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Operational seasonal forecasting of crop performance

Citation

Stone, RC and Meinke, HB, Operational seasonal forecasting of crop performance, Royal Society of London. Philosophical Transactions. Biological Sciences, 360, (1463) pp. 2109-2124. ISSN 0962-8436 (2005) [Refereed Article]

DOI: doi:10.1098/rstb.2005.1753

Abstract

Integrated, 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.

Item Details

Item Type:Refereed Article
Research Division:Agricultural and Veterinary Sciences
Research Group:Agriculture, Land and Farm Management
Research Field:Farm Management, Rural Management and Agribusiness
Objective Division:Environment
Objective Group:Climate and Climate Change
Objective Field:Climate Change Adaptation Measures
Author:Meinke, HB (Professor Holger Meinke)
ID Code:71518
Year Published:2005
Web of Science® Times Cited:28
Deposited By:Research Division
Deposited On:2011-07-21
Last Modified:2011-07-21
Downloads:0

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