2021
DOI: 10.1177/0040517521992769
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Effects of cotton genotype, defoliation timing and season on fiber cross-sectional properties and yarn performance

Abstract: Cotton fiber cross-sectional properties influence the performance of ring spun yarns. The spinning performance of two Gossypium hirsutum L. Upland cotton genotypes known to have inherently different fiber fineness properties were compared. Genotypes were grown together in field experiments conducted over two growing seasons, and crops were subjected to early and late defoliation treatments. The aim was to quantify the differences in yarn properties following changes targeting fiber fineness properties in isola… Show more

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Cited by 15 publications
(9 citation statements)
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“…Similar to our results, Long et al (2021) obtained stronger and more uniform yarns with the finer fibers produced in the first season, whereas weaker and less evenly spun fibers were produced in the second season due to the adverse environmental conditions. Özkan et al (2021) showed that cotton yarn and other yarns were significantly differed in terms of thin places and reported that the blending ratio had a statistically significant (p<0.05) effect on both irregularity and thin place data.…”
Section: Thin Places (-40%)supporting
confidence: 90%
“…Similar to our results, Long et al (2021) obtained stronger and more uniform yarns with the finer fibers produced in the first season, whereas weaker and less evenly spun fibers were produced in the second season due to the adverse environmental conditions. Özkan et al (2021) showed that cotton yarn and other yarns were significantly differed in terms of thin places and reported that the blending ratio had a statistically significant (p<0.05) effect on both irregularity and thin place data.…”
Section: Thin Places (-40%)supporting
confidence: 90%
“…in 2020 exhibited coarse fiber. The base micronaire is between 3.50 and 4.90 [26]. Cotton with fiber fineness other than commercial values is limited in the range of use by the textile industry.…”
Section: Resultsmentioning
confidence: 99%
“…Hence, studying and understanding the distribution and shape of the fibers across the length of the yarn is beneficial [ 2 , 3 ], and this information can be extracted from yarn cross-sectional slices or images. Analyzing the images of these sections can reveal the geometrical parameters, such as packing density, effective packing density, and ellipticity shape [ 4 , 5 , 6 ], which contribute to the yarn’s properties, such as tensile strength, elongation, appearance, compactness, and the overall fabric surface [ 7 ]. Obtaining detailed and high-resolution slices can reveal the details of the yarn’s structure and allow deeper analysis, modeling, and simulation of the textile structure, which can be more realistic and representative of the actual model; several groups simulated the textile yarn using digitally generated models [ 8 , 9 , 10 ].…”
Section: Introductionmentioning
confidence: 99%