Reference number : GC-2017-Q3-00574, amendment number : , agreement type : G, recipient legal name : Rieseberg, Loren (The University of British Columbia), recipient country : CA, recipient province : nan, recipient city : British Columbia|Colombie-Britannique, recipient postal code : nan, program name english : Engage Grants for universities, program name french : Subventions d'engagement partenarial pour les universités, program purpose english : Sunflower in a $20 billion oil crop and one of the world's main sources of vegetable oil. However, sunflower_x000D_
can be a high-risk crop because of potential losses from diseases. A major component of disease management_x000D_
programs is early pathogen detection and immediate implementation of control strategies to minimize_x000D_
economic loss. Monitoring and management is very labor intensive and by the time the symptoms become_x000D_
visible, the infection has become well-established, diminishing the efficacy of fungicides. In contrast,_x000D_
automated sensor-based diagnostics provides a powerful alternative to conventional visual screening. In this_x000D_
project, we will examine the practical utility of high-resolution sensory systems developed by Ecoation for_x000D_
resistance screening of some of the most important diseases in sunflower: rust, Phomopsis stem canker (PSC)_x000D_
and Sclerotinia head rot (SHR). We will also compare efficiency of this technology to some of the available_x000D_
alternatives, as well as to most widely used method - visual screening. This knowledge will enable the_x000D_
development of more accurate and efficient strategies for detecting and quantifying disease severity that could_x000D_
be used for precision agriculture., program purpose french : Sunflower in a $20 billion oil crop and one of the world's main sources of vegetable oil. However, sunflower_x000D_
can be a high-risk crop because of potential losses from diseases. A major component of disease management_x000D_
programs is early pathogen detection and immediate implementation of control strategies to minimize_x000D_
economic loss. Monitoring and management is very labor intensive and by the time the symptoms become_x000D_
visible, the infection has become well-established, diminishing the efficacy of fungicides. In contrast,_x000D_
automated sensor-based diagnostics provides a powerful alternative to conventional visual screening. In this_x000D_
project, we will examine the practical utility of high-resolution sensory systems developed by Ecoation for_x000D_
resistance screening of some of the most important diseases in sunflower: rust, Phomopsis stem canker (PSC)_x000D_
and Sclerotinia head rot (SHR). We will also compare efficiency of this technology to some of the available_x000D_
alternatives, as well as to most widely used method - visual screening. This knowledge will enable the_x000D_
development of more accurate and efficient strategies for detecting and quantifying disease severity that could_x000D_
be used for precision agriculture., agreement title english : Non-invasive method of biotic and abiotic stress detection in sunflowers, agreement title french : Non-invasive method of biotic and abiotic stress detection in sunflowers, agreement number : EGP, agreement value : 25000.0, agreement start date : 2017-10-18, agreement end date : nan, description english : nan, description french : nan, expected results english : nan, expected results french : nan, additional information english : Grant or Award spanning more than one fiscal year (2017-2018 to 2018-2019)., additional information french : Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier (2017-2018 à 2018-2019)., owner organization : nserc-crsng, owner organization title : Natural Sciences and Engineering Research Council of Canada | Conseil de recherches en sciences naturelles et en génie du Canada