Skip to main navigation Skip to search Skip to main content

Machine learning in transforming the food industry

  • Queensland University of Technology

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)
1 Downloads (Pure)

Abstract

The continued evolution and advances in Artificial Intelligence (AI) technologies are offering innovative solutions and setting the futuristic trends in the food sector. The use of different Machine Learning (ML)-based models has demonstrated promising applications in the food processing industry. Processing operations such as drying, frying, cooking, heating, and baking are complex and challenged by multifaceted problems due to simultaneous heat, mass and momentum transport processes. The ML-based tools could potentially categorize each food material and efficiently predict its processing kinetics for optimization of the processing conditions. Furthermore, ML technologies have shown excellent applications in ensuring the traceability of food provenance and quality, enhancing the transparency and traceability from farm to fork, and providing consumers with more reliable product information. Overall, ML tools have untapped potential to identify and accelerate multiple development opportunities across the entire agri-food sector to improve productivity, profitability, and sustainability in the future.

Original languageEnglish
Article number90
Number of pages15
JournalFoods
Volume15
Issue number1
DOIs
Publication statusPublished - 2026

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure

Keywords

  • agri-food sector
  • artificial intelligence
  • food processing
  • machine learning
  • sustainability

Fingerprint

Dive into the research topics of 'Machine learning in transforming the food industry'. Together they form a unique fingerprint.

Cite this