【作者】 刘德稳；

【导师】 王凤来；

【作者基本信息】 中国农业大学 ， 动物营养与饲料科学， 2014， 博士

【摘要】 本研究选用72头杜x长×大三元杂交健康去势公猪,借助猪开放式呼吸测热装置,通过5个能量代谢试验,评价生长猪常用7种饲料原料净能(Net energy,NE)并构建其净能预测方程。试验一研究绝食法和回归法对测定生长猪绝食产热量(Fasting heat production,FHP)的影响。试验选用体重为43±1.4kg的去势公猪6头,饲喂同一饲粮,采用随机区组设计。试验期为20d,其中预试期7d,正式期13d,正式期的前5d饲喂水平为2600kJ ME/kg Bw0.6·d-1,第6-8d饲喂水平为2倍维持代谢能(Metabolizable energy for maintenance,MEm)即2×893kJ ME/kg BW0.6·d-1,第9-11d饲喂水平为1倍维持代谢能水平即893kJ ME/kg BW0.6·d-1,最后2d绝食。结果表明,通过三个饲喂水平线性回归测得生长猪绝食产热量为694kJ/kg BW0.6·d-1(FHP=694+0.27MEintake,R2=0.85:MEintake为绝食前采食量),利用绝食法测得生长猪绝食产热量(774kJ/kg BW0.6·d-1)高于回归法测得数据。试验二研究直接法与替代法对生长猪玉米净能测定的影响。试验选用体重为34±1.1kg的去势公猪18头,随机平均分为3个饲粮处理,即玉米饲粮组,基础饲粮组和试验饲粮组,每个饲粮处理6头猪,分为3批(期)。试验每期15d,包括7d预试期,8d呼吸测热室内的正式期。正式期前5d饲喂水平2400kJ ME/kg BW0.6·d-1,第6-7d饲喂1倍维持代谢能水平948kJ ME/kg BW0.6·d-1,最后1d绝食。结果表明：利用直接法和替代法测得玉米消化能(Digestible energy,DE).代谢能(Metabolizable energy,ME)和NE分别为16.65与16.42、16.31与16.15和13.21与13.69MJ/kg DM,代谢能用于净能的效率(K)分别为80.99%与84.77%,两种方法测得数据差异均不显著(P>0.05)。试验三研究不同基础饲粮对生长猪豆粕净能测定的影响。试验选用体重为36±1.4kg的去势公猪24头,随机平均分为4个饲粮处理,其中饲粮1为玉米型基础饲粮,饲粮2和3分别是两种不同替代比例的豆粕试验饲粮；饲粮4是以玉米-豆粕型饲粮(饲粮3)为基础饲粮的豆粕试验饲粮。试验共分为4批(期),每期的试验时间同试验二。结果表明,不同基础饲粮及同种基础饲粮不同替代比例对测定豆粕的DE、ME、 NE以及能量转化效率间差异均不显著。试验四以玉米-豆粕型基础饲粮,利用替代法分别测定生长猪麦麸、小麦、玉米酒精糟及其可溶物(Dried distillers grains with solubles,DDGS)、菜籽粕和棉籽粕净能值,并通过原料净能值与其营养成分间逐步回归建立净能预测方程。试验选用体重为27±0.5kg的去势公猪12头,采用6×3双尤丁方试验设计,即12头猪分为2组,每组6头猪,平均分到6种试验饲粮处理,即1个基础饲粮和5个不同饲料原料替代基础饲粮后的试验饲粮,每种饲粮处理6头猪,分6期交替进行,每期试验时间同试验二。结果表明,麦麸、小麦、DDGS、菜籽粕和棉籽粕净能分别为7.78、11.44、10.21、8.38和7.32MJ/kg DM,通过试验二(玉米)、试验三(豆粕)和试验四的5种饲料原料净能值与其化学组分进行逐步回归分析,得出7种原料净能预测方程为NE=1.46+0.63GE-0.37ADF(R2=0.94,RSD:0.54)。试验五设计6种不同营养结构的混合饲粮,分别测定其净能值,并结合前4个试验的试验饲粮,通过对饲粮净能值与其化学组分进行逐步回归分析,建立饲料原料净能最优预测方程。试验选用体重为35±1.5kg的去势公猪12头,试验设计同试验四。结果表明,分别以本试验6种饲粮和本研究前4个试验10种饲料合计16种饲粮为基础,通过饲粮净能值与其化学组分进行逐步回归分析,建立的饲料原料净能预测方程为NE=-10.19+0.97DE+0.08St+0.55ADF(R2=0.84,RSD=0.46)。更多还原

【Abstract】 A total of72crossbred barrows (Duroc×Large White×Landrace) were used to determine the net energy (NE) value and establish the NE prediction equations of seven ingredients in growing pigs using open-circuit respiratory chambers, five energy metabolism experiments were conducted in this study. In Exp.1,6crossbred barrows with an initial body weight (BW) of43±1.4kg were used to evaluate the fasting and regression methods to predict fasting heat production (FHP) in growing pigs. Six pigs were housed in open-circuit respiratory chambers for20d. A typical corn-soybean meal ration was fed throughout the experiment. The first7d were an adaptation to the diets, the next5d pigs were fed at2600kJ ME/kg BW0.6·-1, then fed at2×ME for maintenance (MEm) for3d, then fed at1RMEm for3d, and then fasted for2d. Fasting and regression methods were used to predict FHP. The predicted FHP for fasting and regression methods were774and694kJ/kg BW0.6·-1, respectively. In Exp.2,18barrows (initial BW=34±1.1kg) were selected to determine the NE value of corn using direct and substitution methods. Pigs were randomly allotted to3diets. The first diet (Corn) was formulated to contain97.5%corn and was used to determine the energy content in corn directly, while the second diet (Corn-Soybean meal-Basal diet) was formulated to contain72.5%corn and25.0%soybean meal, and the third diet (Corn-Soybean meal-Test diet) substituted40%of the energy supplied by the Corn-Soybean meal-Basal diet with corn. These2diets were used to calculate the energy content in corn using the substitution method. The DE, ME, NE content and k value in corn determined by the direct method were16.65,16.31,13.21MJ/kg DM, and80.99%, respectively, which were not different from the DE, ME, NE content and k value in corn determined by the substitution method which were16.42,16.15,13.69MJ/kg DM, and84.77%, respectively. In Exp.3,24barrows (initial BW=36±1.4kg) were used to determine the NE of soybean meal by the different basal diets methods for growing pigs. Pigs were randomly allotted to4diets. Three diets (1,2, and3) and two diets (3and4) were used to determine the energy value of soybean meal by using the corn basal (Corn-Basal) diet or the corn-soybean meal basal (Corn-SBM-Basal) diet method, respectively. The average DE, ME, NE, and RE content in soybean meal (17.36,16.52,10.62, and5.06MJ/kg DM, respectively) determined by the Corn-SBM-Basal diet method, was not different from the Corn-Basal diet method. In Exp.4,12barrows (initial BW=27±0.5kg) were used to determine the NE value of wheat bran, wheat, dried distillers grains with soluble (DDGS), canola meal, and cottonseed meal, and establish prediction equations for NE content of ingredients. Pigs received one corn-soybean meal basal diet and five experimental diets containing wheat bran, wheat, DDGS, canola meal, and cottonseed meal, respectively. Measurements were conducted on6pigs per experimental diets. The average values for wheat bran, wheat, DDGS, canola meal, and cottonseed meal were7.78,11.44,10.21,8.38, and7.32MJ/kg DM for NE, respectively. Stepwise regression analysis performed by the chemical composition and the NE value of the ingredients, the NE values could be accurately predicted from the chemical characteristics. The equation was as follows:NE=1.46+0.63GE-0.37ADF, with R2=0.94, residual standard deviation (RSD)=0.54MJ/kg, and P<0.01. In Exp.5,12barrows (initial BW=35±1.5kg) were randomly allotted to6mixed diets formulated by corn, soybean meal, wheat bran, wheat, DDGS, canola meal, and cottonseed meal, and each mixed diet was fed to six pigs. The chemical composition of each mixed diet was determined, and the results were used to establish prediction equations for the NE content from chemical characteristics. The equation for NE was established by the stepwise regression between chemical composition and energy value of the16diets (Include10diets in Exp.2,3and4), and the equation was as follows:NE=-10.19+0.97DE+0.08Starch+0.05ADF with R2=0.84, RSD=0.46MJ/kg, and P<0.01.更多还原