Year 2019, Volume 3 , Issue 3, Pages 171 - 181 2019-09-27

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

Derya Dursun Saydam [1] , Ali Coşkun Dalgıç [2]


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. 
Astaxanthin biosynthesis, Neural network, Optimization, Response Surface Methodology, Submerged system
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Primary Language en
Subjects Food Science and Technology, Agriculture, Agricultural, Engineering, Agriculture, Multidisciplinary
Published Date September 2019
Journal Section Research Articles
Authors

Orcid: 0000-0002-9858-6382
Author: Derya Dursun Saydam (Primary Author)
Institution: Department of Nutrition and Dietetics, İstanbul Yeni Yüzyıl University, İstanbul 34025, Turkey
Country: Turkey


Orcid: 0000-0001-6806-5917
Author: Ali Coşkun Dalgıç
Institution: Department of Food Engineering, University of Gaziantep, Gaziantep 27310, Turkey
Country: Turkey


Dates

Application Date : June 29, 2019
Acceptance Date : September 12, 2019
Publication Date : September 27, 2019

Bibtex @research article { jaefs612862, journal = {International Journal of Agriculture Environment and Food Sciences}, issn = {}, eissn = {2618-5946}, address = {Dicle University Faculty of Agriculture Department of Horticulture, 21280 Diyarbakir / Turkey}, publisher = {Gültekin ÖZDEMİR}, year = {2019}, volume = {3}, pages = {171 - 181}, doi = {10.31015/jaefs.2019.3.9}, title = {Astaxanthin biosynthesis: A two-step optimization approach and model construction with Response Surface Methodology and Artificial Neural Network}, key = {cite}, author = {Dursun Saydam, Derya and Dalgıç, Ali Coşkun} }
APA Dursun Saydam, D , Dalgıç, A . (2019). Astaxanthin biosynthesis: A two-step optimization approach and model construction with Response Surface Methodology and Artificial Neural Network. International Journal of Agriculture Environment and Food Sciences , 3 (3) , 171-181 . DOI: 10.31015/jaefs.2019.3.9
MLA Dursun Saydam, D , Dalgıç, A . "Astaxanthin biosynthesis: A two-step optimization approach and model construction with Response Surface Methodology and Artificial Neural Network". International Journal of Agriculture Environment and Food Sciences 3 (2019 ): 171-181 <https://dergipark.org.tr/en/pub/jaefs/issue/48298/612862>
Chicago Dursun Saydam, D , Dalgıç, A . "Astaxanthin biosynthesis: A two-step optimization approach and model construction with Response Surface Methodology and Artificial Neural Network". International Journal of Agriculture Environment and Food Sciences 3 (2019 ): 171-181
RIS TY - JOUR T1 - Astaxanthin biosynthesis: A two-step optimization approach and model construction with Response Surface Methodology and Artificial Neural Network AU - Derya Dursun Saydam , Ali Coşkun Dalgıç Y1 - 2019 PY - 2019 N1 - doi: 10.31015/jaefs.2019.3.9 DO - 10.31015/jaefs.2019.3.9 T2 - International Journal of Agriculture Environment and Food Sciences JF - Journal JO - JOR SP - 171 EP - 181 VL - 3 IS - 3 SN - -2618-5946 M3 - doi: 10.31015/jaefs.2019.3.9 UR - https://doi.org/10.31015/jaefs.2019.3.9 Y2 - 2019 ER -
EndNote %0 International Journal of Agriculture Environment and Food Sciences Astaxanthin biosynthesis: A two-step optimization approach and model construction with Response Surface Methodology and Artificial Neural Network %A Derya Dursun Saydam , Ali Coşkun Dalgıç %T Astaxanthin biosynthesis: A two-step optimization approach and model construction with Response Surface Methodology and Artificial Neural Network %D 2019 %J International Journal of Agriculture Environment and Food Sciences %P -2618-5946 %V 3 %N 3 %R doi: 10.31015/jaefs.2019.3.9 %U 10.31015/jaefs.2019.3.9
ISNAD Dursun Saydam, Derya , Dalgıç, Ali Coşkun . "Astaxanthin biosynthesis: A two-step optimization approach and model construction with Response Surface Methodology and Artificial Neural Network". International Journal of Agriculture Environment and Food Sciences 3 / 3 (September 2019): 171-181 . https://doi.org/10.31015/jaefs.2019.3.9
AMA Dursun Saydam D , Dalgıç A . Astaxanthin biosynthesis: A two-step optimization approach and model construction with Response Surface Methodology and Artificial Neural Network. int. j. agric. environ. food sci.. 2019; 3(3): 171-181.
Vancouver Dursun Saydam D , Dalgıç A . Astaxanthin biosynthesis: A two-step optimization approach and model construction with Response Surface Methodology and Artificial Neural Network. International Journal of Agriculture Environment and Food Sciences. 2019; 3(3): 181-171.