Abstract
The enzymatic degradation of lignocellulosic biomass such as apple pomace is a complex process influenced by a number of hydrolysis conditions. Predicting optimal conditions, including enzyme and substrate concentration, temperature and pH can improve conversion efficiency. In this study, the production of sugar monomers from apple pomace using commercial enzyme preparations, Celluclast 1.5L, Viscozyme L and Novozyme 188 was investigated. A limited number of experiments were carried out and then analysed using an artificial neural network (ANN) to model the enzymatic hydrolysis process. The ANN was used to simulate the enzymatic hydrolysis process for a range of input variables and the optimal conditions were successfully selected as was indicated by the R2 value of 0.99 and a small MSE value. The inputs for the ANN were substrate loading, enzyme loading, temperature, initial pH and a combination of these parameters, while release profiles of glucose and reducing sugars were the outputs. Enzyme loadings of 0.5 and 0.2 mg/g substrate and a substrate loading of 30% were optimal for glucose and reducing sugar release from apple pomace, respectively, resulting in concentrations of 6.5 g/L glucose and 28.9 g/L reducing sugars. Apple pomace hydrolysis can be successfully carried out based on the predicted optimal conditions from the ANN.
Highlights
The production of biofuels from lignocellulosic wastes has received attention from researchers around the world (Dashtban et al 2009; Del Rio et al 2012; Garcia-Aparicio et al 2011)
Enzyme loadings of 0.5 and 0.2 mg/g substrate and a substrate loading of 30% were optimal for glucose and reducing sugar release from apple pomace, respectively, resulting in concentrations of 6.5 g/L glucose and 28.9 g/L reducing sugars
Hydrolysis slows down as there will be changes in substrate structure, with hydrolysable substrate getting depleted, enzymes may become adsorbed on residual substrate and lignin, enzymes may become deactivated, end-product inhibition may occur as well as mass transfer limitations, especially at high substrate loadings (Bommarius et al 2008; Sarkar and Etters 2004; Zhang et al Fig. 1 Concentration of sugars released at different time intervals for the batch reactor mixed with compressed air at room temperature with different substrate loadings. a (Glucose) and b
Summary
The production of biofuels from lignocellulosic wastes has received attention from researchers around the world (Dashtban et al 2009; Del Rio et al 2012; Garcia-Aparicio et al 2011). The main parameters that affect enzymatic hydrolysis of lignocellulose biomass are enzyme and substrate concentrations and hydrolysis conditions such pH, temperature and time (Bansal et al 2009; Gan et al 2003; Gupta et al 2012). Taking into account all these factors at once is a complex task, especially for heterogeneous substrates like apple pomace, a waste product from the apple juice industry. Empirical models use a small number of parameters to understand the initial rate of hydrolysis and how it is affected by different conditions e.g. temperature, pH, enzyme, substrate properties and time (Bansal et al 2009). Predicting optimal conditions for apple pomace hydrolysis successfully is of paramount importance for the design of efficient and cost-effective hydrolysis of apple pomace which will reduce capital and operational costs for the production of biofuels and biorefinery chemicals
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