Leveraging artificial intelligence and advanced food processing techniques for enhanced food safety, quality, and security: a comprehensive review

Использование искусственного интеллекта и передовых технологий переработки пищевых продуктов для повышения безопасности, качества и продовольственной обеспеченности: всесторонний обзор
Sambandh Bhusan Dhal, Debashish Kar
2025-01-11

Advanced food processingArtificial intelligenceComputer visionFood safetyMachine learning
Abstract Artificial intelligence is emerging as a transformative force in addressing the multifaceted challenges of food safety, food quality, and food security. This review synthesizes advancements in AI-driven technologies, such as machine learning, deep learning, natural language processing, and computer vision, and their applications across the food supply chain, based on a comprehensive analysis of literature published from 1990 to 2024. AI enhances food safety through real-time contamination detection, predictive risk modeling, and compliance monitoring, reducing public health risks. It improves food quality by automating defect detection, optimizing shelf-life predictions, and ensuring consistency in taste, texture, and appearance. Furthermore, AI addresses food security by enabling resource-efficient agriculture, yield forecasting, and supply chain optimization to ensure the availability and accessibility of nutritious food resources. This review also highlights the integration of AI with advanced food processing techniques such as high-pressure processing, ultraviolet treatment, pulsed electric fields, cold plasma, and irradiation, which ensure microbial safety, extend shelf life, and enhance product quality. Additionally, the integration of AI with emerging technologies such as the Internet of Things, blockchain, and AI-powered sensors enables proactive risk management, predictive analytics, and automated quality control. By examining these innovations' potential to enhance transparency, efficiency, and decision-making within food systems, this review identifies current research gaps and proposes strategies to address barriers such as data limitations, model generalizability, and ethical concerns. These insights underscore the critical role of AI in advancing safer, higher-quality, and more secure food systems, guiding future research and fostering sustainable food systems that benefit public health and consumer trust.
1
AI contributes to food security through resource-efficient agriculture, yield forecasting, and supply-chain optimization that improve nutritious food availability and accessibility.
2
AI improves food quality by automating defect detection, predicting shelf life, and supporting consistency in taste, texture, and appearance.
3
AI strengthens food safety through real-time contamination detection, predictive risk modeling, and compliance monitoring, thereby reducing public health risks.
4
Integrating AI with advanced processing methods, IoT, blockchain, and AI-powered sensors enables microbial control, extended shelf life, proactive risk management, and automated quality assurance, while data limitations, poor generalizability, and ethical concerns remain barriers.
5
The review synthesizes AI applications across the food supply chain, covering machine learning, deep learning, natural language processing, and computer vision from 1990 to 2024.

AI-driven technologies integrated into the food supply chain and advanced food processing techniques (e.g., machine learning, computer vision, high-pressure processing, pulsed electric fields, cold plasma)

the applications and integration of artificial intelligence and advanced food processing techniques for improving food safety, quality, and security

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2025-01-11
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Sambandh Bhusan Dhal
Debashish Kar
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