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

Abstract

Dilute inorganic acids hydrolysis is one of the most promising pretreatment strategies with high recovery of fermentable sugars and low cost for sustainable production of biofuels and chemicals from lignocellulosic biomass. The diverse phenolics derived from lignin degradation during pretreatment are the main inhibitors for enzymatic hydrolysis and fermentation. However, the content features of derived phenolics and produced glucose under different conditions are still unclear due to the highly non-linear characteristic of biomass pretreatment. Here, an artificial neural network (ANN) model was developed for simultaneous prediction of the derived phenolic contents (CPhe) and glucose yield (CGlc) in corn stover hydrolysate before microbial fermentation by integrating dilute acid pretreatment and enzymatic hydrolysis. Six processing parameters including inorganic acid concentration (CIA), pretreatment temperature (T), residence time (t), solid-to-liquid ratio (RSL), kinds of inorganic acids (kIA), and enzyme loading dosage (E) were used as input variables. The CPhe and CGlc were set as the two output variables. An optimized topology structure of 6–12-2 in the ANN model was determined by comparing root means square errors, which has a better prediction efficiency for CPhe (R2 = 0.904) and CGlc (R2 = 0.906). Additionally, the relative importance of six input variables on CPhe and CGlc was firstly calculated by the Garson equation with net weight matrixes. The results indicated that CIA had strong effects (22%-23%) on CPhe or CGlc, then followed by E and T. In conclusion, the findings provide new insights into the sustainable development and inverse optimization of biorefinery process from ANN modeling perspectives. Graphical Abstract

Bioupgrading of the aqueous phase of pyrolysis oil from lignocellulosic biomass: a platform for renewable chemicals and fuels from the whole fraction of biomass

“…Furanic compounds can deactivate cell reproduction, cause DNA damage, and inhibit the essential enzymes involved in the carbon metabolic pathway (Palmqvist and Hahn-Hagerdal 2000 ). Phenolic compounds can alter the cell membrane permeability and generate multiple oxygen-free radicals (Monlau et al 2014 ; Luo et al 2021 ). Aldehyde is also a toxic compound present in the pyrolytic aqueous phase.…”

Fermentative Lactic Acid Production From Lignocellulosic Feedstocks: From Source to Purified Product

“…Smits et al (2019) developed a fast method for screening of optimal acid-pretreatment conditions in the conversion of wood lignocellulose to sugar. Luo et al (2021) developed an artificial neural network model to simultaneously predict the derived feature of phenolic compounds content and glucose yield in lignocellulosic biomass hydrolysate from dilute inorganic acid pretreatment and enzymatic hydrolysis. Also, there are attempts to use some organic acids to avoid problems with the corrosive action of the acids.…”

Hydrodynamic cavitation for lignocellulosic biomass pretreatment: a review of recent developments and future perspectives

“…Hence the complex lignocellulosic matrix’s highly recalcitrant deconstruction presents itself as the main challenge to be surpassed through the pretreatment step. The pretreatment step aims to open the recalcitrant structure of lignocellulosic material, providing an easier action of enzymes at a later stage of enzymatic hydrolysis, favoring the recovery of monomer sugars that are present in the carbohydrate fractions for later use in bioprocesses (Luo et al 2021 ; Verdini et al 2021 ). A successful pretreatment step should promote the biomass delignification, modifying and/or removing hemicellulose, decrease the crystallinity degree of cellulose, and increase the surface area and porosity, thus increasing the digestibility extension.…”