Skip to main content
ARS Home » Pacific West Area » Corvallis, Oregon » Forage Seed and Cereal Research Unit » Research » Publications at this Location » Publication #397650

Research Project: Improving Plant, Soil, and Cropping Systems Health and Productivity through Advanced Integration of Comprehensive Management Practices

Location: Forage Seed and Cereal Research Unit

Title: Comparing methods to quantify cover in turfgrass research

item KOWALEWSKI, ALEC - Oregon State University
item SCHMID, CHARLES - Oregon State University
item BRAITHWAITE, EMILY - Oregon State University
item MCNALLY, BRANDON - Purdue University
item ELMORE, MATT - Rutgers University
item Mattox, Clint
item MCDONALD, BRIAN - Oregon State University
item WANG, RUYING - Oregon State University
item LAMBRINOS, JOHN - Oregon State University
item FITZPATRICK, GREG - Oregon State University
item Rivedal, Hannah

Submitted to: Crop Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/1/2023
Publication Date: 1/16/2023
Citation: Kowalewski, A.R., Schmid, C.J., Braithwaite, E.T., McNally, B.C., Elmore, M.T., Mattox, C.M., McDonald, B.W., Wang, R., Lambrinos, J.G., Fitzpatrick, G., Rivedal, H.M. 2023. Comparing methods to quantify cover in turfgrass research. Crop Science. 63:1581-1591.

Interpretive Summary: : Assessing the percentage of area covered by turfgrass or affected by biotic or abiotic damage has often been estimated using visual assessments. Quantitative methods that are less prone to human bias are desired, although little guidance exists on other methods. Digital image analysis is a technique that removes the human component; however, variations in image quality from lighting conditions, plant color differences, biotic and abiotic stress, or pigment applications remain a concern. Other options for assessing plant cover include point intercept frames and digital point intercept frames added to images. To compare these methods, a series of four experiments took place in Corvallis, OR and one experiment took place in New Brunswick, NJ. The first experiment demonstrated that point intercept frames using 1 inch spacing, while taking the most time by raters, were able to accurately assess percent cover to a known sample. The second experiment compared the 1 inch point intercept spacing to digital image analysis and a digital grid and found that there were no differences between methods; however, they did overestimate the known percent cover. The third experiment focused on comparing digital image analysis, a digital grid, a point intercept frame, and visual ratings to the turfgrass disease, dollar spot, before and after applying a pigment. Results demonstrated that all methods underestimated disease after pigment application. A fourth experiment determined that in the absence of pigments, a point intercept frame, digital image analysis, and visual ratings were well correlated methods to assess dollar spot; however, concerning the disease, anthracnose, digital image analysis was not correlated with the other methods. A fifth experiment found that the point intercept frame and digital image analysis were well correlated for quantifying seedling establishment.

Technical Abstract: Turfgrass cover can be assessed qualitatively using visual ratings, but quantitative turfgrass cover measurements are desired for producing unbiased data. Digital image analysis and point intercept are two quantitative percent cover data collection methods used in turfgrass research. A potential weakness of digital image analysis is the difficulty in evaluating color variation. Considering this, a series of controlled environment and field experiments were conducted to evaluate the accuracy of the point intercept method compared to using a digital grid, digital image analysis, and visual ratings when utilized in turfgrass research. To explore this topic, four experiments were conducted in Corvallis, OR, and one in New Brunswick, NJ. Results from research conducted in Corvallis, OR, determined that the closest intercept spacing (2.54 cm) results in percent cover that was not different than the known cover and the lowest variance, but the greatest amount of time required to collect the data. Digital image analysis was the most consistent method for measuring percent cover when a known percent cover was being quantified. The estimate of percent dollar spot cover was reduced by a single pigment application regardless of the data collection method. In the absence of pigment applications, the point intercept frame, digital image analysis and visual ratings were well correlated methods used to assess dollar spot cover. Digital image analysis was not correlated with the other data collection methods when used to evaluate percent anthracnose cover. The research conducted in New Brunswick, NJ, determined that the point intercept method and digital image analysis are well correlated methods for quantifying turfgrass establishment from seed.