Characterization of Egyptian Cotton Fiber Quality Using CCS
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The purpose of the current study is to characterize Egyptian cotton using HVI and CCS measurements. The present investigation was carried out at two different locations: The Global Center for Cotton Testing Research in International Cotton Association (ICA) using HVI instrument in Germany and Egyptian and International Cotton Classification Center (EICCC), Cotton Research Institute (CRI), Agricultural Research Center (ARC) using CCS instrument in Egypt. Samples are sourced from standardized preparation stages to obtain more homogeneity. All samples were collected from 2018 and 2019 cotton growing seasons. The studied cotton fiber properties: upper half mean (UHM), uniformity index (UI %), short fiber index (SFI %), strength (FS) and elongation (E %) and micronaire reading (Mike) and maturity ratio (MR). The studied cotton varieties include long staple cotton varieties i.e., Giza 86 and Giza 95 and extra-long staple cotton varieties i.e., Giza 92 and Giza 93, in terms of basic Egyptian cotton grade Good (G). The results of HVI and CCS measurements were detected by using descriptive statistics such as measures of central tendency and dispersion, skewness, and kurtosis. The CCS measurements were more stable than HVI measurements. Confidence intervals of CCS measurements were close to each other compared to HVI measurements. For instance, in Giza 92, confidence interval of UHM was 32.00-32.32for HVI and 32.50-32.55for CCS, adding to confidence intervals for FS were 45.19-46.83for HVI and 46.99-47.17 for CCS. Meanwhile, confidence intervals for Mike were 3.04–3.21 for HVI and 3.12–3.14 for CCS. Basically, sample sizes of CCS were larger more than sample sizes of HVI so that results of CCS measurements were more homogenous than HVI measurements. Applying reliability analysis for consistent results in CCS and HVI measurements elaborated Cronbach's value were more efficient than using Cronbach's value if item deleted for both CCS and HVI. Cronbach's value of CCS measurements was more than HVI measurements and that due to the homogeneity of CCS samples compared to HVI samples.
References
-
ASTM, ASTM standard D1776/D1776M-16, Standard practice for conditioning and testing textiles, ASTM International, west Conshohocken, 2016, pp. 1-5.
Google Scholar
1
-
J. Beyeneand, and R. Moineddin, "Methods for confidence interval estimation of a ratio parameter with application to location quotients," MBC Medical Research Methodology. Vol. 5, no. 32, pp. 1-7, 2005.
Google Scholar
2
-
M. Blank, and J. Peacock, "Interpreting statistics with confidence," The Obstetrician and Gynaecologist. Vol. 4, pp. 176-180, 2002.
Google Scholar
3
-
J. M. Bradow, L. H. Wartelle, P. J. Bauer, and G. F. Sassenrath-Cole, "Small sample cotton fiber quality quantitation," Cotton Science. Vol. 1, pp. 48-60, 1997.
Google Scholar
4
-
J. W. Bradow, and G. H. Davidonis, "Quantization of fiber quality and the cotton production processing interface: A physiologist's perspective," Cotton Science. Vol. 4, pp. 34-64, 2000.
Google Scholar
5
-
Corporate fiber and materials methodology, Fiber convention Methodology, 2019, pp. 1-14.
Google Scholar
6
-
L. J. Cronbach, "Coefficient alpha and the internal structure of tests," Psychometrika, vol. 16, no. 3, pp. 297-334, 2019.
Google Scholar
7
-
C. Duncan, "Basic statistics for social research," Routledge, 1997.
Google Scholar
8
-
S. Ellison, and A. Williams, "Measurement uncertainty: The key to use of recovery factors, the use of recovery factors in trace analyses," Ed M Parkany, pp. 30-37, 1996.
Google Scholar
9
-
Global Agricultural Information Network (GAIN) report Cotton and product annual, Gain report number: EG18011, 2018, pp. 1-14.
Google Scholar
10
-
Guideline for standardized instrument testing of cotton, International Cotton Advisory Committee (ICAC) task force on Commercial Standardization of Instrument Testing of Cotton (CSITC) and International Textile Manufacturers Federation (ITMF) International Committee on Cotton Testing Methods (ICCTM), 2018, pp. 1-45.
Google Scholar
11
-
N. Hirpara, S. Jain, A. Gupta, and S. D. Intern, "Interpretation research findings with confidence interval," Orthodontics and Endodontics, vol. 1, pp. 1-8, 2015.
Google Scholar
12
-
T. T. Houle, "Importance of effect sizes for the accumulation of knowledge, "Anesthesiology, vol. 106, pp. 415-417, 2007.
Google Scholar
13
-
S. Jain, P. R. Punyani, and D. Jain, " Basic of interpreting results," Dent. Med. Advanced Research, vol. 1, pp. 1-4, 2015.
Google Scholar
14
-
R. G. Jansen, L. F. Wiertz, E. S. Meyer, and L. P. Noldus,"Reliability analysis of observational data: problems, solutions and software implementation," Behavior Research Methods, Instruments and Computers, vol. 35, no. 3, pp.391-399, 2003.
Google Scholar
15
-
D. N. Joanes, and C. A. Gill, "Comparing measures of sample skewness and kurtosis," The Statistician, vol. 47, no.1, pp. 183-189, 1998.
Google Scholar
16
-
R. W. Mathangadeera, E. F. Hequet, B. Kelly, J. K. Dever, and C. M. Kell, "Importance of cotton fiber elongation in fiber processing," Industrial Crops and Products, pp.1-7, 2020.
Google Scholar
17
-
J. P. S. Moarais, B. R. Kelly, A. Sayeed, and E. F. Hequet,"Effects of non-lint material on heritability estimates of cotton fiber length parameters," Euphytica, vol. 216, no. 24, pp. 1-32, 2020.
Google Scholar
18
-
Minitab, Reference guide. Prepared for MATH201/MATH202, Bryan Crissinger, University of Delaware. Department of Mathematical Science, 2016.
Google Scholar
19
-
H. H. Perkins, Jr. D. E. Ethridge, and C. K. Bragg, "Cotton. 2nd ed. Longman Scientific and Technical," Harlow, Essex, UK, 1984.
Google Scholar
20
-
M. Puth, M. Neuhauser, and G. D. Ruxton," On the variety of methods for calculating confidence intervals by bootstrapping," Animal Ecology, vol.84, pp. 892-897, 2015.
Google Scholar
21
-
T. Raykov,"Estimation of composite reliability for congeneric measures," Applied Psychological Measurement, vol. 21, no. 2, pp. 173-184, 1997.
Google Scholar
22
-
T. Raykov,"Coefficient alpha and composite reliability with interrelated nonhomogeneous items," Applied Psychological Measurement, vol. 22, no. 4, pp. 375-385, 1998.
Google Scholar
23
-
J. Rogers, J. Zumba, and C. Fortier, "Measurement comparison of cotton fiber micronaire and its components by portable near infrared spectroscopy instruments," Textile Research, vol. 87, no. 1, pp. 57-69, 2016.
Google Scholar
24
-
L. Schruben,"Confidence interval estimation using standardized time series," Operations Research, vol. 31, no. 6, pp.1090-1108, 1983.
Google Scholar
25
-
G. Shieh, «Confidence intervals and sample size calculations for the standardized mean difference effect size between two normal populations under heteroscedasticity," Behavior Research, vol.45, pp.955-967, 2013.
Google Scholar
26
-
SPSS, IBM SPSS Statistics 21 Core System. User's Guide (edited by IBM ® SPSS ® statistics 21), U. S. government users restricted rights by GSA and ADP, 2012.
Google Scholar
27
-
I. Shigeo, "Weights and measures in the Indus valley," Encyclopedia of the history of science Technology and medicine in non-western cultures, 2nd ed., Helaine Selin, 2008, PP.2254-2255.
Google Scholar
28
-
R. G. D. Steel, and J. H. Torrie, "Principles and procedures of statistics," McGraw- Hill Book Co., 1980, New York.
Google Scholar
29
-
Textile Testing Technology Group (TEXTECHNO), Textile Herbert Stein GmbH& Co. KG, D-41066 Monchengladbach, Germany (www.textechno.com) and Lenzing Instruments GmbH & Co. KG, A-4860 Lenzing, Austria (www.lenzing-instruments.com).
Google Scholar
30
-
D. Thibodeaux, H. Senter, J. L. Knowlton, D. McAlister, and X. Cui, "A comparison of methods for measuring the short fiber content of cotton," Cotton Science, vol. 12, pp.298-305, 2008.
Google Scholar
31
-
B. L. Welch, "On confidence limits and sufficiency, with particular reference to parameters of locations," The Annuals of Mathematical Statistics, Vol.10, no.1, pp. 58-69, 1939.
Google Scholar
32
-
P. H. Westfall, "Kurtosis as peakedness," The American Statistician, vol. 86, no.3, pp. 191-195, 2014.
Google Scholar
33
-
P. R. Yarnold, and R. C. Soltysik, "Reliability analysis in P. R. Yarnold & R. C. Soltysik (Eds.), optimal data analysis: A guide book with software for windows," Washington, DC: American Psychological Association, 2005, pp. 121-140.
Google Scholar
34
-
S. Zandarov, "Textechno Publications," Advanced Industrial and Engineering Polymer Research, vol. 1, no.1, pp. 82-92, 2018.
Google Scholar
35