The potential of near-infrared diffuse reflectance spectrometry for qu
ality control analyses in the textile industry was explored with a vie
w 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 encompa
ssed 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 mo
dels from which that leading to the minimum relative standard error fo
r a sample test set was selected, The results provided by various math
ematical treatments [second-derivative, standard normal variate (SNV)]
used to minimize scattering resulting from the differential linear de
nsity of the samples revealed no significant differences between predi
ction errors (only in the number of partial least-squares components),
The model was used to quantify levels of finishing oil in routinely m
anufactured samples for a period of 6 months, during which time two ba
tches showed poor predictions due to a new component appearing in the
product, Modification of the calibration model to account for this com
ponent substantially increased robustness and allowed the accurate qua
ntification of all batches manufactured after the model has been devel
oped.