Combining ion mobility spectrometry and chemometrics for detecting synthetic colorants in black tea: A reliable and fast method.

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

4 citing papers in PubMed.

1. Smart detection of juice adulteration: An approach based on ion mobility spectrometry and machine learning.Journal of the science of food and agriculture · 2026
   Article
2. Operational mechanisms and application advances in artificial olfactory systems.Biomedical engineering online · 2026
   Review
3. Honey adulteration detection using the HS-SPME-IMS technique combined with chemometric analysis.Food chemistry: X · 2025
   Article
4. Research on Rapid Detection Methods of Tea Pigments Content During Rolling of Black Tea Based on Machine Vision Technology.Foods (Basel, Switzerland) · 2024
   Article

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

Authors and funding

4 authors.

Funding

No grant is acknowledged in the PubMed record.

Abstract

Indexed as