A comparative study of the effects of cotton fiber length parameters on modeling yarn properties

Fiber length is one of the key properties of cotton and has important influences on yarn production and yarn quality. Various parameters have been developed to characterize cotton fiber length in the past decades. This study was carried out to investigate the effects of these parameters and their combinations on yarn properties. Linear regression models with different numbers of fiber length parameters and their combinations were developed for predicting ring and open-end (OE) spun yarns' properties. The R-2 and Mallows' Cp plots of the models were compared for model selections. The results indicate that, for predicting a yarn property, a model usually involves more than three length parameters to achieve better prediction when considering the R-2 and Cp values. This may be because only one single length parameter cannot sufficiently represent fiber length characteristics. The results also show that the variations in fiber length distributions play important roles in predicting yarn properties, such as strength and irregularity. The best prediction models for the properties of different yarns (ring, OE) include different combinations of length parameters. Not all yarn properties can be well predicted by linear regression models with length parameters: other fiber properties (strength, micronaire, etc.) need to be included to further improve the models.