Thesis (Ph. D.)--University of Washington, 1998. / Vita. Includes bibliographical references (leaves [158]-162).

Thesis (Ph.D.) in Chemical Engineering--University of Maine, 2008. / Includes vita. Includes bibliographical references (leaves 136-147).

Thesis (M.Sc.). / Written for the Dept. of Bioresource Engineering. Title from title page of PDF (viewed 2009/06/18). Includes bibliographical references.

Thesis (M.Sc.). / Written for the Dept. of Bioresource Engineering. Title from title page of PDF (viewed 2009/06/22). Includes bibliographical references.

Thesis (Ph.D.)--Drexel University, 2010. / Includes abstract and vita. Includes bibliographical references (leaves 105-116).

Thesis (Ph.D.)--Duquesne University, 2009. / Title from document title page. Abstract included in electronic submission form. Includes bibliographical references (p. 184-195) and index.

Thesis (Ph. D.)--Oregon State University, 2006. / Printout. Includes bibliographical references (leaves 139-151). Also available on the World Wide Web.

Thesis (Ph. D.)--University of Texas at Austin, 2006. / Vita. Includes bibliographical references.

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The chemical analysis of feed samples can be time consuming and expensive. The use of near infrared reflectance (NIR) spectroscopy was evaluated in a range of studies as a rapid technique to predict the chemical constituents in feedstuffs and compound ostrich feeds. The prediction of accurate results by NIR spectroscopy relies heavily upon obtaining a calibration set which represents the variation in the main population, accurate laboratory analyses and the application of the best mathematical procedures. This research project was designed to meet five objectives: The first objective was to determine the feasibility of using near infrared reflectance (NIR) spectroscopy to predict dry matter, ash, crude protein, crude fibre, oil content, and fatty acids such as palmitic acid (C16:0), stearic acid (C18:0), oleic acid (C18:1) and linoleic acid (C18:2) in sunflower seed meal. The second objective was to develop calibration models to predict the dry matter, crude protein and oil content in milled canola seed, compared to whole canola seeds. The third objective was to investigate the feasibility of using NIR spectroscopy to predict the dry matter, ash, crude protein, crude fibre and oil content in milled lupin seeds, compared to whole lupin seeds. The fourth objective was to describe the development of near infrared reflectance (NIR) spectroscopy calibration equations for the prediction of chemical composition and amino acid content from different populations of alfalfa hay (Medicago sativa L.). The last objective was to determine the potential of NIR spectroscopy to predict the dry matter, ash, crude protein, crude fibre, ether extract, acid detergent fibre (ADF), neutral detergent fibre (NDF), calcium, phosphorus, in vitro organic matter digestibility (IVOMD) and amino acids such as lysine, methionine, threonine and arginine in compound ostrich feed samples. The results of this study indicate that NIR spectroscopy calibrations in sunflower seed meal are only applicable in sunflower breeding programmes for a fast screening as it was not suitable for prediction purposes. Screening of sunflower seeds by NIR spectroscopy represents a rapid, simple and cost effective alternative that is a great utility for users who need to analyse a large number of samples. Calibrations developed for crude protein and oil content in milled canola seeds proved to be better than calibrations for whole canola seeds. Although the results indicated that calibrations were better for milled canola seeds, it indicated values that were typical of equations suitable for screening purposes to select samples for more detailed chemical analysis. According to calibration statistics obtained for crude protein, crude fibre and oil content in whole lupin seeds, there is no need to grind the seeds to scan the meal as similarly accurate results were obtained by analysing whole seeds. Screening of whole lupin seeds by NIR spectroscopy represents a rapid, simple and cost effective alternative that may be of great utility for users who need to analyse a large number of samples with no sample preparation. The calibration and validation statistics obtained in the study to test the potential of NIR spectroscopy to predict the chemical composition and amino acid contents in alfalfa hay, showed the accuracy was too low for routine analysis, although NIR spectroscopy could be used as a screening tool. Further research needs to be done to improve the accuracy of the NIR spectroscopy analysis, including more samples from different cultivars and years. In the study to examine the possibility of using NIR spectroscopy to predict the chemical composition of compound ostrich feeds, the results indicated that NIR spectroscopy is a suitable tool for a rapid and reliable prediction of the crude protein, crude fibre, ether extract, IVOMD, ADF and NDF in compound ostrich feeds. Calibrations can be improved for amino acids if a larger sample pool is used to develop the calibrations. These studies indicated that NIR spectroscopy can be a rapid and successful tool for the prediction of the nutritive value up to certain amino acid contents of feedstuffs and compound ostrich feeds.