Web-Nep Procedure for Predicting Potential Dyeing Problems in Cotton1

Cheek, Lenore; Hsu, Lun Chen; Thibodeaux, Devron P.

doi:10.1177/004051759006000207

Cited by 5 publications

(3 citation statements)

References 4 publications

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“…SJ-2 has been one of the most studied Acala varieties, and Maxxa is the major variety grown currently in California. SJC-9 is an experimental variety selected for its better dyeability, reported by others [ 2,11 ] . For the SJC-9 variety, first position bolls were randomly collected from branches 4 through 12 at varying ages or developmental stages, including at least two bolls at each developmental stage of 21, 28, 35, 42, 49 days post-anthesis ( dpa ), as well as after boll opening on the plant.…”

Section: Methodsmentioning

confidence: 99%

Dyeing Characteristics of Acala Cotton Seed Fibers

Thompson

Hsieh

1998

Textile Research Journal

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The dyeing characteristics of fibers from three Acala cotton varieties, i.e., Maxxa, SJ-2, and SJC-9, are investigated using direct and reactive dyestuffs along with the Goldthwait cotton maturity test. Dyed and less-dyed fibers are detached from the dyed seed fibers, separated, and characterized by seed fiber weight, single fiber strength, and color measurement. With Direct Blue 1, SJC-9 fibers are dyed to the darkest shade across all seed fiber weights, whereas the Maxxa fibers have the lightest shade. The SJC-9 seed fibers have the least amounts ( ~5%) of less-dyed fibers and the proportions of such fibers are independent of seed fiber weights. For the Maxxa and SJ-2 varieties, the proportions of less-dyed fibers decrease with increasing seed fiber weights. The proportions of less-dyed Maxxa and SJ-2 fibers are above 30% on seed fibers weighing less than 100 mg and are 10% or less on seeds weighing more than 150 mg. The SJ-2 seed fibers contain higher proportions of less-dyed fibers, but their overall shades are deeper than the Maxxa fibers. For all three varieties, most less-dyed fibers are from the chalazal ends of the seeds of all seed fiber weights. Dyeing with Reactive Blue 19 results in the same proportions of less-dyed fibers on the Maxxa seed fibers as with Direct Blue 1. The Goldthwait cotton maturity test confirms the trend of decreasing amounts of less-dyed fibers with increasing seed fiber weight with both direct and reactive dyes. For all three varieties, the force to break is higher for the dyed fibers than the less-dyed fibers, confirming that less-dyed fibers have less developed cell wall structures.Lack of dyeing uniformity in cotton products has been a long-standing concern of the textile processing industry. Dyeing problems with cotton products are thus far associated with less or undeveloped fibers or with fiber immaturity. These dyeing defects are not evident until after the fabrics have been dyed, and they greatly reduce fabric quality, desirability, and value. Considering the significant impact on product quality, however, literature on efforts to understand and solve these dyeing uniformity problems has been modest [ 2-6, II -18. 201.Most such dyeing defects have been associated with neps, specks, and seed coat fragments [ 1, 11 ) . Discussions of neps date back to 1848 in Clegg and Harland's s [ 5 ] review. Neps have had a number of slightly varying definitions: generally, they are clusters of tangled immature or dead fibers that are predisposed to snarling or clumping because of their thin cellulose cell wall and low resistance to bending. Dyeing defects caused by neps have been categorized into three types [ 18 ] . One type consists of matted fibers that are dyed to a similar depth as the rest of the fabric, but appear lighter because of the higher reflectance of their flat surfaces. Another type consists of immature fibers that fail to dye to the same shade or depth as the remaining fibers. The third type occurs when surface neps are removed after dyeing, leaving white or lighter sp...

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Section: Methodsmentioning

confidence: 99%

Dyeing Characteristics of Acala Cotton Seed Fibers

Thompson

Hsieh

1998

Textile Research Journal

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“…[4][5][6][7][8] While modern dyeing factories can carefully control these factors, there are other parameters which are less easily controlled, such as water quality, atmospheric pressure conditions, measuring instrument errors, dyeing equipment errors, and operator experience. 9 Practice has shown that to achieve high one-time success at low costs, it is necessary to improve the dyeing device and the equipment level, control accurately dyeing process and quality of dyeing products and optimize dye concentrations and processing conditions. Thus, the ability to establish a suitable and accurate relationship between the factors affecting the dyeing process and actualized effect on the cotton fabric is paramount for efficient production of commercial fabrics.…”

mentioning

confidence: 99%

“…Depending on the method of adding alkali agents and the type of dyeing bath, exhaustion dyeing can be divided into the one-bath one-step, one-bath two-step, and two-bath three-step. 9 Whereas exhaustion dyeing is the most common method, the appeal of cold pad-batch dyeing is its short dyeing process, simple production equipment, energy-savings and low processing costs. Additionally, it is especially suitable for small batch and multi-variety processing.…”

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confidence: 99%

K/S value prediction of cotton fabric using PSO-LSSVM

et al. 2020

Textile Research Journal

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Cotton is one of the world’s most common natural clothing materials. It is dyed mainly using the exhaustion, cold pad-batch, and pad-dry-pad-steam dyeing methods. The K/S value, an important index for measuring the depth of color, of cotton fabric dyed with reactive dyes is greatly influenced by various factors of the dyeing process. In this study, three models were developed incorporating least squares support vector machine (LSSVM) to predict the K/S values of dyed cotton fabrics, while particle swarm optimization (PSO) was applied to optimize and tune the parameters of the LSSVM model (PSO-LSSVM). Model inputs include dye concentration and process conditions, which are both easily obtainable variables. The K/S values from the PSO-LSSVM model are consistent with actual measured K/S values of dyed cotton fabrics. Moreover, a comparison among PSO-LSSVM, LSSVM and back propagation neural network results shows the superiority of the PSO-LSSVM approach. Results of this work indicate that a PSO-LSSVM model is a powerful tool for predicting the K/S value in cotton fabric dyed with reactive dye and thus a means to improve production processes and reduce costs.

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A review on the formation, causes, measurement, implications and reduction of neps during cotton processing

Sluijs

Hunter

2016

Textile Progress

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Web-Nep Procedure for Predicting Potential Dyeing Problems in Cotton1

Cited by 5 publications

References 4 publications

Dyeing Characteristics of Acala Cotton Seed Fibers

Dyeing Characteristics of Acala Cotton Seed Fibers

K/S value prediction of cotton fabric using PSO-LSSVM

A review on the formation, causes, measurement, implications and reduction of neps during cotton processing

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