Prediction of phenolic compounds and glucose content from dilute inorganic acid pretreatment of lignocellulosic biomass using artificial neural network modeling

Bioresources and Bioprocessing

Table 1 The design of operating conditions to perform the dilute acid pretreatment of lignocellulosic biomass for the development of ANN model

Lignocellulose	Kinds of acids (k_IA)^a	Acid concentration (C_IA, mol/L)	Pretreatment temperature (T, ℃)	Residence time (t, min)	Solid to liquid ratio (R_SL)	Enzyme loading dosage (E, FPU/g)
Corn stover	Hydrochloric acid (HCl)	0.05–0.6	120–200	20–60	10–15%	10–20
	Sulfuric acid (H₂SO₄)	0.05–0.6	120–200	20–60	10–15%	10–20
	Phosphoric acid (H₃PO₄)	0.05–0.6	120–200	20–60	10–15%	10–20

The pretreatment experiments with specified conditions were all carried out with three replicates. The raw data used for ANN development were the means and the detailed means ± SD values are shown in Table S1
Three kinds of inorganic acid including dibasic acid (HCl), binary acid (H₂SO₄), and ternary acid (H₃PO₄) were used
^aThe k value for HCl, H₂SO₄ and H₃PO₄ was set as 1, 2, and 3, respectively, which was used as one input parameter for the development of ANN model