Another approach to solve the problem of high variation is to search for other statistical parameters of cotton fiber length distribution that also

Transcription

1 Relative Short Fiber Content Measurements -Is This the Solution? X. Leon Cui, K. Q. Robert, J. B. Price, D. P. Thibodeaux USDA, ARS, Southern Regional Research Center New Orleans, Louisiana And Mike Watson, Cotton Incorporated Carry, North Carolina Short fibers in cotton reduce textile processing efficiency and product quality. In order to meet the challenge of intensive global competition, the U.S. cotton textile industry has been advocating obtaining the Short Fiber Content (SFC) from the cotton classification. SFC is defined as the percentage of fibers shorter than half-inches. The National Cotton Council has passed a resolution to study the feasibility of including the short fiber content measurement in cotton classification. Studies on the measurement of short fiber content have been carried out at USDA AMS (Agricultural Marketing Service) and ARS (Agricultural Research Service), and Cotton Incorporated (Cui, et al, ; Knowlton, 2000, 2002), among many others (Backe, 1992; El-Mogahzy et al, 2000, Ethridge 1999, Hequet 1999, and Rowland 1999). We have evaluated a large selection of cottons with diverse fiber properties on various instruments including HVI, AFIS, Peyer Almeter, Suter-Webb Array, and Iso Tester*. The influence of short fibers on spinning performance and product quality are under investigation to determine the utility value of SFC. From the test results, a major problem is the very high variation of the measured SFC. Other researchers also identified this problem (Heap, 2004). According to a research by AMS, using a tolerance of 1.0%, the reproducibility of short fiber index between HVI s averaged 57% (Knowlton, 2002). As a natural product, the length of cotton is not uniform. The difficulty in handling shorter fibers in testing augments the variation in the measured SFC. There are ways to deal with high variations. The most common way is to increase the number of tests. In the case of SFC, our results show that in order to obtain a confidence interval of?1%, the current number of tests (2 beards per sample) has to be at least doubled, which requires significant increase in cost of classing. Due to the high variation, the Module Averaging Method for SFC deserves consideration. In the same study as mentioned above, the Module Average Method increased the reproducibility of short fiber index between HVI s for single bale to 95% from 57% (Knowlton, 2002). Modifying the sampling method can also increase the reproducibility, such as selecting specimens from multiple locations of the bale, larger specimen beards, etc. Efforts are also made to predict SFC using longer fiber parameters (UHML, UI) that have less variability (Knowlton, 1999). * Names of companies or commercial products are given solely for the purpose of providing specific information; their mention does not imply recommendation or endorsement by the U.S. Department of Agriculture over others not mentioned.

2 Another approach to solve the problem of high variation is to search for other statistical parameters of cotton fiber length distribution that also characterize the shorter fiber portion. In this study, we included Lower Quartile Length (LQL), and Lower Half Mean Length (LHML). The LQL is the length that is exceeded by 75% of the fibers, by weight or by number, of the specimen. The LHML is the mean length by number of the shorter one-half (50%) by weight of the fibers. In addition, the values of SFC by weight defined by length limits of 0.3, 0.4, 0.6, and 0.7 inches (SFC w0.3, SFC w0.4, SFC w0.6, SFC w0.7 ) were also calculated and compared with the SFC defined by 0.5 inches (SFC w0.5 ). The relationships among these parameters and the variations of these parameters were analyzed. The criteria for selecting alternative parameters to SFC are: be able to characterize short fibers well (having high correlation with SFC), have less variation than that of SFC, and be able to predict spinning performance and yarn quality as well as or better than SFC does. The results presented here are based on samples taken from a set of 21 bales of U.S. Upland cotton in an American Textile Manufacturers Institute (ATMI) leading variety study led by David McAlister at the USDA ARS Cotton Quality Research Station (CQRS) at Clemson, South Carolina. At CQRS, the bales were converted into 20/1 open-end, 20/1 ring yarns, and 35/1 Vortex yarns. The simple correlation coefficients among the length parameters and yarn properties, as well as the spinning performance, were analyzed. A summary of the average values of the length parameters characterizing shorter fibers is shown in Table 1. It needs to be pointed out that the length parameters and their variations used in this paper are based on AFIS length distributions. The length parameters and their variations reported by different instruments may vary to an extent due to sampling, sample preparation, sample size, principle of measurement, and calibration. A summary of the coefficient of variation (CV%) of the various fiber length parameters is given in Tables 2. The CV of SFC decreases as the limiting length defining the short fiber content increases. It is important to notice that the CV of the short fiber content is about 6.8 times higher than that of UQL w and UHML, while the CV of LHML (Lower Half Mean Length) is much lower than that of short fiber content, only about 1/3 of the latter. Although LHML has its advantages over SFC in terms of variation, it does not provide an exact percentage of short fibers in a cotton, which may be more desirable to know in certain situations such as estimating combing waste. Nevertheless, our results show that the SFC can be estimated with good accuracy based on LHML. Based on the data from this study, a simple linear regression yields R 2 of Table 4 lists the simple correlation coefficients among the various fiber length parameters. The short fiber content defined by 0.5 inches shows very high correlation coefficients with short fiber content defined by other lengths (R = to 0.994). The LHML

3 also shows a very strong correlation coefficient (R = ) with short fiber content SFC 0.5. In combination with its low variation, the LHML becomes a good candidate for characterizing short fibers of cotton. Based on the data, the Uniformity Index does contain significant amount of information about short fiber content (R = 0.791). On the other hand, the UHML and UQL w seem to contain very little information on short fiber content (R = and 0.028, respectively) based on the data. The correlation coefficients of the various length parameters with yarn processing parameters and yarn properties were analyzed for open-end, ring and Vortex yarns, respectively. In most cases, the UHML and UI showed much stronger correlations with yarn properties than SFC did. Fiber length properties frequently affect the three kinds of yarns differently. The short fibers primarily affected the yarn evenness or irregularity. The short fibers increase the irregularity of ring and Vortex yarns, but reduce that of open-end yarns. This indicates that cottons with higher short fiber content (usually cheaper) may be used in open-end spinning systems. According to the Classimat data, the short fibers showed no effect on any of the four kinds of imperfections (Major Faults, Minor Faults, Long Thicks, and Long Thins) of open-end yarns, but increased the long-thin places of the ring yarns and Vortex yarns. Surprisingly, the short fibers reduce, not increase, the long thick places of the Vortex yarn. From the results, the LHML and the SFC show similar absolute values of correlation coefficients (although with opposite signs of correlation coefficients) to all spinning and yarn properties. In conjunction with the lower C.V. of the measured LHML as discussed earlier, the LHML is indeed a good parameter for cotton short fibers. The results on LHML reported here were based on data from AFIS, which measures the entire length of individualized fibers. Cotton classification uses HVI instruments to meet the need for rapid measurement. We plan to study the algorithm to obtain the LHML from HVI, which measures the extending portion of a tapered beard (fiber bundle). Summary The results based on the AFIS data on selected cottons show that the short fiber content defined by 0.5 inches is a good indicator of short fibers based on the high correlation coefficients with short fiber contents defined by other lengths from 0.3 to 0.7 inches. However, the measured short fiber content has very high variation. The results also show that the LHML has a very strong correlation with the SFC, but has a much lower variation than that of the SFC. In addition, the LHML has similar correlation coefficient values as SFC does with all yarn properties. Therefore, the LHML is a good short fiber parameter alternative to SFC. The Uniformity Index correlates to the SFC, but the Upper Half Mean Length has a very low correlation with the SFC.

4 References Backe E. E., Effect of short fiber content in cotton on plant performance and quality, Textile Res. J. 56(2): Cui, X., T. A. Calamari, Jr., K. Q. Robert, J. B. Price, and M. Watson, Measuring the short fiber content of cotton, Textile Res. J. 73(10): Cui, X., T. A. Calamari, Jr., J. B. Price, K. Q. Robert, and M. Watson, The variations of cotton fiber properties and their influence on test results. Proc. Beltwide Cotton Prod. Res. Conf., Anaheim, CA 9-13 Jan Natl. Cotton Counc. Am., Memphis, TN. Cui, X., T. A. Calamari, Jr., K. Q. Robert, and M. Watson, New insights into the measurement of short fiber content. Proc. Beltwide Cotton Prod. Res. Conf., San Antonio, TX 4-8 Jan Natl. Cotton Counc. Am., Memphis, TN Cui, X., T. A. Calamari, K. Q. Robert and M. Watson, Short fiber content of cotton and its measurement. Proc. Beltwide Cotton Prod. Res. Conf., Orlando, FL 3-7 Jan Natl. Cotton Counc. Am., Memphis, TN Cui, X., T. A. Calamari, and K. Q. Robert, A comparative study of short fiber content measured by different methods. 11th EFS System Research Forum, Raleigh, NC El-Mogahzy, Y., R. Broughton, and H. Guo, How the machine maker deals with the issue of short fiber content, Proc. Beltwide Cotton Prod. Res. Conf., San Antonio, TX 4-8 Jan Natl. Cotton Counc. Am., Memphis, TN Ethridge, M. D., and E. Hequet, An evaluation of the AFIS short fiber content measurement, Textile Topics, Spring 2-8. Heap, S. A., Relative Short Fiber Content, 27 th International Cotton Conference, Bremen, Hequet, E., Application of the AFIS multidata, Proc. Beltwide Cotton Prod. Res. Conf., Orlando, FL 3-7 Jan. Natl. Cotton Counc. Am., Memphis, TN Knowlton, J. L., Short Fiber Measurement, 12th Engineer Fiber Selection System Conference (

5 Knowlton, J. L., 2002, Module averaging the short fiber measurement, Proc. Beltwide Cotton Prod. Res. Conf., Atlanta, GA 8-13 Jan Natl. Cotton Counc. Am., Memphis, TN. Knowlton, J. L Future Quality Measurement, Proc. Beltwide Cotton Prod. Res. Conf., San Antonio, TX 4-8 Jan Natl. Cotton Counc. Am., Memphis, TN. p Rowland, J. D., Cotton Short-Fiber Testing, 12th Engineer Fiber Selection System Conference (

6 Table 1. Summary of the fiber length parameters characterizing shorter fibers SFC 0.3 SFC 0.4 SFC 0.5 SFC 0.6 SFC 0.7 LQL n (in) LQL w (in) LHML (in) Average Maximum Minimum Table 2. Summary of the Coefficient of Variation (CV%) of the length parameters characterizing shorter fibers SFC 0.3 SFC 0.4 SFC 0.5 SFC 0.6 SFC 0.7 LQL n LQL w LHML Average Maximum Minimum Table 3. Summary of the Coefficient of Variation (CV%) of the various fiber length parameters (longer fibers) UQL n UQL w UHML ML n ML w UI Average Maximum Minimum Table 4. Correlation coefficients among fiber length parameters SFC 0.3 SFC 0.4 SFC 0.5 SFC 0.6 SFC 0.7 LQL w LHML UHML UI SFC SFC SFC SFC SFC LQL w LHML UHML UI