Mixed nonlinear models in ruminal in situ degradability trials

Abstract Classical methods of analysis of nonlinear models are widely used in studies of ruminal degradation kinetics. As this type of study involves repeated measurements in the same experimental unit, the use of mixed nonlinear models (MNLM) is proposed, in order to solve problems of heterogeneity of variances of the responses, correlation among repeated measurements and consequent lack of sphericity in the covariance matrix. The aims of this work are to present an evaluation of the applicability of MNLM in the estimation of parameters to describe the in situ ruminal degradation kinetics of the dry matter of Tifton 85 hay and to compare the results with those obtained from the usual analysis in two-phases. The steers used in the trial were fed diets composed of three different combinations of roughage and concentrate and two hays with different nutritional qualities. The proposed approach was proven as effective as the traditional one for estimating model parameters. However, it adequately models the correlation among the longitudinal data, which can affect the estimates obtained, the standard error associated with them and potentially change the results of the inferences. It is quite attractive when the research seeks to understand the behavior of the process of food degradation throughout the incubation times.

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Main Authors: Medeiros,Simone Daniela Sartorio de, Lima,César Gonçalves de, Savian,Taciana Villela, Malheiros,Euclides Braga, Werner,Simone Silmara
Format: Digital revista
Language:English
Published: Universidade Federal de Goiás 2020
Online Access:http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1809-68912020000100216
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spelling oai:scielo:S1809-689120200001002162020-08-17Mixed nonlinear models in ruminal in situ degradability trialsMedeiros,Simone Daniela Sartorio deLima,César Gonçalves deSavian,Taciana VillelaMalheiros,Euclides BragaWerner,Simone Silmara Ruminal degradation kinetics Longitudinal data Covariance matrix Random effects Dry matter Abstract Classical methods of analysis of nonlinear models are widely used in studies of ruminal degradation kinetics. As this type of study involves repeated measurements in the same experimental unit, the use of mixed nonlinear models (MNLM) is proposed, in order to solve problems of heterogeneity of variances of the responses, correlation among repeated measurements and consequent lack of sphericity in the covariance matrix. The aims of this work are to present an evaluation of the applicability of MNLM in the estimation of parameters to describe the in situ ruminal degradation kinetics of the dry matter of Tifton 85 hay and to compare the results with those obtained from the usual analysis in two-phases. The steers used in the trial were fed diets composed of three different combinations of roughage and concentrate and two hays with different nutritional qualities. The proposed approach was proven as effective as the traditional one for estimating model parameters. However, it adequately models the correlation among the longitudinal data, which can affect the estimates obtained, the standard error associated with them and potentially change the results of the inferences. It is quite attractive when the research seeks to understand the behavior of the process of food degradation throughout the incubation times.info:eu-repo/semantics/openAccessUniversidade Federal de GoiásCiência Animal Brasileira v.21 20202020-01-01info:eu-repo/semantics/articletext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1809-68912020000100216en10.1590/1809-6891v21e-57596
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countrycode BR
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region America del Sur
libraryname SciELO
language English
format Digital
author Medeiros,Simone Daniela Sartorio de
Lima,César Gonçalves de
Savian,Taciana Villela
Malheiros,Euclides Braga
Werner,Simone Silmara
spellingShingle Medeiros,Simone Daniela Sartorio de
Lima,César Gonçalves de
Savian,Taciana Villela
Malheiros,Euclides Braga
Werner,Simone Silmara
Mixed nonlinear models in ruminal in situ degradability trials
author_facet Medeiros,Simone Daniela Sartorio de
Lima,César Gonçalves de
Savian,Taciana Villela
Malheiros,Euclides Braga
Werner,Simone Silmara
author_sort Medeiros,Simone Daniela Sartorio de
title Mixed nonlinear models in ruminal in situ degradability trials
title_short Mixed nonlinear models in ruminal in situ degradability trials
title_full Mixed nonlinear models in ruminal in situ degradability trials
title_fullStr Mixed nonlinear models in ruminal in situ degradability trials
title_full_unstemmed Mixed nonlinear models in ruminal in situ degradability trials
title_sort mixed nonlinear models in ruminal in situ degradability trials
description Abstract Classical methods of analysis of nonlinear models are widely used in studies of ruminal degradation kinetics. As this type of study involves repeated measurements in the same experimental unit, the use of mixed nonlinear models (MNLM) is proposed, in order to solve problems of heterogeneity of variances of the responses, correlation among repeated measurements and consequent lack of sphericity in the covariance matrix. The aims of this work are to present an evaluation of the applicability of MNLM in the estimation of parameters to describe the in situ ruminal degradation kinetics of the dry matter of Tifton 85 hay and to compare the results with those obtained from the usual analysis in two-phases. The steers used in the trial were fed diets composed of three different combinations of roughage and concentrate and two hays with different nutritional qualities. The proposed approach was proven as effective as the traditional one for estimating model parameters. However, it adequately models the correlation among the longitudinal data, which can affect the estimates obtained, the standard error associated with them and potentially change the results of the inferences. It is quite attractive when the research seeks to understand the behavior of the process of food degradation throughout the incubation times.
publisher Universidade Federal de Goiás
publishDate 2020
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1809-68912020000100216
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