Grant: Alliance Grants
University of Saskatchewan
$281,924.00
Applying advanced molecular biology, metabolomics and image analysis using machine-learning technology to improve wheat resistance against Fusarium head blight
EF 2022-23
Résumé
Wheat is a staple crop and an integral part of the Canadian economy, providing income for producers and jobs for Canadians. Canada is the sixth largest producer of wheat in the world and the second largest exporter (~20% of the world market). The Canadian wheat industry, including both bread and durum wheat, is frequently threatened by fungal diseases, such as Fusarium head blight (FHB), which causes hundreds of millions of dollars in losses every year in Canada. Typical FHB symptoms include premature bleaching of spikelets, discolouration of the rachis, and Fusarium damaged kernels (FDK). The light weight of FDKs and even a small amount of FDKs within a commercial wheat crop can result in severe yield and quality losses. FHB is also a food and feed safety concern due to the contamination of grain by the mycotoxin deoxynivalenol (DON). Farmers will likely experience grade loss, restricted marketing opportunities, added costs, and lost income as a result of FHB. Compared to chemical fungicides, cultivation of resistant wheat varieties is the most efficient, eco-friendly and often the most economic strategy to control FHB. With advanced molecular biology, genomics, metabolomics and diverse automated imaging tools, the proposed project aims to provide a comprehensive understanding of the molecular mechanism of FHB resistance in wheat, characterize the genetic basis of the types of FHB resistance, develop useful molecular markers, identify resistant germplasm for breeding programs, and develop the high-throughput imaging and deep-learning tools required to support these advancements. Eventually, the knowledge, germplasm, molecular markers and phenotyping tools generated from this project will accelerate breeding cycles and benefit the wheat industry.
Programme
Alliance Grants
Bénéficiaire
Emplacement
Saskatchewan, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data
Tel que publié
Application id
570375-2021
Name nom
Kutcher, Hadley HR
Department département
Plant Sciences
Organization id
16
Institution établissement
University of Saskatchewan
Province en
Saskatchewan
Province fr
Saskatchewan
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2022
Competition year année de concours
2021
Award amount
281924
Program id
ALLRP
Program name en
Alliance Grants
Program name fr
Subventions Alliance
Group en
RESEARCH PARTNERSHIPS
Group fr
PARTENARIATS DE RECHERCHE
Committee code
96
Committee name en
RPP Internal Decision Cttee
Committee name fr
Cté de décision interne - PPR
Area of application code
1209
Area of application group en
Advancement of knowledge
Area of application group fr
Avancement des connaissances
Area of application en
Agriculture
Area of application fr
Agriculture
Research subject code
4906
Research subject group en
Plant and treebiology
Research subject group fr
Biologie végétale et des arbres
Research subject en
Plant pathology
Research subject fr
Phytopathologie
Installment
inst:2;3
Partie
2
Nb partie
3
Application title
Applying advanced molecular biology, metabolomics and image analysis using machine-learning technology to improve wheat resistance against Fusarium head blight
Application summary
Wheat is a staple crop and an integral part of the Canadian economy, providing income for producers and jobs for Canadians. Canada is the sixth largest producer of wheat in the world and the second largest exporter (~20% of the world market). The Canadian wheat industry, including both bread and durum wheat, is frequently threatened by fungal diseases, such as Fusarium head blight (FHB), which causes hundreds of millions of dollars in losses every year in Canada. Typical FHB symptoms include premature bleaching of spikelets, discolouration of the rachis, and Fusarium damaged kernels (FDK). The light weight of FDKs and even a small amount of FDKs within a commercial wheat crop can result in severe yield and quality losses. FHB is also a food and feed safety concern due to the contamination of grain by the mycotoxin deoxynivalenol (DON). Farmers will likely experience grade loss, restricted marketing opportunities, added costs, and lost income as a result of FHB. Compared to chemical fungicides, cultivation of resistant wheat varieties is the most efficient, eco-friendly and often the most economic strategy to control FHB. With advanced molecular biology, genomics, metabolomics and diverse automated imaging tools, the proposed project aims to provide a comprehensive understanding of the molecular mechanism of FHB resistance in wheat, characterize the genetic basis of the types of FHB resistance, develop useful molecular markers, identify resistant germplasm for breeding programs, and develop the high-throughput imaging and deep-learning tools required to support these advancements. Eventually, the knowledge, germplasm, molecular markers and phenotyping tools generated from this project will accelerate breeding cycles and benefit the wheat industry.