Chemical Fingerprinting of Raicilla Beverage Using Spectroscopy and Chromatography

Chemical analysis data for Raicilla, a traditional Mexican distilled beverage. The dataset includes physicochemical parameters, Fourier Transform Near-Infrared Spectroscopy (FT-NIR) spectra, and results from Solid-Phase Microextraction Gas Chromatography–Mass Spectrometry (HS-SPME-GC–MS). It was created by Magdiel Pablo-Cano and last updated in May 2026.

Use Cases

• Discriminate beverage samples by production process based on FT-NIR spectral data.
• Identify volatile compounds contributing to sensory attributes based on 35 compounds identified via HS-SPME-GC–MS.
• Differentiate samples by botanical origin of the agave raw material using multivariate analysis.
• Relate chemical profiles to geographical origin and agave species through physicochemical parameters.

Strengths

• Data from multiple analytical techniques (FT-NIR and HS-SPME-GC–MS) for cross-validation.
• Identification of 35 volatile compounds contributing to sensory attributes.
• Application of uni- and multivariate statistical methods for pattern recognition.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The dataset is small in scale at 404.8 KB, indicating limited scope.

Provenance

Source

Magdiel Pablo-Cano via figshare

Collection Method

Analysis of Raicilla samples using physicochemical measurements, FT-NIR spectroscopy, and HS-SPME-GC–MS.

Freshness

Last updated 2026-05-27 05:03:34; freshness should be verified.

Geography

Mexico (implied by focus on Raicilla)