The objective of this study was to evaluate the potential of near infrared reflectance spectroscopy (NIRS) for estimating botanical composition of esophageal extrusa samples. Spectral data were collected on 361 samples from fistulated sheep and cattle grazing native tallgrass range. Principal components analysis was used to identify a subset of 73 samples with spectral dissimilarity. These samples were microhistologically analyzed to determine botanical composition and were considered 'actual' for regression and calibration purposes. Thirty-six species (12 grasses, 22 forbs, and 2 sedges) were identified in the microhistologically analyzed samples. However, most accounted for less than 5% of the total diet. Additional pure calibration samples were obtained by feeding individual species to confined fistulated sheep. Initial regression analyses and predictions were made on 13 major species or species groups. Satisfactory prediction equations could only be developed for big bluestem andropogon gerardii Vitman) (r2 =0.61), and the total grasses (r2= 0.79) and total forbs (r2 = 0.79) groups. Addition of spectra from pure samples into the calibration set was beneficial. In general, valid predictions could not be made for individual species that constituted less than 10% of the sample and/or had a low frequency of occurrence in the calibration samples. The NIRS method offered acceptable precision and accuracy in the prediction of major botanical components and it would be practical and efficient because it reduces the number of samples that would have to be microhistologically analyzed. The Journal of Range Management archives are made available by the Society for Range Management and the University of Arizona Libraries. Contact lbry-journals@email.arizona.edu for further information. Migrated from OJS platform August 2020
Scholarly peer-reviewed articles published by the Society for Range Management. Access articles on a rolling-window basis from vol. 1, 1948 up to 5 years from the current year. Formerly Journal of Range Management (JRM). More recent content is available by subscription from SRM.