Operational seasonal forecasting of crop performanceExport / Share PlumX View Altmetrics View AltmetricsStone, R. C. and Meinke, H. (2005) Operational seasonal forecasting of crop performance. Philosophical Transactions of the Royal Society B Biological Sciences, 360 (1463). pp. 2109-2124. ISSN 1471-2970 Full text not currently attached. Access may be available via the Publisher's website or OpenAccess link. Article Link: https://doi.org/10.1098/rstb.2005.1753 AbstractIntegrated, interdisciplinary crop performance forecasting systems, linked with appropriate decision and discussion support tools, could substantially improve operational decision making in agricultural management. Recent developments in connecting numerical weather prediction models and general circulation models with quantitative crop growth models offer the potential for development of integrated systems that incorporate components of long-term climate change. However, operational seasonal forecasting systems have little or no value unless they are able to change key management decisions. Changed decision making through incorporation of seasonal forecasting ultimately has to demonstrate improved long-term performance of the cropping enterprise. Simulation analyses conducted on specific production scenarios are especially useful in improving decisions, particularly if this is done in conjunction with development of decision-support systems and associated facilitated discussion groups. Improved management of the overall crop production system requires an interdisciplinary approach, where climate scientists, agricultural scientists and extension specialists are intimately linked with crop production managers in the development of targeted seasonal forecast systems. The same principle applies in developing improved operational management systems for commodity trading organizations, milling companies and agricultural marketing organizations. Application of seasonal forecast systems across the whole value chain in agricultural production offers considerable benefits in improving overall operational management of agricultural production.
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