Kruve Anneli, Herodes Koit, Leito Ivo
University of Tartu, Institute of Chemistry, Jakobi 2, 51014 Tartu, Estonia.
J AOAC Int. 2010 Jan-Feb;93(1):306-14.
The matrix effects in HPLC/electrospray ionization (ESI)-MS analysis are difficult to compensate for because of their large variability. It is, therefore, often more practical to include uncertainty due to the matrix effect into the uncertainty budget rather than try to compensate. This work presents an empirical approach--the matrix effect graph approach--for estimating the uncertainty due to the matrix effect in HPLC/ESI-MS analysis of pesticide residues in fruits and vegetables. At certain time intervals (1 month), a calibration graph using extracts of different fruits/vegetables as calibration solutions is prepared, and a regression line is fitted through these data. These fruits/vegetables may be either from the commodity group of the samples or from different commodity groups. The relative residuals of the calibration point peak areas are calculated and plotted against the measurement time. We term the resulting graph the matrix effect graph. The root mean square of the relative residuals is calculated and used as the estimate of relative uncertainty of the sample peak areas caused by the matrix effect. The matrix effect graph obtained over fruits/vegetables from different commodity groups can also be used to identify fruits/vegetables with extreme matrix effects. The matrix effect graph approach was used for determination of thiabendazole, aldicarb, imazalil, and methiocarb and was validated with tomato, cucumber, and sweet corn matrixes at the 0.5 mg/kg concentration level. When different commodity groups were used to compile the matrix effect graph, results of analysis of all samples agreed with the spiked concentrations within the expanded uncertainties (at k=2 level). When the matrix effect graph was compiled using fruits from the same commodity group as the analyzed samples (fruiting vegetables in this case), agreement was found in 98% of the cases.
在HPLC/电喷雾电离（ESI）-MS分析中，基质效应因其具有很大的变异性而难以补偿。因此，将基质效应导致的不确定度纳入不确定度预算，而不是试图进行补偿，通常更为实际。本文提出了一种经验方法——基质效应图法，用于估算水果和蔬菜中农药残留HPLC/ESI-MS分析中基质效应导致的不确定度。在特定时间间隔（1个月），制备以不同水果/蔬菜提取物作为校准溶液的校准曲线，并通过这些数据拟合回归线。这些水果/蔬菜可以来自样品的商品组，也可以来自不同的商品组。计算校准点峰面积的相对残差，并将其与测量时间作图。我们将得到的图称为基质效应图。计算相对残差的均方根，并将其用作基质效应引起的样品峰面积相对不确定度的估计值。从不同商品组的水果/蔬菜获得的基质效应图，也可用于识别具有极端基质效应的水果/蔬菜。基质效应图法用于噻菌灵、涕灭威、抑霉唑和甲硫威的测定，并在0.5 mg/kg浓度水平下用番茄、黄瓜和甜玉米基质进行了验证。当使用不同商品组编制基质效应图时，所有样品的分析结果在扩展不确定度（k=2水平）内与加标浓度一致。当使用与分析样品来自同一商品组的水果（本例中为结果实的蔬菜）编制基质效应图时，98%的情况下结果相符。
