[Abstract] 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.

Technology Specialty Fund for Cooperation between Jilin Province and the Chinese Academy of Sciences; 2016SYHZ0022

Planned Science and Technology Project of Hu-nan Province; 2015NK3041

Ministerio de Economía, Industria y Competitividad; FJCI-2015-26071

Hunan Provincial Creation Development Project; 2013TF3006

National Natural Science Foundation of China; 31260556),

National Natural Science Foundation of China; 31172234

Xunta de Galicia; GRC2014/049

Xunta de Galicia; R2014/039