|THIBODEAUX, DEVRON - Retired ARS Employee|
|FOULK, JOHN - Fx - Fibers Llc|
|Rodgers Iii, James|
Submitted to: Journal of Textile Science & Engineering
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 7/22/2014
Publication Date: 8/5/2014
Citation: Liu, Y., Thibodeaux, D., Foulk, J., Rodgers III, J.E. 2014. Preliminary study of determining cotton trash components in lint cottons by near infrared spectroscopy technique. Journal of Textile Science & Engineering. 4(4):1000161.
Interpretive Summary: Presence of trash in commercial cotton bales at varying amounts degrades the market values, requires additional cleaning process, and impacts the end-use qualities for yarn and fabric products. In order to determine the trash amount, a number of methods have been developed. In general, these methods only produce the amount of total trash, instead of the content for individual or targeted trash components. Near infrared (NIR) spectroscopy, as a rapid and low-cost method that can be used, away from the laboratory, in places such as ginning sites, has been examined for its potential in the prediction of specific and unique cotton trash components (leaves, seed coats, hulls, stems, and sand/soil) in grounded samples. Next, these NIR models were transferred to regular bulky samples with various instrumental leaf grade or trash levels. The accumulated knowledge could be of value as a rapid analytical tool to cotton breeders for cotton variety enhancement and also to cotton ginning engineers for effective trash-removal cleaning devices. The outcome provides cotton fiber/textile engineers, researchers, ginners, and regulators a new way in the determination of cotton trash components.
Technical Abstract: The transfer of NIR calibration models for the determination of total trash, leaf trash and non-leaf trash components in cotton fibers was conducted between two sets of samples. These samples to be analyzed are inhomogeneous in a bulky state whereas the samples used as calibrations were much homogeneous in a ground state. The efficacy of the model transfer was evaluated based on instrumental leaf grade readings of diverse samples, because current-in-use trash tests cannot generate the trash amount for individual trash components. Results indicated that the predictions from the direct model transfer were unreliable, but they might be acceptable after the correction or conversion of original predictions with standard samples.