Orthotospoviruses are among the most economically significant plant pathogens in the world at present. Almost all orthotospoviruses are known to be transmitted by thrips, which are minuscule insects from the order Thysanoptera. In Australia, five thrips species can transmit orthotospoviruses. It is therefore important to identify the thrips species in the horticultural sector, to establish appropriate management strategies to prevent virus spread. The most common practice for monitoring thrips in the nursery industry is to use sticky traps and morphological assessments. However, thrips morphological identification can be challenging and time consuming, as they need to be removed from the sticky traps and mounted on slides. Alternatively, molecular identification of thrips can be based on DNA barcoding, comparing the mitochondrial cytochrome c oxidase I (COI) gene, and it is also a time-consuming process, especially considering the high volume of thrips that can be collected on a single sticky trap. This work describes the developing of a high-throughput, scalable method for the identification of all thrips species from a sticky trap using COI metabarcoding performed on Illumina Miseq sequencing platform. Thrips were successfully identified from sticky traps using this methodology, even two years after the sticky traps were collected. The evaluation also revealed that this methodology is highly sensitive, with the ability to identify an individual thrips in a pool with other 999 thrips and without any false identification. This methodology can increase the efficiency of monitoring thrips and are highly important for the biosecurity of the horticulture industry.