ArticleFoods (Basel, Switzerland)2024
The Potential Use of Near Infrared Spectroscopy (NIRS) to Determine the Heavy Metals and the Percentage of Blends in Tea.
Article 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 2 papers.
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Who cites it
2 citing papers in PubMed, 7 citations in OpenAlex.
- Digital Sensing for Comprehensive Tea Quality Evaluation: From Dry Tea to Tea Infusion and Infused Leaves.Comprehensive reviews in food science and food safety · 2026Review
- Application of Fourier Transform Near-Infrared Spectroscopy and Chemometrics for Quantitative Analysis of Milk of Lime (MOL) Used in the Sugar Industry.Molecules (Basel, Switzerland) · 2025Article
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Authors and funding
6 authors at 2 institutions in 2 countries.
Funding
Abstract
The following study analyzed the potential of Near Infrared Spectroscopy (NIRS) to predict the metal composition (Al, Pb, As, Hg and Cu) of tea and for establishing discriminant models for pure teas (green, red, and black) and their different blends. A total of 322 samples of pure black, red, and green teas and binary blends were analyzed. The results showed that pure red teas had the highest content of As and Pb, green teas were the only ones containing Hg, and black teas showed higher levels of Cu. NIRS allowed to predict the content of Al, Pb, As, Hg, and Cu with ratio performance deviation values > 3 for all of them. Additionally, it was possible to discriminate pure samples from their respective blends with an accuracy of 98.3% in calibration and 92.3% in validation. However, when the samples were discriminated according to the percentage of blending (>95%, 95-85%, 85-75%, or 75-50% of pure tea) 100% of the samples of 10 out of 12 groups were correctly classified in calibration, but only the groups with a level of pure tea of >95% showed 100% of the samples as being correctly classified as to validation.
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Registered trials
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