基于近红外光谱与组合间隔偏最小二乘法的稻米镉含量快速检测

采用近红外光谱(near infrared spectroscopy,NIRS)结合组合间隔偏最小二乘法(synergy interval partial least squares,siPLS)建立稻米镉含量快速检测的方法。收集并分析72个稻米样品的NIRS谱图。对光谱前处理方法进行优化,确定平滑、多元散射校正与均值中心化处理为最优方法。采用siPLS法筛选特征波数,建立稻米镉含量的定量模型。稻米镉siPLS模型交叉验证均方根(RMSECV)与预测均方根(RMSEP)值分别为0.247与0.261,训练集相关系数(Rc)与预测集相关系数(Rp)值分别为0.919与0.895。结果表明:运用siPLS法选择特征波长后,不但可以降低模型的复杂度,同时还能够提高预测精度。NIRS作为一种快速、无损与便捷的初筛方法,可用于检测稻米中镉含量是否超标。

The feasibility of rapid determination of the cadmium content in rice based on near infrared spectroscopy and synergy interval partial least squares

Near infrared spectroscopy (NIRS) combined with synergy interval partial least squares (siPLS) were used to establish the rapid method for the determination of cadmium content in rice. The NIR spectra of 72 rice samples were collected and analyzed. After optimization, an approach (SG smoothing combined with MSC and mean-centering) was adopted as a pre-treatment method for raw spectrum. SiPLS method was used as extraction methods of characteristic variables, and the NIRS quantitative model was built and predicted. The RMSECV and RMSEP of the siPLS model were 0.247 and 0.261, respectively. The Rc and Rp were 0.919 and 0.895, respectively. The results showed that siPLS algorithm not only could decrease the complexity of the model, but also improved the predictive precision. NIRS can be useful as a rapid, non-destructive and convenient analytical method for primary screening and detecting cadmium-polluted rice.