Chemical Fingerprinting of Raicilla Beverage Using Spectroscopy and Chromatography

35 volatile compounds were identified in Raicilla, a traditional Mexican distilled beverage, using gas chromatography-mass spectrometry. The dataset relates the chemometric fingerprint of samples to agave species, geographical origin, and manufacturing process through uni- and multivariate statistical methods. It was authored by Magdiel Pablo-Cano and last updated on 2026-05-27.

Use Cases

• Discriminate beverage samples by production process based on FT-NIR spectral data
• Identify compositional patterns associated with botanical origin from volatile compound profiles
• Model relationships between physicochemical parameters and sensory characteristics
• Develop classification models for beverage authentication based on chemical fingerprint

Strengths

• Data integrates results from two analytical techniques: Fourier Transform Near-Infrared Spectroscopy (FT-NIR) and Gas Chromatography–Mass Spectrometry
• Analysis enabled identification of 35 volatile compounds contributing to sensory attributes
• Multivariate statistical methods, including PLS-DA, were applied to the data

Limitations

• Row count is unknown, which may limit suitability assessment
• Column-level documentation is absent; field semantics must be inferred after download
• Description metadata is limited; actual data quality requires manual inspection after download

Provenance

Source

figshare

Collection Method

Chemometric analysis using FT-NIR spectroscopy and HS-SPME-GC–MS on Raicilla samples

Freshness

Last updated 2026-05-27 05:03:33; freshness should be verified

Geography

Mexico