Majid Farhadloo

Fine-grain spatial information may enhance the value of turfgrass cultivar data

By Majid Farhadloo, and Shashi Shekhar, Department of Computer Science, University of Minnesota

Two graphs with color coding showing turfgrass quality in the first graph and the plot randomization in the second graph.

Thanks to NTEP-DB 1.0 [1], the relational database we created for the National Turfgrass Evaluation Program (NTEP), obtaining turfgrass cultivars' data will soon be much easier. In addition, a user-friendly web application by U-Spatial allows homeowners, researchers, and other stakeholders to extract meaningful information from NTEP data in a variety of formats.  For example, retailers can learn the best cultivars to stock in different store locations around the country.

New tools simplify searching for suitable turfgrass using the NTEP data

Entity relationship model for NTEP database

By Yiqun Xie, Majid Farhadloo, Shashi Shekhar, and Len Kne; University of Minnesota

Suppose you have to choose a turfgrass for your lawn. How would you shop for grass seed suitable for your lawn? Would you like to have convenient search and recommendation facilities similar to those available for buying consumer products at e-commerce sites such as amazon.com?

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