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Plant Health Identification of Coleoptera 

Morphological and molecular identification of beetle species on live wood supported by new technologies: Smartphone APPs & Next-Generation-Sequencing (NGS) in the field of plant health.

Many xylobiont beetles are known by plant health authorities for their potential to become invasive and cause devastating economic and ecological damages in new habitats. Therefore, rapid detection and identification of non-native species is very important in order to prevent their successful establishment or further spread. The aim of the PHID-Coleo project series is to develop new diagnostic methods for the identification of non-native and potentially invasive beetle species discovered during plant health inspections, which could be introduced to Germany through imported wood or plant shipments.

PHID-Coleo I focused on longhorn beetles (Cerambycidae), false powderpost beetles (Bostrichidae) and true powderpost beetles (Lyctidae). During the projects runtime, a unique reference collection consisting of pinned insects, photos and gene sequences as well as literature from all over the world was compiled. In addition, dichotomous identification keys were created and molecular identification by DNA barcoding was established. Simultaneously, the University of Hohenheim, our partner in this project, conducted genome analysis of spatially separated populations of the Asian longhorn beetle (Anoplophora glabripennis). This contributed to a better understanding of the introduction and establishment of invasive wood pests. 

PHID-Coleo II now extends the species spectrum to the families of jewel beetles (Buprestidae) and bark beetles (Scolytinae), which will ultimately cover all beetle families relevant to plant health on imported wood. Existing diagnostic procedures will be supported by new technologies to enable import inspectors to make on-site diagnoses and thus accelerate the initiation of protective measures. To this end, a smartphone application is being developed that can recognize selected beetles using artificial intelligence (a "beetle app") and the molecular method LAMP-PCR is being tested for its suitability to reliably identify important quarantine pests directly on-site without a laboratory, even when visual identification is no longer possible because the specimen is damaged. Additionally, metabarcoding using Next-Generation Sequencing (NGS) is being tested for its practical use in plant health. This technology makes it comparably fast and easy to identify mixed samples from trap catches on a species level and may give insights into the abundance of harmful species.

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