Identification of cotton and cotton trash components by Fourier transform near-infrared spectroscopy
Source abstract
Abstract
The high demand for cotton production worldwide has demonstrated the need for standardized classification of foreign matter present with cotton. Cotton trash can become comingled with fiber during the ginning and harvesting processes. The conventional instrumental method used to determine the amount of cotton trash present with cotton fiber, the high volume instrument (HVI), lacks specificity in the identification of individual trash components (leaf, etc.). Fourier transform near-infrared (FT-NIR) spectroscopy was investigated to distinguish the individual types of cotton trash from the fiber. In this study, the concept of monitoring differences in spectral bands of cotton and cotton trash by FT-NIR spectroscopy was demonstrated and provided a ‘proof of concept.’ A spectral library based on NIR spectral data and pre-processing methods was developed using cotton and cotton trash samples (hull, leaf, seed coat, and stem) yielding over 97% identification accuracy of cotton trash components in the prediction set.
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Research context
OpenAlex topics: Textile materials and evaluations · Industrial Vision Systems and Defect Detection
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Southern Regional Research Center (SRRC), Agricultural Research Service, USDA, New Orleans, USA,
Southern Regional Research Center (SRRC), Agricultural Research Service, USDA, New Orleans, USA
Agricultural Research Service, USDA, Clemson, USA
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