New Directions in Deterministic Metabolism Modeling of Sheep
© 2016 Elsevier Inc. All rights reserved.A deterministic whole-body sheep metabolism model relies on biochemical knowledge on how pools absorb nutrients from feed intake and interact with each other. We review previous work in the area with a focus on one of the more comprehensive sheep models publi...
| Main Authors: | , |
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| Format: | Book Chapter |
| Published: |
2016
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| Online Access: | http://hdl.handle.net/20.500.11937/52266 |
| _version_ | 1848758886714048512 |
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| author | Black, E. Rehbock, Volker |
| author_facet | Black, E. Rehbock, Volker |
| author_sort | Black, E. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | © 2016 Elsevier Inc. All rights reserved.A deterministic whole-body sheep metabolism model relies on biochemical knowledge on how pools absorb nutrients from feed intake and interact with each other. We review previous work in the area with a focus on one of the more comprehensive sheep models published. We identify some less transparent limitations to this model and suggest ways to overcome them. We demonstrate the use of dynamic optimization techniques, particularly optimal parameter selection formulations, to improve the model, guided by the observed behavior or actual sheep metabolic processes.We implement the model consisting of differential equations governing transactions between pools in the MISER3.3 dynamic optimization software. This enables us to adjust model parameters and inputs to achieve more realistic outcomes and extend the model to adulthood. While a reliable, widely accepted model to replicate whole-body sheep growth remains a long-term goal, the work demonstrates that significant improvements can be achieved with appropriate mathematical tools. |
| first_indexed | 2025-11-14T09:51:07Z |
| format | Book Chapter |
| id | curtin-20.500.11937-52266 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T09:51:07Z |
| publishDate | 2016 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-522662017-09-13T15:38:43Z New Directions in Deterministic Metabolism Modeling of Sheep Black, E. Rehbock, Volker © 2016 Elsevier Inc. All rights reserved.A deterministic whole-body sheep metabolism model relies on biochemical knowledge on how pools absorb nutrients from feed intake and interact with each other. We review previous work in the area with a focus on one of the more comprehensive sheep models published. We identify some less transparent limitations to this model and suggest ways to overcome them. We demonstrate the use of dynamic optimization techniques, particularly optimal parameter selection formulations, to improve the model, guided by the observed behavior or actual sheep metabolic processes.We implement the model consisting of differential equations governing transactions between pools in the MISER3.3 dynamic optimization software. This enables us to adjust model parameters and inputs to achieve more realistic outcomes and extend the model to adulthood. While a reliable, widely accepted model to replicate whole-body sheep growth remains a long-term goal, the work demonstrates that significant improvements can be achieved with appropriate mathematical tools. 2016 Book Chapter http://hdl.handle.net/20.500.11937/52266 10.1016/B978-0-12-804203-8.00016-X restricted |
| spellingShingle | Black, E. Rehbock, Volker New Directions in Deterministic Metabolism Modeling of Sheep |
| title | New Directions in Deterministic Metabolism Modeling of Sheep |
| title_full | New Directions in Deterministic Metabolism Modeling of Sheep |
| title_fullStr | New Directions in Deterministic Metabolism Modeling of Sheep |
| title_full_unstemmed | New Directions in Deterministic Metabolism Modeling of Sheep |
| title_short | New Directions in Deterministic Metabolism Modeling of Sheep |
| title_sort | new directions in deterministic metabolism modeling of sheep |
| url | http://hdl.handle.net/20.500.11937/52266 |