Comparative analyses on medium optimization using one-factor-at-a-time, response surface methodology, and artificial neural network for lysine–methionine biosynthesis by Pediococcus pentosaceus RF-1

Autor: Norfarina Muhamad Nor, Mohd Shamzi Mohamed, Teck Chwen Loh, Hooi Ling Foo, Raha Abdul Rahim, Joo Shun Tan, Rosfarizan Mohamad
Jazyk: angličtina
Rok vydání: 2017
Předmět:
Zdroj: Biotechnology & Biotechnological Equipment, Vol 31, Iss 5, Pp 935-947 (2017)
Druh dokumentu: article
ISSN: 1310-2818
1314-3530
13102818
DOI: 10.1080/13102818.2017.1335177
Popis: Optimization strategy that encompassed one-factor-at-a-time (OFAT), response surface methodology (RSM), and artificial neural network method was implemented during medium formulation with specific aim for lysine-methionine biosynthesis employing a newly isolated strain of Pediococcus pentosaceus RF-1. OFAT technique was used in the preliminary screening of factors (molasses, nitrogen sources, fish meal, glutamic acid and initial medium pH) before proceeded to optimization study. Implementation of central composite design of experiment subsequently generated 30 experimental runs based on four factors (molasses, fish meal, glutamic acid, and initial medium pH). From RSM analysis, a quadratic polynomial model can be devoted to describing the relationship between various medium components and responses. It also suggested that using molasses (9.86 g/L), fish meal (10.06 g/L), glutamic acid (0.91 g/L), and initial medium pH (5.30) would enhance the biosynthesis of lysine (15.77 g/L) and methionine (4.21 g/L). Alternatively, a three-layer neural network topography at 4-5-2 predicted a further improvement in the biosynthesis of lysine (16.52 g/L) and methionine (4.53 g/L) by using formulation composed of molasses (10.02 g/L), fish meal (18.00 g/L), and glutamic acid (1.17 g/L) with initial medium pH (4.26), respectively.
Databáze: Directory of Open Access Journals
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