Astaxanthin biosynthesis: A two-step optimization approach and model construction with Response Surface Methodology and Artificial Neural Network

Abstract

The first part of this research is investigating and comparing yield of a synthetic medium submerged three sugars(glucose, fructose and sucrose) at four different concentrations and solid fermentation systems with wheat bran andlentil waste for biosynthesis of astaxanthin (ASX) pigment by Xanthophyllomyces dendrorhous ATCC 24202 andSporidiobolus salmonicolor ATCC 24259 microorganisms. The second part is modeling and optimizing the mostefficient biosynthesis depending on waste, yeast and production variables consisted of moisture content, pH andtemperature using a design matrix. The yields produced by X. dendrorhous were 51.88 µg of ASX/g glucose forthe submerged medium with the least glucose, and 210.49 µg of ASX/g glucose for the wheat bran fermentationsystem. It was understood that the yield values of the submerged systems were lower and there was no requirementfor the addition of any supplement to the waste systems. It was found that R2=0.9869 was the highest value with themaximum predicted ASX amount of 109.23 µg of ASX/g wheat bran with X. dendrorhous using Artificial NeuralNetwork modeling and the moisture content was the most significant production parameter.