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Optimizing a Submerged Monascus cultivation for Production of Red Pigment with Bug Damaged Wheat using Artificial Neural Networks
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  • Optimizing a Submerged Monascus cultivation for Production of Red Pigment with Bug Damaged Wheat using Artificial Neural Networks
  • Optimizing a Submerged Monascus cultivation for Production of Red Pigment with Bug Damaged Wheat using Artificial Neural Networks
저자명
Durakh-Velioglu. Serap,Boyaci. Ismail Hakki,Simsek. Osman,Gumus. Tuncay
간행물명
Food science and biotechnology
권/호정보
2013년|22권 6호|pp.1639-1648 (10 pages)
발행정보
한국식품과학회
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정기간행물|ENG|
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이 논문은 한국과학기술정보연구원과 논문 연계를 통해 무료로 제공되는 원문입니다.
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기타언어초록

The combined effect of temperature, agitation speed, and light on red pigment production by Monascus purpureus (M. purpureus) Went DSM 1604 using bug damaged wheat was studied using an artificial neural network (ANN). Information retrieved from the ANN was used to determine the optimal operating conditions for pigment production by M. purpureus using bug damaged wheat meal. The developed ANN had $R^2$ values for training, validation, and testing data sets of 0.993, 0.961, and 0.944, respectively. According to the model, the highest pigment production of 1.874 absorbance units at 510 nm ($A_{510nm}$) would be achieved at $29^{circ}C$ and 150 rpm under light conditions. The mean value of the experimental results obtained under these optimum conditions was $1.787{pm}0.072$ $A_{510nm}$, corresponding to a pigment yield of 35.740 $A_{510nm}/g$. The study showed that bug damaged wheat can be used as a substrate for red pigment production by M. purpureus.