Guo Penghui, Gao Peng, Li Fuhou, Chang Shenghua, Wang Zhaofeng, Yan T, Hou Fujiang
State Key Laboratory of Grassland Agro-Ecosystems, Lanzhou University, Lanzhou 730030, China.
College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou 730030, China.
Animals (Basel). 2020 Feb 26;10(3):376. doi: 10.3390/ani10030376.
Due to its extremely harsh environment, including high altitude, hypoxia, long cold season, and strong ultraviolet radiation in the Qinghai-Tibet Plateau (QTP), herbage species and nutritional value of the pasture may differ considerably from elsewhere across the world. The aim of the present study was to develop biologically relevant equations for estimating the metabolizable energy (ME) value of fresh native herbages in the QTP using digestibility variables and chemical concentrations in the herbage offered to Tibetan sheep at the maintenance level. A total of 11 digestibility trials (6 sheep/trial) were performed in different grazing seasons from 2011 to 2016. The herbage was harvested daily in the morning and offered to sheep at the maintenance feeding level. Thirty-seven equations were developed for the prediction of herbage digestible energy (DE) and ME energy values. The mean prediction error for ME was the lowest when using herbage gross energy digestibility as a sole predictor. When using other digestibility variables (e.g., dry matter and organic matter) as primary predictors, addition of herbage nutrient concentration reduced the difference between predicted and actual values. When DE was used as the primary explanatory variable, mean prediction error was reduced with the addition of ash, nitrogen (N), diethyl ether extract (EE), neutral detergent fiber (NDF), and acid detergent fiber (ADF) concentrations. The internal validation of the present equations showed lower prediction errors when compared with those of existing equations for prediction of DE and ME concentrations in the herbage. Equations developed in the current study may thus allow for an improved and accurate prediction of metabolizable energy concentrations of herbage in practice, which is critical for the development of sustainable grazing systems in the QTP.
由于青藏高原环境极其恶劣，包括高海拔、缺氧、漫长的寒冷季节以及强烈的紫外线辐射，该地区牧草的种类和营养价值可能与世界其他地方有很大差异。本研究的目的是利用维持水平下藏羊所采食牧草的消化率变量和化学组成，建立与生物学相关的方程，以估算青藏高原新鲜天然牧草的代谢能（ME）值。2011年至2016年期间，在不同放牧季节共进行了11次消化率试验（每次试验6只羊）。每天早晨收割牧草，并以维持饲养水平提供给绵羊。建立了37个方程用于预测牧草的消化能（DE）和ME能量值。当仅使用牧草总能消化率作为唯一预测因子时，ME的平均预测误差最低。当使用其他消化率变量（如干物质和有机物）作为主要预测因子时，添加牧草养分浓度可减少预测值与实际值之间的差异。当以DE作为主要解释变量时，添加灰分、氮（N）、乙醚提取物（EE）、中性洗涤纤维（NDF）和酸性洗涤纤维（ADF）浓度可降低平均预测误差。与现有用于预测牧草中DE和ME浓度的方程相比，本方程的内部验证显示预测误差更低。因此，本研究建立的方程可能有助于在实践中更准确地预测牧草的代谢能浓度，这对于青藏高原可持续放牧系统的发展至关重要。
