ReviewHeliyon2023
Detection and prevention of foreign material in food: A review.
Review in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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
14 citing papers in PubMed.
- The Role of Artificial Intelligence and Machine Learning in Revolutionizing Probiotic Research.Microorganisms · 2026Review
- Fully Quantized Training vs. Post-Training Quantization for a Small Hyperspectral Transformer Model for Pixel-Level Foreign Plastic Object Classification.Sensors (Basel, Switzerland) · 2026Article
- Beyond the Status Quo: Particulate Matter Standards in Oral Dosage Forms.Journal of xenobiotics · 2026Review
- Parameter- and Compute-Efficient Spatial-Spectral Transformer Framework for Pixel-Level Classification of Foreign Plastic Objects on Broiler Meat Using NIR-Hyperspectral Imaging.Sensors (Basel, Switzerland) · 2026Article
- Non-destructive detection of micro-impurities in tea using the YOLOv11-PFT model.NPJ science of food · 2026Article
- Identification of factors associated with foreign substance contamination in restaurant food.Scientific reports · 2025Article
- The Piggy Solution: Harnessing Food Waste for Sustainable Hog Farming.Global challenges (Hoboken, NJ) · 2025Review
- Airport-FOD3S: A Three-Stage Detection-Driven Framework for Realistic Foreign Object Debris Synthesis.Sensors (Basel, Switzerland) · 2025Article
- Application of Bioinformatics and Machine Learning Tools in Food Safety.Current nutrition reports · 2025Review
- Deep Learning Model Compression and Hardware Acceleration for High-Performance Foreign Material Detection on Poultry Meat Using NIR Hyperspectral Imaging.Sensors (Basel, Switzerland) · 2025Article
- Advancements in Intelligent Sensing Technologies for Food Safety Detection.Research (Washington, D.C.) · 2025Review
- Detection of Low-Density Foreign Objects in Infant Snacks Using a Continuous-Wave Sub-Terahertz Imaging System for Industrial Applications.Sensors (Basel, Switzerland) · 2024Article
- Near-field microwave sensing technology enhanced with machine learning for the non-destructive evaluation of packaged food and beverage products.Scientific reports · 2024Article
- Dual imaging technique for a real-time inspection system of foreign object detection in fresh-cut vegetables.Current research in food science · 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
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This review highlights the critical concern foreign material contamination poses across the food processing industry and provides information on methods and implementations to minimize the hazards caused by foreign materials. A foreign material is defined as any non-food, foreign bodies that may cause illness or injury to the consumer and are not typically part of the food. Foreign materials can enter the food processing plant as part of the raw materials such as fruit pits, bones, or contaminants like stones, insects, soil, grit, or pieces of harvesting equipment. Over the past 20 years, foreign materials have been responsible for about one out of ten recalls of foods, with plastic fragments being the most common complaint. The goal of this paper is to further the understanding of the risks foreign materials are to consumers and the tools that could be used to minimize the risk of foreign objects in foods.
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.