Wine Grape Leaf Trait and Reflectance Data for 180 Leaves

180 unique winegrape leaves with measured trait values and untransformed reflectance spectroscopy data. The dataset supports the 2025 manuscript "Predicting leaf traits in wine grapes with reflectance spectroscopy". It was authored by Rachel Mariani and harvested from the Borealis Dataverse platform.

Use Cases

• Train machine learning models to predict leaf traits based on spectral reflectance data.
• Analyze the relationship between raw spectral signatures and calculated physiological traits in wine grapes.
• Benchmark non-destructive spectroscopy methods against traditional, measured leaf trait values.

Strengths

• Includes data for 180 unique biological samples (winegrape leaves).
• Contains both raw measured trait values and untransformed reflectance data, allowing for methodological comparison.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment for large-scale modeling.

Provenance

Source

Borealis Harvested Dataverse

Collection Method

Data was collected for a research manuscript; the description mentions raw measured trait values and reflectance spectroscopy.

Freshness

Last updated 2026-04-25 04:16:57; freshness should be verified.