Determination of the biodegradability of chitosan utilizing the most probable number technique

Authors

  • Wender Cardoso Silva Universidade Federal dos Vales do Jequitinhonha e Mucuri Author
  • Ilva de Fátima Souza Universidade Federal dos Vales do Jequitinhonha e Mucuri Author
  • Vivian Machado Benassi Universidade Federal dos Vales do Jequitinhonha e Mucuri Author
  • Juan Pedro Bretas Roa Universidade Federal dos Vales do Jequitinhonha e Mucuri Author
  • Paulo Henrique Graziotti Universidade Federal dos Vales do Jequitinhonha e Mucuri Author
  • David Lee Nelson Universidade Federal dos Vales do Jequitinhonha e Mucuri Author
  • Arlete Barbosa dos Reis Universidade Federal dos Vales do Jequitinhonha e Mucuri Author

DOI:

https://doi.org/10.4025/actascibiolsci.v42i1.52965

Keywords:

Actinobacteria; carbon source; microorganism.

Abstract

The present work aimed to evaluate the degradability of the chitosan polymer by soil microorganisms. This evaluation was accomplished using the Most Probable Number (MPN) method by plating in drops so that soil microorganisms capable of degrading the polymeric material could be quantified. Soil samples diluted in three specific culture media for each type of microorganism were plated – bacteria, fungi and actinobacteria – and they were maintained at 28°C for seven days to determine the growth rate of fungi and actinobacteria, and for 48 hours for the development of bacteria. Significant differences in the MPN of actinobacteria relative to the other groups analyzed were observed. Thus, the method used was effective for determining the degradability of the chitosan biopolymer when observing the development of microorganisms subjected to the replacement of the carbon source by the addition of 2% w v-1 of the chitosan biopolymer to the culture medium. The formation of clear regions around the microbial colonies was a strong indicator of biodegradation.

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Published

2020-08-27

Issue

Section

Biotechnology

How to Cite

Determination of the biodegradability of chitosan utilizing the most probable number technique. (2020). Acta Scientiarum. Biological Sciences, 42(1), e52965. https://doi.org/10.4025/actascibiolsci.v42i1.52965

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