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Abstract
As more individuals use plant-derived products as prophylactic and therapeutic remedies, the herbal medicine market continues to grow rapidly. This trend shows the need for more advanced analytical methods, such as spectral “fingerprinting” – creating spectrum with a distinctive pattern, which is further used as a unique identifier for a plant.
The dataset was generated using Fourier-transform infrared spectroscopy with attenuated total reflectance (FTIR-ATR) to produce distinctive spectral fingerprints of Latvian medicinal plants: red and white clover, purple coneflower, cowslip, common jasmine, sandy everlasting, horse chestnut, pot marigold, chamomile, coltsfoot, common daisy, elderberry, cornflower, Jerusalem artichoke, fireweed, common and Midland hawthorn, small-leaved and large-leaved lime, yarrow, and meadowsweet.
The samples were obtained from ten Latvian herbal medicine producers, along with one additional sample collected independently by Riga Stradiņš University researchers. The analytical method requires minimal sample preparation, involving only the grinding of medicinal plants into fine powder.
The research yielded 329 spectra, each corresponding to a distinct species of medicinal plant, which are sorted in 19 CSV files. These files contain spectral data suitable for various applications, including chemical characterization, species classification, and quality control. In addition, the dataset can be used for multivariate data analysis or chemometrics and will allow for signal processing and spectroscopic data handling.
The dataset was generated using Fourier-transform infrared spectroscopy with attenuated total reflectance (FTIR-ATR) to produce distinctive spectral fingerprints of Latvian medicinal plants: red and white clover, purple coneflower, cowslip, common jasmine, sandy everlasting, horse chestnut, pot marigold, chamomile, coltsfoot, common daisy, elderberry, cornflower, Jerusalem artichoke, fireweed, common and Midland hawthorn, small-leaved and large-leaved lime, yarrow, and meadowsweet.
The samples were obtained from ten Latvian herbal medicine producers, along with one additional sample collected independently by Riga Stradiņš University researchers. The analytical method requires minimal sample preparation, involving only the grinding of medicinal plants into fine powder.
The research yielded 329 spectra, each corresponding to a distinct species of medicinal plant, which are sorted in 19 CSV files. These files contain spectral data suitable for various applications, including chemical characterization, species classification, and quality control. In addition, the dataset can be used for multivariate data analysis or chemometrics and will allow for signal processing and spectroscopic data handling.
| Original language | English |
|---|---|
| Article number | 112378 |
| Journal | Data in Brief |
| Volume | 64 |
| DOIs | |
| Publication status | Published - Feb 2026 |
Keywords*
- Fingerprinting
- chemical profiling
- plant identification
- medicinal plants
- plant characterization
Field of Science*
- 3.1 Basic medicine
Publication Type*
- 1.1. Scientific article indexed in Web of Science and/or Scopus database
Fingerprint
Dive into the research topics of 'Latvian Herbal Medicines Under the Infrared Lens: An FTIR-ATR Dataset'. Together they form a unique fingerprint.Projects
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BBCE: Baltic Biomaterials Centre of Excellence, Phase II
Ločs, J. (Project leader), Bandere, D. (Leading expert), Logviss, K. (Work package leader), Brangule, A. (Partner's coordinator), Krūmiņa, J. (Work package leader), Bārzdiņa, A. (Expert (PhD student)), Prudņikova, D. P. (Assistant (student)) & Teterovska, R. (Expert)
1/01/20 → 31/12/26
Project: EU Programmes › Horizon 2020