Low-temperature pretreatment (LTPT, Temp. < 100 °C or 140 °C) has the advantages of low input, simplicity, and energy saving, which makes engineering easy to use for improving biogas production. However, compared with high-temperature pretreatment (>150 °C) that can destroy recalcitrant polymerized matter in biomass, the action mechanism of heat treatment of biomass is unclear. Improving LTPT on biogas yield is often influenced by feedstock type, treatment temperature, exposure time, and fermentation conditions. Such as, even when belonging to the same algal biomass, the response to LTPT varies between species. Therefore, forming a unified method for LTPT to be applied in practice is difficult. This review focuses on the LTPT used in different biomass materials to improve anaerobic digestion performance, including food waste, sludge, animal manure, algae, straw, etc. It also discusses the challenge and cost issues faced during LTPT application according to the energy balance and proposes some proposals for economically promoting the implementation of LTPT.

The scum layer of straw anaerobic digestion significantly impacts biogas production efficiency. The initial floating of straw after entering the reactor is an important reason for scum layer formation. Improving the settleability of straw particles and reducing the initial floating time of straw are crucial to suppressing the scum layer, and accelerating the water absorption rate of straw entering the reactor is the key to reducing the floating time. Therefore, in this study the corn stalks were kneaded and rolled, and the stalk particles were tested for water absorption and aerobic hydrolysis. The results showed that the water absorption rate of the stalks after conditioning was significantly accelerated, and the water absorption rate was 120% higher than that of the untreated stalks after absorbing water for 12 h. Simultaneously, aerobic hydrolysis destroys the lignocellulose structure to a certain extent, increases the porosity of the stalk particles, and further improves the settleability of the stalk particles. In the subsequent anaerobic digestion process, scum decreased significantly: the scum layer volume ratio was 13% lower than untreated stalks. The methane production efficiency of anaerobic digestion was significantly improved, and the optimal hydrolysis time was 12 h. At this time, the cumulative methane production of the milled treated stalks reached the maximum value of 319.64 mL/g VS, which was 26.59% higher than that of the untreated stalks.

Acetic acid is the primary by-product generated from ethanol production by Fusarium oxysporum using glucose or xylose as a substrate. Aldehyde dehydrogenase (ALDH) is the critical enzyme in acetic acid metabolism. To decrease acetic acid yield in ethanol production, the 1509 bp DNA of aldh, encoding a 502 amino acid protein with a calculated molecular mass of 54.33 kDa and an isoelectric point of 6.21, was cloned from F. oxysporum. Sequence analysis confirmed that the screened proteins belonged to the ALDH family. A knockout vector, ∆aldh, containing positive (hygromycin resistance gene) and negative (thymidine kinase gene from the herpes simplex virus) selectable markers, was constructed. Ethanol production by the mutant (cs28pCAM-Pstal-∆aldh) in glucose- and xylose-containing media was 0.46 and 0.39 g/g, respectively, and these yields were 16.93% and 34.63% higher than those by the wild-type strain (0.393 and 0.289 g/g). Furthermore, the acetic acid yield of the mutant was 3.50 and 3.01 g/L, respectively, showing a 23.10% and 39.55% decrease compared with the wild-type strain (4.308 and 4.196 g/L). The biomass of the mutant (4.05 and 4.52 g/L) was lower than that of the wild-type strain (4.71 and 5.97 g/L). These results demonstrated the potential use of the genetically stable mutant for industrial bioethanol production.

Nine kinds of biomass were used to investigate the correlation of organic composition with the methane yield in continuous anaerobic digestion (AD) mode with different organic loading rates (OLRs). The experimental results showed that the methane yields were different with the change of OLR; thus, only one model was unable to satisfy the prediction accuracy for all the operation conditions. A stepwise regression model and two self-defined models were used to determine the prediction accuracy for different operation OLRs in the present assay. The results showed that the self-defined models constituted by biodegradable components (protein, fat, and readily degradable sugars) obtained a higher determination coefficient (R2) than the model fitted by the traditional stepwise regression method. Biomass with a higher content of easily degradable matter had a lower predictive deviation. Based on this, it is recommended that the various biomasses be divided into two groups to obtain better model fitting and prediction accuracy. The biomass with a content of readily degradable section that was more than 47% or the content of lignin was less than 8% can be classified into one group, and the others can be classified into another group according to the present test results.