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Alternate Relationship between Single Fiber Properties and Both of Fiber Microscopic and Physical Properties | OMICS International
ISSN: 2165-8064
Journal of Textile Science & Engineering
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Alternate Relationship between Single Fiber Properties and Both of Fiber Microscopic and Physical Properties

Abeer S Arafa*

Cotton Research Institute, Agricultural Research Center, Egypt

*Corresponding Author:
Arafa SA
Cotton Research Institute
Agricultural Research Center, Egypt
Tel: 66-81-9750669
E-mail: [email protected]

Received Date: October 17, 2014; Accepted Date: November 21, 2014; Published Date: November 24, 2014

Citation: Arafa AS (2014) Alternate Relationship between Single Fiber Properties and Both of Fiber Microscopic and Physical Properties. J Textile Sci Eng 4:175. doi: 10.4172/2165-8064.1000175

Copyright: © 2014 Arafa AS. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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Abstract

Current study was carried out in Cotton Research Institute, Agricultural Research Center, Egypt and Textechno company labs Monchengladbach, Germany during 2013 season. The materials used in this study comprised 16 different genotypes produced by cotton research institute. In addition to, two upland cotton varieties from Sudan. Aiming to study the effect of environmental conditions, genotypes and thier interaction on each characters under study beside studyig the relationship between single fiber prroperties and bundle properties. Giza 93 variety showed the lowest micronaire, fineness and area of cross section. On contrast, it showed the highest upper half mean. Giza 87 variety exhibited the highest bundle strength, the lowest reversals number per mm and the narrowest convolution angle. As for single fiber properties. Giza 45 variety followed by Giza 87 variety exhibited the lowest single fiber linear density readings. Single fiber strength is a little bit lower than bundle strength. Giza 87 variety surpassed the other genotypes on single fiber strength. Upland cotton varieties showed the worst bundle and single fiber properties. As maturity ratio increased bundle and single fiber properties improved and vice versa. According to, the relationship between single fiber prroperties and bundle properties, there was a nearly linear relation¬ship between fiber properties and single fiber properties. After excluding the weak correlated characters 3 linear multiple regression models for single fiber tenacity, single fiber linear density and single fiber elongation were produced. Fineness and degree of thickness were the predictor variables for single fiber strength parameters. However, fiber fineness per mtex and micronaire values were the most important factors for single fiber linear density, both of them proportionate directly with single fiber linear density. While, single fiber elongation contains 7 predictors i.e. Micronaire reading, UI, area of cross section, theta, fiber strength, fiber elongation and UHM characters. Nevertheless, it showed the weakest relation, UI, area of cross section, and fiber Strength proportionate inversely with single fiber elongation. The model is not reliable enough for single fiber elongation prediction.

Keywords

Cotton; Fiber; Single; Fineness; Strength; Elongation

Introduction

Quality is the ultimate goal of the cotton manufacturer because raw material costs are high up to50% of the total manufacturing costs at the spinning mill. These costs decrease or increase depending on the fiber quality of the raw material.

The quality is a set of attributes, some of them are related to the bundle physical and mechanical characters each measured with fast and easy instruments like AFIS , HVI and Fibrotest while, the others are time consuming attributes such as single fiber characters which need some complicated instruments like Image analyzer, Favimat and Robot tester. In fact, the qualities of single or bundle fiber characters is a result of some genetic factors like fiber perimeter or diameter ,cellulose deposition order, the angle of deposition [1] some others are associated with the growing conditions like the amount of cellulose deposited inside the fiber which represents the fiber body.

On the other hand, the single fiber characters are an indicator for the bundle physical and mechanical characters is that the bundle breaking and elongation were shown to increase as the single fiber breaking elongation increased [2] something like a building consisting of bricks, walls, and then the rooms.

From a commercial and industrial point of view, cotton faces great competition with the other natural and synthetic textile fibers. It should be strong enough to compete with other natural and synthetic textile fibers [3].

Hence it is important:

1. Studing how much each characters affected by the environmental conditions, genotypes and the interaction between them.

2. Understanding how some microscopic characters are associated with bundle and single fiber characters like fiber perimeter or diameter which describes the fiber intrinsic or biological fineness that is controlled by genetics. Intrinsic fineness is completely different from the fineness in millitex or linear density as weight of unit length. When we deal with weight, we do weight of cellulose where the maturity and the growing conditions affect. So, if there are two fibers equally in the intrinsic fineness (diameter or the perimeter) the higher in maturity ratio will give higher millitex reading (Figure 1).

textile-science-engineering-the-relationship-maturity

Figure 1: The Relationship between fineness and maturity.

3. Studying the effect of wall thickening (Figure 2) and the structural properties like convolution angle which refers to spiral angle (the angle formed between the fiber long axis and the cellulose layer the more acute angle the higher, fiber strength and reversals per unit length (the point which the cellulose layer changed the deposition direction from clock wise direction to anti clock wise direction and vice versa. This forms weak points during the tenacity test (Figure 3) [4].

textile-science-engineering-cross-section-mature-fiber

Figure 2: Cross Section of Mature Cotton Fiber.

textile-science-engineering-fiber-reversals

Figure 3: Fiber Reversals.

4. The relationship between single fiber properties and bundle properties.

The investigation was conducted during 2013 season. The materials used in this study comprised 16 different genotypes (G) named (Giza 88, Giza 92, Giza 93, [G.84 (G.70xG.51b)] defined as C1, Giza 45, Giza 87, Giza 80, Giza 90, G90xAus. - defined as C2, [G.83(G75x5844)] G.80 defined as C3, 10229xG86 defined as C4, Giza 86, green cotton and brown cotton) produced by cotton research institute. In addition to, (upland Sudan fine, upland Sudan coarse). Aiming to study the effect of inherent fiber characters on the single fiber properties. Under all the genotypes we used two maturity ratio levels (L1, L2) within each genotype were used to study the effect of the fiber maturity on the single fiber properties. Beside, study the effect of some structural properties on the behavior of the single fiber during the mechanical tests.

The investigation was conducted during 2013 season. The materials used in this study comprised 16 different genotypes (G) named (Giza 88, Giza 92, Giza 93, [G.84 (G.70xG.51b)] defined as C1, Giza 45, Giza 87, Giza 80, Giza 90, G90xAus. - defined as C2, [G.83(G75x5844)] G.80 defined as C3, 10229xG86 defined as C4, Giza 86, green cotton and brown cotton) produced by cotton research institute. In addition to, (upland Sudan fine, upland Sudan coarse). Aiming to study the effect of inherent fiber characters on the single fiber properties. Under all the genotypes we used two maturity ratio levels (L1, L2) within each genotype were used to study the effect of the fiber maturity on the single fiber properties. Beside, study the effect of some structural properties on the behavior of the single fiber during the mechanical tests.

Studied characters

Microscopic characters

The cross sections and the Images were processed at the Textile Consolidation Fund, Alexandria, Egypt. While, the Image Analyzer located in the Fiber Structural and Microscopic lab, Cotton Research Institute, Giza. Was used to analyze the fiber cross section images to calculate fiber perimeter with [μ], fiber area of cross section (ASCW) in [μ]2 and degree of thickening (θ). Number of reversals per mm, number of Convolutions per mm, and ribbon width in micron were tested using (G208 projection microscope according to ASTM D: 2130- 1986). Convolution angle was calculated according to [5], convolution angle=(п/2 X Average ribbon width /C) where, C=Convolutions pitch length divided by the number of convolutions.

Fiber physical characters

The Micromat instrument was used to determine micronaire reading, maturity ratio (MR), hair weight (fiber linear density (millitex)) (ASTM-D;2818-1986). Fiber upper half mean length UHM (mm), length uniformity index UI, short fiber content SFC, fiber strength (g/ tex) and fiber elongation (%) were measured by Fibrotest instrument in Textechno company labs Monchengladbach, Germany.

Single fiber characters

Single fiber measurements and force/elongation curves were performed using Favimate + and Favigraph instruments in Textechno company labs Monchengladbach Germany.

Complete randomized design (two ways ANOVA) was used to analyze the data statistically. The treatment means were compared using. L.S.D. test at 0.05% Level. Simple and multiple regression model were performed between fiber properties (X) variables, single fiber properties (Y) according to the procedures outlined by [6].

Results and Discussions

Data presented in Table 1, explained the effect of the genotypes, maturity level and their interaction on fineness and maturity parameters measurements. As to the micronaire reading, Giza 93 showed the lowest micronaire reading (2.65) followed by Giza 87 (2.70) these reading were fitted to their fineness readings (103.61 and 103.25 mtex) ,respectively. Micronaire reading looks similar to fineness in mtex both could not be good indicator for fineness because it expresses both of fineness and maturity. They are referring to the fineness when the comparison is done between the genotypes of the same maturity or they are referring to the maturity degree when the comparison is done between the two maturity level inside the same genotype, the relation between fineness and maturity is not that easy it is complicated. Thus, determining fineness and maturity parameters using image analyzer as a reference method was very important to explain the results under this study. Giza 93 and Giza 87 exhibited the lowest two readings for the area of cross section (71.07 and 79.70[μ]²) respectively, which explained that the two pervious verities are the finest varieties comparing to the other genotypes. According to maturity ratio and theta values which, determine the amount of cellulose deposition or maturity degree. Giza 93 readings for maturity ratio and theta characters were (0.87 and 0.50), respectively.

Sample Micromat measurements Image analyzer measurements
mic MR Fineness θ ASCW[μ]2
G 88 L1 2.90 0.90 111.62 0.53 73.01
G 88 L2 3.65 1.03 137.59 0.62 98.56
G88mean 3.28 0.97 124.61 0.58 85.79
G 92 L1 3.00 0.85 105.90 0.52 73.00
G 92 L2 4.00 1.05 148.89 0.63 109.62
G92mean 3.50 0.95 127.39 0.58 91.31
G 93 L1 2.15 0.82 93.00 0.45 58.28
G 93 L2 3.15 0.91 114.22 0.55 83.86
G93mean 2.65 0.87 103.61 0.50 71.07
c1 L1 3.30 0.87 127.74 0.49 88.14
c1 L2 4.20 0.95 160.57 0.57 116.21
c1mean 3.75 0.91 144.15 0.53 102.18
G 45 L1 2.60 0.87 99.32 0.51 77.35
G 45 L2 3.20 1.00 120.26 0.60 85.27
G45mean 2.90 0.94 109.79 0.56 81.31
G 87 L1 2.40 0.83 94.69 0.48 72.19
G 87 L2 3.00 1.02 103.25 0.61 79.70
87mean 2.70 1.02 103.25 0.61 79.70
G 80 L1 3.15 0.81 146.63 0.44 83.86
G 80 L2 4.35 0.91 173.72 0.54 121.30
G80mean 3.75 0.86 160.18 0.49 102.58
G 90 L1 3.20 0.81 127.17 0.43 85.27
G 90 L2 3.75 0.93 144.02 0.54 101.66
G90mean 3.48 0.87 135.60 0.49 93.47
c2 L1 4.60 0.84 178.21 0.44 128.33
c2 L2 5.00 0.91 199.19 0.45 144.65
c2mean 4.80 0.88 188.70 0.45 136.49
c3 L1 3.90 0.89 160.15 0.55 101.63
c3 L2 4.40 0.98 176.46 0.59 123.02
c3mean 4.15 0.94 168.30 0.57 112.33
G 86 L1 3.90 0.81 153.26 0.44 106.39
G 86 L2 4.50 0.99 169.50 0.50 126.49
G86mean 4.20 0.90 161.38 0.47 116.44
c4 L1 3.50 0.85 145.70 0.45 92.19
c4 L2 3.85 0.91 152.32 0.50 104.80
c4mean 3.68 0.88 149.01 0.48 98.50
green L1 2.50 0.60 139.70 0.38 80.00
green L2 3.00 0.67 157.13 0.40 87.20
gre.mean 2.75 0.64 148.41 0.39 83.60
brown L1 2.90 0.91 117.78 0.48 101.69
brown L2 3.70 0.76 134.38 0.47 130.10
bro.mean 2.90 0.91 117.78 0.48 101.69
upland L1 3.30 0.64 197.78 0.35 131.70
upland L2 5.10 0.60 231.74 0.39 150.92
up.mean 4.20 0.62 214.76 0.37 141.31
L1 mean 3.15 0.82 133.24 0.46 90.20
L2 mean 3.92 0.90 154.88 0.53 110.89
LSD 0.05G 0.07 0.00 2.37 0.00 1.44
LSD 0.05 L 0.04 0.01 1.92 0.00 1.21
LSD 0.05 LxG 0.10 0.01 3.23 0.01 2.20

Table 1: Effect of cotton genotype, maturity level and their interaction on fiber fineness and maturity parameters.

However Giza 87 Varity showed (1.02 and 0.61) for these two characters, respectively. These two varieties exhibited high maturity ratio. Upland cottons showed the lowest maturity ratio reading (0.62) and the lowest theta reading (0.37) followed by the green colored cotton then Giza 80. On the other hand, Giza 90xAus. C2, showed the highest micronaire reading (4.8). While, the upland cottons exhibited the highest fineness in mtex reading (214.76). Indicating that micronaire reading or fineness in mtex refers to the fineness, since it affected so much by maturity. So, their test should be accompanied by maturity test or image analyzer results.

Data of Fiber length and mechanical properties as affected by the genotype ,maturity level and their interaction are illustrated in Table 2, it is obvious from Table 2, that Giza 45 then Giza 93 varieties gave the highest upper half mean readings (35.28 and 35.248 mm), respectively.

Sample Length parameters Fiber mechanical characters
UHM(mm) SFC UI strength(g/tex) elongation%
G 88 L1 34.50 15.27 85.81 53.11 12.00
G 88 L2 35.76 10.77 85.95 58.54 13.82
G88mean 35.13 13.02 85.88 55.83 12.91
G 92 L1 30.32 16.46 82.01 50.19 11.31
G 92 L2 33.95 5.28 85.91 61.99 13.29
G92mean 32.14 10.87 83.96 56.09 12.30
G 93 L1 34.10 13.76 82.63 51.91 11.68
G 93 L2 36.38 11.26 86.06 55.81 12.68
G93mean 35.24 12.51 84.35 53.86 12.18
c1 L1 33.03 12.96 84.56 49.87 11.22
c1 L2  35.36 9.28 87.47 57.36 12.86
c1mean 34.20 11.12 86.02 53.62 12.04
G 45 L1 34.50 15.27 85.81 53.11 12.00
G 45 L2 36.05 20.39 87.51 55.84 12.93
G45mean 35.28 17.83 86.66 55.84 12.93
G 87 L1 33.59 9.36 81.84 54.85 11.11
G 87 L2 35.51 7.36 85.83 57.85 12.19
87mean 34.55 8.36 83.84 56.35 11.65
G 80 L1 29.02 18.33 81.68 35.96 11.74
G 80 L2 30.02 13.66 82.71 41.72 12.14
G80mean 29.52 16.00 82.20 38.84 11.94
G 90 L1 27.29 20.17 79.50 36.12 11.61
G 90 L2 30.46 15.63 80.73 35.9 11.25
G90mean 28.88 17.9 80.12 36.01 11.43
c2 L1 29.00 11.00 80.81 40.00 13.87
c2 L2 29.94 9.86 83.61 41.66 14.11
c2mean 29.47 10.43 82.21 40.83 13.99
c3 L1 30.00 12.14 81.84 33.00 12.17
c3 L2 30.31 11.81 82.25 36.24 12.56
c3mean 30.16 11.98 82.05 34.62 12.37
G 86 L1 30.42 6.51 84.96 50.1 13.77
G 86 L2 32.19 6.18 86.25 45.45 12.41
G86mean 31.31 6.35 85.61 47.78 13.09
c4 L1 31.31 11.21 83.65 46.00 12.31
c4 L2 32.26 10.13 85.62 47.18 12.48
c4 mean 31.79 10.67 84.64 46.59 12.4
green L1 29.14 13.12 81.32 33.14 10.00
green L2 29.37 10.71 83.17 35.20 10.30
gre.mean 29.26 11.92 82.25 34.17 10.15
brown L1 28.71 18.18 80.00 30.06 9.46
brown L2 29.97 18.96 81.45 35.01 9.83
bro. mean 29.34 18.57 80.73 32.54 9.65
upland L1 26.48 24.43 78.40 22.78 7.99
upland L2 27.69 11.21 81.83 25.22 8.52
up. mean 27.09 17.82 80.12 24.00 8.26
L1 mean 30.76 14.54 82.32 42.68 11.48
L2 mean 32.35 11.50 84.42 46.06 12.09
LSD 0.05 G 0.24 0.03 ns 0.44 0.02
LSD 0.05 L 0.16 0.01 ns 0.34 0.01
LSD 0.05 G.L 0.26 0.10 ns n.s 0.04

Table 2: Effect of the genotype, maturity level and their interaction on fiber length and mechanical parameters as measured by Fibrotest instrument using HVI mode.

As for short fiber content, its worthy to mention that the SFC% measured by fibrotest instrument seems to be higher in content than those measured by the other instruments like fibrograph and sorters instruments. Data in Table 2, showed that the higher the maturity level the lower the short fiber content regardless the cotton genotype. (SFC %) being 11.50% for the higher level of maturity vs. 14.54% for the low maturity level. Immature fiber is easily to be broken during ginning resulting high SFC%. Regarding cotton genotype, Giza 86 variety showed the lower SFC% it is averaged 6.35%. While, the extra long cottons exhibited the higher SFC% it ranged from 8.36% in Giza 87 variety to 17.83% in Giza 45 variety and it ranged in upper Egyptian cottons from 10.43 % in c2 to 17.17.90% in Giza 90 variety. Colored cotton showed moderate SFC% but slightly higher than upper Egyptian varieties. Upland cotton showed the highest SFC% averaged 27.09%. Also, fiber strength could change the result in case of Giza 87 which gave the highest fiber strength and the lowest SFC (8.36) under the study. So, it is complex and its result affected by the inherent genes and the environmental conditions.

According to Uniformity index character, regardless it did show any significance due to the effect of the main factors or their interactions, but the extra long genotype surpassed the long ones. Therefore, upland and color cotton gave the lowest reading of fiber UI. Regarding to the fiber mechanical properties, 87 gave the highest fiber strength (56.35 g/ tex) followed by Giza 92 which gave approximately the same reading (56.09 g/tex), while Giza 45 achieved the third level of the fiber strength (55.84 g/tex). Giza 92 is known as the strongest Egyptian variety, but this may be ascribed to that the result of each genotype under study didn’t express the standard reading because it’s a mean of low and high maturity levels. In addition to, the number of weak points and the convolution angle degree as going to discus later. Consequently the environmental condition expressed by maturity level could affect the strength readings. It could be recognized from the low and high maturity levels strength reading at the end of the table (42.68 vs. 46.06 g/tex), respectively. It’s worthy to mention that the effect of the environmental condition on the fiber length has a limited range. Thus, usually the extra long cultivars are the strongest genotypes. On contrast, upland cotton gave the lowest strength value (24.00 g/tex).

According to the percentage of fiber elongation, genotype, maturity level and their interaction significantly affected the percentage of fiber elongation Giza90xAus. Gave the highest value of fiber elongation (13.99%). In contrast, the lowest value was (8.26%) for upland cotton. The percentage of fiber elongation value of the high maturity level (12.09%) exhibited the low maturity level (11.48%). The interaction between Giza90xAus and the high maturity level regard as the highest elongation value (11.44%).

Table 3 presented the effect of genotype, maturity level and their interaction on fiber microscopic characters. As regard to the number of convolutions per mm. it is well known that the Egyptian cotton have the higher convolutions number comparing to the upland cotton. That’s clear from Table 3, Giza 45 verity exhibited the highest value of convolutions number per mm (3.85). On the other hand, the upland cotton gave the minimum reading of the number of convolutions per mm (2.64). The high maturity level exhibited the higher convolutions number per mm than low maturity level (3.44 vs. 3.08). As for the reversals number per mm, reversal considered as weak points along the fiber where the fiber exposed to breakage when force applied along. Because it the point where the cellulose deposition layer reversed the direction from clock wise to anti-clock wise Figure 3. It affected by both genetic and environmental conditions. Egyptian cotton contains the lowest reversals number comparing to the upland cotton. Giza 87 showed the lowest reversals number per mm (1.30). In contrast the upland cotton gave the maximum value of the reversals per number (2.10). Maturity level also, affected the weak points the highest in maturity ratio the lowest in reversals number per mm and vice versa as shown down in Table 3, accordingly, the interaction between the upland cotton and the low maturity ratio gave the highest value of reversals number per mm (2.11). According to the convolution angle, convolution angle refers to the spiral angle. The Egyptian cotton is characterized by narrow spiral and convolution angles, furthermore the extra-long genotypes has narrower angle of cellulose deposition along the fiber axis comparing to the long genotypes. Giza 87 cultivar gave the lowest value of convolution angle (10.22°) that reflected positively on its strength as mentioned before in Table 2. On the contrary, the upland cotton gave the widest convolution angle (17.11°).

Sample Convolutions no./mm Reversals no./mm Convolution angle
G 88 L1 3.61 1.41 13.00
G 88 L2 4.00 1.32 12.56
88mean 3.81 1.37 12.78
G 92 L1 3.52 1.41 15.38
G 92 L2 3.80 1.37 14.00
G92mean 3.66 1.39 14.69
G 93 L1 3.31 1.33 13.90
G 93 L2 3.42 1.27 13.80
G93mean 3.37 1.30 13.85
c1 L1 2.96 1.33 11.95
c1 L2  3.11 1.29 11.39
c1mean 3.04 1.31 11.67
G 45 L1 3.71 1.35 11.10
G 45 L2 3.98 1.32 10.58
G45mean 3. 85 1.32 10.58
G 87 L1 3.10 1.30 11.06
G 87 L2 3.79 1.30 9.32
87mean 3.45 1.30 10.22
G 80 L1 2.78 1.70 16.05
G 80 L2 3.32 1.50 15.03
G80mean 3.05 1.60 15.54
G 90 L1 3.45 2.10 15.57
G 90 L2 4.20 1.47 15.90
G90mean 3.75 1.79 15.73
c2 L1 3.21 1.71 16.30
c2 L2 3.55 1.66 15.70
c2mean 3.38 1.69 16.00
c3 L1 2.80 1.60 15.77
c3 L2 3.10 1.44 15.04
c3mean 2.95 1.52 15.41
G 86 L1 2.70 1.55 14.45
G 86 L2 3.60 1.53 13.68
G86mean 3.15 1.54 14.06
c4 L1 3.00 1.48 14.01
c4 L2 3.11 1.48 13.67
c4mean 3.06 1.48 13.84
green L1 2.70 1.90 17.01
green L2 2.81 1.70 16.66
gre.mean 2.76 1.80 16.84
brown L1 2.79 1.80 16.58
brown L2 3.00 1.70 16.36
bro.mean 2.90 1.75 16.47
UplandL1 2.54 2.11 17.06
upland L2 2.74 2.10 17.15
up.mean 2.64 2.10 17.11
L1 mean 3.08 1.61 14.61
L2 mean 3.44 1.50 14.06
LSD 0.05 G 0.13 0.02 0.03
LSD 0.05 L 0.15 0.01 0.01
LSD 0.05 GxL ns 0.05 0.06

Table 3: Effect of the genotype, maturity level and their interaction on fiber microscopic characters.

Table 4, showed the effect of genotype, maturity level and their interaction on single fiber properties, it’s clear from Table 4, that the effect of the main factors and their interaction were significant on all single fiber characters under the table. As to the single fiber linear density per mtex, its trend was as similar as bundle linear density. It could be arranged in ascending order according to the fineness mtex as follows: 1- the extra-long genotypes, i.e. Giza 45 (103 mtex) followed by Giza 87 (108 mtex) then Giza 93 (112 mtex), 2- The brown colored cotton (120 mtex), 3- the long Egyptian genotypes, i.e. Giza 90 (136.50 mtex) and 10229xG86 or C4 (149 mtex), 4- the upland cotton (211 mtex). This may be ascribed to that Giza 45, Giza93 and Giza87 which belong to extra-long extra fine fiber gave the lowest area of cross section whether in the lower or in the higher maturity level, while Giza 90 and C4 gave the lowest long fiber areas. On the contrary, the upland cotton exhibited the highest value of the area of cross section as explained before . The interaction between Giza 45 and the lowest maturity level gave the lowest fiber linear density (100 mtex). On the other hand, the highest fiber linear density was obtained from the interaction between the upland cotton and the high maturity level (231.00 mtex).

Sample Linear density(mtex) Single fiber tenacity(g/tex) Single fiber elongation%
G 88 L1 115.00 49.20 11.44
G 88 L2 141.00 51.61 12.04
88mean 128.00 50.41 11.74
G 92 L1 127.00 46.73 10.55
G 92 L2 139.00 55.98 11.18
G92mean 133.00 51.36 10.87
G 93 L1 105.00 45.66 11.89
G 93 L2 119.00 48.35 10.61
G93mean 112.00 47.01 11.25
c1 L1 148.00 49.22 10.98
c1 L2 159.00 50.10 11.38
c1mean 154.00 49.66 11.18
G 45 L1 100.00 51.00 10.00
G 45 L2 105.00 51.28 10.49
G45mean 103.00 51.14 10.25
G 87 L1 103.00 50.09 10.10
G 87 L2 113.00 54.48 10.66
G87mean 108.00 52.29 10.38
G 80 L1 161.00 36.25 13.12
G 80 L2 165.00 41.93 13.77
G80mean 163.00 39.09 13.45
G 90 L1 122.00 42.60 13.12
G 90 L2 151.00 40.37 14.49
G90mean 136.50 41.49 13.81
c2 L1 187.00 33.12 12.27
c2 L2 204.00 35.60 13.45
c2mean 195.50 34.36 12.86
c3 L1 151.00 48.75 15.35
c3 L2 160.00 50.51 16.20
c3mean 155.50 49.63 15.78
G 86 L1 147.00 33.78 13.03
G 86 L2 186.00 35.76 9.76
G86mean 166.50 34.77 11.40
c4 L1 143.00 35.11 11.01
c4 L2 154.00 36.78 11.76
c4mean 149.00 35.95 11.39
green L1 115.00 24.44 10.00
green L2 135.00 26.64 10.15
gre.mean 125.00 25.54 10.08
brown L1 129.00 40.76 10.92
brown L2 111.00 45.99 11.98
bro.mean 120.00 43.38 11.45
upland L1 191.00 29.62 9.60
upland L2 231.00 22.38 13.54
up. mean 211.00 26.00 11.57
L1 mean 135.80 41.52 11.60
L2 mean 151.60 43.18 12.10
LSD 0.05 G 3.10 0.28 0..13
LSD 0.05 L 2.40 0.19 0.11
LSD 0.05 GxL 3.90 0.33 0.16

Table 4: Effect of the genotype, maturity level and their interaction on single fiber properties.

As regards to the single fiber strength it could be recognized from Table 4, that single fiber strength is a little bit lower than bundle strength. Giza 87 recorded (52.29 g/tex) and surpassed the other genotypes on this trait. This may due to that Giza gave highest theta, maturity readings and the lowest structure properties, i.e. convolution angle and number of reversals per mm. on the other hand the upland cotton gave the lowest single fiber strength (26.00 g/tex) according to the reasons discussed above. The higher maturity level surpassed the lower one in single fiber tenacity property, respectively (43.18 vs. 41.52 g/tex). The interaction between Giza 87 and the highest maturity level gave the highest single fiber tenacity. On the other hand, the lowest single fiber tenacity was obtained from the interaction between the upland cotton and the low maturity level.

Concerning the percentage of single fiber elongation, it’s noticeable that single fiber elongation did not behave as bundle elongation, some readings were higher than those of the bundle elongation like, Giza 80, Giza 90, C 3, brown cotton and upland cotton. In contrast, the rest genotypes get lower readings than bundle elongation. In general the low maturity ratio gave low elongation % comparing to the high maturity level within the same genotype. This could be detected from the interaction means as well as the overall maturity level means.

The relationship between single fiber properties and bundle properties

Researchers usually use Regression analysis as a common statistical method for estimation of the relation between Y variable and the x variables. At first, the types of relationship between fiber properties (x variables) and single fiber properties (Y variable) were checked individually by using curve estimation and correlation analysis. Statistical analysis indicated that there was a nearly linear relationship between fiber properties and single fiber properties. After excluding the weak correlated characters 3 linear multiple regression equations were:

a. The relationship between single fiber tenacity and fiber properties.

b. The relationship between single fiber linear density and fiber properties.

c. The relationship between single fiber elongation and fiber properties.

The relationship between single fiber tenacity and fiber properties: It’s clear from Table 5, and Figures 4 to 16 that there were excellent relationship between single fiber tenacity and bundle tenacity (R2=0.8107, r=0.90). While, both of Theta and the reversals number per mm gave nearly the same relation level (r=0.87). Also, convolution angle character and maturity ratio gave good relationship with single fiber tenacity. On the other hand, the weakest relationship was between single fiber tenacity and short fiber content (R2=0.0383, r=0.20). In addition, there were direct relationship between single fiber tenacity and all the studied characters except for, short fiber content, fiber finesses, micronaire reading, area of cross section, reversals and convolution angle; where, there was a kind of negative relationship between each of them and single fiber tenacity.

character equation R2 r
UHM Y=2.0813×-22.559 0.4916 0.70
SFC Y= - 0.3465×+47.869 0.0383 -0.20
UI Y=1.7412×-102.26 0.2562 0.51
Fiber strength(g)tex Y=0.645×+14.404 0.8107 0.90
Fiber elongation Y=3.2271×+5.4688 0.4221 0.65
Fiber finesses Y= - 0.1538×+65.525 0.3409 -0.60
MIC Y= - 1.9691×+51.604 0.0559 -0.24
Theta Y=103.59x-9.495 0.7561 0.87
Area of cross section Y= -0.1908×+62.872 0.3048 -0.55
Convolutions Y=8.2849×+16.588 0.4093 0.64
Reversals Y= - 26.573×+83.814 0.7443 -0.87
Convolution angle Y= - 0.9718×+54.751 0.5855 -0.77
Maturity Y=62.934×-11.932 0.7420 0.86

Table 5: Simple linear regression between each fiber property and Single fiber tenacity.

textile-science-engineering-the-relationship-conv-angle

Figure 4: The relationship between single fiber tenacity and conv. angle.

textile-science-engineering-the-relationship-convolution

Figure 5: The relationship between single fiber tenacity and convolution no.

textile-science-engineering-the-relationship-convolution

Figure 6: The relationship between single fiber tenacity and convolution no.

textile-science-engineering-the-relationship-uhm

Figure 7: The relationship between single fiber tenacity and UHM.

textile-science-engineering-the-relationship-sfc

Figure 8: The relationship between single fiber tenacity and SFC.

textile-science-engineering-the-relationship-ui

Figure 9: The relationship between single fiber tenacity and UI.

textile-science-engineering-the-relationship-strength

Figure 10: The relationship between single fiber tenacity and fiber strength.

textile-science-engineering-the-relationship-elongation

Figure 11: The relationship between single fiber tenacity and fiber elongation.

textile-science-engineering-the-relationship-fineness

Figure 12: The relationship between single fiber tenacity and fiber fineness.

textile-science-engineering-the-relationship-micronaire

Figure 13: The relationship between single fiber tenacity and micronaire reading.

textile-science-engineering-the-relationship-mr

Figure 14: The relationship between single fiber tenacity and MR.

textile-science-engineering-the-relationship-theta

Figure 15: The relationship between single fiber tenacity and theta.

textile-science-engineering-the-relationship-cross

Figure 16: The relationship between single fiber tenacity and area of cross section.

Measuring the relations using the simple regression and correlation is not satisfactory. Also, partial correlation between more than character is very important incase if they used as indicator for building multiple regression models. According to the previous reasons stepwise analysis was used to form the best model for single fiber tenacity and the independent fiber characters. According to the result of the analysis, data in Table 6, indicated that microscopic characters, length and mechanical parameters were excluded from the model. In contrast, fineness and maturity parameters represented by theta and fineness with millitex were the predictors of the model. Table 7 and Figure 17, indicated the strong relationship between the single fiber and the independent variables in the model with correlation= 0.936 and determining factor= 0.874. Table 8, shows regression coefficients of variables, t-values and significance level of theta and fineness variables. Arrangement of variables in the table indicates their relative importance for the model. Signs (+ or -) of regression coefficients of variables indicate the direction of influence.

  Model Beta In t Sig. Partial Correlation
1 MIC
MR
FINN
A SCW
UHM
SFC
UI
STRENGTH
ELONGA TI
CONV
REV ER
CONV A NGL
-.266a
.042a
-.335a
-.251a
.213a
.159a
-.038a
.201a
-.037a
.019a
-.212a
-.230a
-4.517
.235
-5.802
-4.050
2.269
2.304
-.443
2.220
-.443
.199
-2.040
-2.981
.000
.815
.000
.000
.028
.026
.660
.032
.660
.843
.047
.005
-.563
.035
-.658
-.521
.324
.328
-.067
.317
-.067
.030
-.294
-.410
2 MIC
MR
A SCW
UHM
SFC
UI
STRENGTH
ELONGA TI
CONV
REV ER
CONV A NGL
.104b
-.053b
.186b
-.017b
.099b
-.071b
-.011b
-.005b
-.080b
.023b
-.082b
.795
-.388
1.497
-.193
1.804
-1.090
-.126
-.078
-1.092
.240
-1.160
.431
.700
.142
.848
.078
.282
.900
.938
.281
.812
.253
.120
-.059
.223
-.029
.265
-.164
-.019
-.012
-.164
.037
-.174

Table 6: Excluded varibles and predictors for single fiber tenacity.

Model r R square Std. Error Significant
1 0.936 0.874 0.868 0.000

Table 7: Single fiber tenacity model summary.

textile-science-engineering-the-best-model-tenacity

Figure 17: The best model for the relationship between Single fib er tenacity (g/tex)and fiber properties.

Statistical Parameter Constant theta Fineness millitex
B* 8.165 95.22 -9.38E-02
Std. Error 5.016 7.277 0.016
T 1.628 13.085 -5.802
Significant 0.111 0.000 0.000

Table 8: Regression coefficients, t-values and significance level of the variables of the linear regression model for single fiber tenacity (g/tex).

This means fine and mature fiber increased the single fiber strength character.

The relationship between single fiber linear density and fiber properties: It’s clear from Table 9, and Figures 18 to 30 that there were excellent relationship between single fiber linear density and fiber fineness per mtex (R2=0.8847, r=0.94). While, both of micronaire reading and area of cross section gave nearly the same relation level as follows, respectively (R2=0.6622, r=0.81 and R2=0.6779, r=0.82.). On the contrary, short fiber content gave the weakest relationship to single fiber linear density (R2=0.0352, r=0.19), all the characters under study proportionate adversely with single fiber linear density except, fiber finesses, micronaire reading, area of cross section, reversals and convolution angle.

character equation R2 r
UHM Y= - 5.2545x+312.78 0.2370 -0.49
SFC Y= - 1.2075x+162.61 0.0352 -0.19
UI Y= - 2.4339x+350.01 0.0379 -0.19
Fiber strength(g)tex Y=  - 1.4257x+210.21 0.2420 -0.50
Fiber elongation Y= - 3.8406x +191.73 0.0357 -0.19
Fiber finesses Y=0.8985x +15.396 0.8847 0.94
MIC Y=36.6x +14.29 0.6622 0.81
Theta Y= - 165.58x +229.86 0.1491 -0.39
Area of cross section Y=1.1067x +32.929 0.6779 0.82
Convolutions Y= - 38.582x +273.55 0.3563 -0.60
Reversals Y=61.742x +50.833 0.3101 0.56
Convolution angle Y=2.2722x +118.18 0.2470 0.50
Maturity Y= - 97.747x +231.79 0.1323 -0.36

Table 9: Simple linear regression between each fiber property and Single linear density.

textile-science-engineering-the-linear-conv-angle

Figure 18: The relationship between single fiber linear density and conv. Angle.

textile-science-engineering-the-linear-micronaire

Figure 19: The relationship between single fiber linear density and micronaire reading.

textile-science-engineering-the-linear-mr

Figure 20: The relationship between single fiber linear density and MR.

textile-science-engineering-the-linear-fineness

Figure 21: The relationship between single fiber linear density and fiber fineness.

textile-science-engineering-the-linear-theta

Figure 22: The relationship between single fiber linear density and theta.

textile-science-engineering-the-linear-cross

Figure 23: The relationship between single fiber linear density and area of cross section.

textile-science-engineering-the-linear-uhm

Figure 24: The relationship between single fiber linear density and UHM.

textile-science-engineering-the-linear-sfc

Figure 25: The relationship between single fiber linear density and SFC.

textile-science-engineering-the-linear-ui

Figure 26: The relationship between single fiber linear density and UI.

textile-science-engineering-the-linear-strength

Figure 27: The relationship between single fiber linear density and fiber strength.

textile-science-engineering-the-linear-elongation

Figure 28: The relationship between single fiber linear density and Fiber elongation.

textile-science-engineering-the-linear-convolution

Figure 29: The relationship between single fiber linear density and convolution no.

textile-science-engineering-the-linear-reversals

Figure 30: The relationship between single fiber linear density and reversals no.

After Appling the stepwise analyses regression coefficients, t-values and the partial correlation determined the excluded character to build up the best model describes the relationship between single fiber linear density and all the studied fiber properties. Its clear from Table 10, that all the character were excluded from the model except the micronaire reading and the fiber fineness per mtex characters. Thus, the model showed strong correlation r=0.946 and high determining factor=0.894 Table 11 and Figure 31.

  Model Beta In t Sig. Partial Correlation
1 MIC
MR
THETA
A SCW
UHM
SFC
UI
STRENGTH
ELONGA TI
CONV
REV
ER
CONVANGL
.213a
.095a
.030a
.106a
.048a
-.052a
.018a
.097a
.060a
.062a
-.087a
-.074a
2.358
1.749
.533
.922
.740
-1.014
.326
1.540
1.165
1.109
-1.397
-1.214
.023
.087
.597
.362
.463
.316
.746
.131
.250
.274
.169
.231
.335
.255
.080
.138
.111
-.151
.049
.226
.173
.165
-.206
-.180
2 MR
THETA
A SCW
UHM
SFC
UI
STRENGTH
ELONGA TI
CONV
REV ER
CONVANGL
-.006b
-.089b
-.066b
-.021b
-.001b
-.049b
.022b
-.047b
-.015b
-.003b
-.028b
-.065
-1.290
-.491
-.301
-.019
-.851
.286
-.661
-.232
-.045
-.438
.948
.204
.626
.765
.985
.400
.776
.512
.818
.965
.663
-.010
-.193
-.075
-.046
-.003
-.129
.044
-.100
-.035
-.007
-.067

Table 10: Excluded varibles and predictors for single fiber linear density.

Model r R square Std. Error Significant
1 0.946 0.894 10.311 0.023

Table 11: Single fiber linear density model summary.

textile-science-engineering-the-best-model-density

Figure 31: The best model for the relationship between single fiber linear density (mtex) and fiber properties.

Obviously, fiber fineness per mtex was the most important factor for single fiber linear density. Micronaire value as an indicator for the specific surface area of the fiber was another important fiber parameter for single fiber linear density, both of them proportionate directly with single fiber linear density, (Table 12).

Statistical Parameter Constant Fineness millitex mic
B* 4.198 .7400 9.382
Std. Error 7.807 0.088 3.979
T .5380 8.402 2.358
Significant .5930 0.000 .0230

Table 12: Regression coefficients, t-values and significance level of the variables of the linear regression model for single fiber linear density.

The relationship between single fiber elongation and fiber properties: It’s clear from Table 13, and Figures 32 to 44 that the relationship between single fiber elongation and fiber properties weren’t strong enough the strongest relation was for UHM (R2=0.3298, r=0.57). This may attributes to that the linear regression could not fit the relation it could be quadratic or any type other than linear type.

character equation R2 r
UHM Y=0.1669x+3.374 0.3298 0.57
SFC Y= - 0.0149x+12.119 0.0021 -0.05
UI Y= - 0.1823x+27.159 0.0840 -0.29
Fiber strength(g)tex Y= - 0.041x+13.75 0.0790 -0.28
Fiber elongation Y=0.1942x+9.6383 0.0361 0.19
Fiber finesses Y=0.0157x+9.6326 0.1064 0.33
MIC Y=0.9563x+8.4645 0.1787 0.24
Theta Y=0.2625x+11.789 0.0001 0.01
Area of cross section Y=0.0179x+10.083 0.0701 0.27
Convolutions Y=0.2747x+11.017 0.0071 0.08
Reversals Y=0.4292x+11.256 0.0059 0.07
Convolution angle Y=0.0941x+10.528 0.0393 0.20
Maturity Y=1.5633x+10.559 0.0138 0.12

Table 13: Simple linear regression between each fiber property and the percentage of single fiber elongation.

textile-science-engineering-the-elongation-micronaire

Figure 32: The relationship between single fiber elongation and micronaire reading.

textile-science-engineering-the-elongation-mr

Figure 33: The relationship between single fiber elongation and MR.

textile-science-engineering-the-elongation-fineness

Figure 34: The relationship between single fiber elongation and fiber fineness.

textile-science-engineering-the-elongation-theta

Figure 35: The relationship between single fiber elongation and theta.

textile-science-engineering-the-elongation-cross

Figure 36: The relationship between single fiber elongation and area of cross section.

textile-science-engineering-the-elongation-sfc

Figure 37: The relationship between single fiber elongation and SFC.

textile-science-engineering-the-elongation-uhm

Figure 38: The relationship between single fiber elongation and UHM.

textile-science-engineering-the-elongation-ui

Figure 39: The relationship between single fiber elongation and UI.

textile-science-engineering-the-elongation-elongation

Figure 40: The relationship between single fiber elongation and fiber elongation.

textile-science-engineering-the-elongation-strength

Figure 41: The relationship between single fiber elongation and strength.

textile-science-engineering-the-elongation-reversals

Figure 42: The relationship between single fiber elongation and reversals no.

textile-science-engineering-the-elongation-convolution

Figure 43: The relationship between single fiber elongation and convolution no.

textile-science-engineering-the-elongation-conv-angle

Figure 44: The relationship between single fiber elongation and conv. Angle.

All the characters under study proportionate directly with single fiber elongation except, short fiber content, UI, and fiber strength.

Table 14, represents the excluded varibles and predictors for single fiber elongation. This model surpassed the previous models on the number of the predictors variables, it contains 7 predictors. They are: Miconaire reading, UI, ASCW, theta, fiber strength, fiber elongation and UHM characters. Nevertheless, the model results and graph distribution illustrated in Table 15 and Figure 45, showed the lowest correlation value comparing to the others single characters (r=0.888 and determining factor=0.788) Mic, UI, ASCW were the most important factors for single fiber elongation. Theta values was other important fiber parameter for single fiber elongation, then fiber strength followed by fiber elongation finally UHM ranked the last important character in the model. Table 16, Indicated that UI, ASCW, and fiber Strength proportionate inversely with single fiber elongation. However, the rest fiber properties proportionate directly with single fiber elongation. In general the results of the single fiber elongation are absurd and couldn’t be helpful as prediction.

Ex cluded Variablehs
  Model Beta In t Sig . Partial
Correlation
Collinearity Statistics Tolerance
1 MR
FINN
THETA
ASCW
UHM
SFC
UI
STRENGTH
ELONGA TI
CONV
REV ER
CONVANGL
.11 9a
- .12 8a
.11 8a
- .50 4a
- .20 0a
.20 3a
- .32 0a
- .24 1a
.07 0a
- .00 5a
.03 1a
.15 7a
.94 3
- .54 7
.93 4
- 1.8 54
- 1.5 31
1.5 50
- 2.7 16
- 1.9 10
.52 7
- .04 3
.23 8
1.2 00
.35 1
.58 7
.35 6
.07 1
.13 3
.12 8
.00 9
.06 3
.60 1
.96 6
.81 3
.23 7
.14 1
- .08 2
.13 9
- .26 9
- .22 5
.22 8
- .37 9
- .27 7
.07 9
- .00 6
.03 6
.17 8
.9 9 6
.2 9 4
1 .0 0 0
.2 0 3
.8 9 9
.8 9 9
1 .0 0 0
.9 3 7
.9 2 5
.9 9 7
.9 5 2
.9 1 1
2 MR
FINN
THETA
A SCW
UHM
SFC
STRENGTH
EL ONGA TI
CONV
REV ER
CONV A NGL
.42 3b
- .60 8b
.43 6v
- 1.1 79b
.55 3b
.02 6b
.15 3b
.46 9b
.17 5b
- .60 2b
- .37 6b
3.3 21
- 2.5 17
3.4 12
- 4.7 19
1.9 92
.17 3
.64 8
3.2 74
1.3 35
- 3.4 16
- 1.7 57
.00 2
.01 6
.00 1
.00 0
.05 3
.86 3
.52 1
.00 2
.18 9
.00 1
.08 6
.45 2
- .35 8
.46 2
- .58 4
.29 1
.02 6
.09 8
.44 7
.19 9
- .46 2
- .25 9
.6 9 5
.2 1 2
.6 8 2
.1 5 0
.1 6 9
.6 3 0
.2 5 2
.5 5 3
.7 9 3
.3 6 0
.2 9 0
3 MR
FINN
THETA
UHM
SFC
STRENGTH
EL ONGA TI
CONV
REV ER
CONV A NGL
.27 4c
- .22 2c
.32 3c
.41 7c
.17 5c
- .25 6c
.14 4c
.00 6c
- .33 7c
- .26 1c
2.3 41
- .95 3
2.9 00
1.8 03
1.4 09
- 1.2 25
.86 9
.05 3
- 1.9 48
- 1.4 54
.02 4
.34 6
.00 6
.07 9
.16 6
.22 7
.39 0
.95 8
.05 8
.15 3
.34 0
- .14 6
.40 8
.26 8
.21 2
- .18 6
.13 3
.00 8
- .28 8
- .21 9
.6 2 0
.1 7 3
.6 4 3
.1 6 6
.5 9 4
.2 1 1
.3 4 0
.7 0 7
.2 9 3
.2 8 4
4 MR
FINN
UHM
SFC
STRENGTH
EL ONGA TI
CONV
REV ER
CONV A NGL
- .05 8d
.17 9d
.01 3d
.12 4d
- .63 3d
.06 0d
- .20 7d
- .06 0d
- .17 2d
- .24 7
.68 9
.04 6
1.0 56
- 3.2 27
.38 1
- 1.7 08
- .28 0
- 1.0 07
.80 6
.49 5
.96 4
.29 7
.00 2
.70 5
.09 5
.78 1
.32 0
- .03 9
.10 7
.00 7
.16 3
- .45 0
.05 9
- .25 8
- .04 4
- .15 5
.1 4 7
.1 1 9
9 .7 1 2 E -0 2
.5 7 8
.1 6 9
.3 2 7
.5 2 0
.1 7 7
.2 7 3
5 MR
FINN
UHM
SFC
EL ONGA TI
CONV
REV ER
CONV A NGL
.12 9e
- .18 1e
.54 7e
.00 7e
.34 5e
- .12 4e
- .35 2e
- .31 4e
.58 4
- .69 4
1.9 06
.05 7
2.2 76
- 1.0 77
- 1.7 33
- 2.0 46
.56 3
.49 2
.06 4
.95 5
.02 8
.28 8
.09 1
.04 7
.09 2
- .10 9
.28 9
.00 9
.33 9
- .16 8
- .26 4
- .30 8
.1 3 7
9 .7 0 4 E -0 2
7 .4 2 8 E -0 2
.5 1 0
.2 5 7
.4 8 7
.1 5 1
.2 5 6
6 MR
FINN
UHM
SFC
CONV
REV ER
CONV A NGL
- .23 7f
- .08 0f
.57 8f
- .00 5f
- .15 4f
- .30 5f
- .29 5f
- .91 3
- .31 7
2.1 36
- .04 9
- 1.4 08
- 1.5 57
- 2.0 09
.36 7
.75 3
.03 9
.96 1
.16 7
.12 8
.05 1
- .14 5
- .05 1
.32 4
- .00 8
- .22 0
- .24 2
- .30 6
8 .8 3 2 E -0 2
9 .3 7 6 E -0 2
7 .4 1 2 E -0 2
.5 0 8
.4 8 1
.1 4 9
.2 5 5
7 MR
FINN
SFC
CONV
REV ER
CONV A NGL
- .19 9g
- .06 2g
- .00 4g
- .18 4g
- .17 3g
- .16 5g
- .79 6
- .25 3
- .04 1
- 1.7 66
- .83 1
- .87 9
.43 1
.80 1
.96 7
.08 5
.41 1
.38 5
- .12 8
- .04 1
- .00 7
- .27 5
- .13 4
- .14 1
8 .7 8 4 E -0 2
9 .3 6 3 E -0 2
.5 0 8
.4 7 4
.1 2 7
.1 5 6

Table 14: Excluded varibles and predictors for single fiber elongation.

Model r R square Std. Error Significant
1 0.888 0.788 0.7979 0.039

Table 15: single fiber elongation model summary.

textile-science-engineering-the-best-model-elongation

Figure 45: The best model for the relationship between percentage of single fiber elongation and fiber properties.

Statistical Parameter Constant Mic UI Area of cross section Theta Strength Elongation UHM
B* 31.127 2.930 -0.407 -7.72E-02 8.076 -0.166 0.3950 0.3400
Std. Error 8.000 0.6280 0.1310 0.018 2.719 .0350 0.160 0.159
T 3.891 4.667 -3.103 -4.274 2.970 -4.741 2.471 2.136
Significant 0.000 0.000 0.004 0.000 0.005 0.018 0.000 0.039

Table 16: Regression coefficients, t-values and significance level of the variables of the linear regression model for percentage of single fiber elongation.

Acknowledgement

I would like to extend my appreciation to Dr. Guntram Kugler Ph.D., General Manager Laboratory Projects, and all the member of Textechno Herbert Stein GmbH & Co. KG, Monchengladbach, Germany for testing the samples in their labs.

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