糙米蛋白质含量的近红外透射光谱分析

应用近红外透射光谱技术,采用改进的偏最小二乘法(MPLS)建立糙米蛋白质含量(PC)定量分析数学模型。糙米蛋白质含量预测数学模型校正标准误差(SEC)、交叉检验标准误差(SECV)分别为0.2114、0.2365,校正相关系数(RSQ)和交叉验证相关系数(1-VR)分别为0.9807、0.9768,预测误差与常规分析方法的误差接近。内部交叉检验和外部验证结果表明,近红外定量分析有很高的准确度,近红外光谱法完全可以替代常规分析方法。

With the technique of near infrared transmittance spectroscopy(NITS),the predicted model for quantitative analysis of protein content in brown rice was established by using modified Partial Least Square(MPLS). The results were indicated by the standard errors (SEC for calibration, SECV for cross validation)and determination coefficients(RSQ for calibration and 1-VR for validation)when the model was calibrated by MPLS. The SEC and SECV were 0.2114,0.2365; While RSQ and 1-VR were 0.9807,0.9768. The predictive errors measured by NITS were close to those by routine laboratory methods. The method of NITS had high accuracy in predicted tests of cross validation and independent validation and was available to replace the routine laboratory analysis.