ArticleFood chemistry: X2024
FT-NIR combined with machine learning was used to rapidly detect the adulteration of pericarpium citri reticulatae (
Article in Food chemistry: X, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- AI-Driven Food Fraud Detection Systems: A Critical Systematic Review of the Detection-Prevention Gap.Foods (Basel, Switzerland) · 2026Review
- Integrated Flavoromics and Metabolomics Reveal Aroma and Bioactive Characteristics of Six Mainstream Citri Reticulatae Pericarpium Cultivars.Foods (Basel, Switzerland) · 2026Article
- CounterfeitFood science & nutrition · 2026Article
- A convenient method for the accurate identification of Citri Reticulatae Pericarpium using image and multi-stream.PloS one · 2026Article
- Traceability and Adulteration Analysis of Citri Reticulatae Pericarpium Based on "Digital Identity Card" and UHPLC-QTOF-MS Analysis.Food science & nutrition · 2025Article
- Quantitative Analysis of Peanut Skin Adulterants by Fourier Transform Near-Infrared Spectroscopy Combined with Chemometrics.Foods (Basel, Switzerland) · 2025Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Pericarpium citri reticulatae (PCR) has been used as a food and spice for many years and is known for its rich nutritional content and unique aroma. However, price increases are often accompanied by adulteration. In this study, two kinds of adulterants (Orange peel-OP and Mandarin Rind-MR) were identified by chromaticity analysis, FT-NIR and machine learning algorithm, and the doping concentration was predicted quantitatively. The results show that colorimetric analysis cannot completely differentiate between PCR and adulterants. Using spectral preprocessing combined with machine learning algorithms, PCR and two adulterants were successfully distinguished, with classification accuracy reaching 99.30 % and 98.64 % respectively. After selecting characteristic wavelengths, the R
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Registered trials
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