Microwave assisted pretreatment and enzymatic hydrolysis for sugar production from Sago palm bark

Sago palm bark (SPB) is lignocellulosic biomass feedstock and a by-product of starch industry in Malaysia. The complex structure of lignocellulosic materials makes it resistant to enzymatic hydrolysis. Current technologies including physical and chemical pretreatment methods result in relatively low sugar yields, severe reaction conditions and high processing costs. A green and low energy pretreatment process is proposed using microwave irradiation. SPB was subjected to microwave-assisted pretreatment to assess the effects of pretreatment using diluted acid and alkaline solvents on sago palm bark characteristics and inhibitor formation. The effects of microwave-assisted pretreatment parameters (operating conditions) was also evaluated on glucose and xylose yield via enzymatic hydrolysis. Additionally, an estimation model for glucose and xylose yield from the enzymatic hydrolysis of SPB based on microwave-assisted pretreatment conditions was developed. The microwave-assisted pretreatments utilized three solvents which are 0.1 N H2SO4 (MSA), 0.1 N NaOH (MSH), and 0.01 N NaHCO3 (MSB). The microwave-assisted methods were compared to conventional heating pretreatment. The experimental design was done using a response surface methodology (RSM) and Box Bekhen Design (BBD) was used to evaluate the main and interaction effects of the pretreatment parameters on glucose and xylose yield obtained after the enzymatic hydrolysis step. The pretreatment parameters ranged from 5-15% solid loading (SL), 5-15 minutes of exposure time (ET) and 80-800 W of microwave power (MP). The enzymatic hydrolysis was carried out using 24 FPU/g of cellulase, 2 UN/g of xylanase and 50 U/g of β-glucosidase. An estimation model for glucose and xylose yield from the enzymatic hydrolysis of SPB was developed by using artificial neural network (ANN) and particle swarm optimization (PSO). The above-mentioned artificial intelligent systems were combined to form a hybrid PSO–ANN model. The MSA pretreatment resulted in higher lignin and hemicellulose degradation giving more porous structure of SPB compared to microwave-assisted alkaline and conventional pretreatments. No degradation products such as furfural, acetic acid and HMF were found in MSA pretreatment liquor. Conversely, conventional pretreatment using 0.1 N H2SO4 produced 0.47 mg/ml of acetic acid. After the enzymatic hydrolysis steps, it is revealed that the microwave-assisted pretreatment methods resulted in a higher sugar yield than conventional pretreatment methods. The results also show that the pretreatment parameters played a crucial role in the trend of the glucose and xylose yield from enzymatic hydrolysis of SPB. The results of glucose and xylose yield from MSA pretreatment and enzymatic hydrolysis of SPB were selected to develop a hybrid PSO–ANN model. The hybrid PSO–ANN model showed a higher regression coefficient (R2) for the estimation and the experimental values of glucose and xylose at 0.9939 and 0.9479, respectively. Meanwhile, R2 values of the RSM model were only 0.8901 and 0.8439 for glucose and xylose, respectively. This study concluded that the SPB has the potentials to be developed as future fermentable sugars source and the microwave-assisted pretreatment would be a possible route to enhance the release of these sugars.

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