An integrated analytical dataset for eleven flue-cured tobacco cultivars combines sensory evaluation, biochemical characterization, and volatile organic compound (VOC) profiling. The data was generated by author Yanguo Ke and published on figshare in April 2026. Statistical analyses include hierarchical cluster analysis, partial least squares-discriminant analysis, and Spearman correlation to explore relationships between sensory attributes, biochemical components, and VOCs.
Use Cases
- Classifying tobacco cultivars based on volatile organic compound profiles using PLS-DA.
- Correlating biochemical components like total sugar and nitrogen with sensory attributes such as aroma quality and irritancy.
- Identifying key VOC markers for sensory traits like moistness and smoke concentration.
- Applying hierarchical cluster analysis to group cultivars by sensory or biochemical profiles.
Strengths
- Data integrates three analytical modalities: sensory evaluation, biochemical characterization, and VOC profiling.
- Analysis identifies 75 key VOCs as differentiators with VIP scores > 1.0.
- Dataset is published under a CC-BY-4.0 license, permitting reuse with attribution.
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 at 99.2 KB, indicating limited scope.
Provenance
- Source
- figshare
- Collection Method
- An integrated framework combining sensory evaluation, biochemical characterization, and VOC profiling applied to eleven cultivars.
- Time Range
- null
- Freshness
- Last updated 2026-04 05:45:34; freshness should be verified.
- Geography
- null