Abstract #T463

# T463
Predicting ruminal methane inhibition by condensed tannins using nonlinear exponential decay regression analysis.
Harley D. Naumann1, Mozart A. Fonseca*2, Luis O. Tedeschi2, 1University of Missouri, Columbia, MO, 2Texas A&M University, College Station, TX.

Methane (CH4) is a potent greenhouse gas that is normally produced by microbial fermentation in the rumen and released to the environment during the eructation process. Prediction of ruminal CH4 is important for ruminant nutrition, especially for determination of ME intake. Equations have been developed to predict ruminal CH4 production based on dietary constituents, but none have considered condensed tannins (CT). Our objective was to develop an equation to predict ruminal CH4 inhibition by CT. We gathered CH4 production data from 24- to 48-h in vitro fermentation of diverse forages containing different concentrations of CT over the course of 3 years. Our analysis included 113 observations. The predictor variable CT was regressed on the response variable CH4 using PROC NLIN of SAS and the Gauss-Newton method to converge the parameters of the nonlinear regression. We used the following exponential decay model to express the relationship between CT and CH4: Y = span x e(-KxX) + plateau, where Y is CH4, g/kg FOM; span is the difference between Y when CT equals zero and the plateau (Y value at infinite), g/kg FOM; K is the fractional rate of decline, 1/% DM; and X is CT concentration, % DM. The following nonlinear exponential decay regression equation was developed: CH4 = 113.6 x e-0.1751xCT- 2.18 (r2 = 0.52; P < 0.0001). This equation predicted that CH4 production could be reduced by 50% when CT is about 3.85% DM. We used several statistics to evaluate the adequacy of this equation, including precision and accuracy. We determined that this equation is more accurate when screening CT-containing forages for their potential ability to mitigate CH4 production by ruminants when the CT concentration is greater than 5% DM. We concluded that despite the large degree of variability in ruminal CH4 production, this equation can be used as a tool for predicting potential ruminal CH4 inhibition that occurs when feeding CT-containing forages to ruminants. Future research should focus on the development of predictive equations when other potential reducers of ruminal CH4 are used in conjunction with CT.

Key Words: forage, greenhouse gas, modeling