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Prediction of Yields in Glucosylation of Rgocalciferol Through Response Surface Methodology and Artificial Neural Network Analysis.

Manohar, B. and Divakar, S. (2012) Prediction of Yields in Glucosylation of Rgocalciferol Through Response Surface Methodology and Artificial Neural Network Analysis. Indian Journal of Fundamental and Applied Life Sciences, 2 (4). pp. 40-50.

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Abstract

-Glucosidase from sweet almond catalyzed synthesis of 20-O-(D-glucopyranosyl) ergocalciferol was analyzed using response surface methodology (RSM) and artificial neural network (ANN) analysis. In RSM a central composite rotatable design involving 30 experiments with four variables at five levels was employed to develop a predictive equation. The variables employed were immobilized -glucosidase 20 - 100% w/w of D-glucose, pH 4.0 - 8.0, buffer concentration 0.04 - 0.2 mM (0.4 - 2 ml) and incubation period 10 - 50 h. Surface plots clearly brought out the behaviour of immobilized -glucosidase in the glucosylation of ergocalciferol in exhibiting a crossover point at 60% (w/w D-glucose) immobilized -glucosidase, 0.1 mM buffer concentration and pH 6.0. A maximum yield predicted by RSM of 26% under 100% (w/w D-glucose) immobilized -glucosidase, pH 6.0, 0.12 mM (1.2 ml) buffer concentration and 30 h incubation period corresponded with an experimental yield of 26% under the same conditions. ANN analysis carried out with a set of training data also showed good correspondence to the testing data.

Item Type: Article
Uncontrolled Keywords: Ann, Ccrd, Enzyme Concentration, Ergocalciferol, -Glucosidase, Incubation Period, 20-O-(D-Glucopyranosyl) Ergocalciferol, RSM
Subjects: 600 Technology > 08 Food technology > 16 Nutritive value > 04 Vitamins
Divisions: Fermentation Technology and Bioengineering
Food Engineering
Depositing User: Food Sci. & Technol. Information Services
Date Deposited: 28 Mar 2013 07:14
Last Modified: 28 Mar 2013 07:14
URI: http://ir.cftri.com/id/eprint/11166

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