The potential of near-infrared diffuse reflectance spectrometry for quality control analyses in the textile industry was explored with a view to the quantification of finishing oils in acrylic fibres by partial least-squares regression, using a rotary cuvette system for recording spectra. Calibration was performed with a set of samples that encompassed every source of variability (linear density of the fibres, colour, concentration of the finishing oil), and the wavelength region where absorption was mostly due to the oil was used to construct several models from which that leading to the minimum relative standard error for a sample test set was selected. The results provided by various mathematical treatments [second-derivative, standard normal variate (SNV)] used to minimize scattering resulting from the differential linear density of the samples revealed no significant differences between prediction errors (only in the number of partial least-squares components). The model was used to quantify levels of finishing oil in routinely manufactured samples for a period of 6 months, during which time two batches showed poor predictions due to a new component appearing in the product. Modification of the calibration model to account for this component substantially increased robustness and allowed the accurate quantification of all batches manufactured after the model has been developed.
|Publication status||Published - 1 Aug 1997|
- Acrylic fibres
- Finishing oil
- Near-infrared spectrometry
- Partial least-squares calibration
- Standard normal variate