Submitted to: Journal of Cotton Science
Publication Type: Peer reviewed journal
Publication Acceptance Date: 4/19/2005
Publication Date: 9/30/2005
Citation: Montalvo Jr, J.G., Von Hoven, T.M. 2005. Relationships between micronaire, fineness and maturity. part II. experimental. Journal of Cotton Science. 9:89-96. Interpretive Summary: The micronaire of cotton is a combined measure of fiber fineness and maturity. Fineness and maturity are important because yarn made from fine fibers is stronger, and mature fibers absorb dye better. Correlations between micronaire and fineness, and between micronaire and maturity, give widely varying results. This is due to the fact that the associations are visually displayed in charts as a family of lines rather than a single line. There is a need to model the information to understand how to enhance the correlations. New models were developed which resulted in associations displayed in charts as a single line with less variability in the correlations. These new expressions are called diagnostic models because a fit of information to the models provides a proof of important principles in the fiber quality measures of micronaire, fineness and maturity. The work goes on to successfully fit these measures of fiber quality on over 300 worldwide cottons to the new models. The diagnostic models may help to validate the micronaire, fineness and maturity database on U.S. cottons, which could positively influence cotton consumption.
Technical Abstract: In Part I of this series, models were developed and computer simulated to understand the variability in R**2 between cotton (Gossypium hirsutum L.) fineness and maturity, micronaire and fineness, micronaire and maturity (Montalvo,in press). All plots of the simulated fiber properties produced families of lines rather than a single line due to the fact that biological or cross-sectional perimeter plays a significant role in interpretation of the relationships. To enhance the R**2 values, this paper revisits the Part I simulation database to obtain information about how to derive diagnostic relationships to fit to a simple linear model. These new expressions incorporate perimeter in the model in a way that families of lines give a sing line plot. The diagnostic criteria for a fit of data to a model is that a plot of the data will yield a single line with high R**2 predicted slope and intercept values. A fit of the data provides a proof of the underlying principles: the Lord equation for micronaire, and the definitions of fineness and maturity in equation form. Of special significance is that the definitions of fineness and maturity are independant of experimental methods of measure and independant of the Lord equation. The diagnostic models were tested on 305 cottons with experimental data produced by the SRRC upgraded Fineness and Maturity Tester (FMT). For all the diagnostic relationships, plots of the FMT data produced a single line with high R**2 and slopes and intercepts that conform to simulation predictions.