For over forty years, the National Turfgrass Evaluation Program (NTEP) has coordinated trials and collected data on turfgrass traits from multiple species and sites across the U.S. and Canada. These trials are used worldwide for turfgrass cultivar improvement, sales and selection by everyone from researchers to turfgrass professionals to hobbyist turfgrass managers. However, using the NTEP web site (www.ntep.org), consisting of static, PDF or HTML-based tables to select grasses does not allow for customized results based on geography, specific site conditions or management levels. Therefore, the identification of sustainable turfgrasses within NTEP data is currently difficult and in need of improvement.A USDA Specialty Crop Research Initiative (SCRI) grant provided funding for the development of a relational database structure, which then allowed for the creation of an improved mechanism to select and customize NTEP reports. The University of Minnesota, in cooperation with NTEP, has recently developed a user interface to search and publish customized reports of NTEP data. These data can now be summarized based on specific locations, site parameters, management levels and other criteria important in identifying and selecting sustainable grasses. This database and user interface (version 1.0) will soon be available through the NTEP web site.The National Turfgrass Evaluation Program (NTEP) is an internationally recognized repository of turfgrass cultivar information. Starting in 1980, NTEP data has been collected from multiple locations across North America. Summarized results are made freely available via its web site, www.ntep.org. NTEP trials are typically conducted for four to five years, with reports published annually along with a final summary at the trial's conclusion. NTEP collects data on characteristics such as monthly turfgrass quality, genetic color, leaf texture and spring greenup, as well as response to various stresses such as shade, drought, cold, diseases, insects
IntroductionTraditional evaluation procedure in National Turfgrass Evaluation Program (NTEP) relies on visually assessing replicated turf plots at multiple testing locations. This process yields ordinal data; however, statistical models that falsely assume these to be interval or ratio data have almost exclusively been applied in the subsequent analysis. This practice raises concerns about procedural subjectivity, preventing objective comparisons of cultivars across different test locations. It may also lead to serious errors, such as increased false alarms, failures to detect effects, and even inversions of differences among groups.MethodsWe reviewed this problem, identified sources of subjectivity, and presented a model-based approach to minimize subjectivity, allowing objective comparisons of cultivars across different locations and better monitoring of the evaluation procedure. We demonstrate how to fit the described model in a Bayesian framework with Stan, using datasets on overall turf quality ratings from the 2017 NTEP Kentucky bluegrass trials at seven testing locations.ResultsCompared with the existing method, ours allows the estimation of additional parameters, i.e., category thresholds, rating severity, and within-field spatial variations, and provides better separation of cultivar means and more realistic standard deviations.DiscussionTo implement the proposed model, additional information on rater identification, trial layout, rating date is needed. Given the model assumptions, we recommend small trials to reduce rater fatigue. For large trials, ratings can be conducted for each replication on multiple occasions instead of all at once. To minimize subjectivity, multiple raters are required. We also proposed new ideas on temporal analysis, incorporating existing knowledge of turfgrass.
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