番茄表层硫丹残留的近红外快速检测方法

选择经Rubberband 64点基线校正和二阶导数(平滑窗口为17,拟合阶数为2)预处理的近红外漫反射光谱,采用Boosting偏最小二乘法(PLS)，利用5个子模型建立了番茄表层硫丹残留量预测模型,并对模型的预测性能进行验证。模型的定标系数为0.992，预测残留量范围为5.1~134.1 ng,预测均方根误差（RMSEP）和校正均方误差（RMSECV）分别为2.79 和2.82，训练集和预测集的回收率范围分别为（100.1±1.4）%和（98.9±2.6）%。结果表明：本法快速、准确，有望成为新的蔬菜表层农药残留监测方法。

Rapid determination of endosulfan residue on tomato pericarp by near infrared spectroscopy

A rapid method based on near infrared diffuse reflectance spectroscopy was established for the detection of endosulfan residue on tomato pericarp.A Boosting partial least square(Boosting-PLS) regression was applied for building the quantitative models with second derivatives(polynomial order=2,width of the window=17 points) and Rubberband baseline correction(n=64) as the pre-processing method.Promising results were achieved with determination coefficent of 0.992 and the root mean square error of cross validation/prediction(RMSECV and RMSEP) of 2.82/2.79.The confidence interval(α=0.05) of average recoveries for calibration and prediction sets were(101.1±1.4)% and(98.9±2.6)%,respectively.The method showed the potential of being a rapid,economical and environmentally acceptable method for detecting endosulfan residue on fruit pericarp.