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Lignocellulosic biomass, comprising of cellulose, hemicellulose, and lignin, is a difficult-to-degrade substrate when subjected to anaerobic digestion. Hydrothermal pretreatment of lignocellulosic biomass could enhance the process performance by increasing the generation of methane, hydrogen, and bioethanol. The recalcitrants (furfurals, and 5-HMF) could be formed at high temperatures during hydrothermal pretreatment of lignocellulosic biomass, which may hinder the process performance. However, the detoxification process involving the use of genetically engineered microbes may be a promising option to reduce the toxic effects of inhibitors. The key challenge lies in the scaleup of the hydrothermal process, mainly due to necessity of upholding high temperature in sizeable reactors, which may demand high capital and operational costs. Thus, more efforts should be towards the techno-economic feasibility of hydrothermal pre-treatment at full scale.

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Sugar beet by-products are a lignocellulosic waste generated from sugar beet industry during the sugar production process and stand out for their high carbon content. Moreover, cow manure (CM) is hugely produced in rural areas and livestock industry, which requires proper disposal. Anaerobic digestion of such organic wastes has shown to be a suitable technology for these wastes valorization and bioenergy production. In this context, the biomethane production from the anaerobic co-digestion of exhausted sugar beet pulp (ESBP) and CM was investigated in this study. Four mixtures (0:100, 50:50, 75:25, and 90:10) of cow manure and sugar beet by-products were evaluated for methane generation by thermophilic batch anaerobic co-digestion assays. The results showed the highest methane production was observed in mixtures with 75% of CM (159.5 mL CH4/g VolatileSolids added). Nevertheless, the hydrolysis was inhibited by volatile fatty acids accumulation in the 0:100 mixture, which refers to the assay without CM addition. The modified Gompertz model was used to fit the experimental results of methane productions and the results of the modeling show a good fit between the estimated and the observed data.

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