These new protocols will enable farmers to more accurately target the application of pesticides based on accurate, near real-time information on pest presence/absence and abundance. This could result in substantial savings because Ontario farmers spend about $400 million a year on pesticides, comprising about 5% of all farm operating expenses.
The Census of Agriculture conducted by Statistics Canada indicated that agricultural activity in Ontario was worth $11 billion in 2011 while the national total was $51 billion. By providing an augmented capacity to discriminate species that attack crops, DNA barcoding helps to secure the productivity of this sector. As a consequence, researchers at Agriculture and Agri-Food Canada and Canadian Food Inspection Agency now employ DNA barcoding as a routine tool in pest species diagnoses, but this approach has been implemented on a specimen-by-specimen basis.
The research team is developing high-throughput sequencing protocols to analyze bulk samples obtained at agricultural field stations with the goal of providing weekly assessments on the occurrence of the pest insects present at each site. This near real-time monitoring system for agricultural pests will provide information that will optimize the timing of pesticide applications. Initial work will focus on delivering information on the presence/absence of all important pest species, but subsequent efforts will strive to provide abundance data for each species.
New metabarcoding protocols create the potential to establish monitoring programs that deliver near real-time information on the presence/absence of insect pests, information that farmers could employ to optimize the timing, dosing and nature of pesticides or biological control agents used to protect their crops.
Partners: Ontario Ministry of Agriculture- Food and Rural Affairs (OMAFRA) Field Stations (Elora, Arkell); ALUS Network.
Collaborators and students: Kevin McCann, John Fryxell, Andrew MacDougal, Nigel Raine, Vasco Elbrecht, Thomas Braukmann. Marie-Eugenie Maggia.
For more information on this research project, please visit http://biodiversitygenomics.net/
