Assessing cotton maturity using distributional parameters of fiber cross-section measurements

Abstract

Many previous studies on cotton maturity used a sole parameter to rank the maturity of a cotton sample containing a large number of fibers. In light of the complexity of maturity distributions, the sole-parameter approach does not appear to be reliable and rational for cotton maturity evaluation. More distributional parameters should be examined and included in the new classification methods. This paper (1) introduces important changes in the image-analysis algorithms for cotton cross-section measurements to enhance the consistency of fiber detections in order to reduce the bias on immature fibers, (2) investigates the characteristics and patterns of cotton maturity distributions, and (3) presents the experimental results on the cross-section images selected from seven cotton varieties that have a wide range of maturities. It is found that the skewness of a maturity distribution is an essential parameter for classifying the distribution pattern and that the dead fiber content and the mature fiber content are the important distributional parameters for assessing cotton maturity.