The aim of this studentship is to couple changes in winter wheat physiological development with multi-spectral imaging in order to support development of advanced agronomy – through the next generation of crop and field management tools and technologies. This will be achieved by integrating ground-based physiological measurements on wheat with multi-spectral imaging data and analysis.
SRUC is at the leading edge in applying spectral sensing in agriculture e.g. prediction of livestock traits. The combined advanced technologies in multi-spectral imaging supported by process modelling (deep learning) have already been used by SRUC to create phenotype signatures that indicate animal health and predict performance. This wheat science studentship will gather high quality and high-volume growth and developmental and physiological signatures for crops using ground-based and unmanned aerial systems (UASs) to inform on crop health at key growth phases towards prediction of crop yield and quality.
The student’s work programme will consider how spectral imaging can be used to monitor crop growth phases, especially during yield creation and grain filling and ripening, as influenced by cultivar and crop growing conditions. The project will also precisely monitor crop moisture content during grain filling and ripening in order to improve guidance on crop maturity as harvest approaches.
The student will have opportunity to link with crop genetic improvement by utilising wheat resources such as a diverse MAGIC wheat population and a breadth of different cultivars to link phenotypic expression in physiological change with other existing trait and marker data. This adds value towards quantitative analysis of physiological and maturity traits, as well as yield.
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Please fill out the application form and equal opportunities form and send it along with your academic qualifications to [Email Address Removed], quoting reference SRUC/SH.
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