Location: Cotton Structure and Quality ResearchTitle: Fourier transform spectroscopy of cotton and cotton trash Author
Submitted to: Fourier Transform
Publication Type: Book / Chapter
Publication Acceptance Date: 2/29/2012
Publication Date: 5/30/2012
Citation: Fortier, C.A. 2012. Fourier transform spectroscopy of cotton and cotton trash. Fourier Transform. In: Salih, S.M.,editor. Fourier Transform - Materials Analysis. InTech, 5 p.103-120. Interpretive Summary: The widely-used Uster® High Volume Instrument (HVI) and Shirley Analyzer instruments currently are unable to identify pure cotton trash components. With the application of Fourier Transform (FT) techniques coupled to mid-infrared (MIR) and near-infrared (NIR) spectroscopy, the identification of cotton and both botanical and field trash is largely enhanced. The development of FT-MIR and FT-NIR spectral databases has allowed for the classification of independent, pure cotton trash components. FT-NIR spectroscopy along with chemometric software has yielded correct spectral identification greater than 98% of the time for over 100 hull, leaf, seed coat and stem samples of varying particle size. Expanding this spectral library to include seed meat and field trash has increased the robustness of this method. Continuing to explore the capabilities of these FT techniques is worthwhile to increase the marketability of cotton lint through efficient identification of cotton trash types.
Technical Abstract: Fourier Transform techniques have been shown to have higher signal-to-noise capabilities, higher throughput, negligible stray light, continuous spectra, and higher resolution. In addition, FT spectroscopy affords for frequencies in spectra to be measured all at once and more precise wavelength calibrations. FT near-infrared (NIR) and mid-infrared (MIR) spectroscopy techniques are now available to identify cotton trash components. The use of sub-libraries in chemometric software coupled to FT-NIR spectroscopy afforded the creation of a spectral database with the potential to correctly identify pure cotton trash types. The utility of the method for cotton trash identification was proven with a highly accurate (greater than 98%) identification percentage.