Year: 2024
Type: article
Abstract: Plant breeding plays a crucial role in the development of high-performing crop varieties that meet the demands of society. Emerging breeding techniques offer the potential to improve the precision and efficiency of plant breeding programs; however, their optimal implementation requires refinement of existing breeding programs or the design of new ones. Stochastic simulations are a cost-effective solution for testing and optimizing new breeding strategies. The aim of this paper is to provide an introduction to stochastic simulation with software AlphaSimR for plant breeding students, researchers, and experienced breeders. We present an overview of how to use the software and provide an introductory AlphaSimR vignette as well as complete AlphaSimR scripts of breeding programs for self-pollinated, clonal, and cross-pollinated plants, including relevant breeding techniques, such as backcrossing, speed breeding, genomic selection, index selection, and others. Our objective is to provide a foundation for understanding and utilizing simulation software, enabling readers to adapt the provided scripts for their own use or even develop completely new plant breeding programs. By incorporating simulation software into plant breeding education and practice, the next generation of plant breeders will have a valuable tool in their quest to provide sustainable and nutritious food sources for a growing population.
Source: Crop Science
DOI: 10.1002/csc2.21312
Institutions: Roslin Institute, University of Edinburgh
Language: English
Subfield: Genetics
Domain: Life Sciences
SDG: Zero hunger
Open Access status: hybrid
Estimated APC paid: $1,760
Awards: Genes & Traits for Healthy Animals: Understanding the origins of animal phenotypes, Genes & Traits for Healthy Animals: Identifying the genomic basis of complex traits in farmed animals, G2605594305, A strategy to exploit genomic selection for achieving higher genetic gains in groundnut, G4938650597, GplusE: Genomic selection and Environment modelling for next generation wheat breeding, G6120154085, G6566584595, G6889081127, A general method for the imputation of genomic data in crop species, G7380214141
OpenAlex ID: W4401975428