The accurate estimation
of in vitro ruminal biohydrogenation (BH)
kinetics of fatty acids (FA) allows for a more accurate understanding
of their dynamics and develop targeted strategies to enhance desirable
FA bypass. This study comprises a comprehensive evaluation of 33 nonlinear
regression models to determine the most suitable model for accurately
estimating the in vitro BH kinetics of individual FA. The data set
utilized in the present research originates from a recent investigation
on the effects of micronization and vitamin E on the in vitro ruminal
BH of rapeseed. For the nonlinear regression analysis, data comprising
FA concentrations (expressed as g FA/100 g FA) at the conclusion of
2, 4, 8, 12, 24, and 48 h incubation periods were employed. The evaluation
of nonlinear regression models focused on identifying the ideal model
based on criteria including the highest
R
2
value, the lowest RMSE value, and statistically significant coefficients.
The results pinpoint the Gompertz model as an effective choice for
estimating the in vitro ruminal BH kinetics of upward-trending fatty
acids, including intermediate unsaturated fatty acids and saturated
end FA. Additionally, the first-order kinetic model of Ørskov
and McDonald emerges as the preferred model for investigating the
BH kinetics of downward-trending fatty acids, including oleic acid,
linoleic acid, and alpha-linolenic acid. In summary, this rigorous
evaluation led to the identification of the most appropriate model,
one that not only exhibited an exceptional fit to the data but also
provided profound insights into the intricate relationships between
predictors and the dynamic behavior of FA. The established nonlinear
regression models will serve as invaluable tools for future research
investigating FA biohydrogenation kinetics.