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Detection and tracking of airborne rust spores as an information tool for pesticide-reduction strategies

Project Code: PRR06-520

Project Lead

Sarah Hambleton - Agriculture and Agri-Food Canada


To improve the predictive capability of an existing sentinel plot program by including pathogen detection devices for effective timing of fungicide applications to control Asian Soybean Rust (Phakopsora pachyrhizi)

Summary of Results

The Asian soybean rust caused by the pathogenic fungus Phakopsora pachyrhizi, is an economically important disease threatening the soybean industry in many parts of the world. Common throughout Asia and South America, the disease did not occur in North America until November 2004, when it was first found in the southern United States (U.S.). In the following years, rust spores were detected as far north as Dakota and the U.S. Great Lakes Region. This disease has the potential to cause devastating losses to soybean growers in North America as there is no effective resistance to the pathogen in currently available commercial soybean varieties. It was therefore, essential to determine the risk from this new and destructive disease to the soybean industry in Canada.

Currently, foliar fungicides are the primary control method for the Asian soybean rust. Early disease detection and appropriate timing of the first spray application are, therefore, critical to effective management and to avoid unnecessary sprays. A well coordinated monitoring system supported by proper scouting techniques and reliable tools was needed to track presence and dispersal of pathogen airborne spores and help growers make sound management decisions in the event that the disease occurred in Canada.

Agriculture and Agri-Food Canada researchers, in collaboration with soybean industry and government specialists in Ontario and the U.S. implemented a molecular screening pilot study aiming to develop and establish effective methods for detecting and tracking the movement of airborne rust spores into Canada. In this study, innovative DNA-based screening techniques and spore trapping equipment were incorporated to the existing Ontario Soybean Rust Sentinel Plot program which was established in 2005 as part of the North American Soybean Rust Sentinel Plot Network. Under this program, intensive scouting of soybean fields and sentinel plots was conducted throughout the season to monitor the potential spread of this disease into Canada. Rainfall collectors and airborne spore samplers were deployed at 12 sites, 10 in Ontario and one in each of Manitoba and Saskatchewan. Rapid screening of the samples was done using a species-specific real-time PCR and additional DNA-based diagnostic approaches.

The establishment of a spore trapping network and approaches developed though this study allowed for the first time to detect the presence of the fungal pathogen in Canada and assess the risk potential, before disease was found on the ground. The first detection of Asian soybean rust in rainfall and air samples collected in Canada occurred in mid-June 2007. The highest frequency of spores was detected in mid-July and mid-to late August; each of these time periods corresponded to a series of storm front events that suggested long distance transport of the spores was possible. Subsequently, infection from soybean rust was detected on a soybean leaf sample collected at Ridgetown, Ontario in October, 2007.

This is the first report of the Asian Soybean Rust disease occurring in Canada, spread via wind-borne infective spores into Ontario from the U.S., following late season infections documented in soybean fields as far as northern Illinois and Iowa. However, spore loads were low and soybean plants in Ontario were either harvested or too mature for the disease to affect the 2007 crop. The information resulting from this project has contributed to the joint U.S.-Canada efforts to develop and calibrate a forecasting model for the disease under the North American Soybean Rust Sentinel Plot Network.

Spore trapping information validated with molecular based techniques, combined with field scouting and analyses of weather data can assist in early disease detection or to determine where the disease has a low probability of developing. Under this project, the information collected in the field was processed and disseminated to soybean growers through the networks of provincial extension services and soybean grower associations. This information can help growers reduce economic and environmental risk through eliminating unnecessary fungicide applications.

For more information about this project or these forecasting systems, please contact:
Dr. Sarah Hambleton at

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