The purpose of this work was to investigate the detection of the pesticide residual (profenofos) in tomatoes by using visible/near-infrared spectroscopy. Therefore, the experiments were performed on 180 tomato samples with different percentages of profenofos pesticide (higher and lower values than the maximum residual limit (MRL)) as compared to the control (no pesticide). VIS/near infrared (NIR) spectral data from pesticide solution and non-pesticide tomato samples (used as control treatment) impregnated with different concentrations of pesticide in the range of 400 to 1050 nm were recorded by a spectrometer. For classification of tomatoes with pesticide content at lower and higher levels of MRL as healthy and unhealthy samples, we used different spectral pre-processing methods with partial least squares discriminant analysis (PLS-DA) models. The Smoothing Moving Average pre-processing method with the standard error of cross validation (SECV) = 4.2767 was selected as the best model for this study. In addition, in the calibration and prediction sets, the percentages of total correctly classified samples were 90 and 91.66%, respectively. Therefore, it can be concluded that reflective spectroscopy (VIS/NIR) can be used as a non-destructive, low-cost, and rapid technique to control the health of tomatoes impregnated with profenofos pesticide.

中文翻译：

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使用VIS / NIR光谱和多变量分析检测番茄中农药残留的可行性

这项工作的目的是研究使用可见/近红外光谱法检测西红柿中残留的农药（丙溴磷）。因此，与对照组（无农药）相比，对180种番茄样品进行了试验，其中番茄样品中具有不同百分比的Profenofos农药（高于和低于最大残留限量（MRL））。用分光计记录了农药溶液和非农药番茄样品（用作对照处理）的VIS /近红外（NIR）光谱数据，该样品中浸渍了400至1050 nm范围内的不同浓度的农药。为了将农药残留含量在最低和最高残留限量下的番茄分类为健康和不健康样品，我们使用了带有偏最小二乘判别分析（PLS-DA）模型的不同光谱预处理方法。选择交叉验证标准误差（SECV）= 4.2767的平滑移动平均预处理方法作为本研究的最佳模型。此外，在校准和预测集中，正确分类的样本总数的百分比分别为90和91.66％。因此，可以得出结论，反射光谱法（VIS / NIR）可以作为一种无损，低成本，快速的技术来控制浸渍有Profenofos农药的西红柿的健康。