Advancing pest management: Drone-based eDNA monitoring for early detection
ETH researchers are developing a drone-based eDNA analysis approach for early detection of invasive species in viticulture. This interdisciplinary project aims to overcome limitations of traditional monitoring, demonstrating the potential of this approach for biomonitoring in initial field trials.
Pest invasions, intensified by globalization and climate change, pose a threat to global agriculture, causing substantial crop losses and economic damage. Effective monitoring tools are essential for the timely identification of invasive pest outbreaks. However, traditional methods like visual surveys and traps often fail to rapidly and efficiently detect these invasions, especially early on. This is exemplified in Switzerland, where the Japanese beetle (Popillia japonica) infests various crops and trees.
Combining Robotics and eDNA Testing
To overcome limitations of traditional methods, an ongoing project of the Smart Sustainable Farming Research Program leverages robotic and environmental techniques: autonomous drones descend into vineyards to swab plant structures and nets, improving the speed and scale of sample collection, while eDNA— DNA traces shed by organisms—provides a precise and non-invasive way to detect pest presence without disrupting the ecosystem.
The interdisciplinary research team, from the ETH research groups Environmental Robotics and Ecosystems and Landscape Evolution, completed the first field season, during which they compared eDNA sampling strategies. Early-season data suggests eDNA was more effective than visual surveys for detecting P. japonica. In fact, at the first sampling timepoint, eDNA detected the presence of P. japonica, while adults had not yet been observed through visual inspections. This indicates eDNA's potential for early, on-site detection of infestations, as P. japonica's eDNA was detected in the vegetation between crops, the protective nets, and on the vegetation itself.
“While our current focus is on vineyards, the drone-based eDNA monitoring we are developing has broader relevance. The methodology has the potential to be adapted for early pest detection for a variety of other crops, e.g. corn.”Project Researcher Martina Lüthi
Future Research Directions
Building on the initial findings, the next project phase will focus on early detection. This will involve increased sampling efforts to precisely determine the emergence of P. japonica. Acknowledging the potential for broader application beyond vineyards, as noted by Dr. Martina Lüthi, the research will also streamline the analysis process. This will be achieved by conducting on-site analyses, which will eliminate the need for time-consuming laboratory processing and enable the rapid delivery of data. The project aims to provide timely information that can effectively support decision-making and enhance pest management strategies.
Find out more about the project:
Project Webpage Download Project Fact Sheet (PDF, 489 KB)