Literature DB >> 23767845

Will decision-support systems be widely used for the management of plant diseases?

Dani Shtienberg1.   

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.

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Year:  2013        PMID: 23767845     DOI: 10.1146/annurev-phyto-082712-102244

Source DB:  PubMed          Journal:  Annu Rev Phytopathol        ISSN: 0066-4286            Impact factor:   13.078


  5 in total

1.  How Decision Support Systems Can Benefit from a Theory of Change Approach.

Authors:  Will Allen; Jennyffer Cruz; Bruce Warburton
Journal:  Environ Manage       Date:  2017-03-09       Impact factor: 3.266

2.  Assessing expected utility and profitability to support decision-making for disease control strategies in ornamental heather production.

Authors:  Marius Ruett; Tobias Dalhaus; Cory Whitney; Eike Luedeling
Journal:  Precis Agric       Date:  2022-05-22       Impact factor: 5.767

3.  Development and validation of a weather-based model for predicting infection of loquat fruit by Fusicladium eriobotryae.

Authors:  Elisa González-Domínguez; Josep Armengol; Vittorio Rossi
Journal:  PLoS One       Date:  2014-09-18       Impact factor: 3.240

4.  Rain induces temporary shifts in epiphytic bacterial communities of cucumber and tomato fruit.

Authors:  Sarah M Allard; Andrea R Ottesen; Shirley A Micallef
Journal:  Sci Rep       Date:  2020-02-04       Impact factor: 4.379

5.  A Mechanistic Model of Botrytis cinerea on Grapevines That Includes Weather, Vine Growth Stage, and the Main Infection Pathways.

Authors:  Elisa González-Domínguez; Tito Caffi; Nicola Ciliberti; Vittorio Rossi
Journal:  PLoS One       Date:  2015-10-12       Impact factor: 3.240

  5 in total

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