Dr Francesco Martoni1, Dr Lea Rako1, Dr Alexander M. Piper1, Dr Jack L. Scanlan1, Professor Brendan C. Rodoni1,2, Dr Mark J. Blacket1
1Agriculture Victoria Research, AgriBio, Centre for AgriBioscience, Bundoora, Australia, 2La Trobe University, School of Applied Systems Biology, Bundoora, Australia
Biography:
Francesco is a molecular entomologist working as a research scientist for Agriculture Victoria, based in Melbourne at the AgriBio Centre. Francesco has more than 10 years research experience developing and optimising molecular methods to study insects and their associated microflora. During the past 6 years, Francesco has focused on developing and optimising workflows for high throughput metabarcoding of insects, bacteria and fungi for diagnostics and surveillance. More recently, Francesco’s work expanded to include also environmental DNA (eDNA) analysis for a broad range of targets, including marine pests as well as pests of honeybees (e.g., Varroa mites). Francesco’s main interest focuses on exploring the biodiversity “behind the pests”, using metabarcoding to explore the ecological networks linking both pests and beneficial insects to the surrounding environment.
Abstract:
Surveillance and long-term monitoring of insect pest populations are of great importance to detect pest species, and to inform biosecurity and pest management. Within this context, upscalable molecular methods have become increasingly important to provide quick and precise species-level identifications for arthropods, especially using high throughput sequencing (HTS) metabarcoding. HTS arthropod identification can enhance on-farm pest management decision-making when paired with sample collection via development and deployment of “smart” traps, able to collect large volumes of insects from the air. However, our understanding of dispersal and capture of airborne insect eDNA using active and passive suction traps remains limited.
Here we used automated (i.e., active) and traditional (passive) insect traps deployed in agricultural environments to sample the air, detecting insect pests and beneficials. We employed non-destructive insect metabarcoding on trapped insect samples, as well as eDNA metabarcoding from samples of the preservative solutions, to explore the arthropod diversity present in and around Grains crops in Victoria, Australia. We also assessed the presence/absence of insects that were not evident in the physical sample but could be recorded due to traces of eDNA from the air and/or on the insect’s surface. These samples could also be used to identify non-target organisms, such as bacteria and fungi, to better understand the ecological network surrounding agricultural areas as well as providing information within a broader plant pathology context.
Here we present the initial preliminary data from field experiments conducted in grains crops in Victoria, and discuss advantages and limitations linked to the techniques used here.