ReviewFood engineering reviews2022
Application of Artificial Intelligence in Food Industry-a Guideline.
Review in Food engineering reviews, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 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
38 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pooled it
- Artificial Intelligence for Food Safety and Quality Assurance: Technologies, Applications and Future Directions.Food science & nutrition · 2026Review
- What Makes an AI Persuasive? The Interaction Effect of AI Shopping Assistants and Algorithmic Recommendation Cues on Consumers' Organic Food Purchase Intention.Foods (Basel, Switzerland) · 2026Article
- Cost-Cutting or Trust Building: Consumer Motive Inference and Purchase Intention Toward AI-Produced Food.Foods (Basel, Switzerland) · 2026Article
- Hybrid Decoding with Co-Occurrence Awareness for Fine-Grained Food Image Segmentation.Foods (Basel, Switzerland) · 2026Article
- Exploring the broad spectrum of machine learning technologies in the food sector: A comprehensive review of techniques and practical applications.Current research in food science · 2026Review
- Artificial Intelligence in Religious Certification: A Comprehensive Review of Halal Digitalization, Compliance Integrity, and Future Directions.International journal of food science · 2026Review
- AI technologies shaping the future of the cocoa industry from farm to fork: a comprehensive review.Food science and biotechnology · 2025Review
- Adaptive Machine Learning for Electronic Nose-Based Forensic VOC Classification.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- bFuzzy logic-based approach for porcine DNA determination in meat products.NPJ science of food · 2025Article
- Advances in Food Quality Management Driven by Industry 4.0: A Systematic Review-Based Framework.Foods (Basel, Switzerland) · 2025Review
- A Review of Processing, Marketing, and Demographic Influence on Consumer Perception of Pulse Milk- Insights From Traditional and AI-Facilitated Research.Journal of food science · 2025Review
- Artificial Intelligence-Driven Recommendations and Functional Food Purchases: Understanding Consumer Decision-Making.Foods (Basel, Switzerland) · 2025Article
- Artificial Intelligence in Agro-Food Systems: From Farm to Fork.Foods (Basel, Switzerland) · 2025Review
- 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
- Revolutionizing the food industry: The transformative power of artificial intelligence-a review.Food chemistry: X · 2024Review
- Multivariate Modelling Based on Isotopic, Elemental, and Fatty Acid Profiles to Distinguish the Backyard and Barn Eggs.Foods (Basel, Switzerland) · 2024Article
- Is AI Food a Gimmick or the Future Direction of Food Production?-Predicting Consumers' Willingness to Buy AI Food Based on Cognitive Trust and Affective Trust.Foods (Basel, Switzerland) · 2024Article
- The Application of Multi-Parameter Multi-Modal Technology Integrating Biological Sensors and Artificial Intelligence in the Rapid Detection of Food Contaminants.Foods (Basel, Switzerland) · 2024Article
- Causal Artificial Intelligence Models of Food Quality Data.Food technology and biotechnology · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) has embodied the recent technology in the food industry over the past few decades due to the rising of food demands in line with the increasing of the world population. The capability of the said intelligent systems in various tasks such as food quality determination, control tools, classification of food, and prediction purposes has intensified their demand in the food industry. Therefore, this paper reviews those diverse applications in comparing their advantages, limitations, and formulations as a guideline for selecting the most appropriate methods in enhancing future AI- and food industry-related developments. Furthermore, the integration of this system with other devices such as electronic nose, electronic tongue, computer vision system, and near infrared spectroscopy (NIR) is also emphasized, all of which will benefit both the industry players and consumers
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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.