Abstract
This study aimed at examining the effects of rumen inoculum of steers receiving different combinations of ionophore and probiotics in their diets on in vitro gas production of corn silage. The fitting of gas production was performed with five mathematical models and its kinetics was evaluated. Four crossbred steers (403.0 ± 75.5 kg body weight) with ruminal cannula were assigned to a 4 × 4 Latin square design. The additives used were Monensin sodium (Rumensin® 100, 3 g/day), Bacillus toyonensis (Micro-Cell Platinum® 109, 1 g/day) and Saccharomyces cerevisiae boulardii (ProTernative®20, 0.5 g/day). Additives were arranged into the following treatments, supplied daily into total mixed diet: (1) Monensin; (2) Monensin + B. toyonensis; (3) Monensin + S. boulardii; and (4) B. toyonensis + S. boulardii. The gas production data were fitted into the models of Gompertz, Groot, Ørskov, Brody, Richards, and Dual-pool Logistic. A perfect agreement between observed and predicted values in curves of accumulated in vitro gas production was observed in the Groot and Richards models, with higher coefficient of determination (R2 = 0.770 and 0.771, respectively), concordance correlation coefficient (CCC = 0.871 and 0.870, respectively), and root mean square error of prediction (RMSEP = 1.14 and 1.15, respectively). Evaluating the feed additives throughout the Groot model, the B. toyonensis + S. boulardii treatment presented higher VF (12.08 mL/100 mg of DM; p = 0.0022) than Monensin and Monensin + S. boulardii (9.16 and 9.22 mL/100 mg of DM, respectively). In addition, the fractional rate of gas production (k) was higher (p = 0.0193) in B. toyonensis + S. boulardii than in Monensin, not presenting a statistical difference (p > 0.05) from the other two treatments. Additionally, with the time of beginning to gas production, the lag time (λ), was greater (p < 0.001) with Monensin and Monensin + B. toyonensis than with Monensin + S. boulardii and B. toyonensis + S. boulardii. The combination of Monensin and probiotics (B. toyonensis + S. boulardii) resulted in better kinetics of degradation of corn silage, being that the Groot and Richards models had the best fit for estimates of the in vitro gas production data of corn silage tested with different feed additive combinations.
Highlights
Over the years, several mathematical models have been developed to describe biological phenomena
Due to probiotics being related to improvements in high fiber diets, and the corn silage being considered the most common food used as roughage by dairy cows and feedlot cattle [23,28,29], we studied the effects of different combinations of ionophore and probiotics in steer diets on the kinetics of in vitro gas production of corn silage
This study aimed to evaluate the kinetics of in vitro gas production and fit mathematical models of corn silage, using rumen liquid of steers fed different combinations of ionophore and probiotics
Summary
Several mathematical models have been developed to describe biological phenomena. Fermentation 2021, 7, 298 humans [4] was considered one of the most used models to describe growth of animals, embryos, plants, tumors and populations of organisms [5] From these proposed models, it was necessary to expand and elucidate new analysis techniques, through the development of new specific models, such as the models that explain the kinetics of in vitro gas production in research with ruminants [6,7,8]. It was necessary to expand and elucidate new analysis techniques, through the development of new specific models, such as the models that explain the kinetics of in vitro gas production in research with ruminants [6,7,8] This variety of mathematical models is still used to fit in vitro gas production of cattle feeds, additives or diverse conditions due to that its complexity of biological factors fit perfectly in one single model for posterior statistical analysis of the studied treatments. It should be noted that a single model should not be used for all types of feed; rather, it is essential that different models be adjusted for each nutritional situation [14]
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