Advanced Mathematical Models & Applications

Ensuring transparency and traceability in horticultural supply chains is difficult due to complex logistics, seasonal variability, and multiple intermediaries. We propose a framework that couples b-local irregular vertex coloring (b-LIVC) with a blockchain architecture to enable end-to-end verification of production and trade. On the Jember Regency subdistrict graph, we compute the b-local irregular chromatic number and obtain X_b-lis(J)=6, yielding six planting color classes that schedule sowing and harvests to distribute output across the year. The local irregularity induces distinct neighborhood weights, which we use as cryptographic features for unique, verifiable batch identifiers. We implement the pipeline on a public blockchain: harvest lots are tokenized as video NFTs with QR links to a verification page and on-chain records. The integration of discrete mathematics and distributed ledgers provides auditable provenance and transaction history, practical scheduling that reduces harvest clustering, and a low-overhead mechanism for farmer-level transparency.