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1 June 2013 Evaluating Multiple Rating Methods Utilized in Turfgrass Weed Science
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Abstract

Turfgrass weed scientists commonly use visual ratings (VR) to assign a numerical value to a turfgrass or weed response. These ratings lack quantifiable numerical values and are considered subjective. Alternatives to VR, including line intersect analysis (LIA) and digital image analysis (DIA), have been used to varying extents in turfgrass research. Alternatives can be expensive, labor intensive, and can require extensive calibration and increased time for data acquisition. Minimal research has been conducted evaluating rating methods used in turfgrass weed science. Trials were conducted in 2007 and 2008 to evaluate ratings methods used to quantify large crabgrass populations as influenced by tall fescue mowing height (2.5, 5.1, 7.6, and 10.2 cm). Percent large crabgrass cover was assessed utilizing VR, LIA, and DIA to determine if differences existed among evaluation methods. Pairwise comparisons, Pearson's correlation, and linear regression were performed to compare evaluations. All rating methods were significantly correlated to one another. Differences of large crabgrass cover estimates existed between LIA and DIA data at all mowing heights and between VR and DIA data at the 7.6 and 10.2 cm mowing heights in 2007. Authors believe that shadows produced by the turf canopy at higher (≥ 7.6 cm) mowing heights increased DIA estimates of large crabgrass cover. At trial initiation in 2007, researchers did not capture calibration images because the methodology to eliminate a shadow influence using a standard digital image had not been published. Additional DIA calibration in 2008 corrected for canopy shadows, and no differences were observed in large crabgrass cover between all evaluation methods indicated by nonsignificance pairwise comparisons and estimated regression parameters. These data indicate VR are no different than LIA or DIA in estimating large crabgrass cover as affected by tall fescue mowing height.

Nomenclature: Tenacity (mesotrione); large crabgrass, Digitaria sanguinalis (L.) Scop. DIGSA; tall fescue, Lolium arundinaceum (Schreb.) S. J. Darbyshire.

Los científicos de malezas en céspedes usan estimaciones visuales (VR) para asignar un valor numérico a las respuestas del césped o de la maleza. Estas estimaciones carecen de valores numéricos cuantificables y son consideradas subjetivas. Las alternativas a VR incluyen el análisis de intersección de líneas y análisis digital de imágenes (DIA), que han sido usados en diferentes niveles en la investigación en céspedes. Las alternativas pueden ser costosas, intensivas en labor, y pueden requerir una calibración extensiva e incrementos en el tiempo de adquisición de datos. La investigación que se ha realizado ha sido mínima para evaluar los métodos de evaluación usados en la ciencia de malezas en céspedes. Se realizaron estudios en 2007 y 2008 para evaluar los métodos de evaluación usados para cuantificar poblaciones de Digitaria sanguinalis a su vez que la influencia de la altura de poda en Lolium arundinaceum.(2.5, 5.1, 7.6 y 10.2 cm). El porcentaje de cobertura de D. sanguinalis fue evaluado utilizando VR, LIA y DIA para determinar la existencia de diferencias entre estos métodos de evaluación. Comparaciones de pares, correlación Pearson, y regresión lineal fueron realizadas para comparar los diferentes métodos. Todos los métodos de evaluación correlacionaron entre ellos en forma significativa. Hubo diferencias en la cobertura de D. sanguinalis entre los datos de LIA y DIA en todas las alturas de poda y entre los datos de VR y DIA a alturas de 7.6 y 10.2 cm en 2007. Los autores creen que las sombras producidas por el dosel del césped a alturas de poda al

Jared A. Hoyle, FRED H. YELVERTON, and Travis W. Gannon "Evaluating Multiple Rating Methods Utilized in Turfgrass Weed Science," Weed Technology 27(2), 362-368, (1 June 2013). https://doi.org/10.1614/WT-D-12-00126.1
Received: 26 August 2012; Accepted: 1 January 2013; Published: 1 June 2013
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