An empirical model to predict hemp fibre quality, processability and applicability

In recent years, the use of hemp fibres in the textile industry has increased significantly. However, spinning 100% hemp yarn in a sustainable manner remains challenging. This project continues research into pre-treating and spinning of hemp fibres. This is combined with building a clear dataset containing all available results obtained during previous projects. These results will be analysed and the key parameters that determine the quality of hemp fibres will be mapped. The final goal is to establish a regression equation that includes these key properties of hemp in order to quantify the quality of the fibres with a single number. This should enable the textile sector to select the most efficient pre-treatment method (avoiding unnecessary use of energy and chemicals). In addition, the quality indicator should enable the selection of the most suitable application for the available hemp quality. In the long term, the regression equation is a first step towards linking all available data from the entire value chain: cultivation – fibre preparation – spinning – weaving/knitting (textile sector). Targeted quantification enables each player in the value chain to optimise the related processes. Once the equation has been finalised, it will also be possible to investigate the extenstion to long fibres (this is a different spinning process that produces yarns with different properties, which means that other parameters may be included in the equation), and other sectors, e.g. construction and composites that use hemp fibres for specific applications.