Reliable predictions of metabolizable energy (ME) from digestible energy (DE) are necessary to prescribe nutrient requirements of beef cattle accurately. A previously developed database that included 87 treatment means from 23 respiration calorimetry studies has been updated to evaluate the efficiency of converting DE to ME by adding 47 treatment means from 11 additional studies. Diets were fed to growing-finishing cattle under individual feeding conditions. A citation-adjusted linear regression equation was developed where dietary ME concentration (Mcal/kg of dry matter [DM]) was the dependent variable and dietary DE concentration (Mcal/kg) was the independent variable: ME = 1.0001 × DE – 0.3926; r2 = 0.99, root mean square prediction error [RMSPE] = 0.04, and P < 0.01 for the intercept and slope. The slope did not differ from unity (95% CI = 0.936 to 1.065); therefore, the intercept (95% CI = −0.567 to −0.218) defines the value of ME predicted from DE. For practical use, we recommend ME = DE – 0.39. Based on the relationship between DE and ME, we calculated the citation-adjusted loss of methane, which yielded a value of 0.2433 Mcal/kg of dry matter intake (DMI; SE = 0.0134). This value was also adjusted for the effects of DMI above maintenance, yielding a citation-adjusted relationship: CH4, Mcal/kg = 0.3344 – 0.05639 × multiple of maintenance; r2 = 0.536, RMSPE = 0.0245, and P < 0.01 for the intercept and slope. Both the 0.2433 value and the result of the intake-adjusted equation can be multiplied by DMI to yield an estimate of methane production. These two approaches were evaluated using a second, independent database comprising 129 data points from 29 published studies. Four equations in the literature that used DMI or intake energy to predict methane production also were evaluated with the second database. The mean bias was substantially greater for the two new equations, but slope bias was substantially less than noted for the other DMI-based equations. Our results suggest that ME for growing and finishing cattle can be predicted from DE across a wide range of diets, cattle types, and intake levels by simply subtracting a constant from DE. Mean bias associated with our two new methane emission equations suggests that further research is needed to determine whether coefficients to predict methane from DMI could be developed for specific diet types, levels of DMI relative to body weight, or other variables that affect the emission of methane.

中文翻译：

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从可消化能量中预测用于肉牛生长和育成的可代谢能量及其与甲烷预测的关系

从消化能 (DE) 中可靠地预测代谢能 (ME) 是准确规定肉牛营养需求的必要条件。先前开发的数据库已更新，其中包括来自 23 项呼吸量热研究的 87 种治疗方法，通过添加来自 11 项其他研究的 47 种治疗方法来评估将 DE 转换为 ME 的效率。在个体喂养条件下将日粮喂给生长育肥牛。建立了一个引用调整的线性回归方程，其中膳食 ME 浓度（Mcal/kg 干物质 [DM]）是因变量，膳食 DE 浓度（Mcal/kg）是自变量：ME = 1.0001 × DE – 0.3926；r2 = 0.99，均方根预测误差[RMSPE] = 0.04，P＜0.01 为截距和斜率。斜率与统一没有差异（95% CI = 0.936 至 1.065）；因此，截距（95% CI = -0.567 到 -0.218）定义了从 DE 预测的 ME 值。对于实际使用，我们建议 ME = DE – 0.39。基于 DE 和 ME 之间的关系，我们计算了经引文调整的甲烷损失，得出的值为 0.2433 Mcal/kg 干物质摄入量（DMI；SE = 0.0134）。该值还针对 DMI 高于维持的影响进行了调整，产生了引用调整关系：CH4，Mcal/kg = 0.3344 – 0.05639 × 维持倍数；r2 = 0.536，RMSPE = 0.0245，P＜0.01 为截距和斜率。0.2433 值和摄入量调整方程的结果都可以乘以 DMI 以得出甲烷产量的估计值。使用第二个评估这两种方法，独立数据库，包含来自 29 项已发表研究的 129 个数据点。文献中使用 DMI 或摄入能量来预测甲烷产量的四个方程也用第二个数据库进行了评估。两个新方程的平均偏差明显更大，但斜率偏差明显小于其他基于 DMI 的方程。我们的结果表明，通过简单地从 DE 中减去一个常数，可以从广泛的饮食、牛类型和摄入水平的 DE 预测生长和育肥牛的 ME。与我们的两个新的甲烷排放方程相关的平均偏差表明，需要进一步研究以确定是否可以针对特定饮食类型、DMI 相对于体重的水平、DMI 预测甲烷的系数，