Optimal experimental conditions for Welan gum production by support vector regression and adaptive genetic algorithm.

Zhongwei Li,Hu Zhu,Weishan Zhang,Qinghua Lu,Leiquan Wang,Xuerong Cui,Xin Liu,Xiang Yuan,Xiangxiang Zeng

doi:10.1371/journal.pone.0185942

Zhongwei Li, Hu Zhu + Show 7 more

Open Access

https://doi.org/10.1371/journal.pone.0185942

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Abstract

Welan gum is a kind of novel microbial polysaccharide, which is widely produced during the process of microbial growth and metabolism in different external conditions. Welan gum can be used as the thickener, suspending agent, emulsifier, stabilizer, lubricant, film-forming agent and adhesive usage in agriculture. In recent years, finding optimal experimental conditions to maximize the production is paid growing attentions. In this work, a hybrid computational method is proposed to optimize experimental conditions for producing Welan gum with data collected from experiments records. Support Vector Regression (SVR) is used to model the relationship between Welan gum production and experimental conditions, and then adaptive Genetic Algorithm (AGA, for short) is applied to search optimized experimental conditions. As results, a mathematic model of predicting production of Welan gum from experimental conditions is obtained, which achieves accuracy rate 88.36%. As well, a class of optimized experimental conditions is predicted for producing Welan gum 31.65g/L. Comparing the best result in chemical experiment 30.63g/L, the predicted production improves it by 3.3%. The results provide potential optimal experimental conditions to improve the production of Welan gum.

Highlights

Welan gum is a kind of polysaccharide, which is one of the secretions of Alcaligenes sp.NX-3 strain
A mathematic model of predicting production of Welan gum from experimental conditions with accuracy rate 88.36% is obtained, a class of optimized experimental conditions is designed to produce Welan gum 31.65g/L
The result provides a potential experimental conditions by data mining to improve the production of Welan gum in the lab

Summary

Introduction

Welan gum is a kind of polysaccharide, which is one of the secretions of Alcaligenes sp.NX-3 strain. Support Vector Regression (SVR) is used to model relationship between Welan gum production and experimental conditions, and adaptive Genetic Algorithm (AGA) is used to search optimized experimental conditions. Support Vector Machine (SVM) is known as a kind of machine learning method for classification proposed in 1995 [15], has been widely used in biological data processing [16,17,18] and bioinformatics [19,20,21,22,23] It focuses on doing classification with seeking structured minimum risk to improve the generalization ability of learning machine and minimizing empirical risk and confidence limit [24, 25], achieving good statistical law under the condition of the less statistical sample size. The optimization problem can be obtained as follows: mina;aÃ

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Results

Conclusion