Barossa insect surveillance samples trialled using cutting-edge diagnostic technique

Samples from insect suction traps onboard Sentinel 1 at the Nuriootpa research centre in the Barossa are being screened using […]

Samples from insect suction traps onboard Sentinel 1 at the Nuriootpa research centre in the Barossa are being screened using a new method of insect ID. This work is conducted by Agriculture Victoria Research (AVR) for the iMapPESTS program, which aims to monitor insect biodiversity and presence/absence of pests using smart traps in an agricultural environment. The samples of insects collected at the Nuriootpa site are being analysed using High-throughput Sequencing (HTS) technologies.

The HTS approach takes the sample of insects and sucks out the various genetic codes. This results in a ‘DNA soup’ that can be scanned using a database of known DNA barcodes to detect and flag the particular species present. This technique has the potential to detect more targets using a single test and discover biosecurity threats early, allowing for a more effective response to an incursion.

SARDI and AVR have been collaborating to investigate the optimal sampling methods for required for the diverse range of agricultural settings across our landscape. As molecular techniques edge toward faster ID of targets it is important that the research results can be validated by morphological analysis by specialist entomologists. However, this method is time consuming and labour-intensive.

AVR recently published a study on the use of propylene glycol as an insect DNA preservative paired with non-destructive DNA extraction techniques (Martoni et al. 2021; Agriculture, https://doi.org/10.3390/agriculture11010077).

The application of this new technology will enable a better understanding of the diversity of airborne insects for a given trial region. In addition to revealing the population dynamics for a handful of priority targets that will continue to be identified and quantified using traditional morphological ID, the sequencing data can provide an overview of the insect biodiversity of agricultural settings, including the presence of beneficials such as pollinators and/or predators of pests.