Non-destructive insect metabarcoding as a surveillance tool for the Australian grains industry: a first trial for the iMapPESTS smart trap
Francesco Martoni, Reannon L. Smith, Alexander M. Piper, Narelle Nancarrow, Muhammad Nauman Aftab, Piotr Trębicki, R. B. E. Kimber, Brendan Rodoni, Mark J. Blacket
Abstract
Surveillance and long-term monitoring of insect pest populations are of paramount importance to limit dispersal and inform pest management. Molecular methods have been employed in diagnostics, surveillance and monitoring for the past few decades, often paired with more traditional techniques relying on morphological examinations. Within this context, the ‘iMapPESTS: Sentinel Surveillance for Agriculture’ project was conceptualised to enhance on-farm pest management decision-making via development and deployment of smart traps, able to collect insects, as well as recording associated environmental data. Here, we compared an iMapPESTS ‘Sentinel’ smart trap to an alternative suction trap over a 10-week period. We used a non-destructive insect metabarcoding approach complemented by insect morphological diagnostics to assess and compare aphid species presence and diversity across trap samples and time. Furthermore, we paired this with environmental data recorded throughout the sampling period. This methodology recorded a total of 497 different taxa from 70 traps over a 10-week period in the grain-growing region in western Victoria. This included not only the 14 aphid target species, but an additional 12 aphid species, including a new record for Victoria. Ultimately, with more than 450 bycatch species detected, this highlighted the value of insect metabarcoding, not only for pest surveillance, but also at a broader ecosystem level, with potential applications in integrated pest management and biocontrol.