The project aims to introduce "in silico" supported prevention, detection and Integrated Pest Management (IPM) approaches for both new and emerging FF, based on spatial modelling across a wide range of spatial levels, novel decision support systems, and new knowledge regarding biological traits of the target species, fruit trading and socioeconomics.
FF-IPM introduces a fundamental paradigm shift in IPM towards “OFFSeason” management of FF by targeting the overwintering generation when population undergoes significant bottlenecks, preventing, this way, population growth later in the season. “ON-Season” control approaches will be generated for different spatial scales considering both existing and developed by FF-IPM tools and services. Innovative prevention tools to track FF infested fruit (e-Nose) and rapidly identify intercepted specimens (Rapid-Molecular-Pest-ID tools) in imported commodities and at processing industries will be produced. Species-specific e-trapping systems for the three-target FF will be advanced and employed by novel detection strategies based on spatial modelling.
Both “ON and OFF-Season” IPM approaches and detection strategies will be validated in selected locations in eight different countries. FF-IPM generated data on FF response under stress conditions, overwintering dynamics, establishment and dispersion patterns of low population densities combined with advanced spatial population modelling are expected to contribute towards understanding drivers of emerging and new pests under climate change scenarios.