ArticleFood chemistry: X2023
Comparison of a portable Vis-NIR hyperspectral imaging and a snapscan SWIR hyperspectral imaging for evaluation of meat authenticity.
Article in Food chemistry: X, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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.
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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
9 citing papers in PubMed.
- AI-Driven Nondestructive Measurement Technologies for Meat Quality and Safety: A Review.Foods (Basel, Switzerland) · 2026Review
- Hyperspectral-Imaging-Based ECNN-1D for Accurate Origin Classification of Fragrant Pears.Foods (Basel, Switzerland) · 2026Article
- Non-destructive quality assessment and species identification of blood tofu using portable visible/near-infrared spectroscopy.Frontiers in nutrition · 2026Article
- Non-Destructive Detection of Soybean Storage Quality Using Hyperspectral Imaging Technology.Molecules (Basel, Switzerland) · 2025Article
- Short-Wave Infrared Hyperspectral Image-Based Quality Grading of Dried Laver (Foods (Basel, Switzerland) · 2025Article
- Non-destructive identification of commercial jerky types based on multi-band hyperspectral imaging with machine learning.Food chemistry: X · 2025Article
- Application of machine learning approach on halal meat authentication principle, challenges, and prospects: A review.Heliyon · 2024Review
- Hyperspectral imaging-based erythema classification in atopic dermatitis.Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI) · 2024Article
- A Performance Evaluation of Two Hyperspectral Imaging Systems for the Prediction of Strawberries' Pomological Traits.Sensors (Basel, Switzerland) · 2023Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The performance of visible-near infrared hyperspectral imaging (Vis-NIR-HSI) (400-1000 nm) and shortwave infrared hyperspectral imaging (SWIR-HSI) (1116-1670 nm) combined with different classification and regression (linear and non-linear) multivariate methods were assessed for meat authentication. In Vis-NIR-HSI, total accuracies in the prediction set for SVM and ANN-BPN (the best classification models) were 96 and 94 % surpassing the performance of SWIR-HSI with 88 and 89 % accuracy, respectively. In Vis-NIR-HSI, the best-obtained coefficient of determinations for the prediction set (R
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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.