A Bayesian framework to model variance of grain yield response to plant density
Modeling grain yield response to plant density with the proposed framework is suitable for heteroscedastic data scenarios. Future research may focus on exploring how genotypes, environments and their interaction modulate the difference between AOPD and minRPD and, extend the framework to a variety of processes involving crop management decisions.
Authors
- Nicolas Giordano (ORCID: https://orcid.org/0000-0003-0159-4958)
- Lucas A. Haag (ORCID: https://orcid.org/0000-0003-4093-1566)
- Trevor J. Hefley (ORCID: https://orcid.org/0000-0002-5850-328X)
- Brian L. Beres (ORCID: https://orcid.org/0000-0003-0952-0013)
- Romulo P. Lollato (ORCID: https://orcid.org/0000-0001-8615-0074)
- Josefina Lacasa (ORCID: https://orcid.org/0000-0002-7201-7480)
- Deborah C. Hayes (ORCID: https://orcid.org/0009-0004-9209-0994)
Institutions
- Agriculture and Agri-Food Canada (CA)
- Kansas State University (US)
- Université Bourgogne Franche-Comté (FR)
- Lethbridge Research and Development Centre
Publication Details
- Journal
- Plant Methods
- Published
- 2025-03-17
- DOI
- https://doi.org/10.1186/s13007-025-01355-y
- Citations
- 1
- Primary Topic
- Wheat and Barley Genetics and Pathology
- Type
- article
- Field-Weighted Citation Impact
- 1.75
Funders
- Kansas Wheat Commission