Determining Short Fiber Content in Cotton

Abstract

Based on large data sets from three consecutive cotton crop years, linear models for SFW and SFN in terms of the HVI length parameters have been developed. The necessity of modifying the Suter-Webb array distributions is justified. The results are discussed in light of the concept of "similarity" related to fiber length distributions, as defined in Part I. Using normalized regression equations, UI is demonstrated to have a stronger influence on SFC than the range parameters (UHM, ML). The terms UI, UHM, ML are standard measurements of the HVI instruments and have been defined in the text. The models developed in this study have been compared with the one developed by Preysch in 1979, and the relative improvement over Preysch's method is discussed.

The theoretical yarn unevenness of cotton considering the joint influence of fiber length distribution and fiber fineness

“…Fiber fineness among different fibers can vary but be independent of fiber length. [11][12][13] Theoretical derivation of the model If Á(mm) is the length interval in the yarn and l(mm) the fiber length; the fiber length distribution function in the yarn is F(l) and density function is f(l); S(mm) is the length of the fiber with the length l to be found within the length interval Á in the yarn; N is the total number of fibers found within length interval Á; T(tex) is the fiber fineness; and G i (g) the weight of the ith fiber within the length interval Á in the yarn (i ¼ 1, 2, . .…”

“…Each group of 30 fibers for one cotton sample was tested. According to the relationship between fiber diameter and fiber fineness, 12 …”

“…According to equation (12), the coefficient of variation of fiber length for the fibers found within the length interval Á could be calculated. In this paper, Á ¼ 8 mm was assumed, in accordance with the actual test length commonly used in an Uster evenness tester.…”

Adjustment of Cotton Fiber Length by the Statistical Normal Distribution: Application to Binary Blends

“…They assumed a random catching and holding of fibers within each of the length groups generating a triangular distribution by relative weight for each length group. Zeidman, Batra and Sasser [6] [7] discussed the concept of short fibers content and showed relationships between SFC and other fibers length parameters and functions. Later they determined empirical relationships between SFC and the HVI length.…”

Image-based Bilateral Beard Method for measuring weight-based short fiber contents in raw cotton and semi-finished slivers

“…24,25 The low repeatability of the SFI, however, prevents it from being used in the United States Department of Agriculture's (USDA's) raw cotton classification system. [26][27][28][29] Another widely employed automatic instrument is the Advanced Fiber Information System (AFIS), which has a built-in fiber opener for individualizing cotton fibers from a sliver, as well as a photoelectric sensor to test the fibers' length when they are transported by a high-speed airflow. 19 On the basis of at least 3000 single fibers and the assumption that the fibers have uniform linear density, AFIS can output length-number frequency distribution histograms, length-weight frequency distribution histograms, and a series of length parameters extracted from these histograms.…”