|Hyder, Paul - FORMER NMSU GRAD STUDENT|
|Remmenga, Marta - NEW MEXICO STATE UNIV|
|Pieper, R - NEW MEXICO STATE UNIV|
Submitted to: Journal of Range Management
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: May 25, 2002
Publication Date: March 1, 2003
Citation: HYDER, P.W., FREDRICKSON, E.L., REMMENGA, M.D., ESTELL, R.E., PIEPER, R.D., ANDERSON, D.M. A DIGITAL PHOTOGRAPHIC TECHNIQUE FOR ASSESSING FORAGE UTILIZATION. JOURNAL OF RANGE MANAGEMENT. 2003. V. 56(2). P. 140-145. Interpretive Summary: Changes in forage utilization have been difficult to measure nondestructively without some level of subjectivity. Computer-based techniques using readily available imaging analysis software was used to estimate plant biomass from digital photos of target plants acquired before and after partial defoliation. Regression analysis indicated an R-squared of 0.969 for predicted vs. observed plant weights. The technique can potentially be used to measure changes in biomass for application in ecology" botany and range science.
Technical Abstract: Changes in forage utilization have been difficult to measure nondestructively without some level of subjectivity. This subjectivity, combined with a lack of reproducibility of visual estimates, has made forage utilization measurement techniques a topic of considerable discussion. The objective of this study was to develop and test the accuracy and repeatability of an objective, computer-based technique for measuring changes in plant biomass. Digital photographs of target plants acquired before and after partial defoliation were analyzed using readily available image analysis software. Resulting data were used to develop a simple linear random coefficient model (RC) for estimation of plant biomass removed based on the area of the plant in the photo. Sample collection took approximately 20 minutes/plant for alfalfa (Medicago sativa L.). Analysis of images took another 60 to 90 minutes. Regression analysis gave an R2 of 0.969 for predicted vs. observed plant weights. Testing this model using 10 alfalfa plants yielded weight estimates of defoliated plants accurate to within +/- 8.5%. The advantage of the RC model is its ability to use easily obtained coefficients from simple linear regression models developed from each plant in a way that accounts for the lack of independence between samples within an individual plant. The technique described here offers an objective and accurate method for measuring changes in plant biomass with possible applications in ecology, botany, and range science. In particular, application of this technique for estimating forage utilization may improve accuracy of estimates and, thereby, improve range management practices.