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Preventing what ails rice with a strategic, statistical, prescriptive model system.
A. H. SPARKS (1), A. Nelson (2), S. Savary (3). (1) IRRI, Metro Manila, Philippines; (2) IRRI, Los Baños, Philippines; (3) INRA, Castanet Tolosan, France

Because many rice growers and their extension support systems are increasingly unable to diagnose crop health issues, it is important to find new ways to forward recommendations, which will be useful in reducing yield losses. We designed RICE-PRE as a system to predict the most likely crop health syndrome that may occur given the attributes of a production situation. A statistical analysis of survey data from 456 lowland rice farmers' fields in Asia indicated that despite a broad range of environments and highly diverse harmful agents, very strong statistical links exist between syndromes and the production situations. These production situations are then combined with a recently developed typology of rice ecologies, sets of agricultural objectives, and externalities (positive or negative) to create RICE-PRE, a set of prescriptions that include field operations and crop protection strategies aimed at minimizing yield losses. RICE-PRE is meant to be: strategic (before the season starts); based on strong statistical bases; and make use of prophylactic and preventive tools, especially resistant varieties. However, the use of preventive chemical protection is included when other options are unavailable and the risks involved are too high to be accepted. Results from the 2011 rainy season in the Philippines show that RICE-PRE increases yield over the control and farmers' practices, indicating that it is possible to design a simplified strategic recommendation system for farmers’ use.<p><p>Keywords: NA, Cereals-Grains, Rice

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