ReviewFood science & nutrition2025
Recent Advances in Spectroscopy and Imaging Techniques for Nondestructive Detection of Meat Quality and Safety.
Review in Food science & nutrition, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 6 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
6 citing papers in PubMed.
- Intelligent Responsive Nanostructures Toward Food Preservation: Synergizing Antibacterial Activity and Environmental Regulation.Foods (Basel, Switzerland) · 2026Review
- Quality Assessment in Frozen Seafood: Advances in Sensing Technologies and Artificial Intelligence.Foods (Basel, Switzerland) · 2026Review
- AI-Driven Nondestructive Measurement Technologies for Meat Quality and Safety: A Review.Foods (Basel, Switzerland) · 2026Review
- Impact of Freezing on the Nanoarchitecture and Techno-Functional Properties of Camel Myofibrillar Proteins: Insights From Atomic Force Microscopy.Food science & nutrition · 2026Article
- Simultaneous Assessment of Chicken Freshness and Authenticity Using a Single Multispectral Imaging Device: A Cross-Laboratory Evaluation Using Identical Instruments.Sensors (Basel, Switzerland) · 2026Article
- Recent Advances in Spectroscopy and Imaging Techniques for Nondestructive Detection of Meat Quality and Safety.Food science & nutrition · 2025Review
Corrections and comments
- Erratum issued
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Meat is one of the most important foods in the human diet and is a major source of animal protein. It is essential to detect meat quality and safety for ensuring that high-quality foods are delivered to consumers. Advanced spectroscopic techniques (near-infrared spectroscopy, Raman spectroscopy, fluorescence spectroscopy, and terahertz spectroscopy) and imaging techniques (hyperspectral imaging, multispectral imaging, X-ray imaging, and thermal imaging) provide feasible means for testing organoleptic properties, chemical composition, physicochemical properties, and safety indicators of meat. This review aimed to summarize the latest developments of spectroscopic and imaging techniques for meat quality and safety detection. The principles, multi-scenario applications, advantages, disadvantages, and future prospects of these techniques are discussed. Spectroscopic techniques have been demonstrated to accurately detect changes in the chemical constituents and physical properties of meat, but can only perceive localized sample information. Imaging techniques provide visual information on the spatial distribution as well as physical and chemical characteristics of meat, but have a slower detection rate. Despite the remarkable outcomes attained by spectroscopy and imaging techniques in laboratory settings, their industrial applications remain encumbered by challenges, including substantial expenses and intricate data analysis procedures. In order to improve the comprehensiveness and accuracy of detection, future research directions might focus on the integration of multiple techniques combined with deep learning algorithms.
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.