Optimizing ruminant nutrition: Insights from a comprehensive analysis of silage composition and in vitro gas production dynamics using nonlinear models

Evaluation of different mathematical models on fitting the in vitro gas production parameters in beef cattle

“…Table 4 revealed that the model with 2 parameters, EXP0, did not exhibit signi cant advantages, ranking 3.51 (3.10) in AIC (BIC) only for the protein feed where other models struggled to t. On the other hand, the 3-parameter MM model ensured model precision with a slight increase in complexity. This nding aligned with previous research results 13,23 . MIT outperformed other models in roughages, indicating that its theoretical assumptions regarding microbial enzyme diffusion and surface erosion are better suited for di cult-to-degrade roughage 14 .…”

“…The MM model exhibited the highest R 2 across all four groups which surpassed all other models signi cantly in the protein feeds and the uncategorized group. This nding aligned with the conclusions drawn by most previous studies 1,20,23,31 . After deriving the formulas, France et al 12 noted that the MM model's assumption regarding gas production rate was the most exible.…”

“…Considering MM's characteristic of decreasing residuals over time, this could be attributed to differences in fermentation time between the study (72h) and the experiments referenced (48h). Additionally, the MIT, LE0, and LEL models also exhibited high R 2 values when tting energy and roughage feedstuffs, consistent with a few prior studies 13,22,23,35,36 . These ndings further underscore the advantage of employing exible and adaptable curve shapes to enhance model accuracy.…”

“…Though previous studies have investigated the comparison of the goodness of t of different models, they may suffer from issues such as small sample sizes and undivided feed categories 1,11,13,[19][20][21][22][23][24] . To address these issues, this study aims to improve the reliability and accuracy of the research by increasing the sample size and categorizing the data according to feedstuff types.…”