AD process control on current digesters is still relying on input and output data: primarily biogas yield and composition, and pH. When the output data suggest any abnormality in performance, it is often too late to intervene, leading to severe disrup­tion of normal operation. Thus, there is an urgent need for research and development of on-line systems that can monitor important parameters of the actual AD pro­cess. Some of the key parameters of AD and their modeling have been reported [35, 71], which can guide the research effort to develop online monitoring systems. Propionate was recently identified to be an important indicator of AD performance [12, 63], and online monitoring of this important SCFA using gas chromatogra­phy seems promising [12, 70]. Further understanding of the microbial communities involved in AD processes may also allow for the development of biosensors that can achieve microbe-based continuous online monitoring. Such real-time monitor­ing can directly link to automated digester controls, such as loading and mixing. Advanced understanding of the microbial community structure, population dynam­ics, metabolic kinetics, and online monitoring in digesters will also improve the modeling of AD processes [6, 35].