TY - JOUR
T1 - Multi-objective optimization of solid state fermentation process
AU - Gujarathi, Ashish M.
AU - Sadaphal, Ashish
AU - Bathe, Ganesh A.
N1 - Funding Information:
FUNDING The authors appreciate the financial support of Sultan Qaboos University, Muscat, Oman, under the Internal Grant project (IG/ENG/PCED/14/01).
Publisher Copyright:
Copyright © Taylor & Francis Group, LLC.
PY - 2015/4/3
Y1 - 2015/4/3
N2 - Solid state fermentation is among the key processes to produce enzymes and which canserve various purposes in the food and agricultural industries, etc. Modeling ofbioreactor salsoplays an important role in understanding the bioprocess, design, and development of process. The essential parameters best suited for a particular case of enzyme production were recognized in this work.The simulated mathematical model predicts the production of proteaseenzyme by Aspergillusniger under various operating conditions and values of parameters. Evolutionary multi-objective optimization (MOO), inthisstudy, isused for MOO of the solidstatefermentation processcon side ring two case studies of two objectives (maximization of enzyme activity versus minimization of fermentation time and maximization of product to cell yield coefficient versusminimization of fermentationtime)andvariables(airflowrates,airtemperature,moisturecontent,parameters for coolingandpressure).ThispaperpresentstheresultingoptimalParetofrontandthe possibleeffects of individual parameters on multiple objectives. Toserve the same purpose, simulationruns were taken at differen th eight sofbioreactorsoas to foresee the effects of scale-upon the performance of bioreactor and hence forth the process.
AB - Solid state fermentation is among the key processes to produce enzymes and which canserve various purposes in the food and agricultural industries, etc. Modeling ofbioreactor salsoplays an important role in understanding the bioprocess, design, and development of process. The essential parameters best suited for a particular case of enzyme production were recognized in this work.The simulated mathematical model predicts the production of proteaseenzyme by Aspergillusniger under various operating conditions and values of parameters. Evolutionary multi-objective optimization (MOO), inthisstudy, isused for MOO of the solidstatefermentation processcon side ring two case studies of two objectives (maximization of enzyme activity versus minimization of fermentation time and maximization of product to cell yield coefficient versusminimization of fermentationtime)andvariables(airflowrates,airtemperature,moisturecontent,parameters for coolingandpressure).ThispaperpresentstheresultingoptimalParetofrontandthe possibleeffects of individual parameters on multiple objectives. Toserve the same purpose, simulationruns were taken at differen th eight sofbioreactorsoas to foresee the effects of scale-upon the performance of bioreactor and hence forth the process.
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U2 - 10.1080/10426914.2014.984209
DO - 10.1080/10426914.2014.984209
M3 - Article
AN - SCOPUS:84924777805
SN - 1042-6914
VL - 30
SP - 511
EP - 519
JO - Materials and Manufacturing Processes
JF - Materials and Manufacturing Processes
IS - 4
ER -