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Variations in physicochemical characteristics of bacterial cellulose produced by Acetobacter aceti MTCC 2623 under static culture conditions

  • Garima Singh , Pammi Gauba and Garima Mathur ORCID logo EMAIL logo
Published/Copyright: June 17, 2025
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Abstract

Bacterial cellulose is a renewable biomacromolecule with significant environmental benefits over plant cellulose. It is secreted extracellularly by several bacterial species, including Gram-positive Sarcina ventriculi and Gram-negative bacteria such as Gluconacetobacter, Agrobacterium, and Acetobacter. Because of its remarkable physicochemical properties, BC has emerged as an excellent polymer with wide application domains in both industrial as well as biomedical fields. In our study, we investigated the potential of Acetobacter aceti MTCC 2623 for BC production under static conditions and evaluated the impact of incubation temperature, pH, and carbon sources on BC production. The maximum BC yield obtained was 4.18 ± 0.19 g L−1 by A. aceti under static conditions using 2 % w/v glucose as a carbon source, at 30 °C and pH 6.0. The BC samples produced were analyzed for physicochemical properties using Fourier transform infrared spectroscopy and differential scanning calorimetry, providing detailed insights into their structural composition and heat stability. X-ray diffraction indicates the crystallinity and amorphous regions. Fourier transform infrared spectroscopy analysis revealed that all BC samples were crystalline and exhibited variations in crystallinity ratios compared to commercial cellulose.


Corresponding author: Garima Mathur, Department of Biotechnology, Centre of Excellence for Microbial and Plant Biotechnology, Jaypee Institute of Information Technology, A-10, Sector-62, Noida, 201307, UP, India, E-mail:

Acknowledgments

The authors are thankful to the Council of Science and Technology, UP (UPCST) for funding this research work and Department of Biotechnology and Department of Physics and Materials Science and Engineering, JIIT Noida, India for providing necessary facilities to execute this work.

  1. Research ethics: Not applicable.

  2. Informed consent: Not applicable.

  3. Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  4. Use of Large Language Models, AI and Machine Learning Tools: None declared.

  5. Conflict of interest: The authors state no conflict of interest.

  6. Research funding: Council of Science and Technology, UP (UPCST) funded project no. CST/Biotech/2019/D-2157.

  7. Data availability: Not applicable.

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Received: 2024-01-09
Accepted: 2024-12-25
Published Online: 2025-06-17

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