Page Banner

United States Department of Agriculture

Agricultural Research Service

Research Project: New and Improved Assessments of Cotton Quality

Location: Cotton Structure and Quality Research

2011 Annual Report

1a. Objectives (from AD-416)
Objective 1: Develop new industrially supported methods to assess cotton quality. Sub-objective 1a: Develop ways to characterize short fibers in cotton. Sub-objective 1b: Develop methods to measure seed coat fragments. Sub-objective 1c: Develop assessment methods for cotton properties that may contribute to cotton textile processability and product quality, but not conventionally assessed, such as micronaire and its components (such as maturity), three-dimensional color, and environmental impact on fiber properties. Objective 2: Develop new industrially supported methods to establish scientific foundations for standards and the next generation instruments for cotton classing. Sub-objective 2a: Develop new algorithms and methods to obtain fiber length distributions from a rapid fiber beard testing method. Sub-objective 2b: Characterize the distributions of key cotton properties as well as single cotton fiber measurement. Objective 3: Develop new industrially supported assessment techniques and methods for cotton producers, breeders, and others to evaluate fiber properties at various fiber development or processing stages based on small samples. Sub-objective 3a: Develop assessment techniques and methods to evaluate fiber properties at various fiber development stages based through sampling/measurement of the cotton product at-line and/or in the cotton field. Sub-objective 3b: Develop assessment techniques and methods to evaluate fiber properties and textile products during processing stages of small samples of fiber into textile goods.

1b. Approach (from AD-416)
This research is a comprehensive effort to develop improved or new testing methods that are not currently in the cotton classing system so that the textile manufacturers can more efficiently select and utilize cotton to reduce cost and improve product quality and so that our international customers can get quantified U.S. cotton quality. The value of adding new measurements will be studied by processing large numbers of cotton samples into textile yarns and fabrics. The first objective develops new methods to assess cotton quality. Statistical modeling will be used to characterize short fibers in cotton. An automated image analysis system will be developed to relate seed coat fragments to textile processability and product quality. Microscopy and molecular spectroscopy will be used to develop measurement methods and to characterize fiber micronaire and its components (maturity, fineness). Advanced color and spectroscopic instrumentation, combined with statistical modeling, will be used to measure color and trash components. A room whose environment (moisture level) can be changed and controlled will be used to determine the impacts of moisture on quality assessments and instrumentation. The second objective develops methods for fiber length distributions and single fiber measurements. New beard methods and statistical modeling will be used to obtain fiber length distributions. Automated constant-rate of transverse tensile testers and statistical modeling will be used to monitor key single fiber properties (strength, fineness, etc.) and to establish relationships between single fiber properties and conventional bulk properties. The third objective develops new quality assessment tools for cotton breeders and others to evaluate fiber properties at various fiber development or processing stages based on small samples. New molecular spectroscopy, imaging, and textile instrumentation will be used to assess fiber properties and quality at-line or in the field. Very small scale processing systems (50-100 grams) will be developed and used to assess fiber properties and processability from carding to knitting or weaving on miniature equipment.

3. Progress Report
Conventional and nonconventional fiber length parameters were calculated from a large set of cotton samples. Regression models were developed to improve the accuracy of predicting yarn properties. The advantages of those parameters, including parameters for characterizing short fibers, in predicting yarn properties were compared. A new version of Autorate for dark specks caused by seed coat fragments (SCF) and trash particles in cotton was evaluated and optimized. Testing protocol was determined. Various methods (hand-sort, Shirley, Image Analysis, AFIS and Seed Shearing) in predicting SCF potential were examined. A set of 40 samples was spun into yarns and weaved to fabric to compare Autorate dark speck data to the cotton test results. We determined the feasibility of using Near-Infrared (NIR) systems to measure fiber maturity. Optimum instrumental, sampling, and operational procedures and protocols were developed. The NIR systems yielded very good results for maturity. A spectroscopic method to identify common cotton trash components/non-lint content was demonstrated. NIR spectroscopy was employed to create a spectral library to classify pure botanical trash types, seed meat and field trash. Over 98% of the total trash types were correctly identified. We also compared the NIR spectroscopy and Ultra-Violet Visible (UV-Vis) spectroscopy and determined that NIR yielded a much higher correct identification compared to the UV-Vis. Substantial progress was made in obtaining fiber length distribution from the rapid fiber bundle testing method. A method was developed and refined to acquire optical signals from cotton fiber bundle measurements and to use the signals to construct the fiber staple diagrams and fibrograms. A model was developed to compute the entire length distribution of the original sample. The calculated length parameters from the rapid bundle test method showed good agreements with that from much slower single fiber testing methods. A large set of cottons from both domestic and international sources has been gathered and tested using standard bulk property test methods such as AFIS and HVI. A subset of these cottons is being characterized using single fiber measurement technologies. All of the relevant data derived from testing, plus descriptive information on the origin of the material, has been cataloged and stored as part of a comprehensive database. We determined the capabilities of a new instrument, the Cottonscope™, to rapidly and accurately measure cotton maturity and fineness simultaneously. The effectiveness and accuracy of the measurement were established. The impact of environmental conditions was identified. Very good agreements to fiber micronaire were also observed. Operational protocols for routine measurements were recommended. A processing system for the conversion of ~50g samples into textile products has been established, consisting of modified full-scale carding and drafting equipment and a lab spinning frame. Over 800 samples have been processed on the system. Over 150 samples have been processed on both the miniature-scale and large-scale systems for direct comparison.

4. Accomplishments

Review Publications
Mcavey, K.M., Guan, B., Fortier, C.A., Tarr, M.A., Cole, R.B. 2011. Laser-induced oxidation of cholesterol observed during MALDI-TOF mass spectrometry. Journal of American Society for Mass Spectrometry. 22:659-669. DOI: 10.1007/s13361-011-0074-3.

Rodgers III, J.E., Kang, S., Fortier, C.A., Cui, X., Delhom, C.D., Knowlton, J. 2011. Minimization of operational impacts on spectrophotometer color measurements for cotton. Journal of Cotton Science. 14:240-250.

Chun, D.T., Rodgers III, J.E. 2011. Two ways fungul spores can affect cotton color. Journal of Cotton Science. 15:52-60.

Rodgers III, J.E., Fortier, C.A., Montalvo Jr, J.G., Cui, X., Kang, S., Martin, V. 2010. Near infrared measurment of cotton fiber micronaire by portable near infrared instrumentation. Textile Research Journal. 80(15):1503-1515.

Rodgers III, J.E., Kang, S., Fortier, C.A., Cui, X., Davidonis, G.H., Clawson, E., Boquet, D., Pettigrew, W.T. 2010. Preliminary field measurement of cotton fiber micronaire by portable NIR. Spectroscopy Magazine. 25(9):38-44.

Fortier, C.A., Rodgers Iii, J.E., Santiago Cintron, M., Cui, X., Foulk, J.A. 2011. Identification of cotton and cotton trash components by fourier-transform near-infrared spectropscopy. Textile Research Journal. 81 (3)230-238.

Bel, P., Xu, B. 2011. White specks measured by autorate and the relationship to AFIS fiber data. Journal of Cotton Science. 11(4):59-65.

Delhom, C.D., Byler, R.K. 2011. Performance of a microwave bale moisture content meter. Journal of Agricultural Science and Technology. 5(2):181-187.

Cai, Y., Cui, X., Rodgers III, J.E., Thibodeaux, D.P., Martin, V., Watson, M., Pang, S. 2011. An investigation on different parameters used for characterizing short cotton fibers. Textile Research Journal. 81(3)239-246.

Condon, B.D., Gary, L., Sawhney, A.P., Reynolds, M.L., Slopek, R.P., Delhom, C.D., Hui, D. 2010. Properties of nonwoven fabrics made with UltraClean™ cotton. World Journal of Engineering. 7(2):180-184.

Belmasrour, R., Li, L., Cui, X., Cai, Y., Rodgers III, J.E. 2011. Obtaining Cotton Fiber Length Distributions from the Beard Test Method Part 2 – A New Approach through PLS Regression. Journal of Cotton Science. 15:73-79.

Sun, J., Yao, M., Xu, B., and Bel, P., 2011. Fabric wrinkle characterization and classification using modified wavelet coefficients and optimized support-vector-machine classifier. Textile Research Journal. 81(9):902-913.

Hinchliffe, D.J., Meredith Jr, W.R., Delhom, C.D., Thibodeaux, D.P., Fang, D.D. 2011. Elevated growing degree days influence transition stage timing during cotton (Gossypium hirsutum L.) fiber development and result in increased fiber strength. Crop Science. 51:1683-1692. DOI: 10.2135/cropsci2010.10.0569.

Last Modified: 10/18/2017
Footer Content Back to Top of Page