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Adjustment of ruminal degradability models applying the technique of gas production by using classical and Bayesian methodologies Given the national agricultural power and knowing that grazing plays an important role in animal nutrition, it becomes primordial to study the mechanisms of ruminal digestion of forages, for a more rational use of pastures by the animals, providing an optimal rumen fermentation and allowing a more adequate and balanced feed. This approach is possible by using the rumen degradation models, which are classified as non-linear regression models. This essay discusses the classical and Bayesian methods to adjust the models that describe the kinetics of degradation by rumen gas production technique. In the classical approach, the “Non Sigmoidal models”, proposed by Orskov& McDonald (1979), the “Logistic”, proposed by Schofield (1994), and “Gompertz”, proposed by Lavrencic (1997), were considered, taking into account the need for autoregressive factors of first and second order, by the “likelihood ratio test ” (TRV). These models were evaluated using the Akaike criteria (AIC), the coefficient of determination adjusted (R2aj) and “the residual average square” (QMR). In the following stage, the adjustment of the non sigmoidal model without the autoregressive factor were performed, using the Bayesian approach. For these matters, the condition of the convergence of chains was analyzed using Geweke (1992), Heidelberger & Welch (1993), Raftery& Lewis (1992) and Monte Carlo error(EMC) criteria.Among the models used, the one that best settle to the data analyzed was the non sigmoidal model without the autoregressive factor, proposed by Orskov and McDonald (1979), obtaining consistent estimates with the reality of the phenomenon. The results obtained through the Bayesian approach were also satisfactory, showing that the technique, although less diffused in studies of rumen methodology, is very viable and has a lot to add in these area studies.

Ajuste de modelos de degradabilidade ruminal por meio da técnica de produção de gases utilizando as metodologias clássica e bayesiana