Coffee evidence can pass from farms and producer groups through cooperatives, washing stations, mills, warehouses, exporters, and importers before it reaches one shipment. The practical challenge is to preserve lot identity and plot coverage through aggregation while keeping supplier statements, source files, calculations, open gaps, and reviewer decisions attributable.
A practical preparation workflow
- 1
Define the shipment, product, role, and upstream lot structure.
- 2
Connect producers and plot versions through cooperative, mill, and export records.
- 3
Reconcile aggregation, quantity, date, and evidence gaps before DDS handoff.
Define the shipment and its upstream lot model
Begin with the commercial shipment, product description, candidate CN code, quantity, importer or operator role, exporter, supplier, and delivery documents. Then identify the lot identifiers used by cooperatives, mills, warehouses, and exporters. The same physical coffee may receive new references at several handoffs, so record how each downstream lot maps to its immediate upstream inputs instead of assuming identical labels across organizations.
Keep producer identity separate from plot identity
A producer, farm, production unit, and plot are not interchangeable identifiers. Preserve the supplier’s original references and create stable internal links among those objects. For each plot file, record the source version, geometry identifier, producer association, country, and the lot or collection period that relies on it. When several producers share a name or one producer manages several plots, unresolved identity matches should remain explicit issues.
Trace aggregation through cooperatives and mills
Coffee is routinely combined during collection, processing, storage, and export preparation. Capture each merge or split with dated records, input lots, output lots, quantities, organization, and supporting document. The objective is not to pretend every bean remains individually identifiable; it is to make the declared traceability model, its evidence, and any remaining uncertainty visible enough for a reviewer to challenge and reproduce.
Reconcile quantities, dates, and production periods
Compare producer deliveries, cooperative receipts, processing outputs, warehouse movements, export lots, invoices, and packing data. Differences can arise from moisture loss, processing yield, unit conversion, rejected material, or simple data errors. Record the explanation and source rather than changing a number until totals match. Production period and transaction dates should remain connected to the lot and plot evidence they qualify.
Validate plot coverage and investigate missing links
Run bounded structural and geometry checks on submitted GeoJSON or converted files, then verify that each plot belongs to the intended producer and production flow. A complete-looking map can still omit suppliers or contain duplicated, swapped, or unrelated boundaries. Compare the supplier and lot roster with the set of plot associations and turn missing coverage, ambiguous IDs, and unsupported geometry into named follow-up tasks.
Prepare a reviewable DDS handoff
Freeze the source files, confirmed facts, plot versions, transformation links, outstanding issues, and rule versions selected for the filing snapshot. The submission bundle should let an authorised person transfer the prepared fields without reconstructing the case, while the fuller Filing Pack preserves provenance and accepted limitations. New supplier evidence or corrected mappings should produce a new version and a rerun of affected checks.
What to check
- Producer and cooperative identity
- Lot-to-shipment mapping
- Plot completeness
- Production country and period
Filovara does not verify farmer identity or replace due-diligence decisions.
Questions teams ask
How should aggregated coffee lots be represented?
Record each dated split or merge, its input and output lot identifiers, quantities, organization, and source evidence. Keep any unsupported allocation or quantity difference visible.
Is a complete producer list enough without plot associations?
No. Producer identity and plot identity are separate. Review whether the relevant upstream lots have the required, correctly associated production-location evidence.
Can the workflow verify a farmer’s identity?
No. It can preserve supplied identity evidence, source references, conflicts, and confirmations, but authentication and due-diligence conclusions remain human responsibilities.
What happens when a supplier corrects a plot file?
Retain the original, create a new version, validate it again, update affected associations, and generate a new filing snapshot if the selected evidence changes.