Mixed nonlinear models in ruminal in situ degradability trials

• Autor(a) principal: de Medeiros, Simone Daniela Sartorio
• Data de Publicação: 2020
• Outros Autores: de Lima, César Gonçalves, Savian, Taciana Villela, Malheiros, Euclides Braga [UNESP], Werner, Simone Silmara
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://dx.doi.org/10.1590/1809-6891v21e-57596; http://hdl.handle.net/11449/208217
• topic: Covariance matrix; Dry matter; Longitudinal data; Random effects; Ruminal degradation kinetics

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.