近红外透射光谱技术测定黍稷蛋白含量的研究

Analysis of Protein Contents in Panicum miliaceum L. by Near Infrared Transmittance Spectroscopy

为了探索快速测定完整黍稷籽粒蛋白含量的方法。采用近红外光谱分析技术建立数学模型并进行预测,比较原始透射光谱经导数处理结合不同回归算法对模型的影响。结果表明,分别经一阶和二阶导数处理后利用偏最小二乘法和改进的偏最小二乘法,4种方法的分析效果相近,最优的是一阶导数结合改进的偏最小二乘回归法,黍稷蛋白定标模型的定标相关系数(RSQ)为0.8806,定标标准误差(SEC)为0.3424,交互验证相关系数(1-VR)为0.8570,交互验证标准误差(SECV)为0.3751,外部预测标准偏差(SEP)为0.454。最终以完整黍稷籽粒为样品所建立的蛋白NITS模型,可以用于黍稷蛋白含量的快速检测。

To explore a rapid determination method of protein content in grains of Panicum miliaceum L., the predicted models for quantitative analysis of protein contents in the grains was built using near infrared transmittance spectroscopy （NITS）, and the influence of optics derivative treatment methods combined with different regression methods on the model was studied. The results showed that the predicting effects of the four combinations between the partial least squares （PLS）, the modified partial least squares （MPLS） regression method and first derivative and second derivative were similar. MPLS in combination with first derivative was the best model. In this model, the correlation coefficient （1-VR） was 0.8570, the average determinationvalidation （SECV） was 0.3751, and the standard error of prediction （SEP） was 0.454. The NITS model of intact Panicum miliaceum L. grain for protein content determination could be substituted for traditional chemical method.