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Machine Learning in Transforming the Food Industry.

Malik A Hussain1, Md Imran H Khan2, Azharul Karim2

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Summary
This summary is machine-generated.

Artificial Intelligence (AI) and Machine Learning (ML) offer innovative solutions for the food sector. These technologies can optimize food processing, enhance traceability, and improve sustainability across the agri-food industry.

Keywords:
agri-food sectorartificial intelligencefood processingmachine learningsustainability

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Area of Science:

  • Food Science and Technology
  • Artificial Intelligence
  • Machine Learning

Background:

  • Advancements in Artificial Intelligence (AI) are driving innovation in the food sector.
  • Machine Learning (ML) models show significant promise for applications within the food processing industry.
  • Complex food processing operations involve simultaneous heat, mass, and momentum transfer.

Purpose of the Study:

  • To explore the applications of ML-based tools in optimizing food processing conditions.
  • To highlight the role of ML in enhancing food traceability and quality assurance.
  • To identify the potential of ML in driving productivity and sustainability in the agri-food sector.

Main Methods:

  • Utilizing ML-based models to categorize food materials.
  • Employing ML tools to predict food processing kinetics.
  • Leveraging ML technologies for farm-to-fork traceability and quality control.

Main Results:

  • ML models can efficiently predict processing kinetics for optimized conditions.
  • ML enhances transparency and traceability of food provenance and quality.
  • ML provides consumers with more reliable product information.

Conclusions:

  • ML tools have significant untapped potential across the agri-food sector.
  • AI and ML can accelerate development opportunities for improved productivity and profitability.
  • These technologies are key to advancing sustainability in the future of food production.