Chemometric Fingerprinting of Raicilla Using FT-NIR and GC-MS

A dataset containing chemometric fingerprints for Raicilla, a traditional Mexican distilled beverage. The data was generated by Magdiel Pablo-Cano using Fourier Transform Near-Infrared Spectroscopy (FT-NIR) and Solid-Phase Microextraction Gas Chromatography–Mass Spectrometry (HS-SPME-GC–MS) to analyze physicochemical parameters and volatile compounds. The dataset was last updated on 2026-05-27.

Use Cases

• Discriminate Raicilla samples based on elaboration process using FT-NIR spectra and PLS-DA models.
• Identify volatile compounds contributing to sensory attributes via HS-SPME-GC–MS analysis.
• Differentiate Raicilla based on the agave species used as raw material through multivariate analysis.
• Analyze compositional patterns associated with botanical origin and geographical provenance.

Strengths

• Dataset includes 35 identified volatile compounds contributing to sensory attributes.
• Analysis combines multiple techniques: physicochemical parameters, FT-NIR, and HS-SPME-GC–MS.
• Data is structured in a CSV format with a file size of 402.1 KB.

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

Magdiel Pablo-Cano via figshare

Collection Method

Data gathered through laboratory analysis of Raicilla samples using FT-NIR and HS-SPME-GC–MS.

Freshness

Last updated 2026-05-27 05:03:35; freshness should be verified.

Geography

Likely samples from Mexico, given the focus on Raicilla.