肉用绵羊饲料代谢能与代谢蛋白质预测模型的研究
|
摘要
本文以肉用绵羊为试验动物，用体外产气法对用12种不同精粗比日粮建立肉用绵羊饲料代谢能预测模型做可行性分析，采用消化代谢、气体代谢和半体内试验方法较为系统的研究了肉用绵羊能量和蛋白质代谢，建立了代谢能和代谢蛋白质预测模型。具体内容分为以下三部分：
试验一、肉用绵羊饲料有机物体外消化率与代谢能预测模型的建立
采用体外产气法测定12种不同精粗比日粮有机物体外消化率，旨在通过饲料成分建立肉用绵羊饲料有机物体外消化率和代谢能的预测模型。试验采用单因素随机试验设计，分为12个处理，每个处理设3个重复，配制精粗比分别为0:100、8:92、16:84、24:76、32:68、40:60、48:52、56:44、64:36、72:28、80:20和88:12的12种全混合颗粒饲料，测定12种饲料的各项体外发酵参数及有机物体外消化率并计算代谢能，进行饲料有机物体外消化率和代谢能与饲料的饲料成分或体外参数的相关性和回归分析，建立预测模型。结果表明：饲料精粗比显著影响饲料体外24h产气量、潜在产气量、产气速率、发酵液pH、氨态氮浓度以及挥发性脂肪酸比例（P<0.05）。饲料中的粗蛋白质（CP）和中性洗涤纤维（NDF）与有机物体外消化率（IVOMD）相关性极显著（P<0.01），用CP或NDF为变量建立的肉用绵羊饲料IVOMD的预测方程分别为：IVOMD（%）=28.845+2.022CP（%）（R2=0.932，n=12，P<0.001）；IVOMD（%）=88.578-0.734NDF（%）（R2=0.921，n=12，P<0.001）。饲料中的CP、NDF、有机物（OM）以及24h体外产气量（GP24h）与代谢能（MEin vitro）均呈极显著相关（P<0.01），均可作为肉用绵羊饲料代谢能的预测因子，建立的预测方程分别为：代谢能（MEin vitro，MJ/kgDM）=-74.812+0.924OM（%）（R~2=0.849，n=12，P<0.001）；MEin vitro（MJ/kgDM）=3.866+0.285CP（%）（R~2=0.931，n=12，P <0.001）；MEin vitro（MJ/kgDM）=12.293-0.104NDF（%）（R2=0.921，n=12，P <0.001）；MEin vitro（MJ/kgDM）=-2.677+0.241GP_24h（mL/0.2kgDM）（R2=0.885，n=12，P <0.001）。
试验二、肉用绵羊饲料代谢能预测模型的建立
选用安装永久性瘤胃瘘管的杜泊羊（♂）×小尾寒羊（♀）杂交1代肉用公羊12只，采用12×4不完全拉丁方设计，分别饲喂精粗比为0:100、8:92、16:84、24:76、32:68、40:60、48:52、56:44、64:36、72:28、80:20和88:12的12种全混合颗粒饲料，开展消化代谢试验和气体代谢试验，分4期进行，每期22d，预饲期14d，正试期8d。测定日粮养分消化率和有效能值，并进行消化率和有效能与饲料成分含量或可消化营养物质的一元和/或多元线性回归分析，建立肉用绵羊饲料代谢能的预测模型。结果表明：干物质（DM）、有机物（OM）、总能（GE）和粗蛋白质（CP）的消化率与它们在饲料中的含量均呈极显著正相关（P<0.01），而与中性洗涤纤维（NDF）呈极显著负相关（P<0.01）；NDF消化率与饲料中的OM、GE和CP均呈显著负相关（P<0.05），与NDF呈极显著正相关（P<0.01）；消化能（DE）和代谢能（ME）与饲料中的OM、GE和CP的含量均呈极显著正相关（P<0.01），而与NDF呈极显著负相关（P<0.01）。用饲料成分含量预测能量消化率（ED）和代谢能的预测模型分别为：ED（%）=194.907-0.987NDF（%）-0.901OM（%）-0.603CP（%）（R2=0.966，n=12，P<0.001），ME（MJ/kgDM）=50.245-0.136NDF（%）-0.394OM（%）-0.012CP（%）（R2=0.901，n=12，P<0.001）。饲料中可消化营养物质与代谢能之间也存在极显著相关（P<0.01），用可消化营养物质建立的代谢能的预测模型为：ME（MJ/kgDM）=-2.208+0.002DOM（g/kgDM）+0.988DE（g/kgDM）-0.013DP（g/kgDM）（R~2=0.958，n=12，P<0.001），饲料体外参数与代谢能之间同样相关性显著(P<0.01)，利用有机物体外消化率和24h体外产气量建立的代谢能的预测模型为：ME（MJ/kgDM）=3.328-0.078IVOMD（%）+0.259GP24（hmL/0.2kgDM）（R~2=0.901，n=12，P<0.001）。
试验三、肉用绵羊饲料可代谢蛋白质预测模型的建立
选用安装永久性瘤胃瘘管和十二指肠瘘管的杜泊羊（♂）×小尾寒羊（♀）杂交1代肉用公羊12只，采用12×4不完全拉丁方设计，分别饲喂精粗比为0:100、8:92、16:84、24:76、32:68、40:60、48:52、56:44、64:36、72:28、80:20和88:12的12种全混合颗粒饲料，试验分4期进行，每期21d，预饲期14d，正试期7d。采用固相标记物Yb（YbCl3）和液相标记物Co（Co-EDTA）作为双相标记物测定食糜流量和日粮非降解蛋白质，15N标记物测定微生物蛋白质，计算代谢蛋白质，并测定12种不同精粗比饲料的瘤胃发酵参数和24h可发酵有机物。用饲料成分含量、可消化营养物质、24h可发酵有机物为预测因子建立代谢蛋白质的预测模型。结果表明，日粮中精粗比显著影响肉用绵羊瘤胃pH、氨态氮浓度和瘤胃总挥发性脂肪酸含量及比例（P<0.05）。饲料中粗蛋白质或可消化蛋白质与饲料中代谢蛋白质均存在极显著相关（P<0.01），用粗蛋白质或可消化蛋白质建立的代谢蛋白质的预测模型分别为：MP（g/kgDM）=-55.712+9.826CP（%）（R~2=0.986，n=12，P<0.001），MP（g/kgDM）=-9.841+0.983DP（g/kgDM）（R~2=0.999，n=12，P<0.001）。通过尼龙袋法，测定12种饲料的24h可发酵有机物，发现FOM24h与ME或MP之间也存在极显著相关（P<0.01），利用FOM24h作为预测因子建立的模型为：ME（MJ/kgDM）=5.094+0.130FOM24h（g/kgDM）（R~2=0.765，n=12，P<0.001），MP（g/kgDM）=-70.321+4.639FOM_24（hg/kgDM）（R~2=0.858，n=12，P<0.001）。
In these series of research, meat sheep were used as animal models to study the prediction ofmetabolizable energy and metabolizable protein in feeds. The feasibility of the model using twelverations with different concentrate to forage ratio was detected by in vitro gas production experiment.And then prediction equations of metabolizable energy and metabolizable protein were developed by invivo and in situ experiment.The present research consists of three experiments which were listed asfollow.
Experiment1: Prediction of in vitro organic matter digestibility and metabolizable energy in feedsfor meat sheep
The objectives of this experiment were to use the data of chemical composition to developprediction equations for in vitro organic matter digestibility and metabolizable energy of meat sheepfeeds with in vitro gas production technique. Using single-factor random design approach, twelve totalmixed ration with different concentrate to forage ratio,0:100,8:92,16:84,24:76,32:68,40:60,48:52,56:44,64:36,72:28,80:20and88:12were selected and three repetitions were measured by in vitro gasproduction technique for each ration. Chemical composition, in vitro organic matter digestibility and invitro metabolizable energy of each ration were determined and calculated by regression method. Theresults indicated that concentrate to forage ratio of TMR had significant effects on24h gas volume,potential gas production, gas-producing rate and pH, NH3-N VFA of fermentation fluid (P<0.05). Crudeprotein (CP) and neutral detergent fiber (NDF) in feed were significantly related to in vitro organicmatter digestibility (IVOMD)(P<0.01). Prediction equations for IVOMD using CP or NDF wereIVOMD (%)=28.845+2.022CP (%)(R~2=0.932, n=12, P<0.001); IVOMD (%)=88.578-0.734NDF (%)（R~2=0.921, n=12, P<0.001）, respectively. CP, NDF, organic matter (OM) and24h in vitro gasproduction (GP24h) were significantly related to in vitro metabolizable energy (MEin vitro)(P<0.01).Prediction equations for ME using CP, NDF, OM or GP_24hwere MEin vitro(MJ/kgDM)=-74.812+0.924OM (%)(R~2=0.849, n=12, P<0.001); MEin vitro(MJ/kgDM)=3.866+0.285CP (%)(R~2=0.931,n=12, P<0.001); MEin vitro(MJ/kgDM)=12.293-0.104NDF (%)(R~2=0.921, n=12, P<0.001); MEin vitro(MJ/kgDM)=-2.677+0.241GP24h(mL/0.2kgDM)(R~2=0.885, n=12, P <0.001).
Experiment2: Prediction of metabolizable energy in feeds for Meat Sheep
Twelve crossbred rams (Dorper♂×Thin-tailed Han♀) fitted with permanent ruminal cannulas wereused in a uncompleted12×4Latin square arrangement, and fed with twelve different concentrate toforage ratio ration,0:100,8:92,16:84,24:76,32:68,40:60,48:52,56:44,64:36,72:28,80:20and88:12,respectively. Experiment comprised four periods, each period lasted for22d, and the first14d of eachexperiment were for ration adaption, with digestion and metabolism experiments and gas metabolic testduring d15to d22of each period. Chemical composition, nutrient digestibility and energyconcentrations of each ration were determined and calculated by regression method. The results showedthat, digestibility of dry matter (DM), organic matter (OM), gross energy (GE), and crude protein (CP)were positively related to OM, GE and CP (P<0.01), whereas they were negatively related to neutral detergent fiber (NDF)(P<0.01). Digestibility of NDF had an opposite relationship with those variables(P<0.05). There were positive relationship between concentrations of digestible energy (DE) ormetabolizable energy (ME) and feed OM, GE and CP (P<0.01), whereas they were negatively related(P<0.01) to NDF. Prediction equation of energy digestibility (ED) and ME based on chemicalcomposition were ED (%)=194.907-0.987NDF (%)-0.901OM (%)-0.603CP (%)(R~2=0.966, n=12,P<0.001) and ME (MJ/kgDM)=50.245-0.136NDF (%)-0.394OM (%)-0.012CP (%)(R~2=0.901, n=12,P<0.001), respectively. There were significant relationship between digestible nutrient and ME(P<0.01), and the equations developed was ME (MJ/kgDM)=-2.208+0.002DOM (g/kgDM)+0.988DE(g/kgDM)-0.013DP (g/kgDM)(R~2=0.958, n=12, P<0.001).24h in vitro gas production (GP24h) werealso related to ME significantly (P<0.01). Prediction equation for ME using GP24hwas ME (MJ/kgDM)=3.328-0.078IVOMD (%)+0.259GP24h(R~2=0.901, n=12, P<0.001).
Experiment3: Prediction of metabolizable protein in feeds for meat sheep
Twelve crossbred (Dorper♂×Thin-tailed Han♀) rams with permanent cannulas in the rumen andthe proximal duodenum were divided into12groups (4trial periods) according to12×4uncompletedLatin square experiment design, and fed with twelve different concentrate to forage ratio ration,0:100,8:92,16:84,24:76,32:68,40:60,48:52,56:44,64:36,72:28,80:20and88:12, respectively. Experimentcomprised four periods, each period lasted for21d, and the first14d of each experiment were for rationadaption, with sampling during d15to d21of each period. The flow of digesta to the duodenum wasdetermined using Yb and Co as dual-phase markers.15N was used as marker to calculate the bacterial N.Metabolizable protein, rumen fermentation parameters and24h fermentable organic matter weredetermined at present study. Results indicated that concentrate to forage ratio of TMR had significanteffects on ruminal pH, NH3-N and VFA (P<0.05). Metabolizable protein (MP) was significantly relatedto crude protein (CP) or digestible protein (DP)(P<0.01). Prediction equations for MP using CP or DPwere MP (g/kgDM)=-55.712+9.826CP (%)(R~2=0.986, n=12, P<0.001), MP (g/kgDM)=-9.841+0.983DP (g/kgDM)(R~2=0.999, n=12, P<0.001). And24h fermentable organic matter was significantlyrelated to metabolizable energy (ME) or MP (P<0.01), and the equations developed were ME(MJ/kgDM)=5.094+0.130FOM_24h(g/kgDM)(R~2=0.765, n=12, P<0.001), MP (g/kgDM)=-70.321+4.639FOM24h(g/kgDM)(R~2=0.858, n=12, P<0.001).
试验一、肉用绵羊饲料有机物体外消化率与代谢能预测模型的建立
采用体外产气法测定12种不同精粗比日粮有机物体外消化率，旨在通过饲料成分建立肉用绵羊饲料有机物体外消化率和代谢能的预测模型。试验采用单因素随机试验设计，分为12个处理，每个处理设3个重复，配制精粗比分别为0:100、8:92、16:84、24:76、32:68、40:60、48:52、56:44、64:36、72:28、80:20和88:12的12种全混合颗粒饲料，测定12种饲料的各项体外发酵参数及有机物体外消化率并计算代谢能，进行饲料有机物体外消化率和代谢能与饲料的饲料成分或体外参数的相关性和回归分析，建立预测模型。结果表明：饲料精粗比显著影响饲料体外24h产气量、潜在产气量、产气速率、发酵液pH、氨态氮浓度以及挥发性脂肪酸比例（P<0.05）。饲料中的粗蛋白质（CP）和中性洗涤纤维（NDF）与有机物体外消化率（IVOMD）相关性极显著（P<0.01），用CP或NDF为变量建立的肉用绵羊饲料IVOMD的预测方程分别为：IVOMD（%）=28.845+2.022CP（%）（R2=0.932，n=12，P<0.001）；IVOMD（%）=88.578-0.734NDF（%）（R2=0.921，n=12，P<0.001）。饲料中的CP、NDF、有机物（OM）以及24h体外产气量（GP24h）与代谢能（MEin vitro）均呈极显著相关（P<0.01），均可作为肉用绵羊饲料代谢能的预测因子，建立的预测方程分别为：代谢能（MEin vitro，MJ/kgDM）=-74.812+0.924OM（%）（R~2=0.849，n=12，P<0.001）；MEin vitro（MJ/kgDM）=3.866+0.285CP（%）（R~2=0.931，n=12，P <0.001）；MEin vitro（MJ/kgDM）=12.293-0.104NDF（%）（R2=0.921，n=12，P <0.001）；MEin vitro（MJ/kgDM）=-2.677+0.241GP_24h（mL/0.2kgDM）（R2=0.885，n=12，P <0.001）。
试验二、肉用绵羊饲料代谢能预测模型的建立
选用安装永久性瘤胃瘘管的杜泊羊（♂）×小尾寒羊（♀）杂交1代肉用公羊12只，采用12×4不完全拉丁方设计，分别饲喂精粗比为0:100、8:92、16:84、24:76、32:68、40:60、48:52、56:44、64:36、72:28、80:20和88:12的12种全混合颗粒饲料，开展消化代谢试验和气体代谢试验，分4期进行，每期22d，预饲期14d，正试期8d。测定日粮养分消化率和有效能值，并进行消化率和有效能与饲料成分含量或可消化营养物质的一元和/或多元线性回归分析，建立肉用绵羊饲料代谢能的预测模型。结果表明：干物质（DM）、有机物（OM）、总能（GE）和粗蛋白质（CP）的消化率与它们在饲料中的含量均呈极显著正相关（P<0.01），而与中性洗涤纤维（NDF）呈极显著负相关（P<0.01）；NDF消化率与饲料中的OM、GE和CP均呈显著负相关（P<0.05），与NDF呈极显著正相关（P<0.01）；消化能（DE）和代谢能（ME）与饲料中的OM、GE和CP的含量均呈极显著正相关（P<0.01），而与NDF呈极显著负相关（P<0.01）。用饲料成分含量预测能量消化率（ED）和代谢能的预测模型分别为：ED（%）=194.907-0.987NDF（%）-0.901OM（%）-0.603CP（%）（R2=0.966，n=12，P<0.001），ME（MJ/kgDM）=50.245-0.136NDF（%）-0.394OM（%）-0.012CP（%）（R2=0.901，n=12，P<0.001）。饲料中可消化营养物质与代谢能之间也存在极显著相关（P<0.01），用可消化营养物质建立的代谢能的预测模型为：ME（MJ/kgDM）=-2.208+0.002DOM（g/kgDM）+0.988DE（g/kgDM）-0.013DP（g/kgDM）（R~2=0.958，n=12，P<0.001），饲料体外参数与代谢能之间同样相关性显著(P<0.01)，利用有机物体外消化率和24h体外产气量建立的代谢能的预测模型为：ME（MJ/kgDM）=3.328-0.078IVOMD（%）+0.259GP24（hmL/0.2kgDM）（R~2=0.901，n=12，P<0.001）。
试验三、肉用绵羊饲料可代谢蛋白质预测模型的建立
选用安装永久性瘤胃瘘管和十二指肠瘘管的杜泊羊（♂）×小尾寒羊（♀）杂交1代肉用公羊12只，采用12×4不完全拉丁方设计，分别饲喂精粗比为0:100、8:92、16:84、24:76、32:68、40:60、48:52、56:44、64:36、72:28、80:20和88:12的12种全混合颗粒饲料，试验分4期进行，每期21d，预饲期14d，正试期7d。采用固相标记物Yb（YbCl3）和液相标记物Co（Co-EDTA）作为双相标记物测定食糜流量和日粮非降解蛋白质，15N标记物测定微生物蛋白质，计算代谢蛋白质，并测定12种不同精粗比饲料的瘤胃发酵参数和24h可发酵有机物。用饲料成分含量、可消化营养物质、24h可发酵有机物为预测因子建立代谢蛋白质的预测模型。结果表明，日粮中精粗比显著影响肉用绵羊瘤胃pH、氨态氮浓度和瘤胃总挥发性脂肪酸含量及比例（P<0.05）。饲料中粗蛋白质或可消化蛋白质与饲料中代谢蛋白质均存在极显著相关（P<0.01），用粗蛋白质或可消化蛋白质建立的代谢蛋白质的预测模型分别为：MP（g/kgDM）=-55.712+9.826CP（%）（R~2=0.986，n=12，P<0.001），MP（g/kgDM）=-9.841+0.983DP（g/kgDM）（R~2=0.999，n=12，P<0.001）。通过尼龙袋法，测定12种饲料的24h可发酵有机物，发现FOM24h与ME或MP之间也存在极显著相关（P<0.01），利用FOM24h作为预测因子建立的模型为：ME（MJ/kgDM）=5.094+0.130FOM24h（g/kgDM）（R~2=0.765，n=12，P<0.001），MP（g/kgDM）=-70.321+4.639FOM_24（hg/kgDM）（R~2=0.858，n=12，P<0.001）。
In these series of research, meat sheep were used as animal models to study the prediction ofmetabolizable energy and metabolizable protein in feeds. The feasibility of the model using twelverations with different concentrate to forage ratio was detected by in vitro gas production experiment.And then prediction equations of metabolizable energy and metabolizable protein were developed by invivo and in situ experiment.The present research consists of three experiments which were listed asfollow.
Experiment1: Prediction of in vitro organic matter digestibility and metabolizable energy in feedsfor meat sheep
The objectives of this experiment were to use the data of chemical composition to developprediction equations for in vitro organic matter digestibility and metabolizable energy of meat sheepfeeds with in vitro gas production technique. Using single-factor random design approach, twelve totalmixed ration with different concentrate to forage ratio,0:100,8:92,16:84,24:76,32:68,40:60,48:52,56:44,64:36,72:28,80:20and88:12were selected and three repetitions were measured by in vitro gasproduction technique for each ration. Chemical composition, in vitro organic matter digestibility and invitro metabolizable energy of each ration were determined and calculated by regression method. Theresults indicated that concentrate to forage ratio of TMR had significant effects on24h gas volume,potential gas production, gas-producing rate and pH, NH3-N VFA of fermentation fluid (P<0.05). Crudeprotein (CP) and neutral detergent fiber (NDF) in feed were significantly related to in vitro organicmatter digestibility (IVOMD)(P<0.01). Prediction equations for IVOMD using CP or NDF wereIVOMD (%)=28.845+2.022CP (%)(R~2=0.932, n=12, P<0.001); IVOMD (%)=88.578-0.734NDF (%)（R~2=0.921, n=12, P<0.001）, respectively. CP, NDF, organic matter (OM) and24h in vitro gasproduction (GP24h) were significantly related to in vitro metabolizable energy (MEin vitro)(P<0.01).Prediction equations for ME using CP, NDF, OM or GP_24hwere MEin vitro(MJ/kgDM)=-74.812+0.924OM (%)(R~2=0.849, n=12, P<0.001); MEin vitro(MJ/kgDM)=3.866+0.285CP (%)(R~2=0.931,n=12, P<0.001); MEin vitro(MJ/kgDM)=12.293-0.104NDF (%)(R~2=0.921, n=12, P<0.001); MEin vitro(MJ/kgDM)=-2.677+0.241GP24h(mL/0.2kgDM)(R~2=0.885, n=12, P <0.001).
Experiment2: Prediction of metabolizable energy in feeds for Meat Sheep
Twelve crossbred rams (Dorper♂×Thin-tailed Han♀) fitted with permanent ruminal cannulas wereused in a uncompleted12×4Latin square arrangement, and fed with twelve different concentrate toforage ratio ration,0:100,8:92,16:84,24:76,32:68,40:60,48:52,56:44,64:36,72:28,80:20and88:12,respectively. Experiment comprised four periods, each period lasted for22d, and the first14d of eachexperiment were for ration adaption, with digestion and metabolism experiments and gas metabolic testduring d15to d22of each period. Chemical composition, nutrient digestibility and energyconcentrations of each ration were determined and calculated by regression method. The results showedthat, digestibility of dry matter (DM), organic matter (OM), gross energy (GE), and crude protein (CP)were positively related to OM, GE and CP (P<0.01), whereas they were negatively related to neutral detergent fiber (NDF)(P<0.01). Digestibility of NDF had an opposite relationship with those variables(P<0.05). There were positive relationship between concentrations of digestible energy (DE) ormetabolizable energy (ME) and feed OM, GE and CP (P<0.01), whereas they were negatively related(P<0.01) to NDF. Prediction equation of energy digestibility (ED) and ME based on chemicalcomposition were ED (%)=194.907-0.987NDF (%)-0.901OM (%)-0.603CP (%)(R~2=0.966, n=12,P<0.001) and ME (MJ/kgDM)=50.245-0.136NDF (%)-0.394OM (%)-0.012CP (%)(R~2=0.901, n=12,P<0.001), respectively. There were significant relationship between digestible nutrient and ME(P<0.01), and the equations developed was ME (MJ/kgDM)=-2.208+0.002DOM (g/kgDM)+0.988DE(g/kgDM)-0.013DP (g/kgDM)(R~2=0.958, n=12, P<0.001).24h in vitro gas production (GP24h) werealso related to ME significantly (P<0.01). Prediction equation for ME using GP24hwas ME (MJ/kgDM)=3.328-0.078IVOMD (%)+0.259GP24h(R~2=0.901, n=12, P<0.001).
Experiment3: Prediction of metabolizable protein in feeds for meat sheep
Twelve crossbred (Dorper♂×Thin-tailed Han♀) rams with permanent cannulas in the rumen andthe proximal duodenum were divided into12groups (4trial periods) according to12×4uncompletedLatin square experiment design, and fed with twelve different concentrate to forage ratio ration,0:100,8:92,16:84,24:76,32:68,40:60,48:52,56:44,64:36,72:28,80:20and88:12, respectively. Experimentcomprised four periods, each period lasted for21d, and the first14d of each experiment were for rationadaption, with sampling during d15to d21of each period. The flow of digesta to the duodenum wasdetermined using Yb and Co as dual-phase markers.15N was used as marker to calculate the bacterial N.Metabolizable protein, rumen fermentation parameters and24h fermentable organic matter weredetermined at present study. Results indicated that concentrate to forage ratio of TMR had significanteffects on ruminal pH, NH3-N and VFA (P<0.05). Metabolizable protein (MP) was significantly relatedto crude protein (CP) or digestible protein (DP)(P<0.01). Prediction equations for MP using CP or DPwere MP (g/kgDM)=-55.712+9.826CP (%)(R~2=0.986, n=12, P<0.001), MP (g/kgDM)=-9.841+0.983DP (g/kgDM)(R~2=0.999, n=12, P<0.001). And24h fermentable organic matter was significantlyrelated to metabolizable energy (ME) or MP (P<0.01), and the equations developed were ME(MJ/kgDM)=5.094+0.130FOM_24h(g/kgDM)(R~2=0.765, n=12, P<0.001), MP (g/kgDM)=-70.321+4.639FOM24h(g/kgDM)(R~2=0.858, n=12, P<0.001).
引文
1.陈宁.日粮精粗比对断奶初期犊牛瘤胃内环境及粗饲料降解的影响.[硕士学位论文].重庆:西南大学，2006.
2.陈喜斌，冯仰廉.瘤胃VFA产量与瘤胃可发酵有机物质关系的研究.动物营养学报，1996（02）：32-36.
3.陈小连，贾亚红，孙龙生，等.不同中性洗涤纤维与非纤维性碳水化合物比例日粮对山羊瘤胃和血液氮素利用的影响.中国畜牧杂志，2007，43（3）：36-39.
4.邓卫东，席冬梅，等.云南省反刍家畜主要饲料营养价值评价.黄牛杂志，2002，28（1）：23-27.
5.方热军，王康宁，印遇龙.尼龙袋技术评定饲料营养价值研究进展.饲料工业，2003，24（12）：47-52.
6.冯仰廉.反刍动物营养学.北京:科学出版社，2004.
7.冯仰廉.肉牛营养需要和饲养标准.北京:中国农业大学出版社，2000.
8.冯仰廉，陆治年.奶牛营养需要和饲料成分（修订第三版）.北京:中国农业出版社，2007.
9.甘伯中，程胜利，郝正里，等.全饲粮颗粒料对羔羊瘤胃代谢产物浓度变化的影响.中国草食动物，2003，23（4）：10-12.
10.郭旭东.芦丁对奶牛泌乳性能、瘤胃消化代谢和对大鼠乳腺发育的影响.[博士学位论文].北京:中国农业科学院，2011.
11.郭雪峰，李华伟，金海，等.体内法与体外法测定反刍动物日粮的甲烷产生量比较.安徽农业科学，2008，36（12）：4994-4995,4998.
12.韩昊奇，刘大程，民高，等.不同NFC/NDF比对奶山羊瘤胃微生物及瘤胃pH变化的影响.动物营养学报，2011，23（4）：597-603.
13.郝正里，郭天芬，孙玉国，等.采食不同组合全饲粮颗粒料羔羊的瘤胃液代谢参数.甘肃农业大学学报，2002，37（2）：145-152.
14.胡红莲，卢德勋，刘大程，等.日粮不同NFC/NDF比对奶山羊瘤胃pH、挥发性脂肪酸及乳酸含量的影响.动物营养学报，2010，22（3）：595-601.
15.雷冬至，金曙光，乌仁塔娜.用体外产气法评价不同粗饲料与相同精料间的组合效应.饲料工业，2009，30（3）：30-33.
16.李国祥.日粮碳水化合物结构和添加丝兰皂苷对瘤胃发酵及甲烷产生机制的影响.[博士学位论文].扬州:扬州大学，2009.
17.李明元，王康宁.用纤维等饲料成分预测植物性蛋白饲料的猪消化能值.西南农业学报，2000，13（S1）：41-50.
18.李树聪.不同精粗比日粮泌乳奶牛氮素代谢及限制性氨基酸的研究.北京:中国农业科学院，
2005.
19.李元晓，赵广永.反刍动物饲料蛋白质营养价值评定体系研究进展.中国畜牧杂志，2006，42（1）：61-63.
20.刘彩霞.用中性洗涤纤维、酸性洗涤纤维和粗纤维在预测猪饲粮消化能值比较的研究.[硕士学位论文].雅安:四川农业大学，1998.
21.刘大森，单安山.用绵羊尿中嘌呤衍生物估测瘤胃微生物氮的研究.核农学报，2004，18（2）：155-157.
22.刘洁，刁其玉.反刍动物饲料营养价值评定方法的比较.中国畜牧兽医学会养羊学分会全国养羊生产与学术研讨会议.中国宁夏银川:，2010，18-22.
23.刘洁，刁其玉，邓凯东.肉用羊营养需要及研究方法研究进展.中国草食动物，2010（3）：67-70.
24.卢德勋.浅谈羊饲养标准的研究.内蒙古畜牧科学，1989（3）：1-4.
25.马涛，刁其玉，邓凯东.尿嘌呤衍生物法估测瘤胃微生物蛋白质产量.动物营养学报，2011，23（1）：10-14.
26.门小明，雒秋江，唐志高，等.妊娠小尾寒羊对3种不同精粗比日粮的消化与代谢.中国畜牧兽医，2006，33（10）：13-17.
27.莫放.反刍动物营养需要及饲料营养价值评定与应用.北京:中国农业大学出版社，2011.
28.莫放，冯仰廉.用RNA和DNA标记法估测牛瘤胃微生物蛋白质的研究.中国动物营养学报，1991，3（2）：19-25.
29.齐广海.建设饲料工业强国的一大利好——“饲料营养价值与畜禽饲养标准研究与应用”专项启动.饲料与畜牧，2010（1）：1.
30.乔国华，单安山，马宁，等.瘤胃微生物蛋白质合成定量方法研究进展.畜牧与兽医，2008，40（6）：91-94.
31.沈美英.日粮内不同粗饲料品质对绵羊瘤胃发酵功能和微生物区系的影响.[博士学位论文].呼和浩特:内蒙古农业大学，2006.
32.孙德成，赵智力，魏曼琳，等.不同精粗料比全混合日粮对奶牛瘤胃指标的影响.饲料研究，2008（10）：47-50.
33.陶春卫.反刍动物常用粗饲料营养价值评定及其有效能值预测模型的建立.[硕士学位论文].大庆:黑龙江八一农垦大学，2009.
34.汪水平，王文娟，王加启，等.日粮精粗比对奶牛瘤胃发酵及泌乳性能的影响.西北农林科技大学学报(自然科学版)，2007，35（6）：45-50.
35.王海荣，侯先志，王贞贞，等.不同纤维水平日粮对绵羊瘤胃内环境的影响.内蒙古农业大学学报（自然科学版），2008，29（3）：9-14.
36.王虎成，龙瑞军，马亚玲，等.尿嘌呤衍生物估测瘤胃微生物蛋白产量的原理及研究进展.饲料工业，2008，29（1）：47-51.
37.王吉峰，王加启，李树聪，等.不同日粮对奶牛瘤胃发酵模式及泌乳性能的影响.畜牧兽医学报，2005，36（6）：569-573.
38.王菊花，卢德勋，凌书礼，等.体外培养法研究尿素-麻饼型日粮中添加烟酸发酵底物的降解规律.黑龙江畜牧兽医，2010，10：88-90.
39.王立志，宁姜，张爱忠，等.不同精粗比对反刍动物采食行为及饲料利用的影响.现代畜牧兽医，2006，7：20-21.
40.韦升菊，杨纯，邹彩霞，等.应用体外产气法评定广西区内豆腐渣、木薯渣、啤酒糟的营养价值.饲料工业，2011，32（7）：46-48.
41.谢立华.改良拉丁方设计及其在油菜品种试验中的应用.中国油料作物学报，1998，20（4）：38-42.
42.熊本海，庞之洪，罗清尧.饲料数据描述规范及评价进展.北京:中国农业科学技术出版社，
2008.
43.阳伏林，王虎成，郭旭生，等.用尿中嘌呤衍生物估测瘤胃微生物蛋白产量的研究进展.草业学报，2008，17（1）：121-129.
44.杨灿，贺建华.用尼龙袋法评定饲料营养价值的研究进展.饲料博览（技术版），2007（9）：30-33.
45.杨凤.动物营养学.北京:中国农业出版社，2000.
46.杨红建.肉牛和肉用羊饲养标准起草与制定研究.[博士学位论文].北京:中国农业科学院，
2003.
47.杨嘉实，冯仰廉.畜禽能量代谢.北京:中国农业出版社，2004.
48.杨在宾，李风双.小尾寒羊空怀母羊能量维持需要及其代谢规律研究.动物营养学报，1996，8（1）：28-33.
49.杨在宾，李凤双.小尾寒羊泌乳期母羊能量需要量及代谢规律研究.动物营养学报，1997，9（2）：41-48.
50.杨在宾，李凤双.大尾寒羊空怀母羊能量维持需要量及代谢规律研究.山东农业大学学报：自然科学版，1995，26（3）：285-290.
51.杨在宾，杨维仁.大尾寒羊生长期能量需要量及代谢规律研究.山东农业大学学报：自然科学版，1999，30（2）：97-103.
52.袁楷，卢建，顾小卫，等.反刍动物蛋白质小肠消化的研究进展.畜牧兽医科技信息，2008（4）：4-5.
53.张吉鹍，卢德勋，胡明，等.建立各种饲料能量预测模型方法的比较研究.畜牧与饲料科学，2004（03）：7-10.
54.张洁，王洪荣.用体外产气法评价精粗饲料的组合效应.家畜生态学报，2007，28（4）：30-35.
55.张丽英.饲料分析与饲料质量检测技术.北京:中国农业大学出版社，2003.
56.张乃锋，王中华，李福昌，等.非同位素双标记法测定十二指肠、回肠食糜流量方法的研究.畜牧兽医学报，2005，36（3）：225-229.
57.张倩，夏建民，李胜利，等.不同比例压块秸秆与羊草组成粗饲料对奶牛瘤胃发酵和生产性能的影响.动物营养学报，2010，22（2）：474-480.
58.张拴林，黄应祥，杨致玲，等.反刍动物蛋白质评价的新体系.中国饲料，2000（12）：17-18.
59.张欣欣.糠麸糟渣、饼粕类饲料鸭有效能的预测模型研究.[硕士学位论文].雅安:四川农业大学，2004.
60.赵广永，冯仰廉. PEG和CrEDTA作为绵羊瘤胃液相标记物的比较研究.动物营养学报，1997（02）：30-34.
61.赵国琦，贾亚红，陈小莲，等.不同NDF/NFE比的日粮对山羊瘤胃发酵参数影响的研究.中国畜牧杂志，2006，42（13）：29-33.
62.赵一广，刁其玉，邓凯东，等.反刍动物甲烷排放的测定及调控技术研究进展.动物营养学报，2011，23（5）：726-734.
63.邹彩霞，杨炳壮，罗荣太，等.应用体外产气法评定广西区内3种臂形草和2种坚尼草的营养价值.饲料工业，2011，32（19）：45-48.
64. Owens F. N.,Sapienza D. A.,Hassen A. T. Effect of nutrient composition of feeds on digestibilityof organic matter by cattle: a review. Journal Of Animal Science,2010,88（13Suppl）: E151-E169.
65. Abate A. L.,Mayer M. Prediction of the useful energy in tropical feeds from proximate compositionand in vivo derived energetic contents1. Metabolisable energy. Small Ruminant Research,1997,25:51-59.
66. Adesogan A. T.,Owena E.,Givens D. I. Prediction of the in vivo digestibility of whole crop wheatfrom in vitro digestibility, chemical composition,in situ rumen degradability, in vitro gasproduction and near infrared reflectance spectroscopy. Animal Feed Science And Technology,1998,74:259-272.
67. AFRC. Energy and Protein Requirements of Ruminants. Wallingford, UK: CAB International,
1993.
68. Agnew R. E.,Yan T. Impact of recent research on energy feeding systems for dairy cattle.Livestock Production Science,2000,66:197-215.
69. Ahvenjarvi S.,Vanhatalo A.,Shingfield K. J., et al. Determination of digesta flow entering theomasal canal of dairy cows using different marker systems. Br J Nutr,2003,90（1）:41-52.
70. Ammar H.,Lpez S.,Gonzlez J. S., et al. Seasonal variations in the chemical composition and invitro digestibility of some Spanish leguminous shrub species. Animal Feed Science AndTechnology,2004,115（3-4）:327-340.
71. Ankrah P.,Loerch S. C.,Dehority B. A. Occurrence of2-aminoethylphosphonic acid in feeds，ruminal bacteria and duodenal digesta from defaunated sheep. Journal Of Animal Science,1989,67:
1061.
72. Beckman J. L.,Weiss W. P. Nutrient Digestibility of Diets with Different Fiber to Starch Ratioswhen Fed to Lactating Dairy Cows. J. Dairy Sci.,2005,88:1015-1023.
73. Benchaar C.,Rivest J.,Pomar C., et al. Prediction of methane production from dairy cows usingexisting mechanistic models and regression equations. J.Anim.Sci.,1998,76:617-618.
74. Blaxter K. L.,Clapperton J. L. Prediction of the amount of methane produced by ruminants. Br. J.Nutr.,1965,19:511-522.
75.Broderic G. A. Markers for quantifying microbial protein synthesis in the rumen. J.Dairy Sci.,1992,75:2618-2632.
76. Calsamiglia S.,Stern M. D.,Frikins J. L. Comparison of nitrogen-15and purines as microbialmarkers in continous culture. Journal of Animal Sicence,1996,74:1375-1381.
77. Cao Y. C.,Yang H. J. Ruminal digestibility and fermentation characteristics in vitro of fenugreekand alfalfa hay combination with or without the inoculation of Neocallimastix sp. YAK11. AnimalFeed Science And Technology,2011,169（1–2）:53-60.
78. Chen X. B.,Hovell F. D. D.,φrskov E. R., et al. Excretion of purine derivatives by ruminants:Effect of exogenous nucleic acid supply on purine derivative excretion by sheep. British Journal OfNutrition,1990,（63）:131-142.
79. Chowdhury S. Effect of graded levels of wheat bran supplementation On intake, nutrientdigestibility, microbial N yield and growth of native bulls fed rice straw alone.Asian-Aus.Anim.Sci.,1998,11（2）:162-170.
80. Combs D. K.,Satter L. D. Determination of Markers in Digesta and Feces by Direct Current PlasmaEmission Spectroscopy. Journal Of Dairy Science,1992,75（8）:2176-2183.
81. Cone John W.,van Gelder Antonie H.,Bachmann Herwig. Influence of inoculum source on gasproduction profiles. Animal Feed Science And Technology,2002,99（1–4）:221-231.
82. Crutzen P. J. Methane's sinks and sources. Nature,1991,350:380-381.
83. CSIRO. Nutrient Requirements of Domesticated Ruminants. Collingwood, Australia: CSIROPublishing,2007.
84. Dawson J. M.,Bruce C. I.,Buttery P. J., et al. Protein metabolism in the rumen of silage-fedsteers:effect of fishmeal supplementation. Br.J.Nutr.,1988,60:339.
85. Deaville E. R.,Humphries D. J.,Givens D. I. Whole crop cereals:2. Prediction of apparentdigestibility and energy value from in vitro digestion techniques and near infrared reflectancespectroscopy and of chemical composition by near infrared reflectance spectroscopy. Animal FeedScience And Technology,2009,149（1–2）:114-124.
86. Detmann E.,Valadares Filho S. C.,Pina D. S., et al. Prediction of the energy value of cattle dietsbased on the chemical composition of the feeds under tropical conditions. Animal Feed ScienceAnd Technology,2008,143:127-147.
87. Dijkstra J.,Kebreab E.,Bannink A., et al. Application of the gas production technique to feedevaluation systems for ruminants. Animal Feed Science And Technology,2005,123-124（Part1）:561-578.
88. Faichney G. J. The use of markers to partition digestion within the gastro-intestinal tract ofruminants. Digestion and metabolism in ruminants. Armidale, NSW,Univ.of New England,1975,277-291.
89. Firkins J. L.,Lewis S. M.,Montgomery L., et al. Effects of feed intake and dietary ureaconcentration on ruminal dilution rate and efficiency of bacterial growth in steers. Journal Of DairyScience,1987,70:2312-2321.
90. Givens D. I.,Humphries D. J.,Kliem K. E., et al. Whole crop cereals:1. Effect of method ofharvest and preservation on chemical composition, apparent digestibility and energy value. AnimalFeed Science And Technology,2009,149（1–2）:102-113.
91. Gosselink J. M. J.,Dulphy J. P.,Poncet C., et al. A comparison of in situ and in vitro methods toestimate in vivo fermentable organic matter of forages in ruminants. NJAS-Wageningen Journalof Life Sciences,2004,52（1）:29-45.
92. Gosselink J. M. J.,Dulphy J. P.,Poncet C., et al. Prediction of forage digestibility in ruminantsusing in situ and in vitro techniques. Animal Feed Science And Technology,2004,115（3-4）:227-246.
93. Howden S. M.,White D. H.,Mc Keon, et al. Methods for exploring management options to reducegreenhouse gas emissions from tropical grazing systems. Climatic Change,1994,27:49-70.
94. Hristov A. N. Comparative characterization of reticular and duodenal digesta and possibilities ofestimating microbial outflow from the rumen based on reticular sampling in dairy cows. Journal OfAnimal Science,2007,85（10）:2606-2613.
95. Hristov Alexander N.,Ropp Jen K.,Hunt Carl W. Effect of barley and its amylopectin content onruminal fermentation and bacterial utilization of ammonia-N in vitro. Animal Feed Science AndTechnology,2002,99（1-4）:25-36.
96. Huhtanen P.,Kukkonen U. Comparison of methods, markers, sampling sites and models forestimating digesta passage kinetics in cattle fed at two levels of intake. Animal Feed Science AndTechnology,1995,52（1-2）:141-158.
97. Hurly J. J.,Defibaugh D. R.,Moldover M. R. Thermodynamic properties of sulfur hexafluoride.Int.J.Thermophys,2000,（21）:739-765.
98. Iantcheva N.,Steingass H.,Todorov N., et al. A comparison of in vitro rumen fluid and enzymaticmethods to predict digestibility and energy value of grass and alfalfa hay. Animal Feed ScienceAnd Technology,1999,81（3–4）:333-344.
99. INRA. Ruminant Nutrition, Reconmended Allowance and Feed Table. Paris, France: John LibbeyEurotex,1989.
100. Ipharraguerre I. R.,Reynal S. M.,Lieiro M., et al. A Comparison of Sampling Sites, Digesta andMicrobial Markers, and Microbial References for Assessing the Postruminal Supply of Nutrients inDairy Cows. Journal Of Dairy Science,2007,90（4）:1904-1919.
101. Ivan M.,Koenig K. M.,Morgavi D. P., et al. Duodenal flow and digestibility in fauna-free sheepand in sheep monofaunated with Entodinium caudatum or Polyplastron multivesiculatum. Br J Nutr,2006,95（3）:469-476.
102. Johnson Kristen,Mark Huyler,Hal Westberg, et al. Measurement of Methane Emissions fromRuminant Livestock Using a SF6Tracer Technique. Environ. Sci. Technol.,1994,28:359-362.
103. Just A.,J rgensen H.,Fernández J. A. Prediction of metabolizable energy for pigs on the basis ofcrude nutrients in the feeds. Livestock Production Science,1984,11（1）:105-128.
104. Koenig K. M.,Ivan M.,Teferedegne B. T., et al. Effect of dietary Enterolobium cyclocarpum onmicrobial protein flow and nutrient digestibility in sheep maintained fauna-free, with total mixedfauna or with Entodinium caudatum monofauna. Br J Nutr,2007,98（3）:504-516.
105. Koenig K. M.,Newbold C. J.,Mcintosh F. M., et al. Effects of protozoa on bacterial nitrogenrecycling in the rumen. Journal Of Animal Science,2000,78（9）:2431-2445.
106. Krishnamoorthy U.,Soller H.,Steingass H., et al. Energy and protein evaluation of tropicalfeedstuffs for whole tract and ruminal digestion by chemical analyses and rumen inoculum studiesin vitro. Animal Feed Science And Technology,1995,52（3-4）:177-188.
107. Lebzien P.,Voigt J.,Gabel M., et al. Zur Sch tzung der Menge an nutzbarem Rohprotein amDuodenum von Milchkühen. Journal Of Animal Physiology And Animal Nutrition,1996,76:218-223.
108. Lindberg Je. Nitrogen and purine metabolism in prerumainant and ruminant goat kids liverincreasing amounts of ribonucleic acids. Amim.Sci.Tec.,1991,35:3-4,213-226.
109. Liu X.,Wang Z.,Lee F. Influence of concentrate level on dry matter intake, N balance, nutrientdigestibility, ruminal outflow rate, and nutrient degradability in sheep. Small Ruminant Research,2005,58（1）:55-62.
110. Lopez S.,Dijkstra J.,France J. Prediction of energy supply in ruminants, with emphasis on forages.,
2000.
111. Losada B.,García-Rebollar P.,álvarez C., et al. The prediction of apparent metabolisable energycontent of oil seeds and oil seed by-products for poultry from its chemical components, in vitroanalysis or near-infrared reflectance spectroscopy. Animal Feed Science And Technology,2010,160（1–2）:62-72.
112. Lu C. D.,Kawas J. R.,Mahgoub O. G. Fibre digestion and utilization in goats. Small RuminantResearch,2005,60（1–2）:45-52.
113. Luís Orlindo Tedeschi,Danny Gene Fox,Roberto Daniel Sainz, et al. Mathematical models inruminant nutrition. Sci. Agric.,2005,62（1）:76-91.
114. M Islam,H Abe,Y Hayashi, et al. Effects of feeding italian ryegrass with corn on rumenenvironment,nutrient digestibility,methane emission,and energy and nitrogen utilization at twointake levels by goats. Small Ruminant Research,2000,（38）:165-174.
115. Magalhes K. A.,Valadares Filho S. C.,Detmann E., et al. Evaluation of indirect methods toestimate the nutritional value of tropical feeds for ruminants. Animal Feed Science AndTechnology,2010,155（1）:44-54.
116. Mauricio Rogerio M.,Mould Fergus L.,Dhanoa Mewa S., et al. A semi-automated in vitro gasproduction technique for ruminant feedstuff evaluation. Animal Feed Science And Technology,1999,79（4）:321-330.
117. Mcallan A. B. The fate of nucleic acids in ruminants. Proc.Nutr.Soc,1982,41:309-317.
118. Mcdonald P.,Edwards R. A.,Greenhalgh J. F. D., et al. Animal nutrition, Sixth Edition. London:Pearson Education Limited,2002.
119. Menke K. H.,Raab L.,Salewski A., et al. The estimation of the digestibility and metabolizableenergy content of ruminant feedingstuffs from the gas production when they are incubated withrumen liquor in vitro. J. agric. Sci., Camb.,1979,（93）:217-222.
120. Menke K. H.,Steingass H. Estimation of the energetic feed value obtained from chemical analysisand in vitro gas production using rumen fluid. Anim. Res. Dev.,1988,（28）:7-55.
121. Mills J. A. N.,Kebreab E.,Yates C. M., et al. Alternative approaches to predicting methaneemissions from dairy cows. J.Anim.Sci.,2003,81:3141.
122. Moe P. W.,Tyrrell H. F. Methane Production in Dairy Cows. Journal Of Dairy Science,1979,62（10）:1583-1586.
123. Norman H. C.,Revell D. K.,Mayberry D. E., et al. Comparison of in vivo organic matter digestionof native Australian shrubs by sheep to in vitro and in sacco predictions. Small Ruminant Research,2010,91（1）:69-80.
124. Nousiainen J.,Rinne M.,Hell m ki M., et al. Prediction of the digestibility of primary growth andregrowth grass silages from chemical composition, pepsin-cellulase solubility and indigestible cellwall content. Animal Feed Science And Technology,2003,110:61-74.
125. NRC. Nutrient Requirements of Small Ruminants: Sheep, Goats, Cervids and New WorldCamelids. Washington: National Academy Press,2007.
126. Obispo N. E.,Dehority B. A. Feasibility of using total purines as a marker for ruminal bacteria.Journal Of Animal Science,1999,77:3084-3095.
127. Orskov E. R.,Hovell F. D. Deb,Mould F. The use of the nylon bag technique for the evaluation offeedstuffs. Trop Anim Prod,1980,5（3）:195-213.
128. Perez J. F.,Balcells J.,Guada J. A., et al. Rumen microbial production estimated either from urinarypurine derivative excretion or from direct measurements of15N and purine bases as microbialmarkers: effect of protein source and rumen bacteria isolates. Animal Science,1997,65:225-236.
129. Perez J. F.,Balcells J.,Guada J. A., et al. Determination of rumen microbial-nitrogen production insheep: a comparison of urinary purine excretion with methods using15N and purine bases asmarkers of microbial-nitrogen entering the duodenum. Br J Nutr,1996,75（5）:699-709.
130. Peter Uden,Pablo E. Colucci,Peter J. Van Soest. Investigation of Chromium, Cerium and Cobalt asMarkers in Digesta. Rate of Passage Studies. J. Sci. Agric.,1980,（31）:625-632.
131. Pinares-Patino C. S.,Machmuller A.,Molano G., et al. The SF6tracer technique for measurementsof methane emission from cattle-effect of tracer permeation rate. Canadian Journal Of AnimalScience,2008,88（2）:309-320.
132. Rahnema S. H. Comparison of various amino acids for estimation of microbial nitrogen in digesta.J.Anim.Sci.,1986,63:503.
133. Rotger A.,Ferret A.,Calsamiglia S., et al. Changes in ruminal fermentation and protein degradationin growing Holstein heifers from80to250kg fed high-concentrate diets with differentforage-to-concentrate ratios. J Anim Sci.,2005,83（7）:1616-1624.
134. Santini F. J.,Lu C. D.,Potchoiba M. J., et al. Dietary Fiber and Milk Yield, Mastication, Digestion,and Rate of Passage in Goats Fed Alfalfa Hay. Journal Of Dairy Science,1992,75（1）:209-219.
135. Sievert S. J.,Shaver R. D. Effect of Nonfiber Carbohydrate Level and Aspergillus oryzaeFermentation Extract on Intake, Digestion, and Milk Production in Lactating Dairy Cows. J AnimSci.,1993,71（4）:1032-1040.
136. Sutton J. D.,Dhanoa M. S.,Morant S. V., et al. Rates of Production of Acetate, Propionate, andButyrate in the Rumen of Lactating Dairy Cows Given Normal and Low-Roughage Diets. JournalOf Dairy Science,2003,86（11）:3620-3633.
137. Tamminga Seerp. The effect of the supply of rumen degradable protein and metabolisable proteinon negative energy balance and fertility in dairy cows. Animal Reproduction Science,2006,96（3–4）:227-239.
138. Tas B. M.,Susenbeth A. Urinary purine derivates excretion as an indicator of in vivo microbial Nflow in cattle: A review. Livestock Science,2007,111（3）:181-192.
139. Theriez M.,Castrillo C.,Villette Y. Influence of metabolizable energy content of the diet and offeeding level on lamb performances II. Utilization of metabolizable energy for growth andfattening. Livestock Production Science,1982,9（4）:487-500.
140. Tilley J. M. A.,Terry R. A. A two-stage technique for the in vitro digestion of forage crops. GrassAnd Forage Science,1963,18（2）:104-111.
141. Valdes C.,Carro M. D.,Ranilla M. A. J., et al. Effect of forage to concentrate ratio complete dietsoffered to sheep on voluntary food intake and some digestive parameters. Animal Science,2000,70:119-126.
142. Wright A. D. G.,Kennedy P.,O Neill C. J., et al. Reducing methane emissions in sheep byimmunization against rumen methanogens. Vaccine,2004,22（29–30）:3976-3985.
143. Yan T.,Agnew R. E. Prediction of nutritive values in grass silages: I. Nutrient digestibility andenergy concentrations using nutrient compositions and fermentation characteristics. Journal OfAnimal Science,2004,82（5）:1367-1379.
144. Yang W. Z.,Beauchemin K. A.,Rode L. M. Effects of grain processing, forage to concentrate ratio,and forage particle size on rumen pH and digestion by dairy cows. Journal Of Dairy Science,2001,84（10）:2203-2216.
2.陈喜斌，冯仰廉.瘤胃VFA产量与瘤胃可发酵有机物质关系的研究.动物营养学报，1996（02）：32-36.
3.陈小连，贾亚红，孙龙生，等.不同中性洗涤纤维与非纤维性碳水化合物比例日粮对山羊瘤胃和血液氮素利用的影响.中国畜牧杂志，2007，43（3）：36-39.
4.邓卫东，席冬梅，等.云南省反刍家畜主要饲料营养价值评价.黄牛杂志，2002，28（1）：23-27.
5.方热军，王康宁，印遇龙.尼龙袋技术评定饲料营养价值研究进展.饲料工业，2003，24（12）：47-52.
6.冯仰廉.反刍动物营养学.北京:科学出版社，2004.
7.冯仰廉.肉牛营养需要和饲养标准.北京:中国农业大学出版社，2000.
8.冯仰廉，陆治年.奶牛营养需要和饲料成分（修订第三版）.北京:中国农业出版社，2007.
9.甘伯中，程胜利，郝正里，等.全饲粮颗粒料对羔羊瘤胃代谢产物浓度变化的影响.中国草食动物，2003，23（4）：10-12.
10.郭旭东.芦丁对奶牛泌乳性能、瘤胃消化代谢和对大鼠乳腺发育的影响.[博士学位论文].北京:中国农业科学院，2011.
11.郭雪峰，李华伟，金海，等.体内法与体外法测定反刍动物日粮的甲烷产生量比较.安徽农业科学，2008，36（12）：4994-4995,4998.
12.韩昊奇，刘大程，民高，等.不同NFC/NDF比对奶山羊瘤胃微生物及瘤胃pH变化的影响.动物营养学报，2011，23（4）：597-603.
13.郝正里，郭天芬，孙玉国，等.采食不同组合全饲粮颗粒料羔羊的瘤胃液代谢参数.甘肃农业大学学报，2002，37（2）：145-152.
14.胡红莲，卢德勋，刘大程，等.日粮不同NFC/NDF比对奶山羊瘤胃pH、挥发性脂肪酸及乳酸含量的影响.动物营养学报，2010，22（3）：595-601.
15.雷冬至，金曙光，乌仁塔娜.用体外产气法评价不同粗饲料与相同精料间的组合效应.饲料工业，2009，30（3）：30-33.
16.李国祥.日粮碳水化合物结构和添加丝兰皂苷对瘤胃发酵及甲烷产生机制的影响.[博士学位论文].扬州:扬州大学，2009.
17.李明元，王康宁.用纤维等饲料成分预测植物性蛋白饲料的猪消化能值.西南农业学报，2000，13（S1）：41-50.
18.李树聪.不同精粗比日粮泌乳奶牛氮素代谢及限制性氨基酸的研究.北京:中国农业科学院，
2005.
19.李元晓，赵广永.反刍动物饲料蛋白质营养价值评定体系研究进展.中国畜牧杂志，2006，42（1）：61-63.
20.刘彩霞.用中性洗涤纤维、酸性洗涤纤维和粗纤维在预测猪饲粮消化能值比较的研究.[硕士学位论文].雅安:四川农业大学，1998.
21.刘大森，单安山.用绵羊尿中嘌呤衍生物估测瘤胃微生物氮的研究.核农学报，2004，18（2）：155-157.
22.刘洁，刁其玉.反刍动物饲料营养价值评定方法的比较.中国畜牧兽医学会养羊学分会全国养羊生产与学术研讨会议.中国宁夏银川:，2010，18-22.
23.刘洁，刁其玉，邓凯东.肉用羊营养需要及研究方法研究进展.中国草食动物，2010（3）：67-70.
24.卢德勋.浅谈羊饲养标准的研究.内蒙古畜牧科学，1989（3）：1-4.
25.马涛，刁其玉，邓凯东.尿嘌呤衍生物法估测瘤胃微生物蛋白质产量.动物营养学报，2011，23（1）：10-14.
26.门小明，雒秋江，唐志高，等.妊娠小尾寒羊对3种不同精粗比日粮的消化与代谢.中国畜牧兽医，2006，33（10）：13-17.
27.莫放.反刍动物营养需要及饲料营养价值评定与应用.北京:中国农业大学出版社，2011.
28.莫放，冯仰廉.用RNA和DNA标记法估测牛瘤胃微生物蛋白质的研究.中国动物营养学报，1991，3（2）：19-25.
29.齐广海.建设饲料工业强国的一大利好——“饲料营养价值与畜禽饲养标准研究与应用”专项启动.饲料与畜牧，2010（1）：1.
30.乔国华，单安山，马宁，等.瘤胃微生物蛋白质合成定量方法研究进展.畜牧与兽医，2008，40（6）：91-94.
31.沈美英.日粮内不同粗饲料品质对绵羊瘤胃发酵功能和微生物区系的影响.[博士学位论文].呼和浩特:内蒙古农业大学，2006.
32.孙德成，赵智力，魏曼琳，等.不同精粗料比全混合日粮对奶牛瘤胃指标的影响.饲料研究，2008（10）：47-50.
33.陶春卫.反刍动物常用粗饲料营养价值评定及其有效能值预测模型的建立.[硕士学位论文].大庆:黑龙江八一农垦大学，2009.
34.汪水平，王文娟，王加启，等.日粮精粗比对奶牛瘤胃发酵及泌乳性能的影响.西北农林科技大学学报(自然科学版)，2007，35（6）：45-50.
35.王海荣，侯先志，王贞贞，等.不同纤维水平日粮对绵羊瘤胃内环境的影响.内蒙古农业大学学报（自然科学版），2008，29（3）：9-14.
36.王虎成，龙瑞军，马亚玲，等.尿嘌呤衍生物估测瘤胃微生物蛋白产量的原理及研究进展.饲料工业，2008，29（1）：47-51.
37.王吉峰，王加启，李树聪，等.不同日粮对奶牛瘤胃发酵模式及泌乳性能的影响.畜牧兽医学报，2005，36（6）：569-573.
38.王菊花，卢德勋，凌书礼，等.体外培养法研究尿素-麻饼型日粮中添加烟酸发酵底物的降解规律.黑龙江畜牧兽医，2010，10：88-90.
39.王立志，宁姜，张爱忠，等.不同精粗比对反刍动物采食行为及饲料利用的影响.现代畜牧兽医，2006，7：20-21.
40.韦升菊，杨纯，邹彩霞，等.应用体外产气法评定广西区内豆腐渣、木薯渣、啤酒糟的营养价值.饲料工业，2011，32（7）：46-48.
41.谢立华.改良拉丁方设计及其在油菜品种试验中的应用.中国油料作物学报，1998，20（4）：38-42.
42.熊本海，庞之洪，罗清尧.饲料数据描述规范及评价进展.北京:中国农业科学技术出版社，
2008.
43.阳伏林，王虎成，郭旭生，等.用尿中嘌呤衍生物估测瘤胃微生物蛋白产量的研究进展.草业学报，2008，17（1）：121-129.
44.杨灿，贺建华.用尼龙袋法评定饲料营养价值的研究进展.饲料博览（技术版），2007（9）：30-33.
45.杨凤.动物营养学.北京:中国农业出版社，2000.
46.杨红建.肉牛和肉用羊饲养标准起草与制定研究.[博士学位论文].北京:中国农业科学院，
2003.
47.杨嘉实，冯仰廉.畜禽能量代谢.北京:中国农业出版社，2004.
48.杨在宾，李风双.小尾寒羊空怀母羊能量维持需要及其代谢规律研究.动物营养学报，1996，8（1）：28-33.
49.杨在宾，李凤双.小尾寒羊泌乳期母羊能量需要量及代谢规律研究.动物营养学报，1997，9（2）：41-48.
50.杨在宾，李凤双.大尾寒羊空怀母羊能量维持需要量及代谢规律研究.山东农业大学学报：自然科学版，1995，26（3）：285-290.
51.杨在宾，杨维仁.大尾寒羊生长期能量需要量及代谢规律研究.山东农业大学学报：自然科学版，1999，30（2）：97-103.
52.袁楷，卢建，顾小卫，等.反刍动物蛋白质小肠消化的研究进展.畜牧兽医科技信息，2008（4）：4-5.
53.张吉鹍，卢德勋，胡明，等.建立各种饲料能量预测模型方法的比较研究.畜牧与饲料科学，2004（03）：7-10.
54.张洁，王洪荣.用体外产气法评价精粗饲料的组合效应.家畜生态学报，2007，28（4）：30-35.
55.张丽英.饲料分析与饲料质量检测技术.北京:中国农业大学出版社，2003.
56.张乃锋，王中华，李福昌，等.非同位素双标记法测定十二指肠、回肠食糜流量方法的研究.畜牧兽医学报，2005，36（3）：225-229.
57.张倩，夏建民，李胜利，等.不同比例压块秸秆与羊草组成粗饲料对奶牛瘤胃发酵和生产性能的影响.动物营养学报，2010，22（2）：474-480.
58.张拴林，黄应祥，杨致玲，等.反刍动物蛋白质评价的新体系.中国饲料，2000（12）：17-18.
59.张欣欣.糠麸糟渣、饼粕类饲料鸭有效能的预测模型研究.[硕士学位论文].雅安:四川农业大学，2004.
60.赵广永，冯仰廉. PEG和CrEDTA作为绵羊瘤胃液相标记物的比较研究.动物营养学报，1997（02）：30-34.
61.赵国琦，贾亚红，陈小莲，等.不同NDF/NFE比的日粮对山羊瘤胃发酵参数影响的研究.中国畜牧杂志，2006，42（13）：29-33.
62.赵一广，刁其玉，邓凯东，等.反刍动物甲烷排放的测定及调控技术研究进展.动物营养学报，2011，23（5）：726-734.
63.邹彩霞，杨炳壮，罗荣太，等.应用体外产气法评定广西区内3种臂形草和2种坚尼草的营养价值.饲料工业，2011，32（19）：45-48.
64. Owens F. N.,Sapienza D. A.,Hassen A. T. Effect of nutrient composition of feeds on digestibilityof organic matter by cattle: a review. Journal Of Animal Science,2010,88（13Suppl）: E151-E169.
65. Abate A. L.,Mayer M. Prediction of the useful energy in tropical feeds from proximate compositionand in vivo derived energetic contents1. Metabolisable energy. Small Ruminant Research,1997,25:51-59.
66. Adesogan A. T.,Owena E.,Givens D. I. Prediction of the in vivo digestibility of whole crop wheatfrom in vitro digestibility, chemical composition,in situ rumen degradability, in vitro gasproduction and near infrared reflectance spectroscopy. Animal Feed Science And Technology,1998,74:259-272.
67. AFRC. Energy and Protein Requirements of Ruminants. Wallingford, UK: CAB International,
1993.
68. Agnew R. E.,Yan T. Impact of recent research on energy feeding systems for dairy cattle.Livestock Production Science,2000,66:197-215.
69. Ahvenjarvi S.,Vanhatalo A.,Shingfield K. J., et al. Determination of digesta flow entering theomasal canal of dairy cows using different marker systems. Br J Nutr,2003,90（1）:41-52.
70. Ammar H.,Lpez S.,Gonzlez J. S., et al. Seasonal variations in the chemical composition and invitro digestibility of some Spanish leguminous shrub species. Animal Feed Science AndTechnology,2004,115（3-4）:327-340.
71. Ankrah P.,Loerch S. C.,Dehority B. A. Occurrence of2-aminoethylphosphonic acid in feeds，ruminal bacteria and duodenal digesta from defaunated sheep. Journal Of Animal Science,1989,67:
1061.
72. Beckman J. L.,Weiss W. P. Nutrient Digestibility of Diets with Different Fiber to Starch Ratioswhen Fed to Lactating Dairy Cows. J. Dairy Sci.,2005,88:1015-1023.
73. Benchaar C.,Rivest J.,Pomar C., et al. Prediction of methane production from dairy cows usingexisting mechanistic models and regression equations. J.Anim.Sci.,1998,76:617-618.
74. Blaxter K. L.,Clapperton J. L. Prediction of the amount of methane produced by ruminants. Br. J.Nutr.,1965,19:511-522.
75.Broderic G. A. Markers for quantifying microbial protein synthesis in the rumen. J.Dairy Sci.,1992,75:2618-2632.
76. Calsamiglia S.,Stern M. D.,Frikins J. L. Comparison of nitrogen-15and purines as microbialmarkers in continous culture. Journal of Animal Sicence,1996,74:1375-1381.
77. Cao Y. C.,Yang H. J. Ruminal digestibility and fermentation characteristics in vitro of fenugreekand alfalfa hay combination with or without the inoculation of Neocallimastix sp. YAK11. AnimalFeed Science And Technology,2011,169（1–2）:53-60.
78. Chen X. B.,Hovell F. D. D.,φrskov E. R., et al. Excretion of purine derivatives by ruminants:Effect of exogenous nucleic acid supply on purine derivative excretion by sheep. British Journal OfNutrition,1990,（63）:131-142.
79. Chowdhury S. Effect of graded levels of wheat bran supplementation On intake, nutrientdigestibility, microbial N yield and growth of native bulls fed rice straw alone.Asian-Aus.Anim.Sci.,1998,11（2）:162-170.
80. Combs D. K.,Satter L. D. Determination of Markers in Digesta and Feces by Direct Current PlasmaEmission Spectroscopy. Journal Of Dairy Science,1992,75（8）:2176-2183.
81. Cone John W.,van Gelder Antonie H.,Bachmann Herwig. Influence of inoculum source on gasproduction profiles. Animal Feed Science And Technology,2002,99（1–4）:221-231.
82. Crutzen P. J. Methane's sinks and sources. Nature,1991,350:380-381.
83. CSIRO. Nutrient Requirements of Domesticated Ruminants. Collingwood, Australia: CSIROPublishing,2007.
84. Dawson J. M.,Bruce C. I.,Buttery P. J., et al. Protein metabolism in the rumen of silage-fedsteers:effect of fishmeal supplementation. Br.J.Nutr.,1988,60:339.
85. Deaville E. R.,Humphries D. J.,Givens D. I. Whole crop cereals:2. Prediction of apparentdigestibility and energy value from in vitro digestion techniques and near infrared reflectancespectroscopy and of chemical composition by near infrared reflectance spectroscopy. Animal FeedScience And Technology,2009,149（1–2）:114-124.
86. Detmann E.,Valadares Filho S. C.,Pina D. S., et al. Prediction of the energy value of cattle dietsbased on the chemical composition of the feeds under tropical conditions. Animal Feed ScienceAnd Technology,2008,143:127-147.
87. Dijkstra J.,Kebreab E.,Bannink A., et al. Application of the gas production technique to feedevaluation systems for ruminants. Animal Feed Science And Technology,2005,123-124（Part1）:561-578.
88. Faichney G. J. The use of markers to partition digestion within the gastro-intestinal tract ofruminants. Digestion and metabolism in ruminants. Armidale, NSW,Univ.of New England,1975,277-291.
89. Firkins J. L.,Lewis S. M.,Montgomery L., et al. Effects of feed intake and dietary ureaconcentration on ruminal dilution rate and efficiency of bacterial growth in steers. Journal Of DairyScience,1987,70:2312-2321.
90. Givens D. I.,Humphries D. J.,Kliem K. E., et al. Whole crop cereals:1. Effect of method ofharvest and preservation on chemical composition, apparent digestibility and energy value. AnimalFeed Science And Technology,2009,149（1–2）:102-113.
91. Gosselink J. M. J.,Dulphy J. P.,Poncet C., et al. A comparison of in situ and in vitro methods toestimate in vivo fermentable organic matter of forages in ruminants. NJAS-Wageningen Journalof Life Sciences,2004,52（1）:29-45.
92. Gosselink J. M. J.,Dulphy J. P.,Poncet C., et al. Prediction of forage digestibility in ruminantsusing in situ and in vitro techniques. Animal Feed Science And Technology,2004,115（3-4）:227-246.
93. Howden S. M.,White D. H.,Mc Keon, et al. Methods for exploring management options to reducegreenhouse gas emissions from tropical grazing systems. Climatic Change,1994,27:49-70.
94. Hristov A. N. Comparative characterization of reticular and duodenal digesta and possibilities ofestimating microbial outflow from the rumen based on reticular sampling in dairy cows. Journal OfAnimal Science,2007,85（10）:2606-2613.
95. Hristov Alexander N.,Ropp Jen K.,Hunt Carl W. Effect of barley and its amylopectin content onruminal fermentation and bacterial utilization of ammonia-N in vitro. Animal Feed Science AndTechnology,2002,99（1-4）:25-36.
96. Huhtanen P.,Kukkonen U. Comparison of methods, markers, sampling sites and models forestimating digesta passage kinetics in cattle fed at two levels of intake. Animal Feed Science AndTechnology,1995,52（1-2）:141-158.
97. Hurly J. J.,Defibaugh D. R.,Moldover M. R. Thermodynamic properties of sulfur hexafluoride.Int.J.Thermophys,2000,（21）:739-765.
98. Iantcheva N.,Steingass H.,Todorov N., et al. A comparison of in vitro rumen fluid and enzymaticmethods to predict digestibility and energy value of grass and alfalfa hay. Animal Feed ScienceAnd Technology,1999,81（3–4）:333-344.
99. INRA. Ruminant Nutrition, Reconmended Allowance and Feed Table. Paris, France: John LibbeyEurotex,1989.
100. Ipharraguerre I. R.,Reynal S. M.,Lieiro M., et al. A Comparison of Sampling Sites, Digesta andMicrobial Markers, and Microbial References for Assessing the Postruminal Supply of Nutrients inDairy Cows. Journal Of Dairy Science,2007,90（4）:1904-1919.
101. Ivan M.,Koenig K. M.,Morgavi D. P., et al. Duodenal flow and digestibility in fauna-free sheepand in sheep monofaunated with Entodinium caudatum or Polyplastron multivesiculatum. Br J Nutr,2006,95（3）:469-476.
102. Johnson Kristen,Mark Huyler,Hal Westberg, et al. Measurement of Methane Emissions fromRuminant Livestock Using a SF6Tracer Technique. Environ. Sci. Technol.,1994,28:359-362.
103. Just A.,J rgensen H.,Fernández J. A. Prediction of metabolizable energy for pigs on the basis ofcrude nutrients in the feeds. Livestock Production Science,1984,11（1）:105-128.
104. Koenig K. M.,Ivan M.,Teferedegne B. T., et al. Effect of dietary Enterolobium cyclocarpum onmicrobial protein flow and nutrient digestibility in sheep maintained fauna-free, with total mixedfauna or with Entodinium caudatum monofauna. Br J Nutr,2007,98（3）:504-516.
105. Koenig K. M.,Newbold C. J.,Mcintosh F. M., et al. Effects of protozoa on bacterial nitrogenrecycling in the rumen. Journal Of Animal Science,2000,78（9）:2431-2445.
106. Krishnamoorthy U.,Soller H.,Steingass H., et al. Energy and protein evaluation of tropicalfeedstuffs for whole tract and ruminal digestion by chemical analyses and rumen inoculum studiesin vitro. Animal Feed Science And Technology,1995,52（3-4）:177-188.
107. Lebzien P.,Voigt J.,Gabel M., et al. Zur Sch tzung der Menge an nutzbarem Rohprotein amDuodenum von Milchkühen. Journal Of Animal Physiology And Animal Nutrition,1996,76:218-223.
108. Lindberg Je. Nitrogen and purine metabolism in prerumainant and ruminant goat kids liverincreasing amounts of ribonucleic acids. Amim.Sci.Tec.,1991,35:3-4,213-226.
109. Liu X.,Wang Z.,Lee F. Influence of concentrate level on dry matter intake, N balance, nutrientdigestibility, ruminal outflow rate, and nutrient degradability in sheep. Small Ruminant Research,2005,58（1）:55-62.
110. Lopez S.,Dijkstra J.,France J. Prediction of energy supply in ruminants, with emphasis on forages.,
2000.
111. Losada B.,García-Rebollar P.,álvarez C., et al. The prediction of apparent metabolisable energycontent of oil seeds and oil seed by-products for poultry from its chemical components, in vitroanalysis or near-infrared reflectance spectroscopy. Animal Feed Science And Technology,2010,160（1–2）:62-72.
112. Lu C. D.,Kawas J. R.,Mahgoub O. G. Fibre digestion and utilization in goats. Small RuminantResearch,2005,60（1–2）:45-52.
113. Luís Orlindo Tedeschi,Danny Gene Fox,Roberto Daniel Sainz, et al. Mathematical models inruminant nutrition. Sci. Agric.,2005,62（1）:76-91.
114. M Islam,H Abe,Y Hayashi, et al. Effects of feeding italian ryegrass with corn on rumenenvironment,nutrient digestibility,methane emission,and energy and nitrogen utilization at twointake levels by goats. Small Ruminant Research,2000,（38）:165-174.
115. Magalhes K. A.,Valadares Filho S. C.,Detmann E., et al. Evaluation of indirect methods toestimate the nutritional value of tropical feeds for ruminants. Animal Feed Science AndTechnology,2010,155（1）:44-54.
116. Mauricio Rogerio M.,Mould Fergus L.,Dhanoa Mewa S., et al. A semi-automated in vitro gasproduction technique for ruminant feedstuff evaluation. Animal Feed Science And Technology,1999,79（4）:321-330.
117. Mcallan A. B. The fate of nucleic acids in ruminants. Proc.Nutr.Soc,1982,41:309-317.
118. Mcdonald P.,Edwards R. A.,Greenhalgh J. F. D., et al. Animal nutrition, Sixth Edition. London:Pearson Education Limited,2002.
119. Menke K. H.,Raab L.,Salewski A., et al. The estimation of the digestibility and metabolizableenergy content of ruminant feedingstuffs from the gas production when they are incubated withrumen liquor in vitro. J. agric. Sci., Camb.,1979,（93）:217-222.
120. Menke K. H.,Steingass H. Estimation of the energetic feed value obtained from chemical analysisand in vitro gas production using rumen fluid. Anim. Res. Dev.,1988,（28）:7-55.
121. Mills J. A. N.,Kebreab E.,Yates C. M., et al. Alternative approaches to predicting methaneemissions from dairy cows. J.Anim.Sci.,2003,81:3141.
122. Moe P. W.,Tyrrell H. F. Methane Production in Dairy Cows. Journal Of Dairy Science,1979,62（10）:1583-1586.
123. Norman H. C.,Revell D. K.,Mayberry D. E., et al. Comparison of in vivo organic matter digestionof native Australian shrubs by sheep to in vitro and in sacco predictions. Small Ruminant Research,2010,91（1）:69-80.
124. Nousiainen J.,Rinne M.,Hell m ki M., et al. Prediction of the digestibility of primary growth andregrowth grass silages from chemical composition, pepsin-cellulase solubility and indigestible cellwall content. Animal Feed Science And Technology,2003,110:61-74.
125. NRC. Nutrient Requirements of Small Ruminants: Sheep, Goats, Cervids and New WorldCamelids. Washington: National Academy Press,2007.
126. Obispo N. E.,Dehority B. A. Feasibility of using total purines as a marker for ruminal bacteria.Journal Of Animal Science,1999,77:3084-3095.
127. Orskov E. R.,Hovell F. D. Deb,Mould F. The use of the nylon bag technique for the evaluation offeedstuffs. Trop Anim Prod,1980,5（3）:195-213.
128. Perez J. F.,Balcells J.,Guada J. A., et al. Rumen microbial production estimated either from urinarypurine derivative excretion or from direct measurements of15N and purine bases as microbialmarkers: effect of protein source and rumen bacteria isolates. Animal Science,1997,65:225-236.
129. Perez J. F.,Balcells J.,Guada J. A., et al. Determination of rumen microbial-nitrogen production insheep: a comparison of urinary purine excretion with methods using15N and purine bases asmarkers of microbial-nitrogen entering the duodenum. Br J Nutr,1996,75（5）:699-709.
130. Peter Uden,Pablo E. Colucci,Peter J. Van Soest. Investigation of Chromium, Cerium and Cobalt asMarkers in Digesta. Rate of Passage Studies. J. Sci. Agric.,1980,（31）:625-632.
131. Pinares-Patino C. S.,Machmuller A.,Molano G., et al. The SF6tracer technique for measurementsof methane emission from cattle-effect of tracer permeation rate. Canadian Journal Of AnimalScience,2008,88（2）:309-320.
132. Rahnema S. H. Comparison of various amino acids for estimation of microbial nitrogen in digesta.J.Anim.Sci.,1986,63:503.
133. Rotger A.,Ferret A.,Calsamiglia S., et al. Changes in ruminal fermentation and protein degradationin growing Holstein heifers from80to250kg fed high-concentrate diets with differentforage-to-concentrate ratios. J Anim Sci.,2005,83（7）:1616-1624.
134. Santini F. J.,Lu C. D.,Potchoiba M. J., et al. Dietary Fiber and Milk Yield, Mastication, Digestion,and Rate of Passage in Goats Fed Alfalfa Hay. Journal Of Dairy Science,1992,75（1）:209-219.
135. Sievert S. J.,Shaver R. D. Effect of Nonfiber Carbohydrate Level and Aspergillus oryzaeFermentation Extract on Intake, Digestion, and Milk Production in Lactating Dairy Cows. J AnimSci.,1993,71（4）:1032-1040.
136. Sutton J. D.,Dhanoa M. S.,Morant S. V., et al. Rates of Production of Acetate, Propionate, andButyrate in the Rumen of Lactating Dairy Cows Given Normal and Low-Roughage Diets. JournalOf Dairy Science,2003,86（11）:3620-3633.
137. Tamminga Seerp. The effect of the supply of rumen degradable protein and metabolisable proteinon negative energy balance and fertility in dairy cows. Animal Reproduction Science,2006,96（3–4）:227-239.
138. Tas B. M.,Susenbeth A. Urinary purine derivates excretion as an indicator of in vivo microbial Nflow in cattle: A review. Livestock Science,2007,111（3）:181-192.
139. Theriez M.,Castrillo C.,Villette Y. Influence of metabolizable energy content of the diet and offeeding level on lamb performances II. Utilization of metabolizable energy for growth andfattening. Livestock Production Science,1982,9（4）:487-500.
140. Tilley J. M. A.,Terry R. A. A two-stage technique for the in vitro digestion of forage crops. GrassAnd Forage Science,1963,18（2）:104-111.
141. Valdes C.,Carro M. D.,Ranilla M. A. J., et al. Effect of forage to concentrate ratio complete dietsoffered to sheep on voluntary food intake and some digestive parameters. Animal Science,2000,70:119-126.
142. Wright A. D. G.,Kennedy P.,O Neill C. J., et al. Reducing methane emissions in sheep byimmunization against rumen methanogens. Vaccine,2004,22（29–30）:3976-3985.
143. Yan T.,Agnew R. E. Prediction of nutritive values in grass silages: I. Nutrient digestibility andenergy concentrations using nutrient compositions and fermentation characteristics. Journal OfAnimal Science,2004,82（5）:1367-1379.
144. Yang W. Z.,Beauchemin K. A.,Rode L. M. Effects of grain processing, forage to concentrate ratio,and forage particle size on rumen pH and digestion by dairy cows. Journal Of Dairy Science,2001,84（10）:2203-2216.