Developing Methods for Detecting Cotton Fiber Identity Theft
Type of Degreethesis
DepartmentPolymer and Fiber Engineering
MetadataShow full item record
This study focused on determining ways to detect identity theft of cotton fibers through developing identification tests from fibers to end products. Cotton types examined in this study include: Extra-Long Staple cotton fibers such as Giza cotton, Supima cotton, and Chinese cotton, and Medium-Staple cotton such as American Upland cotton. Tests used to identify different cotton fiber type in the raw form included (1) standard methods, and (2) non-standard methods. Standard methods were primarily common fiber testing methods using the High-Volume Instrument (HVI) and the Advanced Fiber Information System (AFIS). These two systems were developed by Uster® Technologies and they are widely used all over the world. These systems provide values of common fiber properties such as fiber length, Micronaire, fiber strength, color, maturity, and trash content (HVI), and fiber length, fineness, neps, maturity, and trash (AFIS). Using the values of these properties, one can easily distinguish between major categories of fiber types. For example, Extra-Long Staple cotton fibers (ELS) will have longer, finer, stronger, and more mature fibers than regular (Upland-like) cotton fibers. Non-standard methods that have never been used for cotton fiber identification were also developed and used. These include: Dyeing Test, Viscosity Test, and Sonic Test. Among these tests, viscosity and sonic modulus seem to provide distinguished differences between different cotton types. The study also dealt with two basic textile end products, namely: bed sheets and knit shirts to examine whether it is possible to identify different cotton fibers through their performances in the end products. This type of analysis showed that different cotton types can indeed have different effects on end product performance through which the identity of fiber can be traced back to its type and sources.
- Yusuf Celikbag - Master Thesis _2009_.pdf