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Published on: April 11, 2016
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Multi-approach optimization of exopolysaccharide production from Leuconostoc mesenteroides ABNFT-1 using statistical
Ankit Barot1, Kalyan Das1, Yogesh Patel2
1Department of Interdisciplinary Sciences, National Institute of Food Technology Entrepreneurship and Management (NIFTEM), Kundli-Sonipat, India.
Preparative Biochemistry & Biotechnology
|October 22, 2025
Summary
This study optimized exopolysaccharide (EPS) production by Leuconostoc mesenteroides ABNFT-1 using a hybrid approach. Machine learning models, particularly the Levenberg-Marquardt Algorithm, significantly enhanced EPS yield for industrial biopolymer applications.
Area of Science:
- Microbiology
- Biotechnology
- Polymer Science
Background:
- Exopolysaccharides (EPS) are microbial polymers with diverse industrial applications.
- Optimizing EPS production is crucial for cost-effective biopolymer synthesis.
- Leuconostoc mesenteroides ABNFT-1 was identified as a high-yield EPS producer.
Purpose of the Study:
- To enhance exopolysaccharide (EPS) production from Leuconostoc mesenteroides ABNFT-1.
- To systematically optimize critical process parameters using a multi-step strategy.
- To compare the predictive accuracy of different artificial neural network (ANN) algorithms for EPS yield.
Main Methods:
- One-factor-at-a-time (OFAT) screening for initial parameter assessment.
- Response Surface Methodology (RSM) with Central Composite Design (CCD) for optimization.
- Artificial Neural Network (ANN) modeling (LMA, SCGA, BRA) for yield prediction.
Main Results:
- Optimized conditions (10% inoculum, 20% sucrose, 4% KNO3, 0.04% FeSO4) yielded 21.74 g/L EPS.
- ANN modeling with LMA predicted a maximum EPS yield of 23.66 g/L.
- LMA demonstrated superior prediction accuracy compared to SCGA and BRA.
Conclusions:
- A hybrid optimization strategy combining statistical methods and machine learning is effective for maximizing EPS production.
- The optimized process offers significant improvements in EPS yield.
- This research provides a foundation for industrial-scale biopolymer synthesis using microbial EPS.
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