Paper

Taurai T. Matengu (1), Paul Bullock (1), Manasah S. Mkhabela (1), Francis Zvomuya (1), Maria A. Henriquez (2), Timi Ojo (3), Réjean Picard (4), Raul Avila (5), Alireza Akhavan (5), and Michael Harding (6) 1. Department of Soil Science, University of Manitoba, Winnipeg, MB, Canada 2. Morden Research and Development Centre, Agriculture and Agri-Food Canada, Morden, MB, Canada 3. Soil and Ag Weather Surveillance, Manitoba Agriculture and Resource Development, Winnipeg, MB, Canada 4. Ag Adaptation Specialist - Crops, Manitoba Agriculture and Resource Development, Morden, MB, Canada 5. Ministry of Agriculture, Government of Saskatchewan, Regina, SK, Canada 6. Plant and Bee Health Surveillance, Alberta Agriculture and Forestry, Brooks, AB, Canada

Paul Bullock

University of Manitoba

Forecasting Fusarium head blight (FHB) epidemics based on visual disease observation in the field assists producers in preventing grain yield and quality loss by identifying where and when fungicide spray is required. However, visual symptoms do not always reflect the actual Fusarium-damaged kernels (FDK) and deoxynivalenol (DON) levels in the grain. Therefore, this study aims to develop weather-based risk models for predicting FHB index (FHBi), FDK, and DON in spring wheat, winter wheat, barley, and durum around the flowering period across three Canadian Prairie provinces. Disease data collected from 15 sites in western Canada in 2019 and 2020 were binary classified as either epidemic or non-epidemic using threshold values of 5% for FHBi (all crops), 1 ppm for DON (all crops) and 0.2, 0.3, 0.8, and 2% FDK for barley, spring wheat, winter wheat, and durum, respectively. Kendall correlation and stepwise logistic regression analysis identified combinations of temperature, relative humidity (RH), precipitation, and solar radiation at 4, 7, 10, 14 days pre-anthesis, and 3 days pre to 3 days post-anthesis that most accurately predicted the measures of FHB risk. RH was frequently the most highly correlated weather variable across crop types for FDK and DON. The prediction accuracy of the models ranged between 75 and 81, 77 and 85, 78 and 79% for FHBi, FDK, and DON, respectively. Dry and hot conditions during the 2019 and 2020 growing seasons likely suppressed FHB disease pressure in western Canada. These models, which will incorporate additional 2021 plot and field data, will be integrated into an online map viewer that will provide early warning of potential FHBi, FDK, and DON epidemics in cereal crops on the Canadian prairies.

 

Acknowledgment

This research was funded under the Integrated Crop Agronomy Cluster by Western Grain Research Foundation, Agriculture and Agri-Food Canada, Manitoba Crop Alliance, Saskatchewan Wheat Development Commission, Alberta Wheat Commission, Brewing and Malting Barley Research Institute, Canadian Agricultural Partnership, and Prairie Oat Growers Association. Special thanks to the producer collaborators, technicians, summer students, and colleagues who took part in this project.