生长猪植物蛋白原料净能推测方程的构建

发布时间：2018-05-03 17:09

本文选题：能量利用效率 + 生长猪　；参考：《中国农业大学》2017年博士论文

【摘要】：本论文通过七个试验测定了豆粕(n = 22)、菜籽饼(n = 3)、菜籽粕(n = 5)、全脂米糠(n =1)、玉米胚芽粕(n=1)、玉米麸质饲料(n=1)、花生粕(n=1)和葵花粕(n=1)的净能值并建立和验证了生长猪蛋白原料净能预测方程。试验一测定了大豆来源分别为中国(n = 6)、美国(n = 6)、巴西(n = 7)和阿根廷(n = 3)豆粕的消化能、代谢能和净能值(预测方程法),并建立了生长猪豆粕消化能和代谢能预测方程。选用69头初始体重为53.1 ±3.7 kg的去势公猪,采用一个连续两期的完全随机试验设计,试验共分为23个日粮处理,分别为1个玉米基础日粮和22个含24.34%豆粕的试验日粮。结果表明,大豆来源于中国、美国、巴西和阿根廷的豆粕的消化能分别为 17.54、17.74、17.45和 17.92 MJ/kg DM,代谢能分别为 16.84、17.04、16.70和 17.38 MJ/kg DM,净能分别为10.00、10.18、9.92和10.35 MJ/kg DM。统计上不同来源豆粕的能值没有显著差异。最适的消化能预测方程为 DE = 38.44-0.43 CF-0.98 GE + 0.11 ADF(R2 = 0.67,P0.01)。最适的代谢能预测方程为ME = 2.74 + 0.97 DE-0.06 CP(R2 = 0.79,P0.01)。试验二通过间接测热法测定了玉米、豆粕、菜籽饼和菜籽粕的净能值。选用24头初始体重为36.4 ±1.6 kg的去势公猪,试验共4个日粮处理,其分别为1个玉米基础日粮、1个玉米豆粕基础日粮和两个含有20%菜籽饼或菜籽粕的日粮。结果表明,玉米、豆粕、菜籽饼和菜籽粕的净能值分别为12.46、11.34、11.71和8.83 MJ/kg DM。试验三选取175头初始体重为36.0 ±5.2 kg的生长猪随机分到5个日粮处理,每个处理7个重复,每个重复5头猪,进行28 d的生长试验以验证试验二中实测四种原料净能值的准确性。五个日粮分别为1个玉米豆粕基础日粮和4个包含10%或20%的菜籽饼或菜籽粕日粮。结果表明,各处理间的净能用于增重的效率没有显著差异,说明试验二测定的四种原料的净能值比较准确。试验四又重新测定了两个菜籽饼和3个菜籽粕的净能值并结合试验二的结果建立了菜籽饼粕净能的预测方程。选取36头初始体重为41.1 ±2.2 kg的去势公猪,试验共6个日粮处理,其分别为1个玉米豆粕基础日粮和5个含有19.50%的菜籽饼粕试验日粮。结果表明,最适菜籽饼粕净能预测方程为NE = 1.14 DE + 0.46 CP-25.24(R2 = 0.96,P0.01)。试验五通过间接测热法测定了全脂米糠、玉米胚芽粕、玉米麸质饲料、花生粕和葵花粕的净能值并结合试验二、四和本实验室前期的结果建立了蛋白原料净能预测方程。选取12头初始体重为32.4 ±3.3 kg的去势公猪,采用两个连续三期的尤登方试验设计。每期包括1个玉米豆粕基础日粮和5个包含29.25%全脂米糠、29.25%玉米胚芽粕、24.38%玉米麸质饲料、19.50%花生粕或29.25%葵花粕的试验日粮。结果表明,全脂米糠、玉米胚芽粕、玉米麸质饲料、花生粕和葵花粕的净能分别为12.33、8.75、7.51、10.79和6.49 MJ/kg DM。最适蛋白原料净能预测方程为NE = 0.75DE + 0.043ADF-2.18(R2 = 0.89,P0.01)。试验六测定了 DDGS、菜籽粕和葵花粕的消化能和代谢能并通过试验五建立的蛋白原料净能预测方程预测了该3种原料的净能值。选取24头初始体重为48.8 ±1.8 kg的去势公猪,随机分配到1个玉米豆粕基础日粮和3个含有30%DDGS、20%菜籽粕或30%葵花粕的试验日粮中,结果表明DDGS、菜籽粕和葵花粕的净能分别为9.56、8.20和6.54 MJ/kg DM。试验七选取144头初始体重为52.2 ± 6.0 kg的生长猪随机分到4个日粮处理,每个处理9个重复,每个重复4头猪,进行两期共56 d的生长试验以验证试验六通过蛋白原料净能预测方程预测的3种蛋白原料净能值的准确性。试验日粮包括1个玉米豆粕基础日粮和3个添加15%DDGS、菜籽粕或葵花粕的日粮。结果表明,添加15%DDGS、菜籽粕或葵花粕不影响生长育肥猪的生长性能、胴体性质和肉品质。各处理组净能转化为日增重、胴体增重或胴体瘦肉增重的效率没有显著差异,说明本研究得到的蛋白原料净能预测方程比较准确。综上所述,生长猪蛋白原料净能变异比较大,豆粕、菜籽饼、花生粕和高油DDGS净能值高于菜籽粕和葵花粕的净能值。消化能、代谢能、粗脂肪和纤维成分可以准确预测生长猪蛋白原料的净能值。
[Abstract]:In this paper, we measured the net energy of soybean meal (n = 22), rapeseed cake (n = 3), rapeseed meal (n = 5), whole fat rice bran (n =1), corn germ meal (n=1), corn gluten feed (n=1), peanut meal (n=1) and sunflower meal (n=1), and established and verified the net energy prediction equation of the growing pig protein. N = 6), United States (n = 6), Brazil (n = 7) and Argentina (n = 3) digestion energy, metabolic energy and net energy value (predicted Fang Chengfa), and a prediction equation for the digestion and metabolic energy of growth pig soybean meal was established. A castrated boar with 69 initial weight of 53.1 + 3.7 kg was selected with a two-stage complete random trial design, and the test was divided into 23. The results showed that the digestibility of soybean meal derived from soybean meal from China, the United States, Brazil and Argentina were 17.54,17.74,17.45 and 17.92 MJ/kg DM respectively, and the metabolic energy was 16.84,17.04,16.70 and 17.38 MJ/kg DM respectively, and the net energy of the soybean meal was 10.00,10.18,9.92 and the net energy was 10.00,10.18,9.92, respectively. 10.35 MJ/kg DM. statistics showed that there was no significant difference in the energy value of soybean meal. The optimum prediction equation for digestive energy was DE = 38.44-0.43 CF-0.98 GE + 0.11 ADF (R2 = 0.67, P0.01). The most suitable metabolic energy prediction equation was ME = 2.74 + 0.97 DE-0.06 CP (0.79). The test two measured corn, soybean meal, rapeseed cake by indirect calorimetry. The net energy value of the rapeseed meal. The castrated boars with 24 initial weight of 36.4 + 1.6 kg were treated with 4 diets, with 1 corn basal diets, 1 corn meal basal diets and two diets containing 20% rapeseed cake or rapeseed meal. The results showed that the net energy of corn, soybean meal, rapeseed cake and rapeseed meal were 12.46,11.34, respectively. 11.71 and 8.83 MJ/kg DM. tests three pigs with 175 initial weight of 36 + 5.2 kg were randomly divided into 5 diets, each treated with 7 repetitions, each repeated 5 pigs, and 28 d growth tests were carried out to verify the accuracy of the net energy value of the four raw materials measured in the second test. The five diets were basal diets for 1 corn soybean meal and 4 respectively. There were 10% or 20% rapeseed cakes or rapeseed meal. The results showed that there was no significant difference in the efficiency of the net energy used for weight gain between the treatments, indicating that the net energy value of the four raw materials measured in the test two was more accurate. The net energy value of the two rapeseed and 3 rapeseed meal was remeasured in trial four and the rapeseed meal was established in combination with the result of test two. The prediction equation of net energy was selected with 36 castration boars with a initial weight of 41.1 + 2.2 kg, and 6 diets were treated with 1 corn meal basal diets and 5 diets containing 19.50% rapeseed meal respectively. The results showed that the optimum prediction equation for the net energy of rapeseed meal was NE = 1.14 DE + 0.46 CP-25.24 (R2 = 0.96, P0.01). Experiment five. The net energy value of full fat rice bran, corn germ meal, corn gluten feed, peanut meal and sunflower meal was measured by indirect calorimetry. The net energy prediction equation of protein raw materials was established by combining the experiment two, four and the results of the previous laboratory. The 12 initial weight of 32.4 + 3.3 kg boars were selected, and two consecutive three periods of eudeng trial were used. The results showed that the net energy of total fat rice bran, corn germ meal, corn gluten meal, corn gluten feed, peanut meal and sunflower meal were 12.33,8.75,7.51,10.79, respectively, with 1 corn soybean meal base diets and 5 experimental diets containing 29.25% full fat rice bran, 29.25% corn germ meal, 24.38% corn gluten feed, 19.50% peanut meal or 29.25% sunflower meal. The net energy prediction equation of the most suitable protein raw material for 6.49 MJ/kg DM. was NE = 0.75DE + 0.043ADF-2.18 (R2 = 0.89, P0.01). Experiment six measured the digestion and metabolic energy of DDGS, rapeseed meal and sunflower meal, and predicted the net energy of the 3 raw materials by the net energy prediction equation established by test five. The initial weight of 24 heads was 48.8 + 1.8. The castrated boar of kg was randomly assigned to 1 corn soybean meal basal diets and 3 experimental diets containing 30%DDGS, 20% rapeseed meal or 30% sunflower meal. The results showed that the net energy of DDGS, rapeseed meal and sunflower meal was 9.56,8.20 and 6.54 MJ/kg DM. test seven and 144 initial weight of 52.2 + 6 kg was randomly divided into 4 diets. To verify the accuracy of the net energy value of 3 protein raw materials predicted by the prediction equation of protein raw material net energy, the accuracy of the net energy of 3 kinds of protein raw materials predicted by the net energy of protein materials was tested for each treatment of 9 duplicates, each repeated 4 pigs. The experimental diet included 1 corn soybean meal basal diets and 3 diets added to 15%DDGS, rapeseed meal or sunflower meal. The results showed that the diets added to the diet were added to the diet. The results showed that the diets added to the diet were added to the diet of 3 D, rapeseed meal or sunflower meal. 15%DDGS, rapeseed meal or sunflower meal did not affect growth performance, carcass properties and meat quality of growing fattening pigs. The net energy of each treatment group was converted to daily gain, carcass weight gain or carcass weight gain was not significantly different. The net energy of the protein raw material obtained in this study was more accurate. In summary, the net energy of the growing pig protein raw material The net energy value of soybean meal, rapeseed cake, peanut meal and high oil DDGS was higher than the net energy of rapeseed meal and sunflower meal. The net energy of pig protein raw material could be accurately predicted by digestive energy, metabolic energy, crude fat and fiber composition.

【学位授予单位】：中国农业大学
【学位级别】：博士
【学位授予年份】：2017
【分类号】：S828.5

【参考文献】