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The Pennsylvania State University, University Park 16802
ABSTRACT
Infrared reflectance is a rapid accurate procedure for measuring nutrients in grains and forages. Factors that affect prediction of forage quality include plant species, method of preservation, and constituents in the forage other than those being measured. Selection of wavelengths for prediction is the key. Statistical procedures are being studied to improve selection of wavelength and to lower prediction errors. Commercial instruments recently introduced have greater data processing capabilities and greater wavelength (filter) selection than earlier models, but more research is needed to determine the appropriate wavelengths for each type of forage and feedstuff. An alternative to the filter instrument would be a small monochromator-based instrument similar to the prototype we have developed. This instrument can collect, process, and select a set of wavelengths to use for prediction for each different type of forage or feedstuff. New applications of infrared reflectance include identification of the sample from the spectra, prediction of percent legume ±10% in grass-legume mixtures, heat damaged protein (acid detergent fiber insoluble nitrogen ±.01%), phosphorous ±.04%, calcium ±.14%, calcium to phosphorous ratio ±.68%, potassium .41%, and boron ±5.4 ppm. Other minerals evaluated having low predictability are aluminum, iron, zinc, sodium, manganese, magnesium, and copper.
1 Authorized as Paper No. 5570 in the Journal Series of the Pennsylvania Agricultural Experiment Station. Presented at the joint regional meeting of the American Dairy Science Association and American Society of Animal Science, July 24, 1978, Amherst, MA.
2 Associate Professor of Plant Breeding, Ph.D. Graduate student in Statistics, Program/analyst, The Pennsylvania State University, University Park, Pennsylvania. The Work reported in this paper was conducted at and in cooperation with the U.S. Regional Pasture Research Laboratory, USDA-ARS, University Park, PA 16802.
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