Optimisation and validation of a colour prediction model for jacquard knitted fabrics with horizontal intermix filaments

Abstract This study addresses colour prediction in horizontal intermix filament fabrics by developing an optimised Stearns‐Noechel model. To account for reflectance losses due to the knitted surface structures, an optimisation parameter α was introduced. The SN‐α model produced substantial improvements, reducing mean colour differences from 8.6 to 2.1 (a 76% reduction) for two‐feeder cyan‐magenta fabrics and from 9.1 to 3.9 (a 57% reduction) for three‐feeder cyan‐magenta‐white fabrics. The optimised parameters were found to be similar across feeder types, confirming the model's strong generalisability. Validation on independent samples demonstrated further reductions of 70% and 67% for two‐feeder cyan‐yellow and three‐feeder cyan‐yellow‐black fabrics, respectively. The findings highlight the combined influence of yarn spectral properties and feeder configuration on predictive performance, with feeder arrangements affecting non‐linear mixing behaviour. Overall, the SN‐α model offers an effective framework for predicting the macroscopic perceived colour of patterned fabrics, improving accuracy and efficiency in digital design workflows and supporting more sustainable textile colour management.