Generation of models from existing models composition: An application to agrarian sciences.
Mathematical models that describe gas production are widely used to estimate the rumen degradation digestibility and kinetics. The present study presents a method to generate models by combining existing models and to propose the von Bertalanffy-Gompertz two-compartment model based on this method. T...
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Public Library of Science (PLoS)
2019-01-01
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| Series: | PLoS ONE |
| Online Access: | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0214778&type=printable |
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| author | André Luiz Pinto Dos Santos Guilherme Rocha Moreira Frank Gomes-Silva Cícero Carlos Ramos de Brito Maria Lindomárcia Leonardo da Costa Luiz Gustavo Ribeiro Pereira Rogério Martins Maurício José Augusto Gomes Azevêdo José Marques Pereira Alexandre Lima Ferreira Moacyr Cunha Filho |
| author_facet | André Luiz Pinto Dos Santos Guilherme Rocha Moreira Frank Gomes-Silva Cícero Carlos Ramos de Brito Maria Lindomárcia Leonardo da Costa Luiz Gustavo Ribeiro Pereira Rogério Martins Maurício José Augusto Gomes Azevêdo José Marques Pereira Alexandre Lima Ferreira Moacyr Cunha Filho |
| author_sort | André Luiz Pinto Dos Santos |
| collection | DOAJ |
| description | Mathematical models that describe gas production are widely used to estimate the rumen degradation digestibility and kinetics. The present study presents a method to generate models by combining existing models and to propose the von Bertalanffy-Gompertz two-compartment model based on this method. The proposed model was compared with the logistic two-compartment one to indicate which best describes the kinetic curve of gas production through the semi-automated in vitro technique from different pinto peanut cultivars. The data came from an experiment grown and harvested at the Far South Animal Sciences station (Essul) in Itabela, BA, Brazil and gas production was read at 2, 4, 6, 8, 10, 12, 14, 17, 20, 24, 28, 32, 48, 72, and 96 h after the start of the in vitro fermentation process. The parameters were estimated by the least squares method using the iterative Gauss-Newton process in the software R version 3.4.1. The best model to describe gas accumulation was based on the adjusted coefficient of determination, residual mean squares, mean absolute deviation, Akaike information criterion, and Bayesian information criterion. The von Bertalanffy-Gompertz two-compartment model had the best fit to describe the cumulative gas production over time according to the methodology and conditions of the present study. |
| format | Article |
| id | doaj-art-9b2cf9f891f04efdbfc9c9102cccf85d |
| institution | OA Journals |
| issn | 1932-6203 |
| language | English |
| publishDate | 2019-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj-art-9b2cf9f891f04efdbfc9c9102cccf85d2025-08-20T02:11:01ZengPublic Library of Science (PLoS)PLoS ONE1932-62032019-01-011412e021477810.1371/journal.pone.0214778Generation of models from existing models composition: An application to agrarian sciences.André Luiz Pinto Dos SantosGuilherme Rocha MoreiraFrank Gomes-SilvaCícero Carlos Ramos de BritoMaria Lindomárcia Leonardo da CostaLuiz Gustavo Ribeiro PereiraRogério Martins MaurícioJosé Augusto Gomes AzevêdoJosé Marques PereiraAlexandre Lima FerreiraMoacyr Cunha FilhoMathematical models that describe gas production are widely used to estimate the rumen degradation digestibility and kinetics. The present study presents a method to generate models by combining existing models and to propose the von Bertalanffy-Gompertz two-compartment model based on this method. The proposed model was compared with the logistic two-compartment one to indicate which best describes the kinetic curve of gas production through the semi-automated in vitro technique from different pinto peanut cultivars. The data came from an experiment grown and harvested at the Far South Animal Sciences station (Essul) in Itabela, BA, Brazil and gas production was read at 2, 4, 6, 8, 10, 12, 14, 17, 20, 24, 28, 32, 48, 72, and 96 h after the start of the in vitro fermentation process. The parameters were estimated by the least squares method using the iterative Gauss-Newton process in the software R version 3.4.1. The best model to describe gas accumulation was based on the adjusted coefficient of determination, residual mean squares, mean absolute deviation, Akaike information criterion, and Bayesian information criterion. The von Bertalanffy-Gompertz two-compartment model had the best fit to describe the cumulative gas production over time according to the methodology and conditions of the present study.https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0214778&type=printable |
| spellingShingle | André Luiz Pinto Dos Santos Guilherme Rocha Moreira Frank Gomes-Silva Cícero Carlos Ramos de Brito Maria Lindomárcia Leonardo da Costa Luiz Gustavo Ribeiro Pereira Rogério Martins Maurício José Augusto Gomes Azevêdo José Marques Pereira Alexandre Lima Ferreira Moacyr Cunha Filho Generation of models from existing models composition: An application to agrarian sciences. PLoS ONE |
| title | Generation of models from existing models composition: An application to agrarian sciences. |
| title_full | Generation of models from existing models composition: An application to agrarian sciences. |
| title_fullStr | Generation of models from existing models composition: An application to agrarian sciences. |
| title_full_unstemmed | Generation of models from existing models composition: An application to agrarian sciences. |
| title_short | Generation of models from existing models composition: An application to agrarian sciences. |
| title_sort | generation of models from existing models composition an application to agrarian sciences |
| url | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0214778&type=printable |
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