狠狠色丁香久久综合婷婷亚洲成人福利在线-欧美日韩在线观看免费-国产99久久久久久免费看-国产欧美在线一区二区三区-欧美精品一区二区三区免费观看-国内精品99亚洲免费高清

 作者： Yong Liu,1,2 Cristian R. Munteanu,2 Carlos Fernandez-Lozano,2,3 Alejandro Pazos,2,3 Tao Ran,1 Zhiliang Tan,1,4 Yizun Yu,5 Chuanshe Zhou,1,4 Shaoxun Tang,1,4,* and Humberto González-Díaz6,7

 

 

摘要：The electrokinetic properties of the rumen microbiota are involved in cell surface adhesion and microbial metabolism. An in vitro study was carried out in batch culture to determine the effects of three levels of special surface area (SSA) of biomaterials and four levels of surface tension (ST) of culture medium on electrokinetic properties (Zeta potential, ξ; electrokinetic mobility, μe), fermentation parameters (volatile fatty acids, VFAs), and ST over fermentation processes (ST-a, γ). The obtained results were combined with previously published data (digestibility, D; pH; concentration of ammonia nitrogen, c(NH3-N)) to establish a predictive artificial neural network (ANN) model. Concepts of dual-time series analysis, perturbation theory (PT), and Box-Jenkins Operators were applied for the first time to develop an ANN model to predict the variations of the electrokinetic properties of microbiota. The best dual-time series Radial Basis Functions (RBR) model for ξ of rumen microbiota predicted ξ for >30,000 cases with a correlation coefficient >0.8. This model provided insight into the correlations between electrokinetic property (zeta potential) of rumen microbiota and the perturbations of physical factors (specific surface area and surface tension) of media, digestibility of substrate, and their metabolites (NH3-N, VFAs) in relation to environmental factors.