基于近红外光谱技术的亚麻纤维化学成分含量快速测定

在推进亚麻纤维的纺纱及其产业化生产过程中,快速、准确的定量分析纤维的化学成分是重要趋势。该研究利用近红外光谱技术分析亚麻纤维化学成分,以化学分析法测定值为对照,采用偏最小二乘法(PLS)建立亚麻纤维化学成分的近红外模型,从而实现了其化学成分的高效、快速定量分析。结果表明,建立的亚麻纤维纤维素、半纤维素、木质素和果胶近红外模型的校正相关系数(R_C)与验证相关系数(R_(CV))均在0.9以上,校正均方根误差(RMSEC)小于预测均方根误差(RMSEP)且均小于1。外部验证和双尾t检验表明模型预测结果较为准确,预测值与化学分析法得到的实测值无显著性差异,故该模型可用于相关化学成分含量的快速预测。

Rapid Determination of Chemical Composition of Flax Fiber by Near Infrared Spectroscopy

In this work,a near infrared(NIR) spectroscopy was developed for detection of the chemical composition of flax fiber,as it had become a development trend to rapidly and accurately analyze the chemical composition of flax fiber used for spinning in the process of promoting the preparation and industrial production.Compared with the determination value by chemical analysis,a NIR model for the chemical composition was set up by partial least square method,which could be used in rapid and efficient quantitative analysis of the composition.Results showed that the correction correlation coefficient(RC) and the verification correlation coefficient(RCV) of the established NIR model for cellulose,hemicellulose,lignin and pectin were all above 0.9.The corrected root mean square error(RMSEC) was less than the predicted root mean square error(RESEP),and they both were smaller than 1.External verification and double tailed t test showed that the model prediction results were relatively accurate,and there was no significant difference between the predicted values and the measured values obtained by chemical analysis.Therefore,the NIR based model could be used for rapid prediction of the chemical composition of flax fiber.