A Comparative Study between Response Surface Methodology and Genetic Algorithm in Optimization and Extraction of Leaf Protein Concentrate from Diplazium esculentum of Assam
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Jayabrata Saha, Sourav Chakraborty and Sankar Chandra Deka

DOI: http://dx.doi.org/10.6000/1927-3037.2016.05.03.5

Published: 04 October 2016 

Abstract: Fern is a seedless vascular plant that reproduces via spores and has various usefulness. This study was carried out to optimize the conditions of leaf protein concentrate extraction using ultrasound from defatted fern type Diplazium esculentum. The extraction of defatted fern protein was conducted using ultrasound. Rotatable central composite design (RCCD) of response surface methodology was used for identification of the best condition and extraction yield optimization. An attempt with genetic algorithm optimization was also carried out and revealed that optimized results were of highest desirability as compared to response surface methodology. The final optimum results, by using genetic algorithm was observed to be 21.12 min of sonication time, 56.88 °C temperature, 7.59 pH and 66.2 ml of solvent for an optimum protein yield of 33.79% where desirability value was 1.00. UHPLC analysis of the sample revealed the presence of all the essential amino acids, except tryptophan.

Keywords: Leaf protein concentrate, Diplazium esculentum, GA, Optimization, Response surface methodology, Genetic algorithm.
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