New prediction equation to predict yarn strength of Egyptian cotton
New Prediction Equations for Yarn Strength of Egyptian Cotton
Utilizing HVI Spectrum Data.
M.G. Sief, H.M. Arafa, and R.M. Hassan
Cotton Research Institute, Agricultural Research Center, Giza, Egypt.
Abstract
This investigation was conducted on ten Egyptian cotton varieties and promising crosses namely, Giza 80, Giza 90, (Giza 90×Aust.) and
[G83×(G75X5844)]×G80 (Upper Egypt long staple cottons), as well as Giza 86 and (10229×Giza 89) (Delta long staple cottons), Giza 88, Giza 92, Giza 93 (Giza77×Ps6) and [G84×(G70×51B)]×P62 (extra long staple cottons), to develop prediction equations for skein strength of 40’s and 60’s carded yarns by subjecting HVI testing
data (measurements of cotton quality properties and SCI) to multiple regression analysis. The developed equations were applied to HVI spectrum data to test the accuracy and reliability of the obtained predicted skein strength values. The predicted values of skein strength matched very well the corresponding determined ones. Regression and correlation between skein strength and SCI were studied.
Introduction
Classical low volume instruments (LVI) used for characterization of cotton fiber as Fibrograph, Stelometer, Pressley tester, Micronaire…etc. were for practical applications replaced by HVI (high volume instrument) testing systems which provide rapid and accurate measurements of the basic cotton fiber properties. Using HVI makes it possible to obtain a big amount of data, furthermore it is provided by special software for automatic calculation of predicted yarn strength in the old generations of HVI (900 system) and predicted SCI (spinning consistency index) in HVI spectrum and new models. The predicted values of yarn strength and SCI were calculated for each tested sample using the measured fiber quality data according to the regression equation
y= a+ bx+ bx+…………bxi122nn
Where y= yarn strength in HVI 900 systems and SCI in Spectrum and 1000 HVI systems.
x, x, …………x are measurements of fiber quality properties. 12n
Nemours research work has been carried out to study the relationship between yarn quality and fiber properties as well as to develop prediction equations that provide calculated values of yarn strength based on fiber quality measurements. Ethridge et al.
(1982), El Mogazhy and Broughton (1990), El Mogazhy et al (1992), Frydrych (1992), Sief et al (1994) Cheng and Adams (1995), Moon et al (1998), Suh et al (1998), Pan (2001), Ureyen and Kadoglu (2006) and Hequet and Abidi (2008)studied this relationship using different statistical models and techniques and came to different prediction equations, For instance, Ethridge et al. (1982) found a linear
empirical relationship between rotor yarn strength, fiber strength, micronaire, fiber length uniformity ratio and grayness. They defined the CSP at the rotor yarn as:
23CSP = - 6487.01 + 728.84 InS – 2913.89 M + 658.41 M – 50.10 M + 2258.54 InU –
2 0.00003(GXY)
Where InS = the natural logarithm of fiber strength M = the micronaire index raised to the power
InU = the natural logarithm of length uniformity ratio
2 ( GXY)= the square product of grayness multiplied by yellowness
Hunter et al. (1982) proposed a range of regression equations for predicting the strength of ring spun yarns from a range of fiber properties, some of these equations are follows:
Ring yarn CSP = 43 UR + 125 BT – 103 BE – 65 Mc + 10.5 YC + 47.3 TF - 3601
Ring yarn tenacity ( cN/tex) = 0.31 UR + 0.80 BT – 1.1 BE – 0.73 Mc + 0.062 YC +
35 TF – 21.8
Where: UR = the uniformity ratio BT = bundle tenacity BE = bundle elongation
Mc = micronaire value YC = yarn count m/tex F = twist factor
TC = trash content measured by Shirley trash analyzer
NTP = the number of trash particles
SL 50% = 50% Span length
El- Moghazy (1988) developed the following regression equation for calculating the count strength product (CSP) of yarns:
CSP = - 4184 + 1141.2 FL + 71.2 LU + 49.4 FE – 22.7 Rd + 2041/FF
Where: FL = UHM length in inches LU = length uniformity FS = fiber strength
FE = fiber elongation Rd = reflectance FF = micronaire value.
Ghosh et al. (2003) developed the following equation for spun yarn tenacity Q as: 1
2 Q1 Q = nh/ne. Fn. Qb/100. Con1
Where nh = the number of the fiber at the place of yarn break
ne = the average number of fiber in the yarn cross section
Fn = the fiber bundle tenacity
Qb = the percentage of broken fiber in the yarn failure zone
1 Q= the average helix of fiber at the time of yarn failure
Regarding Spinlab 900 HVI system the manufacturing company provided the system with two equations for predicting skein breaking load and skein strength (CSP).
y= 173.58+ 86.42 x+ 1.95 x+ 3.0 x+ 8.72 x+ 0.99 x123456
y= 1818.0- 24.0 x+ 270.0 x- 8.0 x+ 45.0 x- 112.0 x- 2.21 x- 1.10 x 21234567
where y skein breaking load (SBr), y2 skein strength (count strength product) 1
for 22s carded yarns, x trash area %, x 2.5% SL in., x LUR%, x fiber strength, x 12345
micronaire value, x Rd% and x +b. 67
In 1989 CRI found that the predicted values of yarn strength and breaking load obtained from the mentioned two equations of HVI 900 system did not match well the determined values of yarn strength and braking load for the 60’s carded yarns
spun from Egyptian cotton which was logic since the two equations were derived from Upland cotton data and they were for 22s carded yarns. Therefore, a research trial was conducted in Cotton Fiber Res. Section during 1990 and 1991 seasons to develop two equations for predicting skein strength and breaking load for 60’s carded
yarns spun from the Egyptian cottons under the conditions of the 60 gm. technique used in CRI (Sief et al. 1994). The obtained equations were:
y(breaking load) = 53.1+ 28.0 x+ 0.84 x+ 0.94 x- 0.89 x- 0.11 x1 23456
y(CSP)= 1383.3- 326.9 x+ 1766.1 x- 27.4 x+ 58.4 x- 89.2 x+ 13.2 x- 17.8 x2 1234567
Where: y skein breaking load (SBr), y2 skein strength (count strength product CSP) 1
for 60s carded yarns, x trash area %, x 2.5% SL in., x LUR%, x fiber strength, x 12345
micronaire value, x Rd% and x +b. 67
Applying the obtained equation of skein strength to HVI 900 fiber data of Egyptian cotton automatically provided reliable predicted values of yarn strength for about 10 years which was very useful in the quality evaluation of the big number of samples delivered from the breeding program and other research trials and programs of Cotton Res. Institute.
In 2002 fiber quality evaluation labs of CRI received the HVI Spectrum system. The manufacturing company made a lot of modifications in this system to be calibrated using HVI calibration cotton only, leading to big differences in fiber strength values besides measuring UHML, ML and uniformity index % instead of 50%, 2.5 % span lengths and length uniformity ratio obtained from the old model HVI 900. Moreover the manufacturing company provided the HVI Spectrum with a prediction equation for calculating the spinning consistency index (SCI) instead of skein strength. Unlikely, the Egyptian cotton breeders are accustomed to deal with skein strength in the breeding program. Many attempts were done to modify mathematically the HVI 900 skein strength prediction equation to be used with the HVI Spectrum data, unfortunately the obtained skein strength predicted values was not valid and accurate. Therefore, the main objective of this work is to develop new equations for predicting yarn strength of Egyptian cottons using HVI Spectrum data and Programming the HVI Spectrum system with this equations to obtain reliable predicted values of yarn strength in the same table of HVI fiber data.
Materials and Methods
The present study was carried out in Cotton Technology Res. Department Cotton Res. Institute, Agric. Res. Center at Giza on ten Egyptian cotton varieties and promising crosses namely, Giza 80, Giza 90, (Giza 90×Aust.) and
[G83×(G75X5844)]×G80 (Upper Egypt long staple cottons), as well as Giza 86 and (10229×Giza 89) (Delta long staple cottons) in addition to Giza 88, Giza 92, Giza 93
(Giza77×Ps6) and [G84×(G70×51B)]×P62 (extra long staple cottons). The chosen cottons represent the long and extra long Egyptian cottons. 250 lint cotton samples were obtained from the commercial crop of 2010 and 2011 seasons as will as from field trials of cotton Research Institute. The raw cotton samples were of different grades ranged from FG-1/4 to G-1/4 in most of these cottons. The cotton samples of the selected cottons were tested using Uster HVI Spectrum system according to ASTM standard test method (D 5867 – 05) to obtain the following fiber quality
measurements: the tensile strength (g/tex), fiber elongation %, micronaire value (Mike), maturity ratio (MR), upper half mean length (UHML) in mm., length uniformity index % (UI %), color reflectance percent (Rd %) and yellowness (+b). 40’s carded yarns at 4.0 T.M. were spun from the different samples of Upper Egypt
long staple cottons, while 60’s carded yarns at 3.6 T.M. were spun from Delta long and extra long staple cottons. All the spun yarns were produced according to the 60 gram technique used in the experimental spinning mill in Spinning Res. Section, Cotton Res. Institute, Giza. The spun yarns were tested for skein strength by Good-brand Lea tester according to ASTM (D- 1598- 93R00). Moreover, the study included and used the HVI and skein strength data of the cotton varieties and promising crosses of Upper Egypt, Delta long staple and extra long staple Egyptian cottons tested in trial B in 2010 and 2011 growing seasons. The obtained data was computed using SAS* multiple regression analysis to develop prediction equations for skein strength of Upper Egypt cottons at 40’s carded yarns, as well as to develop prediction equations for skein strength of Delta long staple and extra long staple Egyptian cottons at 60’s carded ring spun yarns. Data of SCI and actual skein
strength was subjected to linear regression and simple correlation analysis to study the relationship between SCI and skein strength as well as to get a predicted value of skein strength based on SCI data. Predicted values of skein strength were calculated by applying the prediction equations to HVI spectrum data of 10 samples of each of the mentioned cottons in 2011 season (another samples not used in the calculation of the prediction equations). Differences between the determined skein strength and the predicted ones were calculated for each cotton.
Results and discussion
Subjecting the obtained HVI Spectrum data and skein strength of the spun yarns to regression analysis led to five prediction equations, for predicting skein strength of 40’s carded ring yarns spun from Upper Egypt cottons, besides, another
five equations for predicting skein strength of 60’s carded ring yarns spun from Delta
long and extra long staple Egyptian cottons.
Equations for predicting skein strength of 40s yarns of Upper Egypt cottons:
Equation 1 includes length, length uniformity, strength, micronaire, Rd% and +b
Skein strength = -1277.937+ 45.410x Length + 4.402 x Uniformity index + 35.626 x
Strength - 39.355 x Micronaire - 0.919 x Rd +58.472 x +b Equation 2 includes length, length uniformity strength and micronaire.
Skein strength = -961.717 + 46.954 x Length + 5.211 x uniformity index +
8.994x Strength - 20.442x Micronaire Equation 3 includes length, length uniformity, strength, micronaire, and maturity ratio and
elongation%
Skein strength =-1683.455 + 50.970 x Length + 5.232 x uniformity index + 38.079 x
Strength - 22.646 x Micronaire + 178.272 x Maturity ratio + 59.850x Elongation Equation 4 includes length, length uniformity, strength, micronaire, maturity ratio and Rd%.
Skein strength = -1094.35756 + 49.914 x Length + 5.2371 x uniformity index
+ 37.18052 x Strength - 44.83373 x Micronaire + 325.10457 x Maturity
Ratio – 1.3834 x Rd
Equation 5 includes SCI data
Skein strength = 734.528 + 9.445 x SCI
Equations for predicting skein strength of 60s yarns of Delta LS & ELS cottons
Equation 1: Skein strength = -2058.088+ 43.496x Length + 28.172 x Uniformity index +
36.222 x Strength – 129.105 x Micronaire – 4.906 x Rd +9.360x +b
Equation2: Skein strength = -2500.343 + 47.844 x Length + 28.365 x uniformity index +
37.044x Strength – 138.953x Micronaire
Equation 3: Skein strength = -2852.909 + 41.777 x Length + 21.562 x uniformity index +
25.292 x Strength – 308.535 x Micronaire + 2870.007 x Maturity
ratio + 43.654 x Elongation Equation 4: Skein strength = -2736.083 + 41.741 x Length + 22.108x uniformity index
+ 25.622x Strength – 301.420 x Micronaire
+ 2744.514 x Maturity ratio – 5.791x Rd
Equation 5: includes SCI data
Skein strength = - 74.881 + 9.445 x SCI
Prediction of yarn strength of Upper Egypt LS Cottons:
HVI Spectrum data, determined skein strength and corresponding predicted ones derived from the five prediction equations for Upper Egypt cottons as well as the differences between determined and predicted values of skein strength are shown in Table 1 and Fig. 1 (each cotton was represented by ten random samples). Comparing the determined and predicted means of skein strength, the results in Table 1 showed that the determined skein strength of 40s carded yarns spun from Giza 80 averaged 2263 while the predicted values of its skein strength averaged 2352, 2297, 2281, 2298 and 2339 derived from equations 1, 2, 3, 4 and 5 respectively. The determined skein strength of Giza 90 averaged 2193 while the predicted ones averaged 2193, 2191, 2204, 2197 and 2199 derived from the four equations and SCI data respectively. The determined skein strength of Giza 90 x Australi yarns averaged 2100, while the predicted ones obtained from the four equations and SCI data averaged 2140, 2079, 2083, 2085 and 2064 respectively. The determined skein strength of
[G83×(G75X5844)]×G80 yarns averaged 2261 while the predicted ones obtained from the four equations and SCI data averaged 2217, 2239, 2247, 2233 and 2227 respectively. These results indicated that the differences between means of the determined skein strength of Upper Egypt cottons and the corresponding predicted ones ranged from 0 to 40 units which were very low compared to the testing error in measuring skein strength (100 – 150 units). However the
differences between the individual values of determined skein strength and the corresponding predicted ones are bigger than noticed between average values, which is logic since the individual values are characterized by bigger variation than averages. The differences between individual values ranged from 1 to 118 units in the prediction using equation 1, ranged from 2 to 82 units in the values obtained from applying equation 2, ranged from 3 to 95 units when applying equation 3 and from 0 to 92 units when applying equation 4, while ranged from 2 to 131 units when based on SCI data. It is clear from these results that all the prediction equations provide reasonable and reliable predicted skein strength values, however equations 2, 3 and 4 showed smaller differences between individual values of determined skein strength and the corresponding ones (< 100 units) compared to equation 1 and the prediction via SCI data. Furthermore, it is more practical to use equation 2 since it depends only on the main four fiber properties: length, length uniformity, strength and mike, while the addition of Rd% and +b in equation 1, maturity ratio and elongation in equation 2, maturity ratio and Rd% in equation 4 did not improve the accuracy of the prediction compared to equation 2.
Prediction of yarn strength of Delta LS & ELS Cottons:
HVI Spectrum data, determined skein strength and corresponding predicted ones obtained from the five prediction equation for Delta LS and ELS cottons as well as the differences between determined and predicted values of skein strength are shown in table 2 and Fig. 2 (each cotton was represented by ten random samples. The results in Table 2 showed that the determined skein strength of 60s carded yarns spun from Giza 86 averaged 2486 while the means of predicted values of its skein strength were 2540, 2549, 2491, 2503 and 2577 derived from equations 1, 2, 3, 4 and SCI data respectively. The determined skein strength of 10229 x Giza 86 averaged 2495 while the predicted ones averaged 2535, 2539, 2498, 2519 and 2576 derived from the four equations and SCI data respectively. The determined skein strength of Giza 88 yarns averaged 2987 while the pr, 22956, 3005 edicted ones obtained from the four equations and SCI data averaged 3023, 2981
and 2931 respectively. The determined skein strength of Giza 92 yarns averaged 2978 while the
predicted ones obtained from the four equations and SCI data averaged 2844, 2901, 2957, 2926 and 2976 respectively. The determined skein strength of Giza 77 x Ps6 yarns averaged 3100 while the
predicted ones obtained from the four equations and SCI data averaged 3097, 3054, 3085, 3105 and 2986 respectively The determined skein strength of [G84×(G70×51B)]×P62 yarns averaged 2926
while the predicted ones obtained from the four equations and SCI data averaged 2843, 2859, 2872, 2853 and 2859 respectively These results indicated that the differences between means of the determined skein strength of Delta LS & ELS cottons and means of the corresponding predicted ones ranged from 2 in Giza 92 to 114 units in Giza 77 x Ps6 which is lower than the testing error in
measuring skein strength. However the differences between the individual values of determined skein strength and the corresponding predicted ones are bigger than noticed between average values. These differences ranged from 0 to 116 units for the prediction using equation 1, ranged from 1 to 108 units for the values obtained from applying equation 2, ranged from 1 to 110 units when applying equation 3 and from 0 to 114 units when applying equation 4, while showed bigger range when using SCI data, being from 5 to 140. It is clear from these results that all the prediction equations provide reliable predicted skein strength values except the prediction based on SCI data which showed higher fluctuation than the other equations, however equations 2, 3 and 4 showed smaller differences between individual values of determined skein strength and the corresponding ones (< 100 units) compared to equation 1 and the prediction via SCI data. Furthermore, as noticed in case of Upper Egypt cottons, it is more practical to use equation 2 since it depends only on the main four fiber properties: length, length uniformity, strength and mike, while the addition of Rd% and +b in equation 1, maturity and elongation in equation 2, maturity and Rd% in equation 4 did not improve the accuracy of skein strength prediction compared to equation 2.
Based on the obtained data it is decided to use the equation that include length, uniformity, strength, and mike (equation 2) in programming HVI spectrum system in Cotton Res. Institute to get reliable predicted values of skein strength in the same table of HVI fiber quality data. The relationship between SCI and yarn strength:
SCI is a calculation for predicting the overall quality and spinability of cotton to be used on bale management and quality evaluation programs. It depends on fiber data and derived from regression equation. It is developed by HVI manufacturers to substitute the predicted values of CSP and breaking load of the tested cotton samples. Therefore it is worthy to study the relationship between yarn strength and the corresponding SCI values. The results in Table 1, Table 2, Figure 1, Figure 2 and Fig. 3 indicated that the correlation between skein strength and SCI was highly significant whether calculated from Upper Egypt cottons data or from the Delta LS & ELS fiber cottons data. The recorded values of simple correlation coefficients were 0.86 for Upper Egypt cottons and 0.95 for Delta LS and ELS cottons. These results indicate that SCI is a good Criterion for expressing the spinning value of cotton. However the prediction of yarn strength via SCI data showed more fluctuation in the predicted values compared to the prediction via fiber data.
References
ASTM D1578-93R00. (2005). Standard Test Method for Breaking Strength of Yarn in Skein Form. Annual Book of ASTM Standards. Vol. 7. 02 Section 7.
ASTM D5867-05. (2005). Standard Test Method for measurement of physical properties of cotton fibers by High Volume Instruments. Annual Book of ASTM Standards. Vol. 7. 02 Section 7. Cheng L., and D. L. Adams. Yarn strength prediction using neural networks. I. Fiber properties and yarn strength relationship. Textile Research Journal, vol. 65, no. 9, pp. 495–500, 1995.
El-Mogazhy, Y., Broughton, R. M. (1992). Regression observation of HVI fiber properties, yarn quality, and processing performance of medium staple cotton. Part I: HVI fiber parameter, Text. Res. J., 62 (4), 218-226.
El-Mogazhy, Y., Broughton, R., and Lynch, W. K.(1990). A statistical approach for determining the technological value of cotton using HVI fiber properties, Text. Res. J., 60 (9), 495-500.
Ethridge, M. D., J. D. Towery, and J. F. Hembree. (1982). Estimating func nal relationships between fiber properties and the strength of open-end spun yarns. Text. Res. J., vol. 52, no. 1, pp. 35–45.
Frydrych, I., (1992). A new approach for predicting strength properties of yarns. Tex.Res. J., 62, 340-348.
Hequet, E.F. and Abidi, N. (2008). Relationships between fiber and yarn tensile properties properties. Proceedings of 2008 Beltwide Cotton Conferences, Nashville, Tennessee ,PP. 1468-1471.
Moon W. Suh, Hyun-Jin Koo and Michael D. Watson. (1998). Estimation of HVI Bundle Modulus and Toughness as Determinants to Tensile Properties of Spun Yarns. Proceedings of 1998 Beltwide Cotton Conferences, PP 1530-1537.
Pan, N. (2001). Relationship between fiber and yarn strength, Tex. Res. J., 61, 960-964. Price, C. Senter, H. J. Foulk, G. Gamble, and W. Meredith. (2009). Relationship of fiber properties to vortex yarn quality viapartial least squares. Journal of Engineered Fibers and Fabrics, vol. 4, no. 4, pp. 37–46.
Sief, M. G., S. H. M. El-Hariry, and M. B. El- Kadi (1994). Predicted yarn strength of Egyptian thcotton using HVI testing. The 19 Int. Conf.for Stat. & Computer Science, Cairo, Egypt, April
1994:213-227.
Suh M.W., K. Hyun-Jui, and C. Xiaoling. (1998). Prediction of yarn tensile properties based on HVI testing of 36 U.S. Upland cottons,. in Proceedings of the Beltwide Cotton Conferences, pp.786–790, San Diego, Calif, USA, January.
Ureyen M. E. and H. Kadoglu. (2006). Regressional estimation of ring cotton yarn properties from HVI fiber properties. Text. Res. J., vol. 76, no. 5, pp. 360–366.
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Table 1: HVI fiber data, SCI, determined and predicted skein strength of 40’s carded yarns for Upper Egypt LS commercial cotton
varieties and promising crosses.
UHM UI Str. Elon. Rd dtr.- dtr.- dtr.- P5 dtr. - P1 P2 P3 dtr.- P4 Genotype Mike Mat. +bSCI Detr. P3 mm % g/tex % % P1 P2 P4 Via SCI P5
3.7 0.89 31.5 85.0 37.1 8.0 66.3 12.2 170 2260 2355 -95 2331 -71 2333 -73 2334 -74 2340 -80
-68 -13 -15 -13 30 3.9 0.91 31.2 84.2 39.0 8.0 66.6 12.9 170 2370 2438 2383 2385 2383 2340
3.5 0.88 30.2 85.5 36.3 7.6 66.1 12.8 169 2295 2313 -18 2246 49 2218 77 2248 47 2331 -36
3.5 0.88 31.4 85.7 36.0 8.1 66.9 12.5 172 2225 2339 -114 2291 -66 2299 -74 2297 -72 2359 -134
3.5 0.87 31.1 85.0 37.0 8.0 67.9 12.7 172 2315 2369 -54 2313 2 2310 5 2311 4 2359 -44 G80 3.3 0.85 30.8 85.4 35.7 7.4 66.9 12.5 171 2190 2308 -118 2254 -64 2212 -22 2253 -63 2350 -130
3.5 0.87 30.8 85.8 36.1 7.5 67.0 12.9 172 2225 2339 -114 2268 -43 2235 -10 2268 -43 2359 -134
3.5 0.86 31.0 85.3 37.9 8.0 67.5 12.5 175 2270 2387 -117 2345 -75 2339 -69 2338 -68 2387 -117
3.6 0.89 31.3 85.2 35.3 7.5 65.1 12.7 165 2225 2317 -92 2255 -30 2228 -3 2265 -40 2293 -108
3.5 0.86 31.1 83.9 36.4 7.5 65.5 12.8 163 2255 2351 -96 2284 -29 2250 5 2283 -28 2274 -19 Mean 3.6 0.88 31.0 85.1 36.7 7.8 66.6 12.7 170 2259 2352 89 2297 44 2281 39 2298 45 2339 86 Max 3.9 0.91 31.5 85.8 39.0 8.1 67.9 12.9 175 2370 2438 118 2383 75 2385 77 2383 74 2387 140 Min 3.3 0.85 30.2 83.9 35.3 7.4 65.1 12.2 163 2185 2308 18 2246 2 2212 5 2248 4 2274 19
2312 -67 4.1 0.94 30.5 85.3 37.7 8.2 65.5 11.8 167 2245 2294 -49 2301 -56 2319 -74 2308 -63
-34 3.8 0.90 30.0 83.3 34.0 8.3 63.9 12.1 146 2080 2162 -82 2129 -49 2147 -67 2137 -57 2114
3.7 0.90 31.0 83.1 35.5 8.4 66.1 11.9 155 2205 2250 -45 2235 -30 2263 -58 2243 -38 2199 6
4.1 0.93 30.0 83.0 35.0 7.9 62.7 11.7 145 2185 2162 23 2160 25 2158 27 2171 14 2104 81
4.2 0.95 30.4 84.0 36.0 7.9 64.9 11.8 154 2210 2220 -10 2221 -11 2223 -13 2232 -22 2189 21 G90 4.3 0.94 30.3 85.0 35.4 7.9 65.8 11.8 156 2230 2194 36 2196 34 2197 33 2201 29 2208 22
4.3 0.94 30.0 85.6 35.5 8.3 65.5 11.2 159 2250 2151 99 2189 61 2212 38 2193 57 2236 14
4.0 0.90 29.4 84.0 34.7 8.3 66.1 11.9 151 2125 2141 -16 2128 -3 2143 -18 2125 0 2161 -36
4.2 0.92 30.2 85.0 35.7 8.2 65.8 11.7 158 2250 2198 52 2205 45 2220 30 2205 45 2227 23
3.8 0.90 30.1 85.3 34.0 8.2 66.7 11.9 159 2150 2161 -11 2144 6 2157 -7 2149 1 2236 -86 Mean 4.1 0.92 30.2 84.4 35.4 8.2 65.3 11.8 155 2193 2193 42 2191 32 2204 34 2197 33 2199 39 Max 4.3 0.95 31.0 85.6 37.7 8.4 66.7 12.1 167 2250 2294 99 2301 61 2319 74 2308 63 2312 86 Min 3.7 0.90 29.4 83.0 34.0 7.9 62.7 11.2 145 2080 2141 10 2128 3 2143 3 2125 0 2104 6
P1: Predicted skein strength using equation 1 P3: Predicted skein strength using equation 3
P2: Predicted skein strength using equation 2 P4: Predicted skein strength using equation 4
P5: Predicted skein strength using SCI data
Table 1: continue.
UHM UI Str. Elon. Rd dtr.- dtr.- Act.- P5 dtr. - P1 P2 P3 dtr.- P4 Mat. Genotype Mike +bSCI Detr. P3 mm % g/tex % % P1 P2 P4 Via SCI P5
0.93 4.5 30.3 85.1 32.5 7.6 61.8 12.9 144 2100 2151 -51 2080 20 2063 37 2087 13 2095 5
0.93 131 4.5 29.9 82.5 33.9 8.5 63.3 12.9 136 2250 2170 -20 2102 48 2136 14 2104 46 2019
0.93 4.5 29.3 83.0 34.9 7.6 60.1 12.4 138 2105 2154 -49 2115 -10 2092 13 2118 -13 2038 67
0.94 4.6 29.1 83.6 33.9 8.1 58.5 12.9 136 2140 2139 1 2068 72 2076 64 2075 65 2019 121
0.95 4.6 28.2 83.5 32.1 7.8 62.8 12.9 131 2000 2029 -29 1955 45 1945 55 1960 40 1972 28
0.93 4.5 28.9 84.0 33.3 8.0 62.1 13.1 139 2050 2122 -72 2039 11 2040 10 2041 9 2047 3
G90XAUS 0.94 4.5 29.1 84.3 33.5 8.2 59.8 13.1 140 2080 2142 -62 2058 22 2073 7 2066 14 2057 23
0.95 4.6 30.1 85.8 33.8 8.3 65.9 13.1 153 2085 2195 -110 2123 -38 2149 -64 2126 -41 2180 -95
0.96 4.5 29.3 83.8 35.0 7.6 58.8 13.2 142 2200 2100 100 2123 77 2105 95 2137 63 2076 124
0.95 4.6 30.1 85.8 33.9 8.3 58.7 12.9 149 2090 2194 -104 2127 -37 2152 -62 2139 -49 2142 -52 Mean 0.94 4.5 29.4 84.1 33.7 8.0 61.2 12.9 141 2110 2140 60 2079 38 2083 42 2085 35 2064 65 Max 1.0 4.6 30.3 85.8 35.0 8.5 65.9 13.2 153 2250 2195 110 2127 77 2152 95 2139 65 2180 131 Min 0.9 4.5 28.2 82.5 32.1 7.6 58.5 12.4 131 2000 2029 1 1955 10 1945 7 1960 9 1972 3
0.94 4.5 29.2 84.5 38.5 8.3 66.5 11.5 159 2265 2226 39 2259 6 2275 -10 2249 16 2236 29
-21 0.93 4.4 31.9 86.7 38.7 7.8 66.8 11.6 186 2385 2375 10 2407 -22 2403 -18 2404 -19 2406
0.92 4.3 29.6 83.6 37.3 8.2 67.3 11.5 155 2300 2204 96 2230 70 2240 60 2221 79 2199 101
0.94 4.2 30.3 84.3 38.2 8.1 67.4 11.6 163 2330 2281 49 2304 26 2314 16 2304 26 2274 56
0.92 4.2 29.4 84.4 34.6 8.3 67.7 11.6 152 2145 2112 33 2122 23 2140 5 2119 26 2170 -25
0.93 4.4 29.4 84.9 35.4 8.2 66.3 11.6 154 2205 2136 69 2152 53 2164 41 2147 58 2189 16
0.92 4.4 29.4 84.5 36.0 8.0 67.1 11.5 154 2255 2149 106 2173 82 2171 84 2163 92 2189 66
0.93 4.4 29.4 83.6 38.2 8.3 67.0 11.7 156 2210 2235 -25 2254 -44 2270 -60 2244 -34 2208 2
{G83(G75×8544)}G80 0.92 4.3 30.5 84.3 37.5 8.3 66.0 11.5 160 2270 2257 13 2284 -14 2304 -34 2279 -9 2246 24
0.93 4.4 29.5 83.0 36.9 7.8 66.8 11.8 150 2240 2197 43 2205 35 2193 47 2197 43 2151 89 Mean 0.93 4.4 29.9 84.4 37.1 8.1 66.9 11.6 159 2261 2217 46 2239 38 2247 38 2233 40 2227 43 Max 0.94 4.5 31.9 86.7 38.7 8.3 67.7 11.8 186 2385 2375 106 2407 82 2403 84 2404 92 2406 101 Min 0.92 4.2 29.2 83.0 34.6 7.8 66.0 11.5 150 2145 2112 10 2122 6 2140 5 2119 9 2151 2
P1: Predicted skein strength using equation 1 P3: Predicted skein strength using equation 3
P2: Predicted skein strength using equation 2 P4: Predicted skein strength using equation 4
P5: Predicted skein strength using SCI data
Table 2: HVI fiber data, SCI, determined and predicted skein strength of 60’s carded yarns for Delta LS and ELS Egyptian commercial cotton
varieties and promising crosses.
UHM UI Str. Elon. Rd dtr.- dtr.- dtr.- P5 dtr. - P1 P2 P3 dtr.- P4 Genotype Mike Mat +bSCI Deter. P3 mm % g/tex % % P1 P2 P4 via SCI P5
4.7 0.96 33.4 86.6 44.3 7.6 75.7 8.2 197 2430 2538 -108 2532 -102 2465 -35 2487 -57 2568 -138
4.8 0.96 34.0 86.9 44.3 7.8 77.4 8.8 200 2450 2557 -107 2555 -105 2455 -5 2479 -29 2588 -138
4.8 0.98 33.7 86.2 44.4 7.8 77.9 8.5 197 2470 2522 -52 2535 -65 2488 -18 2506 -36 2568 -98
4.6 0.95 34.1 86.2 45.7 7.8 78.4 8.0 203 2550 2605 -55 2630 -80 2513 37 2531 19 2648 -98
4.8 0.96 33.6 86.4 44.6 7.7 78.7 8.5 199 2530 2527 3 2543 -13 2440 90 2451 79 2595 -65 Giza 86 4.5 0.95 33.4 85.6 45.4 7.5 77.3 8.3 199 2590 2568 22 2582 8 2509 81 2517 73 2595 -5
4.5 0.98 34.2 86.0 43.0 7.9 78.3 8.6 196 2460 2525 -65 2543 -83 2557 -97 2574 -114 2554 -94
4.6 0.95 33.7 85.8 45.1 7.4 78.2 8.6 199 2555 2562 -7 2577 -22 2492 63 2491 64 2595 -40
4.6 0.98 33.5 86.8 43.3 7.3 75.0 8.4 196 2470 2530 -60 2529 -59 2551 -81 2559 -89 2554 -84
4.7 0.96 33.5 86.6 42.2 7.1 76.1 8.3 192 2355 2465 -110 2459 -104 2440 -85 2435 -80 2491 -136 Mean 4.7 0.96 33.7 86.3 44.2 7.6 77.3 8.4 198 2486 2540 59 2549 64 2491 59 2503 64 2577 91 Max 4.8 0.98 34.2 86.9 45.7 7.9 78.7 8.8 203 2590 2605 110 2630 105 2557 97 2574 114 2648 138 Min 4.5 0.95 33.4 85.6 42.2 7.1 75.0 8.0 192 2355 2465 3 2459 8 2440 5 2435 19 2491 5
4.3 0.94 33.5 87.6 40.0 7.8 79.6 8.8 196 2515 2453 62 2471 44 2438 77 2447 68 2554 -39
4.2 0.95 33.8 87.6 43.5 7.8 77.7 8.8 201 2530 2615 -85 2629 -99 2598 -68 2617 -87 2662 -132
4.3 0.94 34.4 87.2 42.0 7.2 78.0 8.2 201 2595 2555 40 2577 18 2547 48 2536 59 2622 -27
4.3 0.94 34.7 87.9 41.7 7.4 75.6 8.4 202 2570 2591 -21 2600 -30 2557 13 2570 0 2635 -65
4.3 0.92 33.5 87.8 40.1 7.6 75.6 8.6 195 2480 2480 0 2481 -1 2397 83 2422 58 2541 -61 10229XG86 4.3 0.95 34.3 87.0 41.7 7.6 75.1 8.6 197 2460 2552 -92 2556 -96 2540 -80 2564 -104 2568 -108
4.3 0.94 34.3 87.4 40.1 7.6 74.8 8.6 194 2450 2507 -57 2508 -58 2479 -29 2506 -56 2528 -78
4.3 0.93 34.1 87.8 40.0 7.1 70.8 8.1 192 2410 2521 -111 2506 -96 2473 -63 2500 -90 2501 -91
4.3 0.94 33.4 88.5 40.0 7.7 74.5 8.7 197 2420 2498 -78 2492 -72 2458 -38 2492 -72 2558 -138
4.4 0.94 34.5 87.7 41.7 7.7 74.3 8.7 199 2515 2573 -58 2571 -56 2499 16 2535 -20 2595 -80 Mean 4.3 0.94 34.1 87.7 41.1 7.6 75.6 8.6 198 2495 2535 60 2539 57 2498 52 2519 61 2576 82 Max 4.4 0.95 34.7 88.5 43.5 7.8 79.6 8.8 202 2595 2615 111 2629 99 2598 83 2617 104 2762 138 Min 4.2 0.92 33.4 87 40 7.1 70.8 8.1 192 2410 2453 0 2471 1 2397 13 2422 0 2501 27
P1: Predicted skein strength using equation 1 P3: Predicted skein strength using equation 3
P2: Predicted skein strength using equation 2 P4: Predicted skein strength using equation 4
P5: Predicted skein strength using SCI data
Table 2: continue.
UHM UI Str. Elon Rd Act.- dtr.- Act.- P5 dtr. - P1 P2 P3 dtr.- P4 Genotype Mike Mat +bSCI Deter. P3 mm % g/tex % % P1 P2 P4 via SCI P5
4.0 0.96 36.8 87.0 48.1 7.3 65.7 11.9 218 2935 3008 -73 2954 -19 2942 -7 3004 -69 2850 85
40 3.9 0.95 36.0 88.9 46.0 7.1 66.5 11.9 221 2930 2960 -30 2906 24 2908 22 2957 -27 2890
3.9 0.95 37.4 88.0 48.1 7.4 66.4 11.9 225 3070 3072 -2 3025 45 2986 84 3050 20 2943 127
4.0 0.95 37.5 87.0 47.6 7.5 64.4 11.6 219 3025 2988 37 2932 93 2915 110 2975 50 2896 129
3.9 0.94 36.4 88.9 49.4 7.3 67.8 11.1 232 2985 3087 -102 3051 -66 2973 12 3026 -41 3037 -52 Giza 88 3.9 0.95 37.4 88.2 47.9 7.0 68.1 11.2 227 2995 3056 -61 3023 -28 3005 -10 3040 -45 2970 25
3.9 0.94 36.4 88.0 46.0 7.2 69.2 11.2 219 2995 2932 63 2899 96 2892 103 2911 84 2863 132
4.0 0.96 37.7 87.0 49.6 7.6 68.4 11.8 226 2990 3088 -98 3053 -63 3003 -13 3065 -75 2957 33
3.9 0.95 37.4 88.6 46.2 7.0 68.5 11.7 224 2955 3008 -53 2972 -17 2970 -15 3003 -48 2930 25
4.0 0.96 36.3 88.6 48.5 7.0 67.3 11.4 227 2990 3034 -44 2990 0 2980 10 3020 -30 2970 20 Mean 3.9 0.95 36.9 88.0 47.6 7.2 67.2 11.6 223 2987 3023 56 2981 45 2956 39 3005 49 2931 67 Max 4.0 0.96 37.7 88.9 49.6 7.6 69.2 11.9 232 3070 3088 102 3053 96 3005 110 3065 84 3037 129 Min 3.9 0.94 36.0 87.0 46.0 7.0 64.4 11.1 214 2930 2932 2 2899 0 2892 7 2911 20 2796 20
3.9 0.97 34.3 88.2 48.7 7.3 78.0 8.9 229 3005 2900 105 2905 100 2938 67 2928 77 2997 8
24 3.7 0.96 34.1 87.2 47.8 6.9 74.5 8.8 220 2900 2852 48 2861 39 2938 -38 2928 -28 2876
3.7 0.95 34.3 88.7 47.1 6.9 77.0 8.8 227 2975 2866 109 2887 88 2932 43 2910 65 2970 5
3.8 0.96 34.0 88.8 48.1 6.7 77.9 8.8 230 2980 2874 106 2899 81 2955 25 2917 63 3011 -31
3.6 0.95 33.9 88.1 46.7 6.6 78.5 9.2 225 2900 2826 74 2850 50 2938 -38 2891 9 2943 -43 Giza 92 3.7 0.95 33.8 87.6 48.6 6.6 76.7 8.6 225 2995 2887 108 2888 107 2940 55 2905 90 2943 52
3.6 0.94 34.4 87.9 48.0 6.4 78.3 8.8 228 2975 2887 88 2917 58 2968 7 2914 61 2984 -9
3.6 0.94 35.1 88.1 49.0 7.2 77.7 8.8 233 3065 2962 103 2993 72 2988 77 2977 88 3051 14
3.7 0.96 34.4 88.8 47.9 6.6 73.6 8.8 228 2990 2919 71 2925 65 3002 -12 2984 6 2984 6
3.8 0.96 33.4 88.7 48.5 6.0 76.4 8.9 229 2990 2868 122 2890 100 2972 18 2909 81 2997 -7
2884 Mean 3.7 0.95 34.2 88.2 48.0 6.7 76.9 8.8 227 2978 93 2901 76 2957 38 2926 57 2976 20 4 Max 3.9 0.97 35.1 88.8 49.0 7.3 78.5 9.2 233 3065 2962 108 2993 108 3002 77 2984 90 3051 52 Min 3.6 0.94 33.4 87.2 46.7 6.0 73.6 8.6 220 2900 2826 48 2850 39 2932 7 2891 6 2876 5 P1: Predicted skein strength using equation 1 P3: Predicted skein strength using equation 3
P2: Predicted skein strength using equation 2 P4: Predicted skein strength using equation 4
P5: Predicted skein strength using SCI data
Table 2: continue.
UHM UI Str. Elon Rd dtr.- dtr.- dtr.- P5 dtr. - P1 P2 P3 dtr- P4 Genotype Mike Mat. +bSCI Deter. P3 mm % g/tex % % P1 P2 P4 via SCI P5
3.3 0.92 37.2 88.8 46.4 6.8 65.9 11.3 229 3100 3099 1 3059 41 3080 20 3117 -17 2997 103
123 3.2 0.89 36.2 87.7 46.6 6.4 64.7 11.6 228 3100 3053 47 3001 99 2994 106 3011 89 2977
3.1 0.89 37.1 87.4 45.7 6.3 64.0 11.7 225 3100 3069 31 3016 84 3028 72 3053 47 2960 140
3.3 0.93 36.5 88.8 46.8 6.6 66.7 11.7 229 3060 3083 -23 3040 20 3099 -39 3121 -61 2997 63
3.2 0.89 36.8 87.1 46.2 6.3 65.5 11.1 220 3070 3039 31 2998 72 2991 79 3008 62 2966 134
3.2 0.92 38.0 88.8 45.3 6.0 65.7 11.7 228 3100 3111 -11 3070 30 3156 -56 3154 -54 2984 116 G77XPs6 3.2 0.90 38.1 88.8 45.5 6.2 66.9 11.5 230 3100 3115 -15 3082 18 3098 2 3101 -1 3011 89
3.1 0.92 37.0 88.3 49.2 6.3 64.4 11.6 235 3150 3213 -63 3166 -16 3218 -68 3239 -89 3078 72
3.1 0.91 36.9 88.0 46.7 6.7 66.0 11.5 227 3100 3101 -1 3060 40 3096 4 3127 -27 2970 130
3.1 0.91 36.5 87.5 47.2 6.4 65.7 11.6 226 3120 3090 30 3046 74 3096 24 3114 6 2987 133 Mean 3.2 0.91 37.0 88.1 46.6 6.4 65.6 11.5 227 3100 3097 25 3054 49 3085 47 3105 45 2986 119 Max 3.3 0.93 38.1 88.8 49.2 6.8 66.9 11.7 235 3150 3213 63 3166 99 3218 106 3239 89 3078 140 Min 3.1 0.89 36.2 87.1 45.3 6.0 64.0 11.1 220 3060 3039 1 2998 16 2984 2 3008 1 2960 63
3.9 0.93 35.8 87.5 47.6 6.2 76.4 8.8 224 2980 2892 88 2916 64 2897 83 2877 103 2930 50
3.9 0.96 36.5 86.5 46.7 6.4 76.4 8.8 218 2950 2862 88 2888 62 2958 -8 2913 37 2850 100
4.0 0.94 36.5 88.8 45.3 6.5 74.5 8.7 223 2965 2872 93 2887 78 2879 86 2854 111 2917 48
4.1 0.95 35.8 87.2 46.2 6.8 75.3 8.8 216 2925 2813 112 2828 97 2821 104 2815 110 2823 102
4.0 0.96 36.5 87.1 46.4 6.0 76.4 9.0 219 2910 2857 53 2880 30 2952 -42 2889 21 2863 47
4.0 0.94 35.5 87.7 45.9 6.0 75.1 8.8 218 2915 2817 98 2830 85 2853 62 2820 95 2850 65
4.1 0.95 35.9 87.2 47.5 6.2 74.3 9.3 219 2990 2874 116 2890 100 2888 102 2878 112 2863 127
4.1 0.94 36.2 86.8 44.5 6.7 73.6 8.4 209 2815 2762 53 2772 43 2763 52 2752 63 2729 86
4.0 0.94 36.1 88.4 44.8 6.3 76.2 8.8 220 2850 2817 33 2838 12 2851 -1 2806 44 2876 -26 {G84×(G70×G51B)}×P62 4.1 0.94 35.8 88.7 46.0 6.2 73.0 9.0 221 2960 2861 99 2863 97 2859 101 2849 111 2890 70 Mean 4.0 0.95 36.1 87.6 46.1 6.3 75.1 8.8 219 2926 2843 83 2859 67 2872 64 2853 83 2859 72 Max 4.1 0.96 36.5 88.8 47.6 6.8 76.4 9.3 224 2990 2892 116 2916 100 2958 104 2913 112 2930 127 Min 3.9 0.93 35.5 86.5 44.5 6 73 8.4 209 2815 2762 33 2772 12 2763 1 2752 21 2729 26
P1: Predicted skein strength using equation 1 P3: Predicted skein strength using equation 3
P2: Predicted skein strength using equation 2 P4: Predicted skein strength using equation 4
P5: Predicted skein strength using SCI data
ActualP1P2P3P4P5
250024002300220021002000190018001700160015001400skein strength1300120011001000
G 80G 90G 90×Aus.{G 83(G 75×8544)}G 80Fig.1 Determined and predicted skein strength for 40’s carded yarns spun from Upper Egypt cottons. Fig.2 Determined and predicted skein strength for 60’s carded yarns spun from Delta LS & ELS
ActualP1P2P3P4P5
3200
3000
2800
2600
2400
2200
2000
1800Skein strength1600
1400
1200
1000
G 8610229XG 86G 88G 92G 77XPs6{G 84×(G 70×G 51B)}×P62Egyptian cottons
y= 1340.6+5.5319x r = 0.86y = 1040.8-17.969x r = 0.9533002400
32002350
31002300300022502900220028002150270021002600
20502500
20002400Determined skein strengthDetermined skein strength23001950
22001900
190195200205210215220225230235240100110120130140150160170180190
SCISCI
Upper Egypt cottons data Delta LS & ELS cottons data
Fig.3 Regression equations and correlation coefficients for SCI and determined skein strength of
Upper Egypt and Delta LS & ELS cottons.
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