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ARS Home » Plains Area » Las Cruces, New Mexico » Range Management Research » Research » Publications at this Location » Publication #111536


item Anderson, Dean
item DANIEL, D
item MURRAY, L
item TISONE, G
item Estell, Richard - Rick
item RAYSON, G
item Havstad, Kris

Submitted to: Journal of Range Management
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/7/2000
Publication Date: 7/1/2001
Citation: Mukherjee, A., Anderson, D.M., Daniel, D.L., Murray, L.W., Tisone, G., Fredrickson, E.L., Estell, R.E., Rayson, G.D., Havstad, K.M. Statistical analyses of fluorometry data from chloroform filtrate of lamb feces. Journal of Range Management. 2001. v. 54(4). p. 370-377.

Interpretive Summary: Current procedures to identify what foraging animals eat are oftentimes time consuming and many require painstaking sample preparation; yet none of the routine procedures produce information that can be used for real-time management. Conventional techniques rely on human judgement and eyesight while automated procedures can produce data faster and with higher precision and accuracy. One such promising technique involves exciting molecules with specific wavelengths of focused short wavelength (high- energy) visible light. Energy from this focused light causes certain molecules in the exposed material to become excited. When the light source is removed, the excited molecules give up energy in the form of light of a lower energy content, i.e. longer wavelength. This light can be captured automatically and electronically to produce a spectral signature in an instrument called a fluorometer. Spectral signatures are unique for each particular molecule under the specific conditions in which the signature was captured. Using an organic solvent, fecal samples obtained from 13 lambs fed a diet consisting of tobosa hay into which was added 0, 10, 20 and 30% tarbush woody leaf material produced a series of spectral signatures. These spectral signatures had 2 peaks, 1 in the blue-green and 1 in the red region of the visible spectrum. Five different statistical techniques were evaluated to separate differences among the feces arising from the 4 diets when excited at 310, 320, 330, 340, 350 and 355 nm. This research suggests it may be possible to use spectral signature profiles to differentiate among diets composed of different plant materials.

Technical Abstract: Using fecal samples obtained from 13 lambs maintained in metabolism stalls and fed 4 identical basal diets composed of tobosa hay (Pleuraphis mutica) Buckley, which contained 4 different levels (0, 10, 20 and 30%) of tarbush (Flourensia cernua) D.C. leaf material, a data set of spectral signatures were obtained using fluorometry techniques. A chloroform filtrate obtained from the lamb's feces was exposed to xenon light. This caused certain molecules in the filtrate called fluorophores to have their outer shell electrons move to a higher energy state as a result of the energy coming from the xenon light. Upon removal of the xenon light, which had been focused at 310, 320, 330, 340, 350 and 355 nm, the fluorophores returned to their ground state giving off light. This fluorescence light varied in intensity and when captured using appropriate electronics, produced 1024 pairs of light intensities and fluorescent wavelengths between 175 and 818 nm in 0.6288972 increments. This research demonstrated the entire fluorescence data set could be used to determine statistical differences among diets. Five increasingly complex statistical approaches were evaluated: two-dimensional plots, polynomial regression models, confidence interval plots, discriminant analysis and three-dimensional plots. There was a high statistical reliability when separating diets containing no tarbush leaf from diets containing 30% tarbush leaf; however, it was not possible to routinely statistically separate diets containing intermediate (10 and 20%) amounts of tarbush leaf material from themselves or the two extremes (0 and 30% tarbush leaf). These results suggest spectral signatures arising from fluorometry data may be useful for differentiating among diet botanical compositions that differ in plant form.