Submitted to: American Association of Textile Chemists and Colorists Journal of Research
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/24/2015
Publication Date: 12/1/2015
Citation: Fortier, C.A., Santiago Cintron, M., Rodgers III, J.E. 2015. Fourier transform infrared macro-imaging of botanical cotton trash. American Association of Textile Chemists and Colorists Journal of Research. 2(6):1-6.
Interpretive Summary: The price of cotton is directly tied to its appearance. Thus, cotton that does not appear white may be financially penalized. Moreover, there is some concern that cotton any color other than white is perceived to potentially cause problems during the dyeing stage. Specifically, the current study is aimed at identifying trash types using attenuated total reflectance fourier transform infrared (ATR FT-IR) imaging. The results show that this feasibility study may encourage the use of this relatively new technique to characterize cotton trash.
Technical Abstract: The marketability of cotton fiber is directly tied to the trash comingled with it. Trash can contaminate cotton during harvesting, ginning, and processing. Thus, the removal of trash is important from field to fabric. An ideal prerequisite to removing trash from lint is identifying what trash types are present. Understanding which type of trash is present can lead to the fabrication of highly specific equipment that can both identify and sort cotton from trash. A relatively new and fast analytical technique has been gaining popularity among researchers is hyperspectral imaging, which allows for a three-dimensional spectral cube to be generated composed of infrared spectral and spatial data. In this technique, each point in the cube is associated with a spectrum. Coupling Fourier-Transform infrared (FT-IR) imaging with attenuated total reflectance (ATR) and a focal plane array (FPA) detector allows for larger samples to be analyzed with speed and little to no sample preparation. It is the goal of this study to identify botanical trash using hyperspectral FT-IR imaging as a feasibility study to facilitate wider utility of this method in the textile field.