An assessment of alternative cotton fibre quality attributes and their relationship with yarn strength
Robert L. Long A D E , Michael P. Bange B D , Christopher D. Delhom C , Jeffrey S. Church A and Greg A. Constable B
+ Author Affiliations
- Author Affiliations
A CSIRO Materials Science and Engineering, PO Box 21, Belmont, Vic. 3216, Australia.
B CSIRO Plant Industry, Locked Bag 59, Narrabri, NSW 2390, Australia.
C USDA-ARS Southern Regional Research Centre, 1100 Robert E. Lee Boulevard, New Orleans, LA 70124, USA.
D Cotton Catchment Communities Co-operative Research Centre, Australia.
E Corresponding author. Email: robert.long@csiro.au
Crop and Pasture Science 64(8) 750-762 https://doi.org/10.1071/CP12382
Submitted: 13 November 2012 Accepted: 15 February 2013 Published: 9 April 2013
Journal Compilation © CSIRO Publishing 2013 Open Access CC BY-NC-ND
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, polarised light, calculated, and cross-sectional), and tensile properties (HVI bundle and Favimat Robot single fibre). Multiple linear regression models for yarn strength that 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 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.
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