番茄表层硫丹残留的近红外快速检测方法
Rapid determination of endosulfan residue on tomato pericarp by near infrared spectroscopy
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摘要: 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。
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关键词:
- 硫丹 /
- 近红外光谱技术 /
- 残留检测 /
- Boosting偏最小二乘法 /
- 共识策略
Abstract: 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. -
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