Skip to main content
ARS Home » Southeast Area » New Orleans, Louisiana » Southern Regional Research Center » Cotton Structure and Quality Research » Research » Publications at this Location » Publication #289608
Title: An assessment of alternative cotton fibre quality attributes and their relationship with yarn strength

Author
item LONG, ROBERT - Commonwealth Scientific And Industrial Research Organisation (CSIRO)
item BANGE, MICHAEL - Commonwealth Scientific And Industrial Research Organisation (CSIRO)
item Delhom, Christopher
item CHURCH, JEFFREY - Commonwealth Scientific And Industrial Research Organisation (CSIRO)
item CONSTABLE, GREG - Commonwealth Scientific And Industrial Research Organisation (CSIRO)

Submitted to: Crop and Pasture Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/15/2013
Publication Date: 4/9/2013
Citation: Long, R.L., Bange, M.P., Delhom, C.D., Church, J.S., Constable, G.A. 2013. An assessment of alternative cotton fibre quality attributes and their relationship with yarn strength. Crop and Pasture Science. 64(8):750-762. http://dx.doi.org/10.1071/CP12382.

Interpretive Summary: Knowing the yarn strength performance potential of cotton fibre is advantageous to spinners during mill preparation, and to researchers developing new genotypes and management strategies to produce better fibre. Standard High Volume Instrument (HVI) fibre quality attributes include micronaire, a combined measure of fibre linear density and maturity, and bundle tensile properties. While these attributes relate well to yarn strength, alternative fibre quality attributes may better explain the variation in yarn strength. Two field experiments over two seasons were conducted to assess the fibre and yarn performance of some Australian cotton genotypes. The aim was to assess and compare alternative measures for micronaire, and to compare bundle and single fibre tensile measurements, and assess the relative yarn strength predictive performance of these attributes. Specific fibre measurement comparisons were for linear density [double compression Fineness Maturity Tester (FMT) and gravimetric), maturity ratio (FMT, polarized light, calculated and cross sectional), and tensile properties (HVI bundle and Favimat Robot single fibre). Multiple linear regression models for yarn strength which included yarn manufacturing variables and standard HVI fibre quality parameters performed well [standard error of prediction (SEP) = 2.40 cN tex-1]. Multiple linear regression models performed better when alternatives to micronaire were used; e.g. using gravimetric linear density (SEP = 2.15 cN tex-1), or using laser photometric determined ribbon width (SEP = 1.71 cN tex-1). Yarn strength models were also better when single fibre tensile properties were substituted for bundle tensile properties (SEP = 1.07 cN tex-1). The substitution of alternative fineness variables for micronaire or single fibre strength for bundle strength in a simple fibre quality index also improved the prediction of yarn strength.

Technical Abstract: Knowing the yarn strength performance potential of cotton fibre is advantageous to spinners during mill preparation, and to researchers developing new genotypes and management strategies to produce better fibre. Standard High Volume Instrument (HVI) fibre quality attributes include micronaire, a combined measure of fibre linear density and maturity, and bundle tensile properties. While these attributes relate well to yarn strength, alternative fibre quality attributes may better explain the variation in yarn strength. Two field experiments over two seasons were conducted to assess the fibre and yarn performance of some Australian cotton genotypes. The aim was to assess and compare alternative measures for micronaire, and to compare bundle and single fibre tensile measurements, and assess the relative yarn strength predictive performance of these attributes. Specific fibre measurement comparisons were for linear density [double compression Fineness Maturity Tester (FMT) and gravimetric), maturity ratio (FMT, polarized light, calculated and cross sectional), and tensile properties (HVI bundle and Favimat Robot single fibre). Multiple linear regression models for yarn strength which included yarn manufacturing variables and standard HVI fibre quality parameters performed well [standard error of prediction (SEP) = 2.40 cN tex-1]. Multiple linear regression models performed better when alternatives to micronaire were used; e.g. using gravimetric linear density (SEP = 2.15 cN tex-1), or using laser photometric determined ribbon width (SEP = 1.71 cN tex-1). Yarn strength models were also better when single fibre tensile properties were substituted for bundle tensile properties (SEP = 1.07 cN tex-1). The substitution of alternative fineness variables for micronaire or single fibre strength for bundle strength in a simple fibre quality index also improved the prediction of yarn strength.