| The development and rational utilization of protein resource has become the priority of animal husbandry in China. In protein resource, the cottonseed meal has a high yield in China, but most of it was used as fertilizer, which cause a lot of waste. Therefore, the reasonable exploitation and utilization of cottonseed meal for the shortage of protein resources in our country has a great significance.The study has collected 26 kinds of cottonseed meals from Xinjiang, Shandong, Hubei and Hebei Province. Drying these cottonseed meals first, then determine the conventional physical and chemical index according to the national standard method. There are two tests in this study. Test One:the Hy-line Brown cocks were fed by empty-gavage to do metabolism test, and we can get the metabolism energy and effective amino acids of the cottonseed meals. Test Two was in vitro digestion. We choose two-step enzymatic, pepsin-pancreatic enzymatic to determine the in vitro digestion of the cottonseed meals. We have studied the filter methods (dialysis and non-dialysis), the optimal time and concentration of the pepsin, the optimal time and concentration of the pancreatic and the optimal pH of the buffer. Finally, we have established a set of the optimum conditions of the in vitro digestion for the cottonseed meals. Using SAS analysis software to combine the physical and chemical index, in vitro digestion and the metabolism energy and amino acids data to establish a fast and accurate evaluation of effective amino acids and metabolism energy for cottonseed meals.The study has established a relationship between the theory digestion and the real digestion of the cottonseed meals by SAS analysis software. The prediction models of the real effective amino acids data (y) and the theory digestion (x) as following:Effective Asp y=1.5965x+0.2450, R2=0.7444, P<0.0001Effective Thr y=1.5641x+0.0878, R2=0.7069, P<0.0001Effective Ser y=1.6708x+0.0314, R2=0.7762, P<0.0001Effective Glu y=1.5713x+0.8140, R2=0.7667, P<0.0001Effective Gly y=1.6093x-0.1395, R2=0.6786, P<0.0001Effective Ala y=1.6461x-0.0048, R2=0.7358, P<0.0001Effective Ile y=1.6195x+0.0049, R2=0.7351, P<0.0001Effective Leu y=1.6686x+0.0066,R2=0.7605,P<0.0001Effective Phe y=1.4997x+0.1743,R2=0.7352,P<0.0001Effective Lys y=1.6729x-0.1165,R2=0.7545,P<0.0001Effective Arg y=1.7185x+0.1451,R2=0.7590,P<0.0001Effective Met y=1.6197x-0.0017,R2=0.6861,P<0.0001EffectiveTyr y=1.6472x+0.0070,R2=0.7375,P<0.0001Effective Arg y=1.7340x+0.1390,R2=0.7816,P<0.0001Effective Pro y=2.2612x.0.4786,R2=0.9107,P<0.0001Effective Cys y=1.4754x+0.0494,R2=0.7476,P<0.0001Effective Val y=1.5906x+0.0580,R2=0.7303,P<0.0001Effective His y=1.7185x+0.1451,R2=0.7590,P<0.0001Among them,the x=The content of certain amino acids per gram×in vitro digestibility of dry matter(?).The compoment can predict the metabolizable energy.The prediction models as following:AME=13.74-0.43CF%-0.38ADF%+0.35NDF%-0.10AGE%(R2=0.3903? P=0.0003);TME=15.55-0.44CF%-0.38ADF%+0.35NDF%-0.10AGE%(R2=0.4456?P=0.0053)... |
PDF Full Text Request