme L. Hammer, Thomas R. Sinclair*, Scott C. Chapman and Erik van Oosterom

Agricultural Production Systems Research Unit, School of Land and Food Sciences, The University of Queensland, St. Lucia, Queensland, Australia (G.L.H., E.v.O.); Agricultural Production Systems Research Unit, Queensland Department of Primary Industries, Toowoomba, Queensland, Australia (G.L.H.); Agronomy Physiology Laboratory, United States Department of Agriculture-Agricultural Research Service, University of Florida, Gainesville, Florida (T.R.S.); and Commonwealth Scientific and Industrial Research Organization Plant Industry, St. Lucia, Queensland, Australia (S.C.C.)

The recent summary report of a Department of Energy Workshop on Plant Systems Biology (P.V. Minorsky [2003] Plant Physiol 132: 404–409) offered a welcomed advocacy for systems analysis as essential in understanding plant development, growth, and production. The goal of the Workshop was to consider methods for relating the results of molecular research to real-world challenges in plant production for increased food supplies, alternative energy sources, and environmental improvement. The rather surprising feature of this report, however, was that the Workshop largely overlooked the rich history of plant systems analysis extending over nearly 40 years (Sinclair and Seligman, 1996) that has considered exactly those challenges targeted by the Workshop. Past systems research has explored and incorporated biochemical and physiological knowledge into plant simulation models from a number of perspectives. The research has resulted in considerable understanding and insight about how to simulate plant systems and the relative contribution of various factors in influencing plant production. These past activities have contributed directly to research focused on solving the problems of increasing biomass production and crop yields. These modeling approaches are also now providing an avenue to enhance integration of molecular genetic technologies in plant improvement (Hammer et al., 2002).


http://www.plantphysiol.org/cgi/doi/10.1104/pp.103.034827.

* Corresponding author; e-mail trsincl{at}ifas.ufl.edu; fax 352–392–6139.

Received October 15, 2003; returned for revision October 29, 2003; accepted December 7, 2003.




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