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Soybean Research |
Molecular diagnostics as a
component of soybean rust sentinel plot program
DETECTION
AND TRACKING OF THE AIRBORNE FUNGAL PATHOGEN PHAKOPSORA PACHYRHIZI FOR EARLY-WARNING
DISEASE PREDICTION
Dr. Sarah Hambleton, Agriculture and Agri-Food Canada
Soybean production in North America has been
threatened since the first confirmation in the southern United States (2004)
of Asian Soybean Rust, a potentially devastating disease caused by the rust
fungus Phakopsora pachyrhizi.
The Ontario Soybean Rust Sentinel Plot program was established in 2005 to monitor
the potential spread of this disease into Canada through intensive scouting
for symptoms and field evaluations in test plots. A molecular diagnostics component
was implemented at AAFC to track the movement of airborne spores by screening
samples from a network of rainfall and air collectors using a species-specific
PCR-based DNA test. The first detection of soybean rust spores in Canada was
during the 2007 growing season. In 2008, the network comprised 14 collection
sites from Alberta to Quebec, including the collection and testing of samples
from nine sites in Ontario.
Positive detections from a wide geographical distribution, from Saskatchewan
to Eastern Ontario, occurred in late June/early July, while positive results
for the remainder of the season were limited and scattered. Although there were
several other periods of major storm activity into Canada, rust spore loads
had not built up in the south due to unfavourable conditions for disease development.
Spore trapping results were provided to OMAFRA for risk assessment and the development
of management strategies if warranted. The results were also included in computer
model analyses of North American sentinel plot data for disease forecasting.
Canadian production will be vulnerable if favourable environmental conditions
result in the long range dispersal of viable spores from the US at the most
critical time of crop development, during flowering. Real-time data for airborne
pathogen spore dispersal patterns can be used to alert stakeholders of impending
disease threats, in effect providing an early warning system to manage risk
and avoid unnecessary fungicide applications.