Will Decision-Support Systems Be Widely Used for the Management of Plant Diseases?

Abstract

Decision-support systems (DSSs) are interactive computer-based systems that help decision makers solve unstructured problems under complex, uncertain conditions. Experimental use of DSSs has resulted in improved disease suppression and lowered risks of crop damage. In many cases, it has also led to the use of smaller quantities of active substances, as compared with standard spraying practices. Hundreds of DSSs have been developed over the years and are readily available and affordable. However, most farm managers do not use them as part of their integrated pest management (IPM) practices. Since the mid-1980s, the author of this paper, together with numerous colleagues, has developed DSSs and decision rules for the management of diseases in a variety of crops, including extensive crops, such as wheat, sunflower, and pea; semi-intensive crops, such as pear, chickpea, cotton, and tarragon; and intensive crops, such as tomato, potato, cucumber, sweet pepper, carrot, and grapevine. Some of these systems were used widely, but others were not. This experience may allow us to draw general conclusions regarding the use of DSSs and decision rules. Possible explanations for the widely varying acceptance rates are presented, and the effects of anticipated changes in the agribusiness sector on the future use of DSSs are discussed.

Economics of a decision–support system for managing the main fungal diseases of winter wheat in the Grand-Duchy of Luxembourg

“…The profitability of a crop protection strategy for diseases depends on various factors, namely the basic biological parameters of the pathosystem, the technical details of management tools, and historical and real-time information, so as to provide the basis for an effective and reliable forecasting system (Fabre et al, 2007). Although various disease forecast systems exist, the precise control time or economic injury threshold is not always clearly available (Shtienberg, 2013). In our study, we emphasized the grain yield gain and the financial return of a single fungicide treatment scheduled on the basis of a DSS.…”

“…DSS help by limiting potentially harmful side effects of fungicide applications while ensuring economic benefits (Fabre et al, 2007;Shtienberg, 2013). Indeed, a major incentive in adoption of DSS by farmers is related to the cost advantages over conventional strategies (Wearing, 1988;Langvad and Noe, 2006;Fabre et al, 2007).…”

Fifty Years Since Silent Spring

“…Since the mid-1980s, many disease-forecasting/decision-support systems have been developed (61,141). Funding for system development is often obtained with the justification that implementation of the system will result in a reduction in pesticide use.…”

“…Funding for system development is often obtained with the justification that implementation of the system will result in a reduction in pesticide use. However, there are few examples of sustained use of a forecasting system (61,141), even when data indicate that use of the forecaster would save the farmer money from reduced pesticide applications. Gent et al (61) suggest that this is at least partly because growers apply pesticides as insurance against crop failure.…”

Development and Validation of a Weather-Based Model for Predicting Infection of Loquat Fruit by Fusicladium eriobotryae

“…De facto, the “sustainable use” directive has made IPM mandatory in European agriculture as of 2014. As a consequence, there is an increased interest in the development and use of plant disease models to improve the timing of pesticide applications and to thus limit unnecessary treatments [46], [50], [51].…”