Prediction of ruminal fermentation kinetic of corn silage using some models by in vitro method

In vitro gas production technique (GP) is used for evaluation of ruminal fermentation kinetic of feed stuff. Since structure of GP curve is logarithmic shape, so description of its data is done by fitting them with non-linear models. Some mathematical modelscan be applied for this purpose. The most popular model used in the GP, is exponential model (EXP). But it is reported that some models compared with the EXP model, can predict results of GP more accurately. Thus, the aim of this study was to predict ruminal fermentation kinetic of corn silage using some non-linear models.
In this study, 4 mathematical models, including exponential (EXP), Weibull (WEB), Mitscherlich (MIT) and Richards (RCH) were used to predict ruminal fermentation kinetic of corn silage. Corn silage was sampled at days zero, 20, 40 and 60 after ensiling. Dry matter percentage and chemical composition (OM, CP, ADF and NDF) of samples were determined. GP was done for each sample in four replicates using glass syringes. 200 mg oven dried feed with 30 ml of buffered rumen fluid was poured into a glass syringe and incubated at 39 ° C. The volume of gas produced at zero, 2, 4, 6, 8, 12, 24, 48, 72 and 96 hours after incubation were fitted by the experimental models. Mean square error (MSE), coefficient of determination (R2), relative efficiency (RE), LSD test and Akaike information criterion (AIC) were used as goodness of fit parameters and to select the best model.
Based on the results, MSE values in the EXP model was significantly higher than the other models (P Generally, the results of this study showed that the WEB and RCH models can estimate ruminal fermentation kinetic of corn silage more accurately. Therefore, it can be suggested that the WEB and RCH models can be used for description of GP profile of corn silage instead of the EXP model.