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The Effect of the Application of Thyme Essential Oil on Microbial Load During Meat Drying
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Published on: March 14, 2018

Mechanistically Informed and Omics-Guided Essential Oil Applications for Food Preservation.

Mohammad Nazrul Islam Bhuiyan1, Md Saidur Rahman2, Md Mahfuzur Rahman2

  • 1BCSIR Chattogram Laboratories, BCSIR, Chattogram 4220, Bangladesh; Institute of Food Science and Technology, Bangladesh Council of Scientific and Industrial Research (BCSIR), Dr. Qudrat-i-Khuda Road, Dhaka 1205, Bangladesh.

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|May 8, 2026
PubMed
Summary

Plant-derived essential oils (EOs) show promise for natural food preservation. Integrating multi-omics and AI can overcome challenges like variability and improve safety for sustainable food systems.

Keywords:
Data integrationFood safetyMicrobial inactivationNatural antimicrobialsPredictive analyticsRisk assessmentSystems biology

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Area of Science:

  • Food Science
  • Microbiology
  • Biotechnology

Background:

  • Increasing demand for safe, sustainable, and clean-label food preservation.
  • Plant-derived essential oils (EOs) are explored as natural antimicrobial agents against foodborne pathogens.
  • EOs possess broad-spectrum activity via multi-target mechanisms but face application challenges like variability and instability.

Purpose of the Study:

  • To review mechanistic, omics-driven, and AI-enabled approaches for essential oil-based food preservation.
  • To address key translational barriers hindering the practical application of EOs in food systems.
  • To highlight pathways for developing reliable and precision-oriented EO preservation systems.

Main Methods:

  • Synthesis of current research on essential oil antimicrobial mechanisms.
  • Analysis of multi-omics technologies (transcriptomics, proteomics, metabolomics) for understanding EO-microbe interactions.
  • Evaluation of artificial intelligence (AI) and machine learning (ML) applications in predicting antimicrobial outcomes.

Main Results:

  • Multi-omics provide systems-level insights into coordinated cellular responses to EOs.
  • AI/ML offer tools for modeling complex interactions but require further validation and interpretability.
  • Key barriers include lack of standardization, regulatory complexity, and scalability issues.

Conclusions:

  • Integrating mechanistic biology with data-driven modeling is crucial for optimizing EO-based preservation.
  • Addressing translational barriers will enable more reliable and precision-oriented EO preservation systems.
  • This approach aligns with demands for sustainable food safety and clean-label products.