Investigator: C.J. Lupton
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This project will examine and contribute to several approaches for making the U.S. animal fiber and sheep and goat meat industries more competitive and more profitable. Near-infrared reflectance spectroscopy (NIRS) will be further developed and evaluated to provide rapid, accurate, and less expensive estimates of wool and mohair content, and alpaca and mohair luster. Round trials will be organized and conducted with other labs having NIRS capabilities to estimate wool base in greasy core samples; and, if the trials produce adequate supporting data, a draft ASTM standard method will be submitted for approval. Once a standard method is in place, the NIRS measurements will not only be useful to producers, breeders, and researchers, but also to marketers and processors for commercial transactions. In addition, it is planned to use NIRS to estimate juniper consumption of free-ranging goats by analyzing the spectra of their fecal material. An image analysis instrument, the OFDA2000, will be further evaluated for field-testing of wool and mohair to give producers fast, low-cost measurements of fiber diameter and staple length, and in the warehouse for estimating fiber diameter of commercially baled lots by measuring grab samples. Participation in seven other experiments is planned. All have the general objective of using fleece and fiber measurements to quantify or improve fiber and/or meat production, quality, and income to producers through improved selection, nutrition, management, and marketing efficiency. The experiments are: a central ram performance test; a central Angora billie goat performance test; a cooperative breeding program for Rambouillet sheep; a selection experiment with Angora goats to create a flock that will consume higher levels of juniper species; comparison of female productivity in two sheep breeds, Dorper and Rambouillet; an economic comparison of wool versus hair sheep and fiber versus meat goats maintained on rangeland; and effects of nutrition on fleece and fiber characteristics of sheep and Angora goats.
Develop and evaluate near-infrared reflectance spectroscopy for rapid estimation of clean fiber base in greasy wool and mohair and luster in mohair and alpaca.
Evaluate two automatic image analysis systems for rapid, objective evaluation of fiber diameter of raw wool and mohair, and luster in mohair and alpaca.
Use objective measurements to improve or monitor fiber and/or meat production; quality; and income to producers through improved selection, nutrition, management, and marketing efficiency.
Expected outputs are: a less expensive and faster method for measuring clean yield of wool and mohair; a new method for measuring luster of animal fibers; and, by collaborating with colleagues, fiber data will be made available for seven experiments that include performance tests, selection experiments, and nutrition trials with sheep and Angora goats.
The stated objectives will be met by conducting two sets of experiments. The first set involves a continuing effort by this research group to evaluate and develop instruments and methods for more rapid, accurate characterization of wool, mohair, alpaca, cashmere, and other animal fibers. In the second series of experiments, standard as well as newly developed instrumentation and methods for measuring animal fibers will be used to (ultimately) monitor or optimize fiber (and/or meat) production, quality and value. Justification for the proposed research in based on the premise that the efficiency and profitability of wool, mohair, and animal fiber production and marketing in general can be improved through the expanded use of objective fiber measurements. Expanded use will be achieved by making the measurements more rapid, more accessible to producers, marketers, and manufacturers and, ideally, less expensive. Instruments to be further evaluated and/or developed under objective one include: a near-infrared reflectance spectrometer and two automatic image analysis systems, the Optical Fibre Diameter Analyser2000 and the SAMBA luster system.