Sohn Miryeong, Himmelsbach David S, Morrison W Herbert, Akin Danny E, Barton Franklin E
USDA-Agricultural Research Service, Richard B. Russell Agricultural Research Center, P.O. Box 5677, Athens, Georgia 30605, USA.
Appl Spectrosc. 2006 Apr;60(4):437-40. doi: 10.1366/000370206776593663.
The quality of flax fiber in the textile industry is closely related to the wax content remaining on the fiber after the cleaning process. Extraction by organic solvents, which is currently used for determining wax content, is very time consuming and produces chemical waste. In this study, near-infrared (NIR) spectroscopy was used as a rapid analytical technique to develop models for wax content associated with flax fiber. Calibration samples (n=11) were prepared by manually mixing dewaxed fiber and isolated wax to provide a range of wax content from 0 to 5%. A total of fourteen flax fiber samples obtained after a cleaning process were used for prediction. Principal component analysis demonstrated that one principal component is enough to separate the flax fibers by their wax content. The most highly correlated wavelengths were 2312, 2352, 1732, and 1766 nm, in order of significance. Partial least squares models were developed with various chemometric preprocessing approaches to obtain the best model performance. Two models, one using the entire region (1100-2498 nm) and the other using the selected wavelengths, were developed and the accuracies compared. For the model using the entire region, the correlation coefficient (R2) between actual and predicted values was 0.996 and the standard error of prediction (RMSEP) was 0.289%. For the selected-wavelengths model, the R2 was 0.997 and RMSEP was 0.272%. The results suggested that NIR spectroscopy can be used to determine wax content in very clean flax fiber and that development of a low-cost device, using few wavelengths, should be possible.
纺织工业中亚麻纤维的质量与清洗过程后残留在纤维上的蜡质含量密切相关。目前用于测定蜡质含量的有机溶剂萃取法非常耗时且会产生化学废物。在本研究中，近红外（NIR）光谱法被用作一种快速分析技术来建立与亚麻纤维相关的蜡质含量模型。通过手动混合脱蜡纤维和分离出的蜡来制备校准样品（n = 11），以提供0%至5%的蜡质含量范围。总共14个经过清洗过程后获得的亚麻纤维样品用于预测。主成分分析表明，一个主成分就足以根据蜡质含量区分亚麻纤维。相关性最高的波长依次为2312、2352、1732和1766 nm。采用各种化学计量学预处理方法建立了偏最小二乘模型，以获得最佳的模型性能。开发了两个模型，一个使用整个区域（1100 - 2498 nm），另一个使用选定的波长，并比较了它们的准确性。对于使用整个区域的模型，实际值与预测值之间的相关系数（R2）为0.996，预测标准误差（RMSEP）为0.289%。对于选定波长模型，R2为0.997，RMSEP为0.272%。结果表明，近红外光谱法可用于测定非常干净的亚麻纤维中的蜡质含量，并且开发一种使用较少波长的低成本设备应该是可行的。
