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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.

Methane yield predictive model based on the composition of biomass: Focus on the anaerobic digestion mode and regression method