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Modeling of mold inactivation via cold atmospheric plasma (CAP)

Summary

This research develops a mathematical model to predict how cold atmospheric plasma kills mold colonies on surfaces. Using experiments with Aspergillus brasiliensis, scientists found that when plasma treatment strength matches the mold’s natural growth rate, the mold stops growing and eventually dies. The model can provide predictions in minutes that would normally take weeks of laboratory testing, making it useful for food industry and building material applications.

Background

Molds produce mycotoxins responsible for serious health and material degradation problems. Conventional inactivation methods like chemical treatments and heating have limitations including toxicity and heat-resistant mold survival. Cold atmospheric plasma (CAP) represents a promising environmentally acceptable alternative operating at ambient temperatures with short processing times.

Objective

To develop a mathematical model for eliminating molds using cold atmospheric plasma based on a nonlinear logistic equation with density-dependent inactivation rate. The study aims to validate the model using experimental data for Aspergillus brasiliensis under different plasma operating conditions.

Results

The model successfully predicted mold extinction when plasma inactivation rate was comparable to the maximum natural growth rate. When plasma was activated at 72 h, the mold population became static (I = r), indicating plasma attack terminated further proliferation. At 117 h activation, a 113-hour stagnation period reflected mycelium revitalization before renewed growth resumed with a different growth rate.

Conclusion

The analytical solution of the logistic equation with density-dependent inactivation rate allows determination of substrate coverage by mycelium at arbitrary times. The model provides relevant information in minutes compared to weeks-long experiments and can be extended to other microorganisms and inactivation techniques beyond mold and CAP.
  • Published in:Applied and Environmental Microbiology,
  • Study Type:Mathematical Modeling Study,
  • Source: 10.1128/aem.02102-24, PMID: 40183547
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