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

Yıl 2019, , 171 - 181, 27.09.2019

Derya Dursun Saydam , Ali Coşkun Dalgıç

https://doi.org/10.31015/jaefs.2019.3.9

Öz

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 and lentil waste
for biosynthesis of astaxanthin (ASX) pigment by Xanthophyllomyces dendrorhous ATCC 24202 and Sporidiobolus salmonicolor ATCC 24259 microorganisms. The second
part is modeling and optimizing the most efficient biosynthesis depending on
waste, yeast and production variables consisted of moisture content, pH and
temperature using a design matrix. The yields produced by X. dendrorhous were 51.88 µg of ASX/g glucose for the submerged
medium with the least glucose, and 210.49 µg of ASX/g glucose for the wheat bran
fermentation system. It was understood that the yield values of the
submerged systems were
lower and there was no requirement for the addition of any
supplement to the waste systems. It was found that R²=0.9869 was
the highest value with the maximum predicted ASX amount of 109.23 µg of ASX/g
wheat bran with X. dendrorhous
using Artificial Neural Network modeling and the moisture content was the most
significant production parameter. 

Anahtar Kelimeler

Astaxanthin biosynthesis, Neural network, Optimization, Response Surface Methodology, Submerged system

Kaynakça

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