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

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-...

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Main Authors: Muhamad Nor, Norfarina, Mohamed, Mohd Shamzi, Loh, Teck Chwen, Foo, Hooi Ling, Abdul Rahim, Raha, Tan, Joo Shun, Mohamad, Rosfarizan
Format: Article
Language:English
Published: Taylor & Francis 2017
Online Access:http://psasir.upm.edu.my/id/eprint/61155/1/Comparative%20analyses%20on%20medium%20optimization%20using%20one-factor-at-a-time%2C%20response%20surface%20methodology%2C%20and%20artificial%20neural%20network%20for%20lysine%E2%80%93methionine%20biosynthesis%20by%20Pediococcus%20pentosaceus%20RF-1.pdf
http://psasir.upm.edu.my/id/eprint/61155/
https://www.tandfonline.com/doi/pdf/10.1080/13102818.2017.1335177?needAccess=true
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spelling my.upm.eprints.611552019-04-08T04:37:25Z http://psasir.upm.edu.my/id/eprint/61155/ 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 Muhamad Nor, Norfarina Mohamed, Mohd Shamzi Loh, Teck Chwen Foo, Hooi Ling Abdul Rahim, Raha Tan, Joo Shun Mohamad, Rosfarizan 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. Taylor & Francis 2017 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/61155/1/Comparative%20analyses%20on%20medium%20optimization%20using%20one-factor-at-a-time%2C%20response%20surface%20methodology%2C%20and%20artificial%20neural%20network%20for%20lysine%E2%80%93methionine%20biosynthesis%20by%20Pediococcus%20pentosaceus%20RF-1.pdf Muhamad Nor, Norfarina and Mohamed, Mohd Shamzi and Loh, Teck Chwen and Foo, Hooi Ling and Abdul Rahim, Raha and Tan, Joo Shun and Mohamad, Rosfarizan (2017) 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. Biotechnology & Biotechnological Equipment, 31 (5). pp. 935-947. ISSN 1310-2818; ESSN: 1314-3530 https://www.tandfonline.com/doi/pdf/10.1080/13102818.2017.1335177?needAccess=true 10.1080/13102818.2017.1335177
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description 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.
format Article
author Muhamad Nor, Norfarina
Mohamed, Mohd Shamzi
Loh, Teck Chwen
Foo, Hooi Ling
Abdul Rahim, Raha
Tan, Joo Shun
Mohamad, Rosfarizan
spellingShingle Muhamad Nor, Norfarina
Mohamed, Mohd Shamzi
Loh, Teck Chwen
Foo, Hooi Ling
Abdul Rahim, Raha
Tan, Joo Shun
Mohamad, Rosfarizan
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
author_facet Muhamad Nor, Norfarina
Mohamed, Mohd Shamzi
Loh, Teck Chwen
Foo, Hooi Ling
Abdul Rahim, Raha
Tan, Joo Shun
Mohamad, Rosfarizan
author_sort Muhamad Nor, Norfarina
title 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
title_short 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
title_full 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
title_fullStr 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
title_full_unstemmed 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
title_sort 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
publisher Taylor & Francis
publishDate 2017
url http://psasir.upm.edu.my/id/eprint/61155/1/Comparative%20analyses%20on%20medium%20optimization%20using%20one-factor-at-a-time%2C%20response%20surface%20methodology%2C%20and%20artificial%20neural%20network%20for%20lysine%E2%80%93methionine%20biosynthesis%20by%20Pediococcus%20pentosaceus%20RF-1.pdf
http://psasir.upm.edu.my/id/eprint/61155/
https://www.tandfonline.com/doi/pdf/10.1080/13102818.2017.1335177?needAccess=true
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score 13.1944895