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Proposal of a non-linear model to adjust in vitro gas production at different incubation times
Santos, André Luiz Pinto dos; Ferreira, Tiago Alessandro Espínola; Brito, Cícero Carlos Ramos de; Moreira, Guilherme Rocha; Gomes-Silva, Frank; Jale, Jader Silva; Reis, Ronaldo Braga; Leite, Leonardo Andrade; Pimentel, Patrícia Guimarães.
  • Santos, André Luiz Pinto dos; Universidade Federal Rural de Pernambuco. Recife. BR
  • Ferreira, Tiago Alessandro Espínola; Universidade Federal Rural de Pernambuco. Recife. BR
  • Brito, Cícero Carlos Ramos de; Instituto Federal de Pernambuco. Recife. BR
  • Moreira, Guilherme Rocha; Universidade Federal Rural de Pernambuco. Recife. BR
  • Gomes-Silva, Frank; Universidade Federal Rural de Pernambuco. Recife. BR
  • Jale, Jader Silva; Universidade Federal Rural de Pernambuco. Recife. BR
  • Reis, Ronaldo Braga; Universidade Federal de Minas Gerais. Fortaleza. BR
  • Leite, Leonardo Andrade; Universidade Federal de Minas Gerais. Belo Horizonte. BR
  • Pimentel, Patrícia Guimarães; Universidade Federal do Ceará. Fortaleza. BR
Biosci. j. (Online) ; 39: e39046, 2023. tab, graf
Article Dans Anglais | LILACS | ID: biblio-1428232
ABSTRACT
This work aims to propose a new model named Gompertz-Von Bertalanffy bicompartmental (GVB), a combination of the models Gompertz and Von Bertalanffy. The GVB models is applied to fit the kinetic curve of cumulative gas production (CGP) of four foods (SS ­ sunflower silage; CS ­ corn silage; and the mixtures 340SS ­ 660 gkg-1 of corn silage and 340 gkg-1 of sunflower silage; and 660SS ­ 340 gkg-1 of corn silage and 660 gkg-1 of sunflower silage). The GVB fit is compared to models Logistic-Von Bertalanffy bicompartmental (LVB) and bicompartmental logistic (BL). All the process studied employed the semi-automatic "in vitro" technique of producing gases used in ruminant nutrition. The gas production readout was performed at times 2, 4, 6, 8, 10, 12, 15, 19, 24, 30, 48, 72, and 96 h. The data generated were used to estimate the models' parameters by the least squared method with the iterative Gauss-Newton process. The data fit quality of the models was verified using the adjusted coefficient of determination criterion (), mean residual square (MRS), Akaike information criterion (AIC), and mean absolute deviation (MAD). Among the analyzed models, the LVB model presented the best quality of fit evaluators for CS. In contrast, the GVB model showed better quality of fit to describe CGP over time for 340SS, 660SS, and SS, presenting the highest values of () and the lowest values of MSR, AIC, and MAD.

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Texte intégral: Disponible Indice: LILAS (Amériques) Sujet Principal: Ensilage / Dynamique non linéaire / Gaz Type d'étude: Étude pronostique langue: Anglais Texte intégral: Biosci. j. (Online) Thème du journal: Agricultura / Disciplinas das Ciˆncias Biol¢gicas / Pesquisa Interdisciplinar Année: 2023 Type: Article Pays d'affiliation: Brésil Institution/Pays d'affiliation: Instituto Federal de Pernambuco/BR / Universidade Federal Rural de Pernambuco/BR / Universidade Federal de Minas Gerais/BR / Universidade Federal do Ceará/BR

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Texte intégral: Disponible Indice: LILAS (Amériques) Sujet Principal: Ensilage / Dynamique non linéaire / Gaz Type d'étude: Étude pronostique langue: Anglais Texte intégral: Biosci. j. (Online) Thème du journal: Agricultura / Disciplinas das Ciˆncias Biol¢gicas / Pesquisa Interdisciplinar Année: 2023 Type: Article Pays d'affiliation: Brésil Institution/Pays d'affiliation: Instituto Federal de Pernambuco/BR / Universidade Federal Rural de Pernambuco/BR / Universidade Federal de Minas Gerais/BR / Universidade Federal do Ceará/BR