With increasing global population and food demands, conventional manual and semi-automated workflows for slaughtering, cutting, milling, fermentation and packaging has been limited by labor variability, delayed hazard detection, food degradation, and trace ability gaps. Recent breakthroughs in miniaturized biosensors, optical spectroscopy, machine-vision systems and autonomous robotics now make it possible to monitor and control processing lines continuously, non-destructively, and at scale to enhance throughput, quality, safety, and sustainability from farm to fork.

These innovations in artificial intelligence, sensor technologies, and autonomous robotics offer integrated solutions to these challenges, allowing for smarter, safer, and more efficient processing environments, . These technologies reducing human error, enhancing operational consistency, and supporting proactive management across food and animal systems. This Research Topic seeks contributions that explore such integrated AI, sensing, and robotic frameworks for applications in animal and food supply chains.

Modern animal and food processing systems face mounting demands for efficiency, product quality and biosafety. Recent advances in artificial intelligence, miniaturized biosensors and autonomous robotics in animal and food supply chain, which enable:

(i) Continuous, real-time monitoring of animal and food supply chains
(ii) AI-drive detection of microbial, chemical or physical hazards
(iii) Automated sampling, handling and traceability

This Research Topic invites original research, reviews and perspectives on integrating AI-driven sensing and robotic solutions to advance animal and food processing practices. This collection focuses on innovative research and practical applications of intelligent systems in animal and food systems. We seek contributions that explore the integration of artificial intelligence, sensing/biosensing technologies, and autonomous robotics to address challenges in food quality, safety, labor efficiency, and traceability. Topics of interest include, but are not limited to:

1. AI for Optimizing Animal Production and Food Processing (e.g. predictive analytics, process optimization, quality control, and animal welfare)
2. AI-driven Sensing and Sensor Fusion for Food and Animal Systems (e.g. vision, spectroscopy, acoustic, and multimodal sensing for contaminant detection, product grading, and welfare monitoring)
3. AI-enabled Biosensing Systems (e.g. electrochemical, optical, and molecular biosensors for pathogen detection, residue monitoring, and real-time quality assurance)
4. AI-Integrated Robotics for Sampling and Inspection (e.g. robotic manipulators, mobile systems, and autonomous platforms for precision sampling, automated inspection, and labor-efficient processing)
5. Edge and Cloud Computing in Food and Animal Systems (e.g. distributed architectures for real-time sensing, analytics, and decision support)
6. Field Demonstrations and Industrial Deployments (e.g. case studies of integrated AI systems tested in farms, slaughterhouses, or food processing plants)

We welcome original research articles, reviews, technology reports, methods papers, and case studies that deliver both theoretical insights and practical implementations in industrial or field settings.

Are you interested in contributing a manuscript to this Research Topic?

Artificial Intelligence, Sensing, and Robotic Innovations in Animal and Food Systems for Next-Generation Processing and Safety