Influence of Dextransucrase of Weissella Cibaria Nitcsk4 on Low Molecular Weight Dextran Yield: a Statistical Approach using Mixed Level Taguchi Design and Artificial Neural Network

Abstract

In the present study, the influence of dextransucrase of Weissella cibaria NITCSK4 (DSWc4), sucrose concentration, and reaction temperature on the yield of low molecular weight dextran (LMWD-DexWc4) was investigated using mixed level Taguchi design and back propagation neural network (BPNN). BPNN model with three neurons in a hidden layer generated a low mean squared error (MSE). The determination coefficients (R2 -value) for ANN and Taguchi models were 0.991 and 0.998, respectively. Considering absolute average deviation (AAD) and MSE, Taguchi model is more adequate. Among three factors, the percentage yield of low molecular weight of dextran is invariably dependent on the sucrose concentration. The study suggested that a low sucrose concentration (3% w/v), DSWc4 (0.25 IU/ml) and slightly high temperature (35°C) ultimately favored the production of LMWD-DexWc4 (91.639%). LMW-DexWc4 produced by DSWc4 at optimized conditions was analyzed. The weight average molecular weight of LMW-DexWc4 was calculated using M-H expression, found to be 85775 (≈90 kDa). The relative percentage error between the number and weight average molecular weight was found to be less (4.42%). The polydispersity (PD) index of the LMW-DexWc4 was found to be 0.9576 and the value is close to 1. The PD value depicted that the molecular weight distribution of dextran was narrowly dispersed.