|Estell, Richard - Rick|
Submitted to: African Journal of Range and Forest Science
Publication Type: Abstract only
Publication Acceptance Date: 8/6/2002
Publication Date: 7/26/2003
Citation: ANDERSON, D.M., PARKER, E., RALPHS, M., GRAY, P., RAYSON, G., ESTELL, R.E., DANIEL, D., FREDRICKSON, E.L., HAVSTAD, K.M., WAGNER, J. FLUOROMETRY AS A TOOL FOR REAL-TIME BOTANICAL ANALYSIS. AFRICAN JOURNAL OF RANGE AND FORAGE SCIENCE. PROCEEDINGS OF THE VIITH INTERNATIONAL RANGELAND CONGRESS, ADDITIONAL ABSTRACTS. 2003. ABSTRACT P. 132. Interpretive Summary: Interpretive summary not required for proceedings.
Technical Abstract: Determining the botanical composition of forage and free-ranging animal diets is essential for accurate rangeland management and optimum economic returns. Multidimensional fluorometry offers a unique, real-time optical approach for accurately determining the composition of plant materials based on their chemical properties. By focusing on electronic transitions between 190 and 800 nm, specific chemical structures within dietary extrusa and fecal matter can be determined using ¿trainable¿ intelligent algorithms. During November 1991 we began investigating fluorometry as a tool to evaluate both pre- and post-digested plant materials. In the ensuing 12 years, light sources such as lasers and xenon arc lamps have been successfully used to excite fluorescence from plant and fecal extracts in both polar and nonpolar solvents. Unique spectral signatures in the blue, green and red regions of the visible spectrum were obtained. Prior research has concentrated on the acquisition and post-processing of excitation/emission matrices obtained from individual plant species as well as postdigested plant materials. Similarities have been shown among different plants within the same species of grass, forb and shrub as well as differences among grasses, forbs and shrubs. Statistical differences have also been found among simple diets containing varying amounts of one of the components. Previous research suggests fluorometry can become a promising method to differentiate between both pre- and postdigested plant materials. Current research using intelligent algorithms such as neural net processing to characterize three-dimensional spectral signatures among plants, including some poisonous to livestock, will be discussed.