UNSPSC 10312103: Fresh cut tuberosa asclepia

Fresh cut bloom of the tuberosa variety of asclepias

UNSPSC 10312103 Fresh cut tuberosa asclepia is a Commodity code that state and local governments are soliciting under for ornamental plant materials and floral supplies, though recent opportunities tagged to this code show significant divergence from the nominal commodity name. The code's actual procurement activity encompasses hanging flower baskets, general plant purchases, and educational supplies catalogs rather than the specific tuberosa asclepia species the code nominally names. Issuing bodies span county parks and recreation divisions, city procurement offices, and regional education service centers operating cooperative purchasing vehicles. Los Alamos County in New Mexico and the City of Dallas in Texas have posted recent solicitations for plant materials and maintenance services; Region 7 Purchasing Cooperative, a Texas education service center, solicited educational activities and supplies under a multi-year catalog discount bid serving multiple school districts.

Geographic activity concentrates in Texas and New Mexico based on recent postings. Representative opportunities include Los Alamos County's RFP26-55 for design, installation, and maintenance of up to 144 hanging flower baskets on Central Avenue and Knecht, 15th, and 20th Streets, with proposals due June 4, 2026 and contract award targeted for July 14, 2026; the City of Dallas's Informal Solicitation 215260 for plant purchases with delivery to 1775 California Crossing Road, Suite 100, due February 3, 2026; and Region 7 Purchasing Cooperative's EDACT2628 catalog discount bid for educational activities and supplies from multiple school districts, with proposals due July 30, 2026 and an estimated two-year contract value of $40.677 billion from August 20, 2026 through August 20, 2028. The code shows light activity overall, and the mismatch between the nominal commodity (tuberosa asclepia) and the work actually being solicited suggests potential tagging inconsistency in the underlying opportunity data.