Unit of Measure (UoM or pack size) Guidelines

The Unit of Measure, or UoM, is a familiar concept for produce markets. However, in local markets, there is tremendous variability in count, weight, and packing containers that makes product comparisons and aggregation difficult. This variability also makes it challenging for local and regional producers to integrate with mainstream purchasing systems because purchasers lack sufficient information to guarantee that the product meets client needs. For example, kale and other leafy greens may be sold in bunches, or loose in a bag or case. If a food hub or school food buyer are trying to source 100 pounds of kale, this variation in unit of measure can make it difficult for these buyers to know how many units to order. Further, variability in UoM information makes market analysis challenging, as sector level prices per unit are almost impossible to pin down. This stands in contrast to mainstream produce markets where sector level pricing information is available for most commodities.

In the absence of uniformity for local and specialty products, the strategy of the data guidelines is to provide complete data on all four fields for UoM rather than just one or two: count, unit, weight, and case size. While a departure from typical UoM record keeping, providing four data points allows distributors and buyers a more complete picture that includes variation they might expect in a product, and instills greater confidence that the product will meet their need and expectation. Further adapting those entries to account for variability by providing a range or estimate (e.g. 10-12 oz, 50-60 count) gives even greater insight into the product characteristics and allows for better comparison of products across market channels.

The Market Data Guidelines for Produce in Regional Food Systems were developed through a collaboration among USDA AMS Local and Regional Food Systems, Wolfe’s Neck Center for Agriculture and the Environment, and the International Center for Food Ontology Operability Data and Semantics. Funding was provided through USDA AMS Cooperative agreement #22-TMMSD-ME-0002.