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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 #324425

Research Project: Improved Quality Assessments of Cotton from Fiber to Final Products

Location: Cotton Structure and Quality Research

Title: Micronaire measurements on seedcotton and cotton fiber, in and outside of laboratory using micro nir-infrared instruments

Author
item Zumba, Jimmy - Oak Ridge Institute For Science And Education (ORISE)
item Rodgers Iii, James

Submitted to: National Cotton Council Beltwide Cotton Conference
Publication Type: Proceedings
Publication Acceptance Date: 1/22/2016
Publication Date: 5/18/2016
Citation: Zumba, J., Rodgers III, J.E. 2016. Micronaire measurements on seedcotton and cotton fiber, in and outside of laboratory using micro nir-infrared instruments. Proceedings of the National Cotton Council Beltwide Cotton Conference, January 5-7, 2016, New Orleans, Louisiana. p. 327-330.

Interpretive Summary: Micronaire is a key quality parameter in cotton fiber. NIR-spectroscopy has the ability to measure micronaire in and out of the laboratory. New very small microNIR instruments have recently been introduced. A program was established to measure micronaire in and outside the laboratory on seedcotton fiber and cotton lint using micro portable handheld NIR-Infrared instruments. Adding new data to the original 189 samples, including data from different environments (laboratory and greenhouse) and fiber type conditions (lint and cottonseed) makes the calibration more robust, increasing the accuracy of the prediction and reducing the variability of the prediction.

Technical Abstract: Micronaire is a key quality parameter in cotton fiber. NIR-spectroscopy has the ability to measure micronaire in and out of the laboratory. New very small micronaire instruments have recently been introduced. A program was established to measure micronaire in and outside the laboratory on seed cotton fiber and cotton lint using micro portable handheld NIR-Infrared instruments. Adding new data to the original 189 lint samples, including data from different environments (laboratory and greenhouse) and fiber type conditions (lint and seed cotton) made the calibration more robust, increasing the accuracy of the prediction and reducing the variability of the prediction. The accuracy of the prediction was improved with both instrument, but when compared each instrument they differed on the predictability and variability, and it may be due to the precision of each instrument. It is advisable to use the instrument that fits the best the laboratory research objectives, considering its weight or size.