🍯 Blockchain Traceability for Honey and Hive Products

About this simulation

A honey batch travels down a six-stage supply chain — Hive → Extraction → Bottling → Distribution → Retail → Consumer. At every hand-off, a record is written and linked into a chain of blocks floating above the line. This models what a blockchain-based traceability system actually does: it doesn't taste the honey or see the bees — it just makes the paper trail between hand-offs very hard to quietly rewrite.

How it works

• Each arrival at a station appends a block, hash-linked to the one before it (in blockchain mode).
• Tamper with a past record — attacks an already-written block. On a blockchain, every block downstream depends on the previous one's hash, so the rewrite is detected and rejected. On a centralized database, one party can just edit the row — silently, with no trace.
• Inject adulterated batch — simulates a real fraud case: a batch is stretched with cheap syrup, but its paperwork still claims pure honey. The ledger faithfully records whatever it's told — it cannot taste the honey.
• Lab / isotope test at bottling — represents the physical testing (e.g. carbon isotope ratio, pollen analysis) that actually catches adulteration. Only this — not the ledger — can flag a fraudulent batch.

The takeaway

Blockchain secures the record of who-handed-off-what-when against quiet after-the-fact edits. It does nothing to verify that what was recorded was true in the first place — that still requires testing, audits, or trusted humans at the point of entry. For many small apiaries, a simpler tamper-evident log paired with real lab testing achieves the same fraud protection without the overhead of a distributed ledger.

Controls

• Flow speed — how fast batches move through the chain.
• Ledger type — switch between a blockchain and a plain centralized database to compare tamper resistance.
• ⚠ Tamper with a past record — attempts to secretly rewrite an existing block.
• Drag to rotate, scroll to zoom.