ReviewFoods (Basel, Switzerland)2024
NIR Sensing Technologies for the Detection of Fraud in Nuts and Nut Products: A Review.
Review in Foods (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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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.
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Who cites it
6 citing papers in PubMed.
- Quality Assessment in Frozen Seafood: Advances in Sensing Technologies and Artificial Intelligence.Foods (Basel, Switzerland) · 2026Review
- Next-Generation Harvester Technologies: Synergizing Smart Grading and Biomechanical Damage Control in Mechanized Tomato Production.Sensors (Basel, Switzerland) · 2026Review
- New Developments and Future Challenges of Non-Destructive Near-Infrared Spectroscopy Sensors in the Cheese Industry.Sensors (Basel, Switzerland) · 2026Review
- Food Fraud in Plant-Based Proteins: Analytical Strategies and Regulatory Perspectives.Foods (Basel, Switzerland) · 2025Review
- Towards Sustainable and Dynamic Modeling Analysis in Korean Pine Nuts: An Online Learning Approach with NIRS.Foods (Basel, Switzerland) · 2024Article
- Determination of leaf nitrogen content in apple and jujube by near-infrared spectroscopy.Scientific reports · 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
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Food fraud is a major threat to the integrity of the nut supply chain. Strategies using a wide range of analytical techniques have been developed over the past few years to detect fraud and to assure the quality, safety, and authenticity of nut products. However, most of these techniques present the limitations of being slow and destructive and entailing a high cost per analysis. Nevertheless, near-infrared (NIR) spectroscopy and NIR imaging techniques represent a suitable non-destructive alternative to prevent fraud in the nut industry with the advantages of a high throughput and low cost per analysis. This review collects and includes all major findings of all of the published studies focused on the application of NIR spectroscopy and NIR imaging technologies to detect fraud in the nut supply chain from 2018 onwards. The results suggest that NIR spectroscopy and NIR imaging are suitable technologies to detect the main types of fraud in nuts.
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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.