Decision support systems for plant disease and insect management in commercial nurseries in the Midwest: A perspective review

Authors: Wallhead, Matthew; Zhu, Heping

Submitted to: Journal of Environmental Horticulture
Publication Type: Review Article
Publication Acceptance Date: 7/13/2017
Publication Date: 1/15/2018
Citation: Wallhead, M.W., Zhu, H. 2018. Decision support systems for plant disease and insect management in commercial nurseries in the Midwest: A perspective review. Journal of Environmental Horticulture. 35(2):84-92.

Interpretive Summary: The decision of whether or not and when to apply a pesticide for a given insect pest or plant disease is not always obvious. Decision-support systems are tools that help growers to decide which management options to employ and make spray decisions. To date, no decision-support systems have been developed to aid in the management of insects pests and plant diseases for commercial nursery production. As the development and implementation of decision-support systems takes considerable time and resources, the authors reviewed and proposed four decision-support systems originally developed for orchards that have the capacity to be adapted for use in commercial nursery production. Additionally, the authors proposed the development of a consensus forecast model, by combining the information generated from multiple independent models into a single spray-decision recommendation. The model will assist nursery managers, extension agents, consultants, and other agricultural clientele in the management of plant diseases and insect pests to solve problems under complex and uncertain conditions.

Technical Abstract: Decision-support systems (DDSs) are techniques that help decision makers utilize models to solve problems under complex and uncertain conditions. Predicting conditions that warrant intervention is a key tenet of the concept of integrated pest management (IPM) with the use of expert systems and pest models being characteristics of higher-level IPM. In this paper, potentials of four DSSs including Ag-Radar, NEWA, RIMpro and Skybit to be used for ornamental nursery production were discussed. These systems were previously developed for orchard growers to effectively manage plant diseases and insects. Their development was based on the input of historical disease, insect pest and weather information. It will be an instrumental management aid to control insects and diseases in a timely manner if nursery growers can adaptively implement these orchard DSSs into their production practices. In order to maximize effectiveness, however, next-generation DSSs should consider the addition of consensus forecast models into user interfaces by combining the information generated from multiple independent models into a single spray-decision recommendation.