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ARS Home » Southeast Area » New Orleans, Louisiana » Southern Regional Research Center » Cotton Structure and Quality Research » Research » Publications at this Location » Publication #290506
Title: NIR technique in the classification of cotton leaf grade

Author
item Liu, Yongliang
item FOULK, JONN - Fx - Fibers Llc

Submitted to: National Cotton Council Beltwide Cotton Conference
Publication Type: Proceedings
Publication Acceptance Date: 1/26/2013
Publication Date: 5/28/2013
Citation: Liu, Y., Foulk, J. 2013. NIR technique in the classification of cotton leaf grade. Proceedings of the 2013 National Cotton Council Beltwide Cotton Conference,January 1-10,2013, San Antonio, Texas. p.610-613.

Interpretive Summary: As a universal testing method and official classification, the USDA’s Agricultural Marketing Service (AMS) has implemented the automation based high volume instrument (HVITM) procedure to identify the number of non-lint particles and to measure the surface area covered by non-lint particles. Meanwhile, qualified AMS human classers manually determined the leaf grade and extraneous matter through a process of visually examining the cotton samples and then comparing them to the Universal Cotton Standards. Lately, the AMS has revised the protocol for cotton leaf grade classification, by replacing the classer’s leaf determination with instrumental leaf measurement from cotton classification HVITM system. This study examined the feasibility of visible and near infrared (NIR) technique in the discrimination of cotton samples with various leaf grade categories, with a acceptable separation of ~ 95.0%. The outcome provides cotton fiber / textile engineers, researchers and regulators a new sight in applying visible and NIR spectroscopy for rapid and routine determination of cotton leaf grade.

Technical Abstract: Near infrared (NIR) spectroscopy, a useful technique due to the speed, ease of use, and adaptability to on-line or off-line implementation, has been applied to perform the qualitative classification and quantitative prediction of cotton quality characteristics, including trash index. One term to assess the degree of trash amount is leaf grade, which is determined by cotton classification HVITM system. In this study, visible/NIR spectra were collected to explore the feasibility for the discrimination of cotton samples with various leaf grade categories. The results suggested that the optimal model in the 1105-1700 nm region could determine the cotton leaf grade with a ~95.0% success rate.