ReviewFoods (Basel, Switzerland)2025
Machine Learning for Quality Control in the Food Industry: A Review.
Review in Foods (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 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
20 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
- Food Intelligent Quality and Safety Analysis: From Data-Driven to Data-Mechanism Hybrid-Driven Paradigm.Foods (Basel, Switzerland) · 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
- Beyond Mixed Utilization: Fractionation, Functional Divergence, and Precision Applications of Soybean 7S and 11S Globulins.Comprehensive reviews in food science and food safety · 2026Review
- Extruded Pseudocereal Snacks Mathematical Modelling Approaches for Prediction and Optimisation: A Review.Foods (Basel, Switzerland) · 2026Review
- A Review of Machine Learning and AI Applications in Enhancing HACCP Systems for Ice Cream Manufacturing.Foods (Basel, Switzerland) · 2026Review
- Self-Powered Triboelectric Nanogenerators in Intelligent Food Packaging: Recent Advances and Applications.Small (Weinheim an der Bergstrasse, Germany) · 2026Review
- AI-Driven Nondestructive Measurement Technologies for Meat Quality and Safety: A Review.Foods (Basel, Switzerland) · 2026Review
- Machine learning-based prediction and quality control of meat and meat products: applications for intelligent quality management in the meat industry.Food science of animal resources · 2026Review
- Feasibility of Hyperspectral Imaging and Machine Learning for Rapid Prescreening of Aflatoxin BToxins · 2026Article
- Precision Livestock Farming and Biomedical Engineering: Assessing Feed Quality, Animal Health, and Behavior Using Machine Learning for Sensor Data.Sensors (Basel, Switzerland) · 2026Review
- Cost-Cutting or Trust Building: Consumer Motive Inference and Purchase Intention Toward AI-Produced Food.Foods (Basel, Switzerland) · 2026Article
- Industrial internet data management framework with blockchain integration for data integrity assurance and access control resolution.Scientific reports · 2026Article
- Valorization of Plant-Based Food By-Products Through Green Extraction of Bioactive Compounds for Functional Food.Molecules (Basel, Switzerland) · 2026Review
- Multimodal AI for Real-Time Food Safety and Quality: From Sensors to Foundation Models, Edge Deployment, and Regulation.Food science & nutrition · 2026Review
- Artificial intelligence in bread making: Applications in quality control, formulation and sensory prediction.Food chemistry: X · 2026Review
- Artificial Intelligence in Religious Certification: A Comprehensive Review of Halal Digitalization, Compliance Integrity, and Future Directions.International journal of food science · 2026Review
- AI virtual streamers in sustainable food marketing: how expertise, interactivity, and anthropomorphism shape consumer acceptance of upcycled foods.Frontiers in nutrition · 2026Article
- Artificial intelligence-driven food and nutrition systems: from smart food production to personalized nutrition.Frontiers in nutrition · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The increasing complexity of modern food production demands advanced solutions for quality control (QC), safety monitoring, and process optimization. This review systematically explores recent advancements in machine learning (ML) for QC across six domains: Food Quality Applications; Defect Detection and Visual Inspection Systems; Ingredient Optimization and Nutritional Assessment; Packaging-Sensors and Predictive QC; Supply Chain-Traceability and Transparency and Food Industry Efficiency; and Industry 4.0 Models. Following a PRISMA-based methodology, a structured search of the Scopus database using thematic Boolean keywords identified 124 peer-reviewed publications (2005-2025), from which 25 studies were selected based on predefined inclusion and exclusion criteria, methodological rigor, and innovation. Neural networks dominated the reviewed approaches, with ensemble learning as a secondary method, and supervised learning prevailing across tasks. Emerging trends include hyperspectral imaging, sensor fusion, explainable AI, and blockchain-enabled traceability. Limitations in current research include domain coverage biases, data scarcity, and underexplored unsupervised and hybrid methods. Real-world implementation challenges involve integration with legacy systems, regulatory compliance, scalability, and cost-benefit trade-offs. The novelty of this review lies in combining a transparent PRISMA approach, a six-domain thematic framework, and Industry 4.0/5.0 integration, providing cross-domain insights and a roadmap for robust, transparent, and adaptive QC systems in the food industry.
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.