Abstract

Shive is the main contaminant in flax fibre and affects fibre quality. In this study, we developed a calibration for determining shive content in flax using near infrared (NIR) spectroscopy and applied the model to pilot plant processed flax to predict shive content. The model based on “ground” mixtures performed best from multiplicative scatter correction after a second derivative treatment of the spectral data, giving a standard error of cross-validation of 0.35% using five factors. Prediction samples were Jordan enzyme-(ER) and Natasja dew-retted (DR) flax that was collected after various stages of processing. When the model was applied to the “ground” flax, a high correlation was obtained between the NIR predicted value and actual shive content, giving a correlation coefficient of > 0.98 for both retted flax samples. However, when the model was applied to the “as-is” flax, a slope and bias were observed. These deviations were corrected by a linear regression between predicted values of “ground” and “as-is” flax. For the NIR analysis of ER flax, the shive content decreased rapidly by the third processing step to 4 to 5% and almost 0% after the last step. For the DR flax, the shive content continuously decreased with processing to about 5% after the last step. The results indicate that it is possibile to measure shive in flax on a commercial processing line.

© 2004 NIR Publications

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