ReviewFood chemistry: X2024
Revolutionizing the food industry: The transformative power of artificial intelligence-a review.
Review in Food chemistry: X, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
17 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Hybrid Intelligence for Fouling Prediction and Adaptive Clean-in-Place Optimization in Food Processing Heat Exchangers: A Systematic Review.Journal of food science · 2026Pooled it
- Artificial intelligence in poultry processing: applications, validation gaps, and pathways toward intelligent and autonomous processing systems.Poultry science · 2026Review
- AI-Enabled Shrinkage Analysis and Morphology Control in Food Processing: Mechanisms, Multimodal Perception, Modeling, and Intelligent Regulation.Comprehensive reviews in food science and food safety · 2026Review
- Synergistic Optimization of In Vitro Digestibility and Sensory Quality of Moderately Milled Rice Based on the RiceMambaOpt Model.Foods (Basel, Switzerland) · 2026Article
- Automation, Robotics, and Artificial Intelligence in Seafood Processing: Advancements, Challenges, and Future Prospects.Journal of food science · 2026Review
- AI-driven personalization of food systems: From precision nutrition to climate-resilient supply chains.NPJ science of food · 2026Review
- Machine learning-assisted optimization of ultrasound-ohmic processing of hawthorn vinegar: antidiabetic activity, phenolic profiling, and molecular docking insights.Frontiers in nutrition · 2026Article
- Machine Learning in Transforming the Food Industry.Foods (Basel, Switzerland) · 2025Review
- Artificial intelligence-generated sustainable gift box design evaluation via reinforcement learning-driven hybrid molecular fuzzy modelling.Scientific reports · 2025Article
- A Comprehensive Review of Artificial Intelligence (AI)-Driven Approaches to Meat Quality and Safety.Food science of animal resources · 2025Review
- AI for food: accelerating and democratizing discovery and innovation.NPJ science of food · 2025Review
- Big data analytics in food industry: a state-of-the-art literature review.NPJ science of food · 2025Review
- Artificial Intelligence-Driven Recommendations and Functional Food Purchases: Understanding Consumer Decision-Making.Foods (Basel, Switzerland) · 2025Article
- Advances in Starch-Based Nanocomposites for Functional Food Systems: Harnessing AI and Nuclear Magnetic Resonance Technologies for Tailored Stability and Bioactivity.Foods (Basel, Switzerland) · 2025Review
- Foodborne Event Detection Based on Social Media Mining: A Systematic Review.Foods (Basel, Switzerland) · 2025Article
- Mapping the AI Landscape in Food Science and Engineering: A Bibliometric Analysis Enhanced with Interactive Digital Tools and Company Case Studies.Food engineering reviews · 2025Review
- AI-driven transformation in food manufacturing: a pathway to sustainable efficiency and quality assurance.Frontiers in nutrition · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial Intelligence (AI) is revolutionizing the food industry by optimizing processes, improving food quality and safety, and fostering innovation. This review examines AI's applications in food science, including supply chain management, production, sensory science, and personalized nutrition. It discusses techniques like knowledge-based expert systems, fuzzy logic, artificial neural networks, and machine learning, highlighting their roles in predictive maintenance, quality control, product development, and waste management. The integration of AI with sophisticated sensors enhances real-time monitoring and decision-making in food safety and packaging. However, challenges such as ethical concerns, data security, transparency, and high costs persist. AI is poised to advance sustainability by optimizing resource use, enhance food security through predictive analytics of crop yields, and drive innovation in personalized nutrition and supply chain automation, ensuring tailored products and efficient delivery. This paper underscores AI's transformative potential in the food industry while addressing the obstacles to its widespread adoption.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.