Statistical evaluation of analytical curves for quantification of pesticides in bananas

Abstract

The aim of this paper is to statistically validate the analytical curves of a chromatography method to identify and quantify azoxystrobin, difenoconazole and propiconazole residues in banana pulp, using QuEChERS and GC-SQ/MS. A matrix-matched calibration was used and analytical curves were estimated by weighted least squares regression (WLS), confirming heteroscedasticity for all compounds. Statistical tests were performed to confirm the quality adjustment of the proposed linear model. The correlation coefficient for azoxystrobin, difenoconazole and propiconazole were, respectively, 0.9985, 0.9966 and 0.9997 (concentration range: 0.05 and 2.0 mg kg−1). The limits of detection and quantification were, respectively, between 0.007 and 0.066 mg kg−1, and between 0.022 and 0.199 mg kg−1, below the maximum limits stipulated by Brazilian, American, and European legislation. Only difenoconazole had an insignificant matrix effect (6.8%). Thus, the weighted least squares method is shown to be a safe linear regression model, providing greater reliability of the results.