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Supplementary material from Growth profiling, kinetics and substrate utilization of low-cost dairy waste for production of β-cryptoxanthin by Kocuria marina DAGII

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posted on 25.06.2018 by Ruchira Mitra, Debjani Dutta
Dairy industry produces enormous amount of cheese whey compromising of major milk nutrients but remains unutilized all over the globe. The present study investigates the production of β-cryptoxanthin (β-CRX) by Kocuria marina DAGII using cheese whey as substrate. Response surface methodology (RSM) and artificial neural network (ANN) was implemented to obtain the maximum β-CRX yield. Significant factors viz. yeast extract, peptone, cheese whey and initial pH were the input variables in both the optimizing studies, and β-CRX yield and biomass were taken as output variables. The ANN topology of 4-9-2 was found to be optimum when trained with feed-forward back-propagation algorithm. Experimental values of β-CRX yield (17.14 mg l−1) and biomass (5.35 g l−1) were compared and ANN predicted (16.99 mg l−1 and 5.33 g l−1, respectively) values were found to be more accurate compared to RSM predicted values (16.95 mg l−1 and 5.23 g l−1, respectively). Detailed kinetic analysis of cellular growth, substrate consumption and product formation revealed that growth inhibition took place at substrate concentrations higher than 12%(v/v) of cheese whey. Han and Levenspiel model was the best fitted substrate inhibition model that described the cell growth in cheese whey with a R2 and MSE of 0.9982% and 0.00477%, respectively. The potential importance of this study lies in the development, optimization and modelling of a suitable cheese whey supplemented medium for increased β-CRX production.

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