摘要

Universally applicable empirical equations specific for high-and low-forage diets were developed to improve the prediction of enteric methane production (eCH(4)) from beef cattle. A database built using treatment means from published beef studies conducted in numerous countries was divided into two datasets: high-forage diet [>= 40% forage dry matter (DM), n = 123] and low-forage diet (<= 20% forage DM, n = 34). Monte-Carlo techniques were used to overcome the limited numbers of observations in each dataset, and multiple regression analysis and cross validation were used to develop new eCH4 prediction equations. Precision, accuracy, and analysis of errors were evaluated using concordance correlation (r(c)) and root mean square prediction error (RMSPE). The best-fit equations for high and low forage content included the following variables: body weight (kg) and intakes (kg d(-1)) of DM, fat, neutral detergent fiber (NDF), acid detergent fiber, crude protein to NDF ratio, and starch to NDF ratio. For high and low forages, best-fit equations had r(c) = 0.70 and RMSPE <= 40 g eCH(4) d(-1) and r(c) >= 0.90 and RMSPE = 15 g eCH(4) d(-1), respectively. Use of equations specific to dietary forage proportion reduced the uncertainty of estimating beef cattle eCH(4) emission compared with the Intergovernmental Panel on Climate Change Tier 2 methodology.

  • 出版日期2017-3

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