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

Achieving sustainable livestock management necessitates optimizing animal production while minimizing environmental impact. To achieve this, feed efficiency must be enhanced, and nutrition blueprints must be understood. In ruminant nutrition, this is of paramount importance, as it exposes degradation kinetics and nutritional benchmarks, allowing feed management and formulations to be more ecologically balanced. Previous research efforts have focused on exploring the relationship between a restricted set of nutrient parameters and the in vitro gas production dynamics. In the current study, an extensive dataset derived from freeze-dried kefir culture treated white clover silage was used to examine intricate relationships between eight nonlinear models and diverse variables. This dataset contains in vitro gas production data along with nutritional composition, microbial populations, fermentation quality, digestibility, mineral concentration, and fatty acid profiles. Through rigorous application of mathematical models, the performance in capturing gas production dynamics was critically assessed. Among these, the Michaelis‒Menten (MM) and Mitscherlich (MIT) models fit the data well and offer superior predictions of gas production dynamics. Asymptotic gas volume was negatively correlated with crude protein content, emphasizing the influence of protein on gas production. Fiber composition plays a significant role in fermentation kinetics, as evidenced by significant correlations between degradation rate constant and crude protein concentrations. The degradation rate constant of insoluble fraction exhibited significant positive correlations with crude protein and neutral detergent fiber contents. Moreover, mineral content had significant effects on gas production dynamics. Zinc content showed a strong and significant positive correlation with the gas production rate coefficient, underscoring its crucial role in enhancing microbial activity. Conversely, calcium content displayed a significant but weak negative correlation with the final asymptotic gas volume, indicating its potential to modulate gas production. In summury, this study provides detailed insights into the intricate relationship between mathematical models and various variables in rumen fermentation. The MM and MIT models have proven to be robust tools, offering nuanced perspectives on gas production dynamics. These findings pave the path for improving sustainable ruminant nutritional practices and ref