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Fourier Transform Near-infrared Spectroscopy for Determining Linen Content in Linen/Cotton Blend Products
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Flax fibers may be blended with cotton to provide an aesthetic property, improve performance and tailor fabric properties. The quality and cost of the woven fabric blends are affected by the amount of linen in the blend. Microscopic and chemical analyses are currently used to determine linen content in fabrics. This study describes a method to predict the linen percentage in linen/cotton blends using Fourier transform near-infrared (FT-NIR) spectroscopy, rapidly and non-invasively. A calibration model using partial least squares regression analysis was developed with gravimetrically measured ground flax-cotton fiber mixtures as reference samples versus NIR spectra. The best model occurred with a combination of multiplicative scatter correction and first derivative processing of the spectral data gave a standard error of validation of 2.20%, and only one factor was used for the model performance. Using this model, flax content was predicted in specific mixtures of flax and cotton fibers, blended flax-cotton yarns, and various non-scoured flax-cotton fabrics, giving standard errors of prediction less than 3%. Application of the calibration model to the scoured fabric, however, resulted in a higher error value. This result seemed to be due to loss in wax components and substantial changes in the NIR absorbance values of the fabric resulting from the scouring process. An alternative calibration model for scoured and dyed fabrics was developed, and using the model it was possible to predict flax contents in dyed fabrics with an error of 4–6%.
SAGE Publications
Title: Fourier Transform Near-infrared Spectroscopy for Determining Linen Content in Linen/Cotton Blend Products
Description:
Flax fibers may be blended with cotton to provide an aesthetic property, improve performance and tailor fabric properties.
The quality and cost of the woven fabric blends are affected by the amount of linen in the blend.
Microscopic and chemical analyses are currently used to determine linen content in fabrics.
This study describes a method to predict the linen percentage in linen/cotton blends using Fourier transform near-infrared (FT-NIR) spectroscopy, rapidly and non-invasively.
A calibration model using partial least squares regression analysis was developed with gravimetrically measured ground flax-cotton fiber mixtures as reference samples versus NIR spectra.
The best model occurred with a combination of multiplicative scatter correction and first derivative processing of the spectral data gave a standard error of validation of 2.
20%, and only one factor was used for the model performance.
Using this model, flax content was predicted in specific mixtures of flax and cotton fibers, blended flax-cotton yarns, and various non-scoured flax-cotton fabrics, giving standard errors of prediction less than 3%.
Application of the calibration model to the scoured fabric, however, resulted in a higher error value.
This result seemed to be due to loss in wax components and substantial changes in the NIR absorbance values of the fabric resulting from the scouring process.
An alternative calibration model for scoured and dyed fabrics was developed, and using the model it was possible to predict flax contents in dyed fabrics with an error of 4–6%.
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