Growth profiling, kinetics and substrate utilization of low-cost dairy waste for production of ?-cryptoxanthin by Kocuria marina DAGII.
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ABSTRACT: The dairy industry produces enormous amount of cheese whey containing the major milk nutrients, but this remains unutilized all over the globe. The present study investigates the production of ?-cryptoxanthin (?-CRX) by Kocuria marina DAGII using cheese whey as substrate. Response surface methodology (RSM) and an artificial neural network (ANN) approach were implemented to obtain the maximum ?-CRX yield. Significant factors, i.e. yeast extract, peptone, cheese whey and initial pH, were the input variables in both the optimizing studies, and ?-CRX yield and biomass were taken as output variables. The ANN topology of 4-9-2 was found to be optimum when trained with a feed-forward back-propagation algorithm. Experimental values of ?-CRX yield (17.14?mg?l-1) and biomass (5.35?g?l-1) were compared and ANN predicted values (16.99?mg?l-1 and 5.33?g?l-1, respectively) were found to be more accurate compared with 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. The Han and Levenspiel model was the best fitted substrate inhibition model that described the cell growth in cheese whey with an 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 ?-CRX production.
SUBMITTER: Mitra R
PROVIDER: S-EPMC6083662 | biostudies-literature | 2018 Jul
REPOSITORIES: biostudies-literature
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