This online course will equip participants with an understanding of computer modelling of breeding programmes to enhance genetic improvements in agriculture. The modelling is done through the AlphaSimR package.
The package provides a set of functions that represent breeding activities. The combination of these functions in an R script allows the modelling of simple and arbitrarily complex breeding programmes. It also allows evaluation of the effects of alternative breeding scenarios on the rate of genetic improvement and other key performance indicators.
The course is taught by experts in the field and is applicable to a range of breeding programmes as demonstrated through local and global case studies.
Wheat field image by Alf Ceplitis.
Recall the key steps in setting up and designing a computer (in-silico) breeding programme to simulate and study a chosen population and understand the objectives that the in-silico breeding programme is being tailored to address.
Apply and build a breeding programme with AlphaSimR and use it to simulate and analyse a range of scenarios for a chosen population using an online R platform, which allows participants to access, manipulate, and run code.
Evaluate different breeding scenarios best suited to different species, populations, and available resources. Use information from the course to create a breeding programme which meets these objectives and derive tangible interpretations based on the simulation results.
Week 1: Introduction to breeding programme modelling
Week 2: Relationship between DNA & traits
Week 3: DNA Lottery
Week 4: Response to selection
Week 5: Modelling complex breeding programmes
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