Toward a Bayesian procedure for using process-based models in plant breeding, with application to ideotype design

Van Oijen, M.; Hoglind, M.. 2016 Toward a Bayesian procedure for using process-based models in plant breeding, with application to ideotype design. Euphytica, 207 (3). 627-643.

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Process-based grassland models (PBMs) simulate growth and development of vegetation over time. The models tend to have a large number of parameters that represent properties of the plants. To simulate different cultivars of the same species, different parameter values are required. Parameter differences may be interpreted as genetic variation for plant traits. Despite this natural connection between PBMs and plant genetics, there are only few examples of successful use of PBMs in plant breeding. Here we present a new procedure by which PBMs can help design ideotypes, i.e. virtual cultivars that optimally combine properties of existing cultivars. Ideotypes constitute selection targets for breeding. The procedure consists of four steps: (1) Bayesian calibration of model parameters using data from cultivar trials, (2) Estimating genetic variation for parameters from the combination of cultivar-specific calibrated parameter distributions, (3) Identifying parameter combinations that meet breeding objectives, (4) Translating model results to practice, i.e. interpreting parameters in terms of practical selection criteria. We show an application of the procedure to timothy (Phleum pratense L.) as grown in different regions of Norway.

Item Type: Publication - Article
Digital Object Identifier (DOI):
UKCEH and CEH Sections/Science Areas: Dise
ISSN: 0014-2336
Additional Information. Not used in RCUK Gateway to Research.: Open Access paper - full text available via Official URL link.
Additional Keywords: BASGRA, cold tolerance, genotype-environment interaction, plant breeding, process-based modelling, yield stability
NORA Subject Terms: Agriculture and Soil Science
Date made live: 30 Sep 2015 14:55 +0 (UTC)

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