Are yarn quality prediction tools useful in the breeding of high yielding and better fibre quality cotton (Gossypium hirsutum L.)?

Abstract

AbstractBackgroundThe approach of directly testing yarn quality to define fibre quality breeding objectives and progress the selection is attractive but difficult when considering the need for time and labour. The question remains whether yarn prediction tools from textile research can serve as an alternative. In this study, using a dataset from three seasons of field testing recombinant inbred line population, Cottonspec, a software developed by the Commonwealth Scientific and Industrial Research Organisation (CSIRO) for predicting ring spun yarn quality from fibre properties measured by High Volume Instrument (HVI), was used to select improved fibre quality and lint yield in the population. The population was derived from an advanced generation inter-crossing of four CSIRO conventional commercial varieties. The Cottonspec program was able to provide an integrated index of the fibre qualities affecting yarn properties. That was compared with selection based on HVI-measured fibre properties, and two composite fibre quality variables, namely, fibre quality index (FQI), and premium and discount (PD) points. The latter represents the net points of fibre length, strength, and micronaire based on the Premiums and Discounts Schedule used in the market while modified by the inclusion of elongation.ResultsThe population had large variations for lint yield, fibre properties, predicted yarn properties, and composite fibre quality values. Lint yield with all fibre quality traits was not correlated. When the selection was conducted first to keep those with improved fibre quality, and followed for high yields, a large proportion in the resultant populations was the same between selections based on Cottonspec predicted yarn quality and HVI-measured fibre properties. They both exceeded the selection based on FQI and PD points.ConclusionsThe population contained elite segregants with improved yield and fibre properties, and Cottonspec predicted yarn quality is useful to effectively capture these elites. There is a need to further develop yarn quality prediction tools through collaborative efforts with textile mills, to draw better connectedness between fibre and yarn quality. This connection will support the entire cotton value chain research and evolution.