Pedon

Seed a profile three ways:

• Fixture – pick one of the 44 canonical profiles (31 WRB reference soil groups + 13 SiBCS ordens). These are the same fixtures the test suite uses, so they are guaranteed to classify cleanly.
• Upload CSV – one row per horizon. Columns are matched against the canonical horizon schema; unknown columns are kept, missing ones are filled with NA. A starter CSV is available from the sidebar.
• Blank – start from an empty template and build the profile by hand.

Every horizon cell is editable in place – click a cell, type, press Enter. The depth-profile plot on the right updates live; switch the plotted attribute with the dropdown. When the table looks right, fill in the site metadata (ID, latitude, longitude, country, parent material) and press Build / update pedon.

Classify

Runs WRB 2022, SiBCS 5 and USDA Soil Taxonomy 13 side-by-side. Each result card shows the full classification name, the bare RSG / order, the principal and supplementary qualifiers, and the provenance-aware evidence grade.

The Decision detail panel exposes:

• Key trace – every RSG tested, in key order, with pass / fail / indeterminate status. Failed and passed rows are colour-coded.
• Ambiguities – RSGs that nearly satisfied; useful hints for follow-up measurement.
• Missing data – attributes whose measurement would refine or resolve the result.

Photo

Drives the vision-language extraction pipeline. A profile photograph yields Munsell colour per horizon; a field-sheet image yields site metadata. The taxonomic key is never delegated to a model – extraction only fills the PedonRecord.

The default Demo (mock) provider returns a canned, schema-valid response so the pipeline runs offline with no API key. To use a live model, configure an ellmer chat object before launching:

options(soilKey.vlm_chat = ellmer::chat_anthropic())
run_classify_app()

Spectra

Attach a Vis-NIR spectrum (one row per horizon, one column per wavelength) and gap-fill missing horizon attributes against the Open Soil Spectral Library. Filled values enter the provenance ledger tagged predicted_spectra. The first gap-fill downloads an OSSL cache, which needs network access.

Spatial

Queries a SoilGrids “MostProbable WRB” raster around the profile coordinates and reports the spatial distribution of reference soil groups – a prior to sanity-check the deterministic classification against. Point the Raster path or URL field at a SoilGrids GeoTIFF, or set a local raster for demos:

options(soilKey.test_raster = "/path/to/a/wrb_raster.tif")

Uncertainty

A Monte-Carlo robustness analysis: each run perturbs texture, pH and organic carbon within typical analytical error, then re-classifies. The robustness percentage tells you how often the class holds; the bar chart shows which alternative classes the profile flipped to. (From v0.9.100 this tab upgrades to a provenance-weighted posterior distribution.)

Report

Downloads a self-contained cross-system report (WRB / SiBCS / USDA plus the horizon table and provenance log) as HTML or PDF. PDF needs a working LaTeX install; if it is missing, the app falls back to HTML and tells you.

Settings

Sets the diagnostic engine (soilKey strict thresholds vs. aqp regional tolerance), the WRB Tier-3 strict-mode toggle, and the missing-data policy. These choices propagate to every classification run in the app.