EmergeNOW uses digital, molecular tools for rapid CBS, HLB detection, enabling early warning at EU import points. Consortium introduces novel tools and autonavigated robots for inspectors: a) on-site Phyllosticta citricarpa (P.c) and Candidatus Liberibacter’ (Ca. L) species rapid detection a molecular tool based on Recombinase Polymerase Amplification kits, b)Fluorescent Array-based Sensing Technology for P.c and Ca.L rapid detection, c) Artificial Intelligence- powered mobile apps for rapid CBS and HLB image analysis detection integrated with low-cost hyperspectral imagers, d) UAVs for AI-based RGB and hyperspectral imaging of abiotic and biotic symptom response of CBS and HLB and similar to these; e) Autonomous Mobile Robots for HLB and CBS AI imaging symptoms detection discriminate from abiotic stress. Also, deployment plans are in place for detecting the vector Diaphorina citri (ACP), Trioza erytreae (T.e ), and Cacopsylla citrisuga (C.c) by: f) e-Nose sensors, g) AI - based robotic traps for real time detection and monitoring, and h) AI-powered mobile apps for their early detection. Τhese systemic innovations could be incorporated in the EFSA Survey Cards. Digital tools link in systemic alert system with blockchain, ML analytics and will enable informed decisions for import control. Focusing on showcasing real problem scenarios, the developed tools and methods will be initially tested and optimised in biosecure enviroments at Plant Health Centers (PHC) and afterwards validated in citrus orchards in USA (CBS, HLB, ACP), Uganda (CBS, HLB, T.e), Vietnam (HLB, ACP, C.c), and in Cyprus (ACP). The optimised tools will be demonstrated in authorized Border Control Posts in Greece, Italy, Spain and Cyprus.

The FF-IPM project targets three highly polyphagous fruit fly (FF) species (Tephritidae) that cause devastating losses in the fresh fruit producing industry, the Mediterranean fruit fly (Ceratitis capitata), a serious emerging pest in northern temperate areas of Europe, the Oriental fruit fly (Bactrocera dorsalis) and the peach fruit fly (B. zonata) two major new (invasive) pests, which pose an imminent threat to European horticulture. 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 “OFF-Season” management of FF by targeting the overwintering generation when population undergoes significant bottlenecks, preventing, this way, population growth later in 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 modeling are expected to contribute towards understanding drivers of emerging and new pests under climate change scenarios.