Location: Location not imported yet.Title: Rapid assessment of above-ground biomass of Giant Reed using visibility estimates Author
|Racelis, Alex - Former Ars Employee|
Submitted to: Journal Subtropical Plant Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/20/2012
Publication Date: 7/18/2013
Citation: Racelis, A., Goolsby, J. 2013. Rapid assessment of above-ground biomass of Giant Reed using visibility estimates. Journal Subtropical Plant Science. 64:61-66.
Interpretive Summary: A predictive tool was developed to rapidly quantify infestation of giant reed across different sites in South Texas. Digital photos of a white poster board embedded into a stand of giant reed were analyzed using image processing software (Adobe Photoshop Creative Suite version 5). The visibility of the board was calculated as the percent of white pixels detected by imaging program relative to the total number of pixels for the total square area of the white board. These percentages were found to be significantly correlated to the total plant biomass harvested immediately in front of the board. Visibility measures also accurately predicted plant density. These results demonstrate that this visibility metric is an accurate and rapid predictive technique for estimating giant reed biomass, and is a promising tool for measuring impact of different management on both plant biomass and visibility.
Technical Abstract: A method for the rapid estimation of biomass and density of giant reed (Arundo donax L.) was developed using estimates of visibility as a predictive tool. Visibility estimates were derived by capturing digital images of a 0.25 m2 polystyrene whiteboard placed a set distance (1m) from the edge of giant reed infested areas of the Lower Rio Grande Valley in South Texas. Images were analyzed using image editing software to calculate the percent visibility of the embedded whiteboard. A range of visibility values were captured across nine different sites. All above-ground biomass immediately in front of the whiteboard was harvested, partitioned, and dried. Visibility into the stand was strongly correlated with above ground giant reed biomass. Visibility measures most strongly predicted total leaf biomass, but also accurately predicted total shoot biomass and total dry weight biomass, as well as stem density. These results demonstrate a simple predictive way to rapidly quantify infestation in terms of biomass and density of giant reed across different sites in South Texas.