Abstract

Abstract Owing to the decreasing availability of synthetic pesticides, there is an urgent need for developing and improving alternative pest control methods in horticulture. Integrated Pest Management (IPM) aims to reduce and control the damage caused by pest organisms by making use of ecological interactions between the pest, its antagonists and the environment. IPM usually involves combined use of pesticides, pest antagonists, mass trapping and environmental manipulation. This gives rise to potentially negative interference amongst these components as well as with other environmental and crop-related factors. Such interference has the potential to reduce IPM efficacy, especially as the use of IPM is broadened and intensified. Evidence for such interference among components of IPM is briefly reviewed and the need for a research agenda that investigates such interference experimentally is discussed along with the potential for using 'big data' generated in IPM to conduct meta-analyses and construct powerful models for IPM. These approaches to research and data management should support the expansion and improvement of Decision Support Systems (DSS) for IPM practitioners that combine databases, expert networks and models. The success of DSS based on increasingly complex and extensive knowledge and data greatly depends on their accessibility, ease of use and whether they produce clear outputs that support decision-making by growers and consultants. The aim must be to improve IPM efficacy, predictability, cost-effectiveness and sustainability, while still finding ways of helping IPM practitioners identify IPM strategies that are optimal for their needs amongst an increasing number of options.

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