Counting dandelion blooms in field plots using an image processing program

Abstract

Digital image analysis provides researchers a method to accurately and efficiently analyze turfgrass parameters including cover, color, disease severity, and more. Opportunities for processing images has increased due to the free and open-source nature of many new programs. We developed a macro (set of macroinstructions) within the open-source software ImageJ that is able to count the number and quantify the percent coverage of dandelion (Taraxacum officinale F.H. Wigg.) blooms in field plot images, which allows for collection of objective data on broadleaf weeds. A particle analysis function in ImageJ was used to distinguish dandelion blooms from other yellow objects (e.g. chlorotic turfgrass leaves) based on their size and circularity. We also explored the use of binary watershed segmentation to separate groupings of dandelion blooms into individual blooms that could be counted. To verify the accuracy of the macro, we analyzed 164 images for the number of dandelion blooms with the macro and regressed data against visual counts of dandelion bloom. The resulting linear regression analysis (visual count vs. macro) had a slope of 1.034 and an R 2 value of 0.9795. This macro provides researchers with a rapid and accurate method of determining the number and percent coverage of dandelion blooms in field plots using image analysis.

Improved control of Taraxacum officinale with 2,4‐D in the field from ammonium sulphate additions

“…Digital images were obtained using a Coolpix P7800 digital camera (Nikon Inc., Melville, NY) and collected in the JPEG (.jpg) format, with an image size of 2272 × 1704 pixels (3.8 Megapixels) and a file size of approximately 1.2 Megabytes. Images were analysed using ImageJ software (v1.48v, National Institute of Health, Bethesda, MD) (Schneider et al, 2012) as described by Patton et al (2021) to count the number of flowers (inflorescences) in bloom within each plot.…”