Theme 09: Forage Quality
Description
The in vitro gas production technique was used as a tool to develop an improved prediction model of dry matter digestibility of ensiled forage based diets. Eleven diets were tested through conventional experiments of in vivo dry matter digestibility (DMD). The same diets were evaluated by the in vitro gas production technique using a gas pressure transducer . The parameters of the model y = A - B Qt Z√t were calculated with data from the accumulated gas curves, i.e. y=cumulative gas production (ml), Q=e-b, Z=e-c, B=ebT+c√T , being A the value for gas pool size (ml), plus lag time, minimum lag time, time for 50% gas production and time for 95% gas production. A stepwise linear regression procedure was used to obtain a model with the best fit. The higher adjusted R2 (0.85) was obtained for a model with: 1. accumulated gas, 2. lag time, 3. Q, 4. B, 5. time for 50% gas production and 6. minimum lag time were included in the model.
Citation
Wawrzkiewicz, M.; Danelón, J. L.; and Jaurena, G., "In Vitro Gas Production Technique to Predict DMD of Ensiled Forage Ruminant Based Diets" (2021). IGC Proceedings (1993-2023). 24.
https://uknowledge.uky.edu/igc/19/9/24
Included in
In Vitro Gas Production Technique to Predict DMD of Ensiled Forage Ruminant Based Diets
The in vitro gas production technique was used as a tool to develop an improved prediction model of dry matter digestibility of ensiled forage based diets. Eleven diets were tested through conventional experiments of in vivo dry matter digestibility (DMD). The same diets were evaluated by the in vitro gas production technique using a gas pressure transducer . The parameters of the model y = A - B Qt Z√t were calculated with data from the accumulated gas curves, i.e. y=cumulative gas production (ml), Q=e-b, Z=e-c, B=ebT+c√T , being A the value for gas pool size (ml), plus lag time, minimum lag time, time for 50% gas production and time for 95% gas production. A stepwise linear regression procedure was used to obtain a model with the best fit. The higher adjusted R2 (0.85) was obtained for a model with: 1. accumulated gas, 2. lag time, 3. Q, 4. B, 5. time for 50% gas production and 6. minimum lag time were included in the model.
