Statistical analyses of fluorometry data from chloroform filtrate of lamb feces

• Published in: Journal of range management 2001-07, Vol.54 (4), p.370-377
• Main Authors: 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
• Format: Article
• Language: English
• Subjects: botanical composition; Confidence interval; Diet; Discriminant analysis; evaluation; Feces; feces composition; feed intake; feeds; Fluorescence; forage; lambs; light intensity; Measurement/Sampling; methodology; Polynomials; Regression coefficients; selective grazing; statistical analysis; Visible spectrum; Wave excitation; Wavelengths
• ISSN: 0022-409X; 2162-2728
• DOI: 10.2307/4003105

Accurately identifying the botanical composition of free-ranging animal diets remains a challenge. Currently accepted procedures are time consuming, many requiring painstaking sample preparation while none produce data useful for real-time management. Automated procedures focusing on detection of chemical and/or physical plant properties using specific molecules called fluorophores offers possibilities for determining the species composition of herbivore diets. This study was designed to evaluate fluorometry techniques in herbivore diet determinations using fecal samples obtained from 13 lambs fed a basal diet of tobosa hay (Pleuraphis mutica Buckley), and containing 4 different levels (0, 10, 20, and 30%) of tarbush (Flourensia cernua D C.) leaf material. Chloroform (CHCl3) filtrate obtained from the lamb's feces was exposed to UV light from a xenon arc lamp. This caused fluorophore molecules in the filtrate to have their outer shell electrons move to a higher energy state as a result of UV light excitation. After excitation by UV light at 310, 320, 330, 340, 350, and 355 nm, the fluorophores returned to their ground state giving off light (fluorescence). This fluorescence intensity (counts) varied and when captured using appropriate electronics, produced 1,024 pairs of light intensities (counts) and fluorescent wavelengths between 175 and 818 nm in 0.63 nm increments. Previous research indicated differences among diets could be determined using distinct peaks in the red and blue regions of the visible light spectrum and a univariate (1 variable at a time) analysis. This research demonstrates the entire fluorescence data set can be used to determine differences among diets using multivariate statistics. Sequences of 5 increasingly complex statistical techniques were used to distinguish among diets: 2-dimensional plots, polynomial regression models, confidence interval plots, discriminant analysis, and 3-dimensional plots. Two-dimensional plots indicated 2 spectral fluorescence peaks, 1 in the blue-green (420-600 nm) and 1 in the red (640-720 nm) region of the visible spectrum. Because of the asymmetrical nature of these peaks, fifth-order polynomials were developed to differentiate among the 4 diets. Statistical reliability was high when discriminating between diets containing no tarbush leaf and the diets containing 30% tarbush leaf; however, it was not possible to statistically separate diets containing intermediate (10 and 20%) amounts of tarbush leaf