An evaluation of the crop‐physiological and epidemiological information in EPIPRE

Abstract

EPIPRE is an integrated pest and disease management system for wheat based on on-line calculations of costs and benefits of pesticide treatments. It is field-specific and utilizes disease and pest incidences which are collected by the participating farmers. Incidences are transformed to severities through pest-specific relations with which a prediction of the epidemic is made according to an exponential development model. Integration of the epidemic over time, with multiplication by a pest-specific damage factor, delivers the expected damage till the end of the season, expressed as a fraction of the expected yield. Chemical control is only recommended when benefit of control exceeds total costs, including those for pesticide(s), labour, machinery and wheel-track damage. The current model needs improvement especially for the forecast of septaria blotch diseases, the field-specific quantification of the relative growth rates used and the damage relations of Puccinia striiformis and Mycosphaerella graminicola/Leptosphaeria nodorum. Also the cost-benefit analysis of the model can be improved, and it therefore, in the near future, needs contributions from research topics such as phytopathology, crop physiology, farm economics and information management. Using the model during the last 10 years has led to a reduced input of pesticides, which in its turn results in a lowering of production costs and a marked decrease in environmental pollution. Therefore future efforts to improve the model seem to be worthwhile. Historical contextEPIPRE, an acronym for EPidemic PREdiction or PREvention, is a computer-based advisory system for supervised control of pests and diseases in spring and winter wheat. Its development started in 1977 as a project of the Department of Phytopathology of the Agricultural University of Wageningen (NL) and the Netherlands Grain Centre. Initially its aim was to generate recommendations on chemical control of stripe rust (Puccinia striiformis) on individual fields of winter wheat. Later, the Department of Theoretical Production Ecology of the Agricultural University, the Research Institute for Plant Protection (IPO, Wageningen) and the Research Station for Arable Farming (PAGV, Lelystad) joined in. From 1982, further development of the system and support of the participants was achieved by the ]oint efforts of fundamental and applied research organizations and the extension service. The advisory model which resulted from the collaboration was tested and used on a routine basis by voluntarily participating wheat farmers.The system was introduced when cropping practice in wheat was changing considerably. New systemic fungicides were made available for control of diseases in wheat. Concomitantly, 417

Uncertainty analysis applied to supervised control of aphids and brown rust in winter wheat. Part 2. Relative importance of different components of uncertainty

“…As the decision model constitutes an upgraded version of analogous modules in the EPIPRE advisory system which was tested extensively (Reinink, 1986;Drenth et al, 1989), this seems a valid assumption.…”

“…Apparently the research effort put into the development and maintenance of EPIPRE (Zadoks, 1984;Drenth et al, 1989;Daamen, 1991) has yielded sufficiently precise parameter estimates. The uncertainty about financial loss due to the sample estimate of initial brown rust incidence is commensurate with the uncertainty due to the parameter estimates (Table 4).…”

“…It represents an upgraded version of part of the EPIPRE advisory system (Zadoks et al, 1984;Drenth et al, 1989). The model predicts financial.…”

Simulation of damage in winter wheat caused by the grain aphid Sitobion avenae. 3. Calculation of damage at various attainable yield levels

“…plant density due to wintering of the crop. Thus, attainable yield calculated in this study may differ from the concept of 'expected yield' in the advisory system EPIPRE, which is the farmer's grain yield estimate at the onset of the growing season (Drenth et al, 1989).…”

“…Due to the explanatory nature of the model, differences in effects of aphid injury on yield can be attributed to their crop-physiological causes. Next, the results of the simulation study are summarized in regression models suitable for use in decision support systems like EPIPRE (Drenth et al, 1989). Finally, the accuracy of these regression models is compared to the accuracy of a number of published models of damage by S. avenae in winter wheat, using a set of independent field data.…”