The objectives of this research were two-folds: firstly, to study the biogas production from anaerobic co-digestion of Thai rice noodle wastewater (TRW) with rice husk and different types of animal manure (cow manure, quail manure, and chicken manure); secondly, to obtain kinetic parameters for the purpose of designing continuous systems. The main focus of the research was to study the effect of pretreatment of rice husk with potassium permanganate (KMnO4) solution for 24 hours on the biochemical methane potential (BMP). The experiments were divided into 6 digesters including: the digesters 1-3 in which rice husk was pre-treated with potassium permanganate, adjusting the pH to 10 and then being soaked in the solution for the retention time of 24 hr. The digesters 4-5 which used untreated rice husk as a co-substrate. In each digester, 10 g of manure, 10 g of rice husk and 200 mL of TRW were used as co-substrates. The results show that the digester 1 which used pre-treated rice husk co-digested with cow manure and TRW gave the highest cumulative biogas (average value of 1,375 mL, 426.0 mL biogas/gCODadded) as well as the biochemical methane potential (215 mL CH4 /gCODadded), followed by digester 2 which used pre-treated rice husk co-digested with quail manure and TRW (1,144 mL biogas, 221.7 mL biogas/gCODadded and 112 mL CH4 /gCODadded), and digester number 3 (pre-treated rice husk co-digested with chicken manure and TRW, 862 mL biogas, 186.3 mL biogas/gCODadded and 94.1 mL CH4 /gCODadded). The results show that pretreatment of rice husk with KMnO4 increased the co-substrate biodigestibility greatly (almost double for digest 2 and 3) which could be a result of the destruction of lignin and hemicellulose structures, helping the microorganisms to digest more substrate and thus produce more biogas. Furthermore, due to the complexity of substrate and accumulative biogas evolution (ABE) curves, the conventional the Gompertz model did not represent the ABE data very well. We also showed how Gompertz-type models and parameters can be converted to Monod-type (in this case Contois model) parameters and become more valuable not only for representing the results in batch AD specifically but also for being used directly in AD process design.