Regional Optimization of Roadside Turfgrass Seed Mixtures Phase 2: Regional Field Trials and Economic Analysis

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Regional Optimization of Roadside Turfgrass Seed Mixtures Phase 2: Regional Field Trials and Economic Analysis

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2022-07

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Minnesota Department of Transportation

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Report

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Our goal was to develop seed mixture recommendations to improve establishment and development of roadside vegetation in Minnesota. We selected 14 research sites across Minnesota and seeded 40 turfgrass mixtures. Turfgrass coverage was assessed at each site twice a year and the weed seed bank was examined. We found that greater seeded turfgrass species richness was important for increasing and stabilizing roadside turfgrass coverage across space. We also found differences in the type and density of the weed seed bank at many sites, but its impact was relatively low on weed coverage over time. We considered soil and weather variables and found three significant seeding clusters for Minnesota consisting of two geographical seeding clusters (north and central/south) and one non-geographical cluster for sites with poor soil quality. Three new mixtures for each cluster were recommended for Minnesota. Implementing these mixtures will reduce soil erosion, improve aesthetics, save local communities' financial resources, and improve the overall environment we occupy. As a complement to the field research, we developed cost prediction models that were incorporated into a detailed enterprise budget tool to calculate the roadside establishment costs that include labor, water, seed, sod, fertilizer, and other factors. This Excel-based tool can be used by local and state officials in determining budgets for roadside installations and which types or combinations of turfgrasses would be most cost effective, while also generating optimal performance.

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Watkins, Eric; Christensen, Dominic; Yue, Chengyan; Moncada, Kristine. (2022). Regional Optimization of Roadside Turfgrass Seed Mixtures Phase 2: Regional Field Trials and Economic Analysis. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/241776.

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