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Water activity and biomass estimation using digital image processing in solid-state fermentation.

Vidhu Agarwal1, Dinesh Kumar1, Pritish Varadwaj1

  • 1Modeling and Simulation Laboratory, Department of Applied Sciences, Indian Institute of Information Technology, Allahabad, Deoghat, Jhalwa, Allahabad 211015, UP, India.

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Summary

This study introduces a digital image processing method in MATLAB to quantify biomass and water condensate, crucial for biotechnological applications. The developed model accurately estimates water activity, enhancing product quality and aiding solid-state fermentation processes.

Keywords:
Biomass estimationCondensation estimationDigital image processingMATLABPeltier moduleSolid state fermenter

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Area of Science:

  • Biotechnology
  • Image Processing
  • Bioprocess Engineering

Background:

  • Water activity is critical in biotechnological applications, influencing product quality and process efficiency.
  • Accurate estimation and control of water activity are essential for optimizing biotechnological products.
  • Current methods for water activity estimation may lack precision or cost-effectiveness in certain applications.

Purpose of the Study:

  • To develop and validate a digital image processing technique using MATLAB for quantifying biomass and water condensate.
  • To establish a predictive model for water activity based on experimental data.
  • To assess the applicability of the developed method in both abiotic and biotic conditions for biotechnological processes.

Main Methods:

  • Utilizing digital image processing in MATLAB for image analysis.
  • Developing an experimental model based on abiotic condition data.
  • Conducting comparative studies for water condensate estimation.
  • Validating the model with experimental data under both abiotic and biotic conditions.

Main Results:

  • A model was developed showing a linear relationship with experimental results.
  • The image processing technique demonstrated good accuracy in quantifying biomass and water condensate.
  • An error rate of less than 30% was observed at a specific threshold value.
  • Experimental estimations in biotic conditions showed good agreement with the developed model.

Conclusions:

  • The digital image processing technique offers a viable, low-cost method for water activity estimation in biotechnological applications.
  • The developed model accurately predicts biomass and water condensate, applicable in various conditions.
  • This approach holds potential for real-time monitoring and control in processes like solid-state fermentation.