Measurement comparison of cotton fiber micronaire and its components by portable near infrared spectroscopy instruments

2016 ◽  
Vol 87 (1) ◽  
pp. 57-69 ◽  
Author(s):  
James Rodgers ◽  
Jimmy Zumba ◽  
Chanel Fortier
Keyword(s):  
Cotton Fiber ◽  
Textile Industry ◽  
Near Infrared ◽  
Fiber Quality ◽  
Nir Spectroscopy ◽  
Fiber Properties ◽  
Fiber Fineness ◽  
Cotton Fiber Quality ◽  
Fiber Processing ◽  
Universal Nature

Micronaire is a key cotton fiber quality assessment property, and changes in fiber micronaire can impact fiber processing and dyeing consistency. Micronaire is a function of two fiber components—maturity and fineness. Historically, micronaire is measured in a laboratory under tightly controlled environmental conditions. There is increased interest by the cotton and textile industry to measure key fiber properties both in the laboratory and in-field (non-controlled conditions), using small portable near infrared (NIR) spectroscopy instruments. A program was implemented to determine the feasibility of using portable NIR instruments to monitor fiber micronaire, maturity, and fineness. Prior to outside the laboratory measurements (field, warehouse, etc.), laboratory feasibility was performed to assess the NIR instruments’ capabilities. Comparative evaluations for fiber micronaire, maturity, and fineness were performed on three portable NIR instruments. Instrumental, sampling, and operational procedures and protocols for each instrument were established. Although representing different measurement technologies, very good spectral agreement was observed between the portable NIR instruments and a bench-top NIR unit used as a comparison. Rapid (less than 3 minutes per sample), easy to use, and accurate measurements of fiber micronaire and maturity were achieved, with regressions ( R values) greater than 0.85, low residuals, and a low number of outliers observed for each NIR instrument. Improvements are required for the accurate measurement of fiber fineness by portable NIR instruments. Thus, for well-defined cotton fiber samples, the universal nature of the NIR measurement of cotton fiber micronaire and maturity by portable NIR instruments was validated.

scholarly journals DETERMINATION OF THE FACTORS LIMITING COTTON FIBER QUALITY IN TURKEY

2021 ◽  
Vol 185 (1) ◽  
pp. 85-99
Author(s):  
Seyhan YASAR ◽  
Emine KARADEMIR
Keyword(s):  
Textile Industry ◽  
Fiber Strength ◽  
Fiber Quality ◽  
Short Fiber ◽  
Light Yellow ◽  
Fiber Fineness ◽  
Two Samples ◽  
Mature Group ◽  
Cotton Fiber Quality ◽  
Fiber Maturity

This study aims to determine the variation of fiber quality in cotton varieties produced in the Southeastern Anatolia Region and Sanliurfa, Diyarbakir provinces. 1090 fiber samples were obtained from 6 cotton varieties (Lima, Stoneville 468, Candia and Babylon for Sanliurfa, Lima, Stoneville 468, Lodos and Gloria for Diyarbakir) collected from ginning factories in Sanliurfa and Diyarbakir. Statistical analyzes were done with HVI device and obtained data were analyzed by using Excel and TOTEMSTAT programs. In the frequency distribution, cotton varieties of the region are in the medium and long fiber group in terms of fiber length. They were in the medium (only two samples), strong and very strong group in terms of fiber strength. They were generally in the medium and thick group in terms of fiber fineness (micronaire). In terms of fiber uniformity index, the majority of the fibers were in the middle group. In terms of short fiber index, most of the fibers were in the very low and low groups. The majority of the samples were in the high and medium group in terms of fiber elongation, in the mature and very mature group in terms of fiber maturity. In terms of spinning consistency index (SCI) 59,2% of the fibers were between 119,41 and 135,83; 31,3% of them, were between 135,83 and 152,24, 58,2% of the material has a reflectance value of 74 and above. All materials were in white and light-yellow groups in terms of yellowness. It has been observed that the majority of the fibers (66%) are in the low group in terms of trash count. The results obtained from the study of cotton produce of Southeastern Anatolia Region of Turkey has shown that good fiber quality and to meet the demand of textile industry.

scholarly journals Use of Pressured-Air for Cotton Lint Cleaning

2019 ◽  
Vol 12 (1) ◽  
pp. 31
Author(s):  
Ruixiu Sui
Keyword(s):  
Cotton Fiber ◽  
Fiber Length ◽  
Fiber Quality ◽  
High Volume ◽  
Short Fiber ◽  
Fiber Content ◽  
Mechanical Contact ◽  
Cotton Lint ◽  
Fiber Properties ◽  
Cotton Fiber Quality

Saw-type lint cleaner (STLC) was most efficient lint cleaner in cotton ginning. However, STLC damaged fiber quality. An air-bar lint cleaner (ABLC) was developed and evaluated to preserve cotton fiber quality. The ABLC used pressurized-air to remove non-lint materials from cotton fiber. During lint cleaning process, non-lint materials attached to the fiber were blown off the fiber without the fiber making aggressive mechanical contact with a grid bar in conventional saw-type lint cleaner (STLC). It was expected using this concept that the fiber quality could be preserved by reducing the damage from mechanical impact of the fiber against the grid bar. Preliminary testing of the ABLC prototype showed that ABLC generated less lint waste and had a higher turnout rate than STLC. Use of ABLC could save 2.8 kg of lint in each 225 kg bale of cotton. The High Volume Instrument (HVI) analysis indicated the fiber properties in fiber length, uniformity, short fiber content, and color were not significantly different between ABLC and STLC. However, the Advanced Fiber Information System (AFIS) tests showed STLC had better performance than ABLC in fiber length and short fiber content while the trash and dust content with ABLC was lower than the STLC. More research was necessary to further prove the concept of ABLC and improve its performance in preserving cotton fiber quality.

Discriminant analysis-based modeling of cotton fiber and yarn properties

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Baneswar Sarker ◽  
Shankar Chakraborty
Keyword(s):  
Discriminant Analysis ◽  
Physical Properties ◽  
Cotton Fiber ◽  
Fiber Strength ◽  
Natural Fibers ◽  
Content Type ◽  
Fiber Properties ◽  
Yarn Properties ◽  
Fiber Fineness ◽  
Genetic And Environmental Factors

Purpose Like all other natural fibers, the physical properties of cotton also vary owing to changes in the related genetic and environmental factors, which ultimately affect both the mechanics involved in yarn spinning and the quality of the yarn produced. However, information is lacking about the degree of influence that those properties impart on the spinnability of cotton fiber and the strength of the final yarn. This paper aims to discuss this issue. Design/methodology/approach This paper proposes the application of discriminant analysis as a multivariate regression tool to develop the causal relationships between six cotton fiber properties, i.e. fiber strength (FS), fiber fineness (FF), upper half mean length (UHML), uniformity index (UI), reflectance degree and yellowness and spinning consistency index (SCI) and yarn strength (YS) along with the determination of the respective contributive roles of those fiber properties on the considered dependent variables. Findings Based on the developed discriminant function, it can be revealed that FS, UI, FF and reflectance degree are responsible for higher YS. On the other hand, with increasing values of UHML and fiber yellowness, YS would tend to decrease. Similarly, SCI would increase with higher values of FS, UHML, UI and reflectance degree, and its value would decrease with increasing FF and yellowness. Originality/value The discriminant functions can effectively envisage the contributive role of each of the considered cotton fiber properties on SCI and YS. The discriminant analysis can also be adopted as an efficient tool for investigating the effects of various physical properties of other natural fibers on the corresponding yarn characteristics.

RAPID SAMPLING SYSTEM FOR DETERMINATION OF COTTON FIBER QUALITY SPATIAL VARIABILITY

2005 ◽  
Vol 21 (1) ◽  
pp. 9-14 ◽  
Author(s):  
G. F. Sassenrath ◽  
E. R. Adams ◽  
J. R. Williford
Keyword(s):  
Spatial Variability ◽  
Cotton Fiber ◽  
Fiber Quality ◽  
Sampling System ◽  
Rapid Sampling ◽  
Cotton Fiber Quality

Influence of Cotton Fiber Strength and Fineness on Fiber Damage during Lint Cleaning

1988 ◽  
Vol 58 (8) ◽  
pp. 433-438 ◽  
Author(s):  
J. K. Dever ◽  
J. R. Gannaway ◽  
R. V. Baker
Keyword(s):  
Significant Relationship ◽  
Cotton Fiber ◽  
Fiber Length ◽  
Fiber Strength ◽  
Fiber Breakage ◽  
Fiber Damage ◽  
Fiber Properties ◽  
Fiber Fineness ◽  
Wide Range ◽  
Induced Changes

Seven sources of cotton representing a wide range of fiber properties were roller ginned, saw ginned, or saw ginned plus processed through tandem saw lint cleaners or through an aggressive carding-type cleaner (Cottonmaster1). Lint cleaner induced changes in fiber length and nep count were compared to fiber property measurements from roller ginned samples. Fiber length deterioration from saw ginning was negatively correlated with fiber strength. Fiber breakage in lint cleaning was positively correlated with fiber fineness. Resistance to fiber length damage in ginning was explained best by fiber strength and fineness, or an estimate of individual fiber strength. Initial and final nep level were related to fineness, nonlint content, and upper quartile length, but an increase in neps due to lint cleaning had no significant relationship to fiber properties.

A Wireless GPS System for in-field Cotton Fiber Quality Mapping

2006 ◽  
Author(s):  
Yufeng Ge ◽  
J. A. Thomasson ◽  
Ruixiu Sui
Keyword(s):  
Cotton Fiber ◽  
Fiber Quality ◽  
Cotton Fiber Quality ◽  
Gps System

QTL analysis of genotype × environment interactions affecting cotton fiber quality

2003 ◽  
Vol 106 (3) ◽  
pp. 384-396 ◽  
Author(s):  
A. H. Paterson ◽  
Y. Saranga ◽  
M. Menz ◽  
C.-X. Jiang ◽  
R. Wright
Keyword(s):  
Qtl Analysis ◽  
Cotton Fiber ◽  
Fiber Quality ◽  
Cotton Fiber Quality

scholarly journals Historical Datasets Support Genomic Selection Models for the Prediction of Cotton Fiber Quality Phenotypes Across Multiple Environments

2018 ◽  
Vol 8 (5) ◽  
pp. 1721-1732 ◽  
Author(s):  
Washington Gapare ◽  
Shiming Liu ◽  
Warren Conaty ◽  
Qian-Hao Zhu ◽  
Vanessa Gillespie ◽  
...  
Keyword(s):  
Genomic Selection ◽  
Cotton Fiber ◽  
Fiber Quality ◽  
Selection Models ◽  
Cotton Fiber Quality ◽  
Multiple Environments

Harvester-Based Cotton Fiber Quality Sensor

2009 ◽  
Author(s):  
Vince P Schielack III ◽  
Ruixiu Sui ◽  
J A Thomasson ◽  
Eric Hequet ◽  
Christine Morgan
Keyword(s):  
Cotton Fiber ◽  
Fiber Quality ◽  
Cotton Fiber Quality
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